Stuart Cheetham, CEO at MPowered Mortgages, on how AI-powered technology allows mortgage lenders to fully underwrite loan applications in minutes
SHARE THIS STORY
AI technologies are about to have a huge impact on the mortgage market… In November last year the founders of Revolut announced plans to launch a “fully digital, instant” mortgage in Lithuania and Ireland in 2025. Details were sketchy but the company said that mortgages will be part of a “comprehensive credit offering” it intends to build.
Neobanking progress with AI
Digital only banks, like Revolut and Monzo, are renowned for using the power of technology and data science to create efficiencies and improve customer experience. The reason neobanks have been so successful is because they provide a modern, convenient and cost-effective alternative to traditional banking. This is done a transparent way, through fast onboarding, 24/7 app access and instant notifications. All with a user-friendly interface.
While many financial services sectors have embraced financial technology in the way Revolut and Monzo have for the retail banking sector, the mortgage sector has struggled to make a real breakthrough here. Why hasn’t the mortgage industry caught up one might ask? Mortgages are complex financial products, existing at the intersection of justifiably stringent regulation. They represent the single biggest financial commitment people make in their lifetimes. Financial advisors who source mortgages on behalf of borrowers are hindered at every stage by outdated systems and inadequate or commoditised product offerings.
Disrupting the Mortgage Market
The mortgage industry is one financial services sector that has been yearning to be shaken up by the FinTech industry for some time. While it’s encouraging to see a successful brand like Revolut enter this market, what is less known is that huge progress is being made already by smaller and less well known FinTech disruptors.
For example, the mortgage technology company MQube has developed a “new fast way” of delivering mortgage offers using the cutting edge of AI technology and data science. Today, it still typically takes several weeks to get a confirmed mortgage offer. This is one of the major reasons the homebuying process can be so time consuming and stressful for brokers and borrowers. The mortgage process is characterised by bureaucracy, paperwork, delays and often frustratingly opaque decision-making by lenders. This leads to stress and uncertainty for consumers, and their advisors. And at a time when they have plenty of other property-purchase related challenges to contend with.
Our proprietary research shows us, and this will come as no surprise, that the biggest pain point for borrowers and brokers about the mortgage process is that it is time consuming, paperwork heavy and stressful. Imagine a world where getting a mortgage is as quick and as easy as getting car insurance. This is MQube’s vision.
MQube – AI-powered Mortgages
MQube‘s AI-powered mortgage origination platform allows mortgage lenders to fully underwrite loan applications in minutes. MPowered Mortgages is MQube’s lending arm and competes for residential business alongside the big banks. It uses MQube’s AI-driven mortgage origination platform and is now able to offer a lending decision within one working day to 96% of completed applications.
The platform leverages state-of-the-art artificial intelligence and machine learning to assess around 20,000 data points in real-time. This enables lenders to process mortgage applications in minutes, transforming the industry standard of days or weeks. It automates the entire underwriting journey, from application to completion. This helps to provide a faster service, reduce costs, mitigate risks, and to make strategic adjustments quickly and effectively. By assessing documents and data in real-time during the application, it is able to build a clearer and deeper understanding of a consumers’ circumstances and specific needs. Applicants are never asked questions when MQube can independently source and verify that data, leading to a streamlined and paperless experience. Furthermore, this whole process reduces dependency on human intervention.
The benefits of AI
More and more lenders are seeing the benefits AI and financial technology can bring to their business. They are beginning to adopt such AI-driven financial systems which are scalable and serve to address systemic problems in this industry. The mortgage industry is still some way behind the neobanks, but what’s hugely exciting to see is the progress that has been made so far. Moreover, if FinTechs continue to innovate this sector and if lenders continue to embrace financial technology and use at scale, then getting a mortgage could genuinely become a quick, easy and stress free process. At this point, the mortgage industry could begin to see a shift in consumer perception and change in consumer behaviour. A new frontier for the mortgage industry is upon us.
FICO’s use of Blockchain for AI model governance wins Tech of the Future: Blockchain and Tokenisation award
SHARE THIS STORY
Global analytics software leader FICO has won the Tech of the Future – Blockchain and Tokenisation award. The Banking Tech Awards in London recognised FICO for its innovative work using Blockchain technology for AI model governance. FICO’s use of blockchain to advance responsible AI is the first time blockchain has been used to track end-to-end provenance of a machine learning model. This approach can help meet responsible AI and regulatory requirements.
FICO’s AI Innovation and Development team has developed and patented an immutable blockchain ledger. It tracks end-to-end provenance of the development, operationalisation and monitoring of machine learning models. The technology enforces the use of a corporate-wide responsible AI model development standard by organisations. It demonstrates adherence to the standard with specific requirements, people, results, testing, approvals and revisions. In addition to the Banking Tech award, Global Finance recognised FICO’s blockchain for AI technology with The Innovators award last year.
Responsible AI
“The rapid growth of AI use has made Responsible AI an imperative,” commented Dr. Scott Zoldi, chief analytics officer at FICO. “FICO is focused on technologies that ensure AI is used in an ethical way, and governance is absolutely critical. We are proud to receive another award for our groundbreaking work in this area.”
FICO is well-known as a leader in AI for financial services. Its FICO® Falcon® Fraud Manager solution, launched in 1992, was the first fraud solution to use neural networks. Today it manages some four billion payment cards worldwide. FICO has built advanced analytics capabilities into FICO® Platform, an applied intelligence platform for building decision management solutions.
We chat with the CIO of Urenco, Sarah Leteney, about the ways this unique business leverages technology, and the big difference a small team can make.
SHARE THIS STORY
Urenco does things a little differently. It has to. It supplies uranium enrichment services and fuel cycle products for the nuclear industry – a niche that requires a lot of specialist care and attention. Urenco has a clear vision for the net zero world. A world in which carbon-free energy is the norm. And for its CIO, Sarah Leteney, this means approaching the world of technology in different and interesting ways.
Leteney speaks exclusively to Interface Magazine about what it means to operate IT in a high-risk environment that requires an enormous amount of consistency. She also discusses the types of systems that are vital to Urenco, how the business leverages suppliers, bringing in the most talented possible people, and how Urenco balances a small team with a high pressure environment.
How does the role of CIO within the nuclear industry differ from one for a consumer goods company?
Most CIOs spend their time thinking about how to talk to customers through the rapid exchanges that are needed to maintain the flow of high volumes of traffic. They need to know how to keep up with their competitors in terms of customer experience and how to quickly bring new products to market.
At Urenco, we are quite literally the polar opposite of this. We are concerned with the consistency and timeliness of highly individualised communications with our customers, how internal control software can enable the accurate flow of information to our regulators, and how to support our teams to keep track of every gram of raw material, and product in our organisation. Our systems are vital to keep our operations safe and reliable. It is not fast-paced – rather a very careful and considered environment where accuracy is everything.
What is it like to enable and provision services in such an environment? Can you keep in touch with market trends? Is there much recognition of what you do?
I work in a high threat environment and there are many special considerations to understand. There is a certain cadence and rhythm to what we do and we have to work at a pace which suits the organisation, rather than keep up with the latest trends in the IT industry. Although, we do keep abreast of developments through networks such as Gartner and Aurora and introduce them where appropriate and relevant.
In relation to the recognition of this role, like every other CIO out there, you are noticed more when something is not working properly. That said, Urenco is very good at making you feel as if you are part of something that matters. People readily ask you questions and understand when something is a minor glitch compared to something more significant. And we actively encourage people to report issues because that is how you get continuous improvement. Overall, the organisation takes care of my team, we’re not under siege when things go wrong and what we do is widely appreciated.
What sorts of systems are you looking after and what are the challenges around these?
We have all the same systems that you see in many other large organisations, plus a few really niche products used only in our industry.
Like lots of businesses, we are on a SAP journey, moving existing systems into S4. This programme impacts all parts of the organisation and we have to drive the changes forward from a business point of view. We consider the IT team an enabler for this work as it’s ultimately the transformation of our business processes which we are trying to facilitate.
We also look after the information assets of the organisation – both the structured and unstructured data. Like many organisations, it’s an on-going process to work out how to extract genuine business insights from vast amounts of historical data which has been stored in multiple places and not always in the most logical manner. We have a significant amount of historical information which still remains important (think plant designs and maintenance records, etc.) so effective archiving and retention policies are very much at the forefront of our minds. It’s so easy to over store or over classify information in an effort to be ‘safe rather than sorry’, but in reality, as well as increasing on-going costs, this sort of behaviour tends to make it harder to find what you need. We are investigating new technologies to help us search through our data faster and more effectively than ever before.
We’re also currently extending into the Operational Technology sphere, sharing our experience and tools with our OT colleagues and directly addressing operational security challenges, investing significantly in our cyber defences to further strengthen our plant security services.
What is it like to work in a company with a large turnover but a relatively small number of employees? How does that affect the service you provide?
We try to think through what every employee needs from IT and provide them with the level of service their role requires, regardless of their position in the business. We are in the fortunate position where having fewer employees means individual changes to software, hardware, or SAAS costs tend to have a less significant impact on our profitability than in many organisations with higher staff complements. Many organisations have tiers of users which determine the level of service received. However, in our organisation, every minute of everyone’s time is important, as we don’t have many employees driving our engine forward. We are investing in our employee experience as one of the key organisational imperatives working alongside our colleagues in the People and Culture team, and this is going to be an on-going focus for us for the next few years.
Whilst the company turnover is important, it is less of a driving factor for us in IT. We benchmark ourselves against what proportion of operational expenditure we are investing in IT and IS to ensure we invest an appropriate amount in IT for an organisation of this size.
How do you work with your team to ensure they can provide the most effective service to the business?
We are organised primarily around our production sites, with a centralised team to provide shared services like architecture and finance. The organisation is only two layers deep in most teams, so information flow is mainly managed by direct cascade. The senior team is made up of heads of shared functions and site IT managers, and opinions flow freely between them.
Our IT Leadership team has a monthly two-day meeting where we come together in person. We sit together without our PCs and the constant pinging of information. This helps us to realign, to reprioritise matters, and include coaching and learning techniques. We all have daily pressures in our lives, and these meetings are about supporting each other and working effectively together.
Once a quarter we also visit one of our sites as a group, hosted by our IT site managers. This is critical to us because we cannot do our jobs without thoroughly understanding the experience of IT services on the ground. These visits also allow us to meet up with our business colleagues as part of their site leadership teams so we can exchange experiences and strategic thinking quite freely in person.
We also run monthly townhall meetings for all members of the IT team, and invite our colleagues from Information Security to join us. We have found this to be a really valuable information exchange point. IS can hear exactly what we are saying to the wider team on the ground, so they can gain real insight into our issues first hand. Our key suppliers are also invited to these sessions on a quarterly basis, again to foster free exchange of information.
How about diversity and inclusion – what are you doing within that area and what have you achieved?
This is one of the biggest areas I would like to tackle further. Within our company, like the whole of the nuclear sector, the age of our employees is increasing year on year as we have a very low employee turnover. So we have a small number of vacancies on an annual basis and we are working hard to get a better talent pool for when these opportunities arise, reaching out to people with a wider range of backgrounds.
Our strategy includes blind sifting, engaging with people who have had periods of time out of the workplace and may need to work certain hours, and being open to job-sharing. It is possible for us to be very flexible and we are trying to ensure this is known out in the world of recruitment.
One area we are doing really well in right now is neurodiversity. We have a significant proportion of our team who identify as neurodivergent and a new staff network focussing on the specific issues of importance to this community was actually started by a member of our team.
I’d love to see an ethnicity and gender mix in the future which is closer to the population norms in each of our operating countries and I’m pleased to say that our talent acquisition partners are working hard to promote our roles in new talent pools with a much more diverse population.
How do you work with your suppliers to maintain a good relationship with them?
We’re currently in the process of diversifying our IT supply base. We have had a couple of really strong suppliers for a long period of time who work very closely with us, but what we are aiming to do now is widen our group of key suppliers to create a supplier ecosystem consisting of four different types of partner – Advisory, Development, Configuration, and Support. A key part of this initiative will be about embedding the behaviours we would like suppliers to demonstrate when working with us to create an inclusive and transparent relationship, which we are progressing through setting up a Urenco Academy to provide initial onboarding and on-going behavioural reinforcement of Urenco’s core values across our partnerships.
You recently won a CIO 100 award. How did that come about and what reaction did you get from people who know you?
The CIO 100 award came about through my external mentor asking me why I wasn’t looking at it! He encouraged me to put myself forward for consideration. Sometimes you need a bit of a push from a critical friend to remind you that whilst you see how much remains to be done, it’s good to acknowledge the great results you have already achieved.
The most gratifying thing about the whole experience for me was that you are judged by really experienced CIOs, so they fully understand the complexity of what you do. I’m incredibly grateful and humbled to be included in such an inspiring group of people, who are all wrestling with organisational struggles and trying to keep up in a fast-paced world, solving problems all day, every day.
My colleagues were delighted for me and sent lots of congratulatory messages. I think my team were slightly surprised because they also don’t always see what a good job they are all doing. One of them was even inspired to send an AI-created poem in celebration!
Urenco gave me the opportunity to take on a challenging and exciting role initially as an interim CIO. They chose to promote from within despite having strong external candidates, and not only that, but they asked if I would like to have a mentor in my first year to help me to cement the skills I wanted to strengthen for my own peace of mind. I’m not sure what else I could have asked for from this organisation. When I look at the award all I really think, looking back over the last three years, is ‘how amazing is that’!
Paul O’Sullivan, Global Head of Banking and Lending at Aryza, on the rise of AI in banking
SHARE THIS STORY
The banking sector stands at the crossroads of technological innovation and operational transformation. AI is taking centre stage in reshaping how financial institutions operate. The banking sector is beginning to recognise AI’s potential. It can address challenges, enhance operational efficiency, and deliver more personalised customer experiences.
The Current State of AI in Banking
Research reveals that while a number of banking organisations have yet to fully integrate AI into their operations, key areas such as debt recovery are leading the charge. The slower pace of adoption can be attributed to the highly regulated environment of banking. Because transparency, compliance, and customer trust are non-negotiable. However, despite this cautious approach, banks that have implemented artificial intelligence are already seeing significant benefits, particularly in risk management.
AI’s Role in Risk Management
Effective risk management is a cornerstone of the banking sector. AI is proving to be a powerful tool in this area. By analysing vast amounts of data and providing predictive insights, AI enables banks to mitigate risks early. They can strengthen customer portfolio stability, and make data-driven lending decisions. These capabilities are essential in a landscape where financial risks can escalate rapidly.
Beyond the expected benefits, banks have also reported enhanced customer insights as an unexpected advantage. By leveraging AI to analyse customer behaviours and preferences, banks can tailor their products and services more effectively. Furthermore, they can improve customer satisfaction and experience, whilst fostering long-term loyalty.
Challenges to Adoption
Although organisations are experiencing a multitude of advantages, the integration of AI in banking is not without its hurdles. Legacy IT systems, stringent regulatory requirements, and concerns around data privacy pose significant challenges to widespread adoption. Banks must ensure AI-driven decision-making processes are effective. Moreover, they must also be fully transparent and compliant with industry regulations. Further highlighting the importance of a gradual, strategic approach to AI implementation.
Opportunities Ahead
The potential for AI in banking extends far beyond risk management. From streamlining operational workflows to enhancing customer personalisation and improving decision-making. AI is set to drive innovation across the sector. For example, AI-powered chatbots and virtual assistants transform customer service by providing instant, 24/7 support. They can handle complex interactions, enhancing customer satisfaction. At the same time, advanced analytics enable banks to analyse behaviour patterns, predict trends, and personalise product offerings. Furthermore. enhancing cross-selling opportunities and driving deeper customer engagement. These tools are becoming strategic enablers for innovation in the financial landscape.
A Call to Action
For banks to fully realise the benefits of AI, they must address the digital transformation gap, modernising outdated infrastructures and fostering a culture of innovation. This includes investing in technologies that align with their strategic goals, ensuring robust data security measures alongside maintaining compliance with evolving regulations.
As the banking sector continues its journey towards digital maturity, AI will play a pivotal role in defining its future. By overcoming current barriers and embracing AI-driven solutions, banks can not only enhance operational efficiency but also deliver the seamless, personalised experiences that customers now expect in an increasingly digital world.
About Aryza
At Aryza know that in today’s highly regulated world, there is huge value in quickly guiding your customers through the product that best fit their immediate needs, through a seamless journey that is tailored to their specific circumstances.
We created smart platforms, responsible and compliant products, and a unique system of companies and capabilities so that businesses can optimise their customers’ journey through the right product at the right time.
For our teams across the globe, the growth of Aryza is a good news story and a testament to our clear vision and goals as an international business.
And also front of mind as we build a global footprint is our impact on the environment. Aryza is committed to reducing its carbon impact through the choices it makes and we are pleased to say that we follow an active roadmap.
Xerox has been a household name for decades. For many, it’s associated with photocopiers and printers. After all, it’s the…
SHARE THIS STORY
Xerox has been a household name for decades. For many, it’s associated with photocopiers and printers. After all, it’s the largest print company in the world. But it’s also a technology powerhouse that’s been at the forefront of a great deal of innovation. It has undergone a journey of evolution and reinvention into an IT and digital services provider. That’s what led to the business acquiring a large managed service provider, Altodigital, in 2020.
Derek Gunton has spent nearly 20 years in the technology sphere. He came to Xerox as part of the Altodigital acquisition. Altodigital also started out as a management print organisation and evolved into the IT services side, so its journey mirrors Xerox’s in many ways. “Now, as we move into the next technological age powered by AI and automation, we’ve put ourselves in a good position,” says Gunton.
“Xerox continues to evolve as a company. It recently announced the acquisition of another large managed services IT business called Savvy, which will double the size of the IT services business. That gives us a lot of speciality, a lot of scale, and prepares us for that leap into the technologies of the future.”
Supporting Lanes Group’s technology
Xerox has been supporting Lanes Group in its own growth journey for a few years now. It doesn’t provide print services, but the IT and digital services Xerox is gradually becoming known for. The relationship began during the COVID-19 pandemic, when the working environment was very different. Businesses were trying to figure out how to continue to operate as normally as possible and provide certainty for staff.
“There were just two of us from Xerox working with them, and we were talking about room planning software,” says Gunton. “How do you manage how many people are in the building? How do they book spaces, or manage people in line with the COVID legislation that was in place? The conversation started there. Then, we were asked what we could do around providing some managed service desk support just to assist the internal team at the time – and it’s grown from there. Four years later, we have over 30 members of staff dedicated to the Lanes account, supporting more than 4,000 users across over 50 states.
“We’re very much an operation that compliments Lanes Group. The thing that has always worked well is that we have the ability to respond and scale. Lanes have been on their own journey over the last few years to the point that they’re truly industry-leading, and we’ve managed to keep up whilst always looking to innovate, make suggestions, and bring new solutions to the table.”
An integrated technology partnership
Lanes Group supports key utilities including water and gas. What it does is absolutely critical. If there are problems in those areas, millions of people can be affected. So while Lanes has a huge responsibility to always be ready to support those utilities at all times, Xerox has just as much of a responsibility to be in a position to support Lanes.
“It’s massively important, and everybody in our business is briefed on what Lanes does to ensure we understand that responsibility,” says Gunton. “In my career, I’ve seen lots of different structures in terms of how we work with clients. Sometimes it can be very much a supplier-client relationship where it’s very siloed and formal. What sets our relationship with Lanes Group apart is that it’s a very integrated partnership. There are several meetings every week. There are dedicated program managers, and every product area has its owner. We have very strict SLAs to adhere to and the only way to deliver what Lanes needs is through communication and mutual support.”
Streamlining inconsistencies
A perfect example of the collaborative relationship between Xerox and Lanes Group is the secure network solution Xerox put in place. Effectively, Xerox mapped out and replaced the network infrastructure of all Lanes Group sites, giving better visibility, better control, and a better user experience.
“When we first reviewed the sites, there were over 50 of them running independently. That was difficult for the IT team to manage,” says Gunton. “It led to a lot of inconsistencies. We had mixed feedback from end users. Our aim was to introduce a technology system that would give the users the ability to have a consistent experience across all sites. We worked with our partners at HPE to identify the latest Ariba access solutions available, and deployment across all sites has been very successful. It’s also improved security, giving users the ability to skip length authentication processes. The user experience is really smooth now, which is what we were after.”
Creating agility
Working as partners, not in a supplier-client capacity, has made all the difference for the two businesses. From robot process automation to take manual tasks away from humans, to the increased use of AI-driven tools, Xerox is providing Lanes with what it needs to be agile. It’s a relationship based on trust and a shared goal.
“I do appreciate the help from the stakeholders at Lanes, because they embrace the same kind of culture,” Gunton says. “Often we’ll do joint meetings where we all address the same problem or desire to innovate together. We trust each others’ skill sets and openness to really come up with a solution. Ultimately, it’s all people-driven. It’s based on having really clever people in the right places, and we’ve built up a really solid team over the years.”
The evolution Lanes Group is going through isn’t going to slow down any time soon. That means Xerox’s work won’t either. Gunton states: “Our broad priorities with Lanes also reflect the current UK landscape. Data integration and automation are the areas we’re continuing to focus on. We have to think about how we deliver that. In terms of data, there needs to be one true source. You have to be really confident in the information you have, being as accurate as possible.”
What’s key for Xerox is ensuring that Lanes Group is able to shift from being reactive to more proactive. That is its focus. “We’re already delivering technology solutions to better equip Lanes to respond in that manner. I think the next year is going to be really exciting as we continue to develop that. We believe that we will continue to put Lanes at the forefront of their industry with the solutions that we supply.”
There were many inspiring themes on peoples’ lips at DPW Amsterdam 2024, including collaboration. One of the major reasons procurement…
SHARE THIS STORY
There were many inspiring themes on peoples’ lips at DPW Amsterdam 2024, including collaboration. One of the major reasons procurement professionals flock to DPW is the opportunity to learn from their peers, strategise with them, and make connections in order to partner up and grow. We sat down with Dr Matthias Dohrn and Sudhir Bhojwani, business collaborators of several years who prove the benefits of coming together for growth.
Dohrn is the CPO of BASF, a global chemical company, making him responsible for direct, indirect, and traded goods. Prior to this role he headed up a business unit – and things weren’t going well. It got to the point where the question of how to drive performance became a priority. The business needed to consistently drive value, not just be, in Dohrn’s words, a “one-hit wonder”.
“I’ve been in a lot of meetings where people come together and say, ‘we should do something’ – but the next month, you have the same meeting and nothing has changed,” Dohrn explains. “Structuring an organisation in a manner that really drives and extracts value, that’s key.”
This eventually led to meeting with ORO Labs and asking how it could help BASF build a solution that enabled the growth it needed. Sudhir Bhojwani, CEO and Co-Founder of ORO Labs, knew Dohrn already from his SAP Ariba days He even credits him with explaining what ‘supplier management’ means. When he co-founded ORO Labs, his team wanted to focus on being a procurement orchestration platform and build smart workflows.
“When Matthias was running his business unit, as he mentioned, he had this Excel-based process where he was running thousands of measures,” Bhojwani explains. “It was an interesting process. We let him know that our workflow could solve his problems way more efficiently. So we worked with this business unit at that time and saw some positive results. Roughly a year later, Matthias took over as CPO and wanted to bring in the same structure that we’d implemented at the business unit, but on a bigger scale.”
Kicking off the project
Getting this project off the ground meant having a business case, first and foremost. This required actually sitting down with the people who do the ordering, because procurement needed to understand the options it had. “So, with every plant in BASF – all approximately 150 of them – we had to talk to them, and look at the individual spend of each plant,” Dohrn explains. “This included direct procurement of raw materials, energy, logistics, indirect spend for services, and so on. Then we had brainstorming workshops, generating between 30 and 50 improvement measures per workshop.
“Then, because it’s bottom-up, you bring in the performance management tool to prioritise the measures. Then you go through the business case and confirm the value. As these measures go through the implementation levels, it’s very satisfying because you can see how you’re making progress in driving value every day. The people who own the measures set the timeline themselves, and there are incentive schemes behind the best ideas.”
Driving value to motivate people was a priority from the start, and something BASF discussed with ORO Labs early on. People are able to see the status of their measures thanks to ORO Labs, which means they’re able to see the results and also see other peoples’ great ideas. “You create a wave of people who are driving value, much faster,” Dohrn adds.
Addressing the challenges
From Bhojwani’s perspective, there were multiple challenges when approaching BASF’s requirements. Fundamentally, ORO Labs was building a brand new workflow, as BASF required a very different take on what that means. ORO understanding how that translated to what BASF needed was the first challenge.
“We needed to understand the structure Matthias has, and what the work streams should look like,” Bhojwani explains. “We had to figure out how to model these work streams within our tool in a way that made sense. An indirect work stream is not the same as something in direct material; those things are very different. So here’s where our workflow tool worked quite well. We could customise how direct material work streams should behave, compared to indirect work streams, how country A should behave compared to country B, and so on.
“It was important that we could bring flexibility, and that we could solve workflow problems in innovative ways. Another challenge was the user experience part. We had to make sure that the system worked for everybody, otherwise nobody would participate in the system. We had to keep working on it, keep fixing it, and that took a good 18 months of tweaking. The biggest thing has been understanding how BASF actually generates value, and how a workflow can help. It’s been very interesting.”
Identifying the value
Collaborating with ORO Labs has unlocked an enormous amount of value for BASF. Dohrn has seen the business come together thanks to the work that was put into communicating and collaborating with every site across businesses and functions, and BASF is continuing to conduct workshops for further improvement. There’s also, of course, the EBIT being gained from the business cases, putting BASF on track to generate sustainable savings.
“There’s been a real mindset change,” Dohrn states. “We’re now really focused on value, and we’re using this ORO Labs tool to hold each other accountable. You can see the progress every day. We call it the iceberg because you can see below the implementation levels. Everything starts off below the water line – no value created yet, just potential. Then you see it moving beyond the zero line into the positives, and every day I can see the difference between now and yesterday with just a click. It’s so fulfilling to see what we have created.
“We’re able to see the interaction with the plants, the interaction between people, and interaction with the requisitioners, and we can create something positive together. I think that’s huge. It’s only going to bring more and more value over the next few years. People are used to the tool now, they find it easy. It has created value and everyone’s happy because the cost pressure on the plants has gone down.”
Tonkean is built differently. Tonkean is a first-of-its-kind intake and orchestration platform. Powered by AI, Tonkean helps enterprise internal service…
SHARE THIS STORY
Tonkean is built differently.
Tonkean is a first-of-its-kind intake and orchestration platform. Powered by AI, Tonkean helps enterprise internal service teams like procurement and legal create process experiences that transform how businesses operate. The transformation hinges on four key functionalities, intake, AI-powered orchestration, visibility, and business-led configuration (no-code), which internal teams leverage to use existing tools better together, automate complex processes across teams and tools, and empower employees to do better, higher-value work.
Jennifer O’Gara is the Senior Director of Marketing, Director People and Talent at Tonkean. O’Gara’s route into procurement came when Tonkean became active within the space. “While we initially focused on solving complex process challenges across entire enterprises, we quickly realised how much procurement could benefit from this approach,” she explains. “Procurement processes are inherently complex and collaborative and cross-functional, making them a perfect fit for Tonkean’s orchestration capabilities. We were right. Since we entered the market, we’ve been blown away by how enthusiastically process orchestration has been received. That’s keeping us excited about procurement.”
This year, DPW Amsterdam 2024’s theme was 10X, with a focus on the importance of companies aiming for a moonshot mindset instead of an incremental approach. As far as O’Gara is concerned, achieving 10X improvements in performance is within reach for procurement, but it requires a shift in how the function thinks about growth. “It’s not just about doing more of the same faster—it’s about fundamentally rethinking the processes that drive your business,” reveals O’Gara. “Your processes are like your company’s infrastructure. When you optimise at the process level, you don’t just create incremental gains; you can fundamentally transform the way you operate at scale. You can remove bottlenecks permanently, facilitate easier collaboration org-wide, and drive true, reliable automation across all your teams and systems. The result is exponential performance improvements that can be sustained over time. Aiming for 10X isn’t just a lofty goal—it’s achievable. The key is focusing your improvement efforts at the process level.”
However, the journey to 10X isn’t straightforward. Some organisations believe they can just layer new technology on top of old processes. According to O’Gara, this won’t unlock 10X growth and will still leave your company lagging behind. “Getting to 10X starts, instead, with building better processes—and moving away from the idea that any one technology will do the trick,” she says. “For example, AI. AI is powerful, but it’s just a tool, and it’s only valuable if used strategically. To truly unlock 10X improvements in performance, you need to integrate technologies like AI into your core processes in a way that’s structured, strategic, and scalable. You will only ever be as innovative or adaptive or as effective as your processes are dynamic, dexterous and dependable. How do you build better processes? That’s where process orchestration comes in.”
Process orchestration refers to the strategy — enabled by process orchestration platforms — of coordinating automated business processes across teams and existing, integrated systems. These processes can facilitate all procurement-related activities. Importantly, they can also accommodate employees’ many different working preferences and styles.
Instead of simply adding to an organisation’s existing tech stack, process orchestration allows companies to use their existing mix of people, data, and tech better together. One promise of process orchestration is to finally put internal shared service teams like procurement in charge of the tools they deploy.
This goes a long way towards solving one of the enterprise’s most vexing operational challenges: the inefficiency of over-complexity born of too much new technology. It also allows procurement teams to truly make their technology work for them and the employees they serve. As opposed to making people work for technology. Process orchestration breaks down the silos that typically separate working environments. No longer do stakeholders have to log in to an ERP or P2P platform to submit or approve intake requests, just for example. The technology will meet them wherever they are.
“It helps you create and scale processes that can seamlessly connect with all of your existing systems, databases, and teams, while accommodating the individual needs of your employees and meeting them in the tools they already use,” adds O’Gara. “Orchestration allows you to automate processes across existing systems—like ERP, P2P, and messaging apps—so data flows automatically between them. It allows you to surface technologies like AI when and where they’re most impactful for stakeholders.”
Speaking of AI, it remains one of the biggest buzzwords in procurement. Indeed, anything that offers Chief Procurement Officers cost savings and efficiency will prick their ears, but the question remains: can the industry fully trust it? O’Gara believes it is ‘overhyped.’ “When it first emerged, it wasn’t just seen as a new tool—it was almost treated like magic,” she explains. “The hype still hasn’t died down, and that’s been a problem. It’s created unrealistic expectations and skewed perceptions of what innovation with this sort of technology actually entails; I can’t tell you how many procurement leaders have admitted to us that they’re getting pressure from the C-suite to invest in AI-powered tools just because they have ‘AI’ in the name.”
While clear with her scepticism regarding generative AI’s current place in the market, O’Gara recognises its potential. “Generative AI’s potential is huge—especially if it’s deployed strategically at the process level,” she reveals. “It could truly transform procurement, shifting teams from transactional roles to strategic partners who are involved early in the buying process and appreciated for their unique expertise—and for the unique business value procurement alone can deliver. But AI on its own isn’t going to save procurement. The reality is, many organisations jumped into the AI hype without a real strategy, and that’s why they haven’t seen its full value yet. The key is integrating AI thoughtfully into core processes—that’s when we’ll start seeing its real potential.”
With an eye on the future, O’Gara expects the next year to continue to revolve around AI adoption, but in ways that deliver real value. “I think we’ll see procurement truly stepping into a more strategic role, with businesses recognising procurement as a key partner, not just a back-office function,” she says. “This shift will be driven in part by new technology, especially process orchestration and AI, helping procurement bridge gaps in communication and collaboration across teams. Another big trend will be the rise of personalised, consumer-like experiences in procurement—making buying and approval processes smoother, more intuitive, and better tailored to the needs of individual users. It’s an exciting time, and we’re just scratching the surface of what’s possible.”
The buzz of DPW Amsterdam draws in the most innovative minds across the industry. They’re there to have riveting conversations…
SHARE THIS STORY
The buzz of DPW Amsterdam draws in the most innovative minds across the industry. They’re there to have riveting conversations with their peers, to inspire, to teach and learn in kind. And they’re there to keep an eye on an industry that doesn’t stop changing for the better.
This is a big part of the appeal for Fraser Woodhouse. Woodhouse leads the digital procurement team within Deloitte in the UK. His team historically focused on large-scale transformations, providing a backbone for suite implementation. Increasingly, however, it’s turning its attention to helping clients navigate a plethora of technology solutions. The goal is to help them build and scale, and take advantage of some of the more niche functionalities available. These are things that can be highly daunting for many customers, which is why Deloitte is there for support.
“We’re helping clients ask the big questions,” Woodhouse explains as he sits down with us at DPW Amsterdam 2024. “How do you connect the technology in a way that allows data to flow from one system to another? How do you deal with processes that are connected to solutions which all have their own release cycles? How do you approach change management? That underpins so much of where the value is going to be achieved, and a lot of the providers will be focusing on it. They just might not have the same capability that Deloitte can provide.”
For Woodhouse, getting involved with procurement was a total accident. He even left the sector at one point, but his strong foundational knowledge – and the exciting landscape procurement is enjoying right now – lured him back in. “It changes faster than I can get bored with it, that’s for sure,” he explains. “Procurement is fascinating.”
Aspiring to greatness
Especially now, with constant conversations around genAI, 10X, and beyond. Procurement is only becoming more interesting, more enticing, drawing young professionals in to fill gaps in the talent pool. 10X was actually the theme of DPW Amsterdam this year, a notion that’s on everyone’s lips. And for Woodhouse, it’s absolutely something to aspire to.
“Aiming for 10X is sensible. You just have to consider your timescale. I’d caution against running before you can walk, but a culture of experimentation is important. Running small-scale pilots can help you hone in on where you really want to see value, or where value is likely to be generated. Starting with requirements is a fundamental thing at the moment, but you shouldn’t underestimate how long that will take. And it’s a continuous consideration, because requirements change. Just keep trying to refine your solution in order to take advantage of everything that’s out there right now.”
Fotograaf: MichielTon.com
Having the wrong mindset is one of the major barriers to adopting 10X thinking. It all starts with the company’s culture, and whether that’s one of growth or not. “I imagine most of the people here at DPW Amsterdam have already made that mental shift,” says Woodhouse. “Last year, people were still trying to understand how they, as big companies, could utilise startups. That’s changed now, and it’s amazing to see companies that were startups three years ago working with all these big enterprise customers.
“They have scaled and grown in partnership with those customers. Mindset is so important, and having the wrong one will only create barriers and missed opportunities.”
Always improving, never slowing down
When it comes to the advantages that technology has brought to procurement in the last few years, the list is endless. Procurement has gone from an overlooked segment of any given organisation, to having a seat at the table and helping make major business decisions. 10X thinking – whether it goes by that name or not – has been spreading across the segment and fuelling businesses to aim higher.
“The layers of automation have really improved,” says Woodhouse. “A year or so back, there were a handful of use cases that you could truly automate, but now you can do it at a much larger scale. Another big change is around security concerns. There are more tried and tested case studies to draw upon now, and solutions are more readily available. You don’t necessarily have to be a pioneer, because someone else has already taken that first step.”
The question of data
Something else that holds businesses back, despite the innovation at their disposal, is an element that can be harder to change: poor quality data. When trying to implement advanced technology solutions, bad data can make or break their success.
“It’s always useful to focus on that and have a dedicated work stream,” Woodhouse advises. “You need someone who really understands data. I think there’s a tendency to try to boil the ocean before you even get going in your transformation, which isn’t necessarily a bad thing. Cleaning up your data before you start, and having a fresh foundation will help you make decisions on what to implement on top of that good data.
“Doing all of that is obviously hugely beneficial, but it’s going to slow you down, in many cases. There are ways around that, like embedding the cleanup of data within the new processes. Data is important – we shouldn’t underestimate that – but there are different approaches to solving the issue of poor quality data, like buying it or using genAI to restructure your data into something more powerful. Either way, you need a strategy.”
Novel thinking 101
Some businesses fall into the trap of thinking that they can’t achieve specific things because their data isn’t in the right position, but novel thinking around data can allow them to still drive forward. “You’ve just got to focus on it. You can’t assume the data’s going to fix itself,” Woodhouse adds.
Novel thinking is certainly something that can be seen at DPW events, and DPW Amsterdam 2024 was no exception. People congregated there to learn, to share stories, to inspire. For Woodhouse, the magic of the digital procurement sector right now is that everybody recognises that their journey has no end. While that may be daunting, it’s a positive thing and keeps procurement professionals striving for more.
“It’s a continuous improvement journey, and I think the best-performing organisations will recognise that, and invest in the business capability to continue that journey,” Woodhouse concludes. “That’s how you get proper value. I love hearing about how people frame problems differently, and how they approach the solutions.”
Making procurement slicker, more streamlined, is the name of the game right now – and this is precisely why Globality…
SHARE THIS STORY
Making procurement slicker, more streamlined, is the name of the game right now – and this is precisely why Globality exists. It’s an organisation which leverages advanced, native-built AI to make sourcing more autonomous for Fortune 500 and Global 2000 companies, meaning it has a finger on a pulse of the technology tools procurement now has access to as the industry shifts and evolves.
Keith Hausmann is the Chief Customer Officer at Globality. He has been working in procurement since the early 90s, both in industry as a service provider, and now, at a technology company. He came to Globality from Accenture, where he ran the operations business. During his first real job after college, Hausmann was also part of a training program at a major Fortune 500 company, working closely with a COO. At some point they got into a conversation about salespeople seemingly having an advantage over procurement people due to their access to information, knowledge, and training. The COO suggested that they launch a company to help support procurement. For Hausmann, it was a serendipitous entry to the industry.
“I came to Globality because I saw the business was struggling with how to scale, automate, and deliver a differentiated user experience. Ultimately, I found it really compelling, and joined about five years ago.”
Achieving 10X thinking
Hausmann admits that the concept of what procurement is has only been defined relatively recently, and he’s been in the industry long enough to have seen the shift happen and suddenly accelerate over the last few years. Now, procurement professionals are in a position where they’re able to think big, and they have the tools to support that way of thinking. One of the most-discussed topics right now is 10X, whereby businesses are setting targets for themselves that are 10 times greater than what they can realistically achieve.
“There continues to be, and always has been, so many mind-numbing manual activities that go on in procurement spaces,” says Hausmann. “We’ve built small armies of teams to handle those things. I think 10X has prompted us to take a step back and ask if there’s now technology that can uplift the role of people in the function and take on some of those automatable tasks. Whether that’s writing RFPs, discovering suppliers, or analysing proposals – these are all things that can be automated in today’s technological world. With 10X thinking, you can imagine the many, many, many things that can be automated and just go after them.
“There are barriers, of course. The biggest one is not being able to convey a compelling vision of what we want people to do in the new world. It’s not necessarily about making them go away – it’s about making their daily jobs, lives, and work more valuable. There are so many things around category thinking and strategy that don’t get done because people are spending so much time on tasks that could be automated. So I think the barrier is creating that vision and that plan to shift the operating models, roles, and the skill sets to something new and different.”
People power
Hausmann believes that if roles are reshaped and honed in response to automation, it’s less likely that there will be resistance to change because employees will know exactly what they’re doing, rather than being concerned about their future. “They have to know what they’re doing before they jump on board. It just requires a mindset change and good change management.”
Hausmann believes it’s down to the CPO to drive that change management by conveying the activities, impacts, roles, and operating model they envision. If they can paint a picture of how humans can impact things in a new way, alongside the new technology rather than against it, suddenly it’s an exciting prospect and people are keen to make a bigger impact.
CFOs and CPOs joining forces
While CPOs now have a long-deserved seat at the table to help push change business-wide, CFOs’ roles are also expanding and having an increased impact on procurement. “I think they’ve always influenced what’s going on in procurement,” says Hausmann. “CFOs are the champions of many things, but certainly improving the bottom line of the company. They’re also champions of using technology to make the organisation more resilient, more scalable, and more efficient. There was a time when people thought that the CTO or CIO would be doing that, but more often than not, the CFO is the ultimate owner of improving business impacts. More and more, we’re seeing our customers leaning on the CFO to help them make decisions about investments that have a big impact through technology and AI.
“These days, the relationship between the CFO and CPO is wildly different to what it once was, and CFOs are showing more interest in procurement as a function than ever, making a difference to the bottom line. It makes sense because, in theory, procurement controls one of the biggest cost line items in a company, besides raw headcount.”
Matching the pace of technology
The fact that we still need to focus on change management and relationships confirms that the way procurement is changing isn’t just about the technology. Far from it. However, technology is moving at an incredible pace and needs to be taken seriously. There are things that are possible now which couldn’t be done even one or two years ago.
“A few years ago, technology couldn’t write an RFX document for you,” Hausmann says. “Technology could not instantaneously bring to light the most relevant suppliers from within a customer’s supply base, or in the broader market. It couldn’t write a contract, or an SOW, or a work order. It can now. Those are things that are near and dear to my heart that were impossible 3-5 years ago.”
With these tools in mind, procurement professionals are able to think about the future in short-term stints. Five-year plans are no longer good enough when it comes to the way procurement is shifting – a year is now the maximum for putting plans in place.
“I’ve always thought that procurement, from the perspective of technological advancement and investment perspective, should sit under a broader business umbrella,” says Hausmann. “I’d guess that probably 50% of companies in the world right now have some kind of program in place to save money or improve agility by investing in technology. And speed to market is more important than ever, so sourcing can’t be a bottleneck.”
Looking ahead, Hausmann expects to see many of the unique, differentiated technology providers becoming interoperable together, because big enterprises want services that operate and scale well in combination with others.
“We’re seeing that a lot, and working with our customers on how we improve interoperability and integration,” he says. “Tools will become more seamless, more easy-to-use, more scalable. Another big thing is, and will continue to be, analytics. It’s a hot topic in procurement, and I think there are profound opportunities to be deployed. For Globality, we’ll continue to endlessly innovate on user experience, ease of use, and beyond.”
“I’m overwhelmed,” are Matthias Gutzmann’s first words when asked about DPW Amsterdam 2024. At the end of the bustling two-day…
SHARE THIS STORY
“I’m overwhelmed,” are Matthias Gutzmann’s first words when asked about DPW Amsterdam 2024. At the end of the bustling two-day event, we sat down with Gutzmann, the company’s founder, and Herman Knevel, DPW’s CEO, for a debrief. Gutzmann also quite rightly pointed out that the final word on summarising those 48 hours is in the hands of the sponsors and attendees, but if the countless conversations we had with said sponsors and attendees are anything to go by, it was the best DPW event yet. And Gutzmann and Knevel agree.
“I really think that’s the case,” says Gutzmann. “We almost doubled the number of exhibiting startups, we had over 120 sponsors, more startup pitches than ever, and all the feedback I’ve heard so far has been amazing. There are always things you can do better, but I’m absolutely happy.”
Across the 9th and 10th of October, DPW Amsterdam welcomed over 1,300 attendees through its doors at Beurs van Berlage, Amsterdam. Those attendees arrived from 44 countries across 32 industries, and the event itself featured 72 sessions with 140 speakers across five stages. It’s abundantly clear that people are deeply passionate about DPW.
“On day one, it was already packed at 8:30 in the morning,” Knevel states. “The energy in the room was contagious, and the numbers speak for themselves. The startups, the innovators, the corporates, the mid-market – everybody who’s here has a genuine interest in what these guys are bringing to the procurement space.”
Reconnecting with the vision
Gutzmann describes that intangible energy as “bringing a little bit of joy back to procurement”. For many years, procurement was a very ill-defined concept – almost as ill-defined as the role of CPO. The shift has been a quick one, accelerated further by the COVID-19 pandemic, and events like DPW Amsterdam are part of the reason why. CPOs having somewhere to go, to meet, to learn about the procurement landscape is vital, hence that inspiring energy that permeates every DPW event.
“A lot of people are missing that vibe,” Gutzmann continues. “It’s why I founded DPW. I was inspired by Mark Perera [Chairman of DPW], who I worked with at Vizibl, and had great technology while also being so inspiring. I realised we needed to connect founders with CPOs. I think every CPO should talk to one startup founder per week, at least. It’s important that we listen to their vision.”
Striving for 10X
The core of those visions for the 2024 event revolves around the concept of 10X, the idea being that you set targets for your business that are 10 times greater than what you think you can realistically achieve. It keeps people ambitious, always striving for greatness, and it’s especially prevalent in startup culture – hence Gutzmann’s belief that CPOs should be connecting with them more.
“Deciding on 10X for this year’s theme was serendipity,” says Knevel. “The term came along and Matthias said, ‘this is it – this is what we need in procurement’. This is what the industry needs, and we’re exploring it, diving deeper.”
“Last year’s theme was ‘Make Tech Work’, which was all about getting the basics right in order to scale,” Gutzmann continues. “This year we said, ‘how can we take it further?’ We are entering the biggest wave of AI yet. That technology is giving us the opportunity and the possibility to scale outcomes. The world around us is changing so fast, so we need to be more agile, scalable, and faster in procurement. It’s a very ambitious, maybe lofty theme, but it’s a mindset more than anything else.”
“It’s the mindset that drives innovation and speed,” Knevel adds. “That’s really important in this age of procuretech and supply chain tech.”
When it comes to honing that 10X mindset, it’s all about having a purpose in mind. A lot of the procurement professionals we spoke to at DPW Amsterdam called this a ‘north star’, which is the phase Gutzmann uses too. “That’s where it starts. There’s so much procurement can do. There are so many problems in the world, and I believe procurement can be the solution to many of those. So I think it starts with the CPO and their leadership, their vision. You also have to embrace startup innovation, be more experimental in the way you work, instigate new ways of working, and be bold in your thinking. You also have to remember it’s okay to fail.”
Growing DPW
Something that’s particularly impressive about DPW Amsterdam 2024 is that it’s actually the second of the year. Back in June, DPW ventured into the North American market with an intimate summit held in New York City, which CPOstrategy was fortunate enough to be invited to. Planning one wildly popular event a year is one thing, but venturing into a whole new part of the world with an additional one is incredibly dedicated.
“I’m a bit more conservative when planning ahead, so there probably wouldn’t be a New York event without Herman encouraging me,” says Gutzmann. “I’m glad he said ‘let’s go for it’. It was a short-term plan, but it was ultimately very successful and the right decision.”
Knevel adds: “The feedback we got from sponsors and delegates was quite impressive. They were asking for more. And it’s not just Matthias and myself – we have a great team here. This is a massive production, but we made the jump and it’s paid off.”
Inspiration for 2025
When it comes to the lessons Gutzmann and Knevel have learned in response to this event, it’s more about narrowing down the influx of ideas DPW gives them. By the time we spoke with them at the end of the Amsterdam 2024 event, their heads were spinning with inspiration.
“I have so many ideas,” says Gutzmann. “Every year we reinvent the show, so we never rest. We’re always asking what we can do better. How can we improve? I think this year we maxed out the number of sponsor stands that are possible to have. We doubled the number of under-30 attendees. There’s the potential to go a little deeper on the talent side, connecting students with the corporates and building a proper program around that.”
There was also the Tech Safari this year. The idea was to make the expo hall easier to navigate, since it was more crowded than ever this year. Members of the DPW team acted as ‘super connectors’ to help attendees find the right solutions and help startups find new customers. The aim was to simply make it easier for everyone involved to find what they’re looking for in small groups,enabling them to find who they wanted, talk to them, and ask questions. It turned out to be an amazing interactive experience for people, making sure they felt thoroughly looked after and valued.
“Plus there’s an opportunity to cater more to the corporates coming in,” Gutzmann continues. “Perhaps we will build a custom program for them around the event. Some of them are already coming in with teams and doing annual leadership meetings outside of the venue, but I think there’s scope to show them solutions and do some workshops within the event. We can also do more with day zero, where we have site events. There’s much more we can do.”
Giving CPOs what they want
As for the broader future of the event, DPW’s heart lies in Amsterdam and will continue to do so. The organisation is building its team even further and putting strategies in place for future events, allowing it to move forward. “We follow the demand of what our customers want,” Knevel says. That’s what really drives DPW and how the event is themed and set up. The organisation listens to CPOs so it can give them exactly what they need, and what will help the industry level up further and further.
“There are things we’re still developing,” says Gutzmann. “For example, the podcast studio [something introduced in its current form for 2024] is something Herman is very passionate about, so it was great to test it out here. There’s more we can do with that. We have so many ideas and it’s important to engage our amazing team on these ideas and see what they think along the way.”
“We’re ideating a lot,” Knevel adds. “And we’re asking our ecosystem what we should do more of.”
“Ultimately, we’re bringing in the voice of the customer to make sure we’re giving them what they want and need,” Gutzmann concludes. “That’s the whole purpose of DPW.”
It’s impossible not to be inspired by the energy at a DPW event. DPW Amsterdam 2024 was buzzing with that…
SHARE THIS STORY
It’s impossible not to be inspired by the energy at a DPW event. DPW Amsterdam 2024 was buzzing with that same energy, its attendees soaking in information and inspiration from speakers, peers, other experts. We caught up with Rujul Zaparde, Co-Founder and CEO of Zip, at the event to dive into the procurement landscape and chat about the specific qualities DPW brings to the sector.
Zaparde is the Co-Founder and CEO of Zip. At the beginning of Zip’s journey, Zaparde and his fellow founder, Lu Cheng, based the company around their own experiences as end-users of the procurement process. They took their lived confusion around having multiple intakes for a contract, for the purchase request, and all the different complicated components of the process, and created a solution.
“And so, we started Zip and created the category of intake and procurement orchestration. We’re very grateful to have been named the leader in the category,” says Zaparde, in reference to having just been named a category leader in IDC’s first ever Marketscape for Spend Orchestration.
So, as is often the case, procurement is something Zaparde fell into. In this case, he got involved with procurement specifically to solve pain points. Prior to Zip, he was a Product Manager and Cheng was an Engineering Leader, both at Airbnb; they knew very little about procurement. “We were just end-users,” he explains. The upside of this was that they were able to come into the industry fresh, without the baggage and legacy issues that can come with being in a sector for a long time.
UX first
“At Zip, we really try to take a user experience first approach,” Zaparde continues. “What we found is the highest leverage change you can make in any procurement organisation is to make it easier for your employees to actually adopt and follow whatever the right process is. If you do that, then all of finance, procurement, accounting, and even IT find that they’re suddenly swimming with the current, not against it. And you can’t do any of that unless you solve for user experience.”
Taking away problems, the way Zip does, also takes away a barrier to ambition. The theme of DPW Amsterdam 2024 was 10X, a term on the lips of many across all sectors. Once immediate issues and pain points are addressed, 10X is something businesses can aspire to, with many talks and workshops during DPW Amsterdam focusing on how to approach this.
Getting the mindset right
For Zaparde, 10X thinking is a necessity for growth. “You have to aim for 10X to even end up at something X,” he explains. “That requires ambition. I also think that when you think in terms of 10X, and your mindset is angled towards incremental change, you’re much more open to thinking of solutions that are perhaps a little more risky. It changes your perspective.”
A mindset shift needs to happen before anything else. This involves considering the needs of procurement and the wider company, having a north star in mind, and then breaking changes down to an incremental level.
“Then you can start to think about the steps you need to take to get there,” Zaparde explains. “A big component of this is bringing along your peers and stakeholders across every function that’s tangential and critical to the core procurement workflow and path.”
Innovating for good
The work Zip does is indicative of the shift towards continuous improvement and advanced technology that procurement has been going through in recent years. There are things that are possible now that weren’t possible even a year ago, thanks to the vast innovations being made. One of the hot topics right now is generative AI, something that’s opening up a world of possibilities.
“It’s the elephant in the room right now,” says Zaparde. “With the capabilities that gen AI unlocks, you can automate a lot more. That allows you to cut down a lot of the transactional and operational work that procurement and sourcing organisations are doing. Procurement is tired of the status quo. It’s been an underserved function for over 20 years, and I’m glad that’s finally changing. I feel privileged for myself and Zip to be part of the conversation, and that we’re seeing all these amazing changes happening.”
Zaparde believes we’re already seeing the benefits of the major changes that have occurred over the last couple of years in procurement. In fact, he knows this, because Zip has helped its customers save around $4.5bn of spend over the last two years, which is an astonishing statistic.
“One customer of ours, Snowflake, achieved over $300m in savings alone,” Zaparde continues. “We’ve seen tangible benefits already. The way procurement is evolving isn’t a hypothetical thing – it’s really happening.”
Fragmentation on fragmentation
The key, again, is overcoming base level issues for the sake of evolution. This is precisely what Zip provides, after all. But sometimes, the issue is at a data level. Unclean data is something that technology leaders are talking about a great deal right now, with some feeling that it holds them back from implementing new technology. Zaparde believes that businesses should be questioning why their data isn’t clean from the start, rather than worrying about trying to cleanse existing data.
“You don’t just clean your data – the real question is why is your data not clean in the first place?” he muses. “You have to have a clean entry point for it. I don’t think I’ve ever spoken to a Fortune 500 CPO that said they had clean data. I think it’s because of the upstream processes in intake and orchestration. If all the cross-functional teams – the IT review, the legal review, the finance – are being manually shepherded by the procurement operations organisation, then how can you possibly end up with clean data?
“People are keying the same information into multiple systems, which might mean they answer in similar – but different – ways. So you end up with fragmentation on fragmentation. But if you have one single door to that data, you’ll be able to drive only clean data, because it’s a funnel. If you let everyone have different swim lanes that never intersect, you won’t have clean data.”
As 2025 approaches, Zip has multiple product capabilities and features coming up that Zaparde and his team are very excited about. This includes leveraging gen AI, something we’re seeing incredible utilisation of across the sector.
For Zaparde, attending events like DPW Amsterdam to talk about what Zip does and interact with peers and clients alike is a joyous part of his job. “DPW is really accelerating the rate of change in the procurement industry. That’s very much needed, and it’s energising to see so many incredible people from the procurement world in one place. I love spending time with these forward-thinking procurement leaders at this event.”
Whether we’re talking about gen AI, 10X, or any other kind of advanced tech solution, data is at the core…
SHARE THIS STORY
Whether we’re talking about gen AI, 10X, or any other kind of advanced tech solution, data is at the core of the discussion. And when data isn’t clean or ready for the implementation of something being built on top of it, businesses can end up significantly held back. Mithra-Ai is an organisation that helps its customers to build trust in their data, which is a core issue for many.
“That sets us apart,” says Christophe Frère, Co-Founder of Mithra-AI. “We help procurement leaders and category managers create, execute, and realise their strategies. This is backed by reliable, comprehensive data, both internal and external, tailored specifically for their categories.
“Maintaining high-quality data is crucial as it influences the accuracy and reliability of AI-driven insights and recommendations. That’s where Mitha-AI comes in. Our cleansing, enrichment, and auto-classification engines ensure that procurement stakeholders, including data scientists, begin with a reliable data foundation.”
Cleaning and classifying data
Mithra-Ai is an AI-native SaaS solution, which starts off by proposing a meaningful spend hierarchy for every category. What’s key is that this is paired with an automated cleansing and classification engine. This is so important because the only way to achieve truly clean data is to make sure it enters the system clean in the first place.
“Clear visibility into categorised spending eliminates uncategorised expenses and wrong assumptions,” says Frère. “When supplemented by relevant external data intelligence, category managers are empowered to negotiate with confidence, achieve greater savings, and monitor initiatives effectively.”
A world beyond cost savings
When launching Mithra-Ai in 2021, the company’s founders rightly foresaw that the role of procurement would evolve beyond focusing merely on cost savings, and become the central hub of every organisation. Because of that, they knew that accurate, reliable information was needed – hence the necessity for Mithra-Ai.
As procurement has shifted, the status quo is no longer good enough. It’s an exciting time for the sector, but also one of high demand in the race to adopt increasingly advanced technology. But it’s necessary for efficiency and growth.
“Tesla and Nvidia exemplify the power of embracing change over maintaining that status quo,” says Frère. “Procurement is facing intense pressure to evolve with organisational needs. Those organisations can opt for incremental changes, which will likely slow them down, or pursue a 10X leap to maintain competitive advantage. The latter requires bold and decisive leadership from heads of procurement.”
The road to 10X thinking
The way to drive 10X thinking, Frère believes, is through having a clear vision of your goals. Sometimes businesses, especially ones which are going through major change or those navigating outdated legacy systems, are at risk of losing sight of their goals. But having that vision is a foundational necessity, regardless of what stage you’re at.
“Set aspirations high, and question existing norms,” says Frère. “Procurement leaders can draw inspiration from startups by fostering a culture of innovation through small-scale initiatives that can rapidly expand. Reevaluate the skills and team structure necessary for future success.”
Another important aspect to bear in mind when considering these things is the level of risk you’re willing to undertake when setting goals and aspirations. “That’s often overlooked,” Frère continues. “Determining the acceptable level of risk is crucial. It significantly influences partner selection and the outcome of RFPs.”
Thinking big, starting small
While ambition is vital to 10X thinking and beyond, businesses must also make sure they don’t bite off more than they can chew. Launching into adopting huge volumes of advanced technology can lead to overwhelm and can make a business stall rather than evolving. A more careful approach is required.
“Think big, start small,” says Frère. “Prioritise high-impact, low-effort initiatives over those requiring significant effort. Many transformation projects fail to deliver the expected benefits and incur high costs during the program.” This is another reason to decide on the appropriate risk level early on, in order to guide prioritisation decisions and transformation pace.
It’s an incredibly exciting time for procurement, and that includes Mithra-Ai. In a very short time, it’s developed several foundational modules for its data-driven category management solution. This includes the Collaborative Initiative Tracker that was launched during DPW Amsterdam 2024 – just one of Mithra-Ai’s inspiring undertakings as we approach 2025.
“The tracker means that procurement teams can now involve multiple stakeholders in collaboratively tracking and enhancing the impact of key initiatives, such as cost-saving measures,” says Frère. “Exciting times lie ahead.”
DPW Amsterdam is the perfect stage for launching a solution like this. It’s an event that inspires a culture of innovation, bringing procurement professionals together to teach, learn, and shout about their latest additions to the procurement landscape.
“DPW stands out as the premier procurement tech event of the year,” says Frère. “Practitioners can explore and engage with procuretech suppliers, showcasing valuable use cases and personal stories across multiple stages. DPW is a catalyst for ideation, creating trust and confidence in the benefits of applying cutting-edge technologies to improve business outcomes. This year’s event felt even more international than previous years. I look forward to seeing it continue to grow.”
Frère’s main takeaway from DPW Amsterdam this year is that a solid data foundation is essential – something he was well aware of as part of Mithra-Ai. “Without it, transformation projects and new technologies will struggle to succeed,” he concludes. “In the past two years, there has been increased focus on sustainability and risk intelligence, driven by numerous new solution providers. However, during the DPW Amsterdam 2024 conference, we observed new trends coming up and, again, more focus on data quality, which works to our advantage.”
When we’re talking about technology in procurement, the importance of partnership is a major component for success. No business is…
SHARE THIS STORY
When we’re talking about technology in procurement, the importance of partnership is a major component for success. No business is an island, and joining forces with experts is, increasingly, the direction many move in for the sake of growth.
At DPW Amsterdam 2024, we met many businesses who were looking around at the procurement sector in search of either what direction to move in next, or who they can help. The event is one that brings people together to learn, to teach, to discover the cutting edge of procurement, and be inspired by it. So when we sat down with the CEO of Fairmarkit, Kevin Frechette, it wasn’t surprising that he brought Nick Wright, who leads bp’s Procurement Digital Garage, into the conversation.
For Frechette, one of the best things about working in the advanced procurement technology sphere is joining forces with other businesses to help them keep improving, and vice versa. “Having the chance to work with people like Nick, who are pushing the envelope when it comes to autonomous sourcing, is amazing,” he explains. “We’re fired up to be at DPW, absorbing this atmosphere.”
While it’s something of a running joke in the procurement world that most professionals in the sector don’t deliberately choose it, Wright actually did. “I went to university and thought ‘wow, I fancy a career in procurement or vendor management’. I know a lot of people don’t have that story, but I’ve been doing something I’m passionate about from the beginning. I love making deals, whether I’m buying a car, a house, or something for BP.” The Procurement Digital Garage he leads exists to look at problems being faced across procurement, and figuring out possible solutions.
For Frechette, the intention wasn’t to start a company in the procurement space, but his team quickly saw the opportunities within it. “We had this ‘aha’ moment,” he says. “It was a tough pivot. There was a lot of debate, a lot of late nights. I’m super glad we made it because we got to be in a space where people can be forgotten about, and we’re able to give them centre stage.”
The realistic approach to 10X
DPW itself exists to put procurement under the limelight. Each event is themed in a way that gets conversations flowing around the next big thing in procurement. For Amsterdam 2024, this theme was 10X – something Frechette believes isn’t achievable right off the bat.
“It’s something to strive towards,” he says. “It’s something where you work on getting a little better every single month, every quarter. You keep getting those small wins, and you build credibility. There’s no silver bullet. You just have to start the journey and learn as you go.”
For Wright, it’s about not getting caught up in the hype, but figuring out what’s realistic. “There’s a lot of hype out there, and the beauty of something like my team at the Procurement Digital Garage is to weed out that hype, because what’s right for us might not be right for someone else. Having a team that’s out there in the market, testing and figuring out what’s real, will put you in good stead.”
“There’s a leap of faith element that can be challenging to achieve, before you can really strive for 10X,” Frechette adds. “It’s like Amara’s Law: humans typically overestimate the value of technology in the short term, but underestimate it in the long term. So the hype is needed. We have to help people on that journey and sometimes, a leap of faith is needed. For the people that risk it, it’s exciting, and they’re then well positioned for the future.”
However, again, managing expectations is important. “People might be on the sidelines expecting a 10X solution,” says Wright. “But the reality is, you’re going to get 5% here, 10% – smaller pockets of improvement.”
The benefits of advanced technology are absolutely being seen at this stage, but being realistic about the future outcomes is important. “The benefits are there – not at the scale of 10X – but if you just make a start, you’ll achieve wins,” says Frechette. “You broadcast those wins across the organisation. That generates excitement, and then you can work on the next thing because you have ground swell.”
How ‘the future’ has changed
What’s interesting is that this 10X focus, this drive towards incremental wins, has reframed the way businesses plan for the road ahead. ‘The future’ used to mean having a three or five-year plan. Now, the future is only 12 months away.
“The thought process right now is ‘what can we do that’s super optimistic in just 12 months’?” says Frechette. “Then you can put in realistic time frames and set off on a sprint to get there. You have to be able to move fast. We have launches every two weeks now, and we have to be flexible with our roadmap along the way. But we always know where we’re going – we have a north star.”
“To me, that’s the only way to do it,” Wright adds. “I don’t have a crystal ball. Nobody knows what’s going to happen in two or three years. So what’s the point of creating a plan that’s going to get you to a certain point in those two or three years? You have to work on small iterations, make adjustments, change direction as necessary.”
It’s part of what makes Fairmarkit and BP an active partnership – the ability to be flexible and open up discussions at every point. It’s all about real-time feedback and trust-building, to the extent that both parties feel like they’re on the same team.
The right people in the right places
Because ultimately, it’s the human element that makes transformation happen. Having the right people in place is one of the elements that’s key to making sure implementing advanced tech for the sake of business strategy works at all. “It’s about access to talent and making sure you’ve got a capable user group that can make the most of that technology,” says Wright. “You don’t need to be a data scientist, but you do need to have the right mindset to take advantage of the tools you’ve got.”
“I agree – you have to get the right people on the bus,” adds Frechette. “You all have to be committed to going on the journey together. Prioritise where you start and where you’re going to have the most value with the lowest risk, and have people on your side who can give suggestions and ideas.”
While the much-discussed talent shortage can create challenges there, DPW as an entity proves that not only does procurement keep becoming more appealing and exciting, but where there are gaps, there are digital tools. “I’ve noticed a lot of folks under 30 who are here at DPW Amsterdam, and they’re genuinely interested in procurement,” says Wright. “We’re at a tipping point that makes me really excited about the profession I’m in.”
‘Digitalisation is just the beginning’ according to Crowdfox, a business which aims to improve procurement by bettering the ordering process…
SHARE THIS STORY
‘Digitalisation is just the beginning’ according to Crowdfox, a business which aims to improve procurement by bettering the ordering process while lowering costs. That tagline speaks to Crowdfox’s dedication to advancing procurement using the exciting tools the sector now has at its disposal, and this push to innovate is being driven, in part, by Martin Rademacher, Crowdfox’s CSO. We sat down with Rademacher at DPW Amsterdam 2024, the exciting vibe of the event spreading far and wide around us.
Rademacher is responsible for everything to do with Crowdfox’s customers. From sales, to marketing, to customer onboarding and success, and everything in between – that’s Rademacher’s wheelhouse. His background is in management consulting, with a focus on procurement and supply chain. So, while he started out in sales, he soon decided that procurement was the direction to move in.
“During my time as a consultant, I found procurement very interesting because it’s so versatile,” explains Rademacher. “Of course, it’s about the transactional phase with suppliers – but also you’re so connected with R&D, production, logistics, and so on. You have so many fields of application.”
10X thinking
At DPW Amsterdam, the overall theme of the two-day event was 10X. The concept of the 10X rule is around taking a goal you’ve set for yourself and multiplying it by 10. It’s an aspirational tool, coaxing all of us to aim higher. In procurement, that means innovating.
“In the last two years we’ve seen tools like ChatGPT trigger some big adaptations in the procurement world,” says Rademacher. “I think there is the opportunity now to achieve 10X in terms of efficiency gains. Especially when it comes to making better decisions, more quickly, in order to analyse data. We’re now finding out what AI can really do, and focusing on how that can help with strategy.”
For Rademacher, he believes people have the right tools to achieve 10X – it’s now about implementing those tools properly, and having the right culture.
“In the last couple of years, implementing tools has become much easier than it was a decade ago,” Rademacher continues. “They’re so well designed that they fit into large procurement systems, and can connect with other best-of-breed tools. I’d say implementation should be the focus, but it’s not that complicated anymore. AI tools especially are really intuitive. As a result, you don’t need much in the way of change management. People just intuitively cooperate with AI.”
The question of security
The big challenge, Rademacher believes, is data protection. When it comes to barriers preventing a 10X approach, concerns around data privacy are among the biggest issues. As a result, organisations have to take the necessary precautions before plunging into making major technological changes, or risk falling at the first hurdle.
“In the EU, it’s all about data protection,” says Rademacher. These concerns led to the Artificial Intelligence Act (AI Act) coming into force in the EU in August 2024. It was created in response to the rise in generative AI systems, and ensures that there’s a common regulatory framework for AI within the European Union. “Companies are very concerned about their data, but I wouldn’t call this an obstacle – more like a challenge.
“The key is making sure you have a protected environment. Start with a pilot in a limited space, for instance, and then make sure you can find a solution you can control in a safe environment that suits your operations.”
Shooting for the stars
With these measures in mind, it’s never been easier to implement new technologies and aim for that ambitious 10X goal. Certainly, advanced tools have never been more accessible, or more straightforward for businesses to educate themselves about. Even as recently as two years ago, integrating multiple elements of advanced tech – like genAI – wasn’t really possible.
“It definitely wasn’t easy to combine sources the way we can now,” says Rademacher. “Now, you can provide a much better user experience experience not only for procurement professionals, but for anyone who takes advantage of what procurement introduces to the company. Finding the supply to fulfil your demand is so much easier now. You no longer have to have difficult conversations starting with an email to your procurement professional to identify whether you’re allowed to purchase from a certain vendor, and whether they’re vetted or not. Streamlining processes like that makes that information quick and easy to identify.”
Additionally, we’re at a point with advanced technology where the tools we have access to are capable of handling more and more volumes of data at an extremely fast pace. “In consulting, for example, every project started with an analysis of the status quo of a firm,” says Rademacher. “We’d figure out who the vendors are, the categories, and the spend. Depending on the workforce, this could take one or two weeks. Now, with the tools we have access to, you can gather this information in 24 hours.”
The evolution continues
While we’re seeing many of the benefits that come with genAI and other advanced technologies already, it’s only the beginning of what we can achieve using these tools. GenAI is at a peak right now, but according to Rademacher, it might take another five years to achieve its full productivity level. “There’s also this ambitious idea going around of fully autonomous procurement, and it’ll likely take a good 10 years to reach that level of productivity,” he adds. “On the other hand, nobody is talking about robotic process automation anymore because we’re almost there with that already.”
Another challenge is data quality. The cleanliness of an organisation’s data can make or break its use of advanced technology, which is where making the right connections with service providers comes in. “It’s a good example of when to find the right partner,” says Rademacher. “Find someone from the innovative tech space who you think you can rely on. Don’t try to do it all on your own – that’ll just hold you back more and more. Be bold; find the right partner to make the most of your data and that helps you constantly improve. There’s a lot of talent out there, a lot of solutions that are really helpful for organisations of all sizes. You’ll improve step by step.”
There’s no doubt that it’s an exciting time for procurement. The atmosphere at DPW Amsterdam 2024 was electric for that exact reason. The event, in Rademacher’s words, has “a really strong influence on the sector and enables attendees to learn about how the landscape is developing in real time”.
“The AI-driven future is already a reality for us,” he states. “We’re beyond the pilot phase with our AI tool, ChatCFX, and now we really want to drive market share. 2024 going into 2025 sees us in a good position with high user visibility, and now we’re adding ChatCFX to the game, pushing it into the European market. We’re at DPW Amsterdam to meet the players who are looking for a solution exactly like ours, making it an invaluable place to be.”
Certain procurement pain points can prove debilitating for a business, freezing it in its tracks when it’s trying to grow…
SHARE THIS STORY
Certain procurement pain points can prove debilitating for a business, freezing it in its tracks when it’s trying to grow and improve. This is where companies like Candex are able to step in and turn a headache into something so simple, it requires no further thought.
Danielle McQuiston is the Chief Customer Officer at Candex. She’s been with the fintech startup for five years, spending two decades prior to that working in procurement at Sanofi. Candex is a technology-based master vendor that allows customers to engage with and pay one-off or small suppliers without setting them up in their system. This means that the system doesn’t get clogged up with suppliers that are rarely or never going to be used again.
“We’re primarily used for what companies consider tail spend, and we typically deliver it as a punchout catalogue for a really simple user experience,” McQuiston explains. That ability to support lots of customers was what drew her to the role. “Coming to Candex, I was very excited about what they were doing and wanted to help as many companies as possible.”
Addressing tail spend
That ability to address tail spend in a unique way is the main thing that differentiates Candex. It’s an enormous problem for procurement professionals. The way Candex delivers it is through a digital plug-and-play solution, removing the need to be dependent on human intervention. “It’s a horizontal solution for any good or service, and it’s available in over 45 countries now,” says McQuiston. “It becomes part of the customer’s ecosystems and leverages the P2P process. It’s super compliant, and allows a lot of control.”
With this tool in place, Candex’s customers are able to gain much better control over their smaller purchases, defining what is allowed to be purchased. For many, this tool allows them to put tighter restrictions on purchases than their e-procurement systems are able to do. Additionally, Candex runs suppliers through screenings every day, which generally doesn’t happen for small, rarely-used suppliers.
“We run really detailed compliance and sanction screening against all those vendors, taking away a really daunting task from customers,” McQuiston states. “Customers probably check those suppliers once when they’re being set up, but then they never look at them again. Every day, we’re checking them, and keeping an eye on them when our customers can’t.”
Candex’s reporting is extremely detailed, and provides customers with the kind of real-time visibility they wouldn’t normally get – even in their own systems. Reports are generated weekly or monthly, including the diversity status of suppliers. This is data that a lot of clients then feed directly into their Power BI tools and data lakes, meaning they’re able to integrate it seamlessly into their other data.
Cleaning up the data
The whole purpose and aim of Candex’s tool is to make life easier for its customers, streamline its processes, and improve efficiencies. To that end, standardisation is key when it comes to business improvements, and that includes preparing data prior to implementing new technologies and processes. When it comes to ensuring a business’s data is healthy – before launching into major tech changes – accepting the necessity of making foundational change is key.
“Data cleansing processes are ugly, cumbersome, and long – and everyone has to do them,” McQuiston comments. “But you have to accept that you’re going to have to do something, if you want to get a handle on your spend. First and foremost, you need to standardise the way you name things, the way you put data in the system, and you need a really strict discipline around that. All of those things will make backend processes a lot easier.”
It’s just one of many considerations CPOs need to bear in mind when seeking out technology solutions and implementation. Modern procurement departments have a seat at the wider business table now, and what they do impacts the entire business. So when it comes to utilising solutions for the sake of the business at large, there are many factors to think about.
“As with any data or technology, it’s all about garbage in and garbage out,” says McQuiston. “Any advanced technology should be used with caution and viewed with a critical eye. You have to start with knowing what you want out of it.
“A lot of times, people put technology in place because it looks interesting, but you need to start with the problem and work backwards. If the issue is user experience, you need to make sure that whatever you’re implementing focuses on a positive UX. If the problem is unclean data, you need to make sure you’re putting in place all the foundational elements you need to make that better. Always start from the perspective of implementing a technology based on a problem, rather than the other way around.”
Improving UX in 2025
It’s a seriously dynamic time to be involved in procurement right now, as evidenced by the intense buzz around us at DPW Amsterdam as we sit with McQuiston. As we look ahead, she envisions that procurement will have an increasingly powerful impact on user experience. This is particularly important at a time when tasks are becoming increasingly automated, with less and less direct human interaction.
“We’re also seeing a pretty big leap forward in terms of best practice sharing amongst our clients,” says McQuiston, something that events like DPW also encourage. “For Candex, a big theme of 2024 has been getting our clients together to share best practices and information, helping them to develop further expertise in the field. 2025 will have more of the same, but there’s now a higher level of maturity out there in the way customers are considering tail spend. As people continue to onboard solutions, it will be interesting to see how that impacts the UX in relation to Candex. We’re always looking for ways to make our tool more user-friendly and add better functionality.”
All of this is why Candex’s customers love the company. On a base level, Candex takes a complex pain point and makes it simple. In a broader sense, the reason Candex is becoming so popular is the way it works with people. “The most common feedback we get from customers and suppliers is that we’re great to work with because we’re so flexible,” says McQuiston. “We hired a team of procurement experts, so our team is made up of people who really understand the pain of our clients, and can anticipate their fears, their needs, and cater to those.”
Scott Zoldi, Chief Analytics Officer at FICO considers whether the current AI bubble is set to burst, the potential repercussions of such an event, and how businesses can prepare
SHARE THIS STORY
Since artificial intelligence emerged more than fifty years ago, it has experienced cycles of peaks and troughs. Periods of hype, quickly followed by unmet expectations that lead to bleak periods of AI-winter as users and investment pull back. We are currently in the biggest period of hype yet. Does that mean we are setting ourselves up for the biggest, most catastrophic fall to date?
AI drawback
There is a significant chance of such a drawback occurring in the near future. So, the growing number of businesses relying on AI must take steps to prepare and mitigate the impact a drawback or complete collapse could have. Research from Lloyds recently found adoption has doubled in the last year, with 63% of firms now investing in AI, compared to 32% in 2023. In addition, the same study found 81% of financial institutions now view it as a business opportunity, up from 56% in 2023.
This hype has led organisations to explore AI use for the first time. Often with little understanding of the algorithms’ core limitations. According to Gartner, in 2023 less than 10% of organisations were capable of operationalising AI to enable meaningful execution. This could be leading to the ‘unmet expectations’ stage of the damaging hype/drawback cycle. The all-encompassing FOMO of repeating the narrative of the incredible value of AI does not align with organisations’ ability to scale, manage huge risks, or derive real sustained business value.
Regulatory pressures for AI
There has been a lack of trust in AI by consumers and businsses alike. It has resulted in new AI regulations specifying strong responsibility and transparency requirements for applications. The vast majority of organisations are unable to meet these in traditional AI, let alone newer GenAI applications. Large language models (LLMs) were prematurely released to the public. The resulting succession of fails fuelled substantial pressure on companies to pull back from using such solutions other than for internal applications. It has been reported that 60% of banking businesses are actively limiting AI usage. This shows that the drawback has already begun. Organisations that have gone all-in on GenAI – especially those early adopters – will be the ones to pull back the most, and the fastest.
In financial services, where AI use has matured over decades, analytic technologies exist today that can withstand regulatory scrutiny. Forward-looking companies are ensuring they are prepared. They are moving to interpretable AI and backup traditional analytics on hand while they explore newer technologies with appropriate caution. This is in line with proper business accountability, vs the ‘build fast, break it’, mentality of the hype spinners.
Customer trust with AI
Customer trust has been violated by repeated failures in AI, and a lack of businesses taking customer safety seriously. A pull-back will assuage inherent mistrust in companies’ use of artificial intelligence in customer facing applications and repeated harmful outcomes.
Businesses who want their AI usage to survive the impending winter need to establish corporate standards for building safe, transparent, trustworthy Responsible AI models that focus on the tenets of robust, interpretable, ethical and auditable AI. Concurrently, these practices will demonstrate that regulations are being adhered to – and that their customers can trust AI. Organisations will move from the constant broadcast of a dizzying array of possible applications, to a few well-structured, accountable and meaningful applications that provide value to consumers, built responsibly. Regulation will be the catalyst.
Preparing for the worst
Too many organisations are driving AI strategy through business owners or software engineers who often have limited to no knowledge of the specifics of algorithm mathematics and the very signifiicant risk in using the technology.
Stringing together AI is easy. Building AI that is responsible and safe is a much harder and exhausting exercise requiring model development and deployment corporate standards. Businesses need to start now to define standards for adopting the right types of AI for appropriate business applications, meet regulatory compliances, and achieve optimal consumer outcomes.
Companies need to show true data science leadership by developing a Responsible AI programme or boosting practices that have atrophied during the GenAI hype cycle which for many threw standards to the wind. They should start with a review of how regulation is developing, and whether they have the standards, data science staff and algorithm experience to appropriately address and pressure-test their applications and to establish trust in AI usage. If they’re not prepared, they need to understand the business impacts of potentially having artificial intelligence pulled from their repository of tools.
Next, these companies must determine where to use traditional AI and where they use GenAI, and ensure this is not driven by marketing narrative but meeting both regulation and real business objectives safely. Finally, companies will want to adopt a humble approach to back up their deployments, to tier down to safer tech when the model indicates its decisioning is not trustworthy.
Now is the time to go beyond aspirational and boastful claims, to have honest discussions around the risks of this technology, and to define what mature and immature AI look like. This will help prevent a major drawback.
Fred Fuller, Global Head of Banking at Endava, on how banks can effectively communicate AI advancements and demonstrate ROI to investors
SHARE THIS STORY
There is no single solution, AI or otherwise, that can prepare financial institutions for the modern world. To build a bank capable of successfully navigating the challenges of the future, a long-term digital transformation strategy is required. Especially relevant in the wake of recent IT outages,
At present, according to Endava’s Retail Banking Report 2024, 67% of banks are still heavily reliant on legacy systems. This leads to wasted budget and decreased efficiency. With limited resources available to modernise their tech stack, company leaders are often forced to choose which technology-type to prioritise. When doing this, 50% have chosen artificial intelligence (AI).
Is AI alone enough?
Can AI overhaul archaic processes or are there too many hurdles in the way? The first hurdle to successful digital transformation in financial services is overcoming the employees’ perception of the process. Time and time again, corporations have failed in the goal to integrate solutions that successfully feed into a long-term tech strategy. Often, this is due to wide-spread change fatigue. When exhausted by continuous efforts to change their day-to-day, workers become resistant to transformation. The best way to overcome change fatigue, and drive digital transformation in financial institutions, is through overhauling legacy systems. And adopting solutions that will stand the test of time.
Legacy Systems
Across the world, outdated legacy systems are holding financial institutions back and costing them billions. From 2022 to 2028, this expense is expected to grow at a rate of 7.8%. Not only do these archaic processes cost money, but they force banks to contend with a multitude of siloes. From departments to data. We live in a world where neobanks are growing in popularity. They are able to provide a frictionless customer experience using their modern tech stack. Traditional organisations must rid themselves of siloes to enable all areas of the business to leverage AI. In turn, this will provide them with strong data collection and support from departments who are agreed on next steps.
At present, three quarters of financial institutions feel they need to modernise their core. Without this change, they lack the secure, data-driven foundation necessary to utilise AI and see return on their technical investments.
The benefits of AI integration
Once a strong foundation has been laid, it becomes easier to see the practical benefits of integrating AI. For example, when data is no longer siloed by legacy systems, using chat bots to support customers with simple queries creates an efficient consumer experience. There are internal benefits too. AI can spot potentially suspicious activity, flagging it before it is too late. Or analysing data to ensure risk management and process automation. Despite its wide-reaching capabilities, AI alone is not the only option for financial institutions…
Routes to the future
Endava’s Retail Banking Report also showcased the variety of solutions that banks are using to improve their tech stack. 45% of respondents recognised data analytics, in and of themselves, as a top area for investment. Meanwhile 30% flagged IoT, and 14% the Metaverse.
There’s a reason for the emphasis on strong data. It not only supports the integration and use of AI-fuelled capabilities, but it is the driving force behind numerous functions of the bank itself. Of those surveyed, 37% aimed to use data to improve customer service. 34% to strengthen security, and 33% to personalise products and improve the customer experience.
As well as attracting and retaining consumers, business leaders can benefit from their access to strong data by attracting and retaining talent. With 39% of failed digital transformations viewing lack of employee buy-in as a factor, financial institutions are encouraged to educate workers on their technology integration plans, and ensure solutions are user-friendly. Fortunately, looking ahead, 20% of banks surveyed seek to use data to improve the workplace.
A bank’s priority – looking ahead
More than ever, banks are reliant on data to keep operations running smoothly. From providing customers with a personalised experience to improving the workplace in the competition for talent, there are a multitude of reasons to ensure the foundations of your tech stack are strong.
Doing so makes integration of new technology a smoother experience for all. To this end, it’s no shock that 50% of banks are keen to embrace AI, using it to benefit customers and speed up processes. However, with many hampered by the legacy technology and the ever-looming threat of change fatigue, integration of any technology should be carefully planned, customer focused and data led.
Combining advanced technology with a people-led focus is the name of the game for Bravo Consulting Group. Bravo was founded…
SHARE THIS STORY
Combining advanced technology with a people-led focus is the name of the game for Bravo Consulting Group. Bravo was founded in 2007 by President and CEO Gino Degregori. He had his sights squarely set on leveraging Microsoft technologies to deliver cloud services, application modernization, and cybersecurity compliance. Bravo’s aim is to simplify how organisations create, share, and secure their intelligent information. In nearly 17 years of its existence, the business has grown into a premier Microsoft solutions provider serving the federal government, the Department of Defense, the Intelligence Community, and multiple Fortune 500 organisations.
Human-centric leadership and core values
Degregori began his career in software engineering and entrepreneurship. However, he quickly realised that his true calling was beyond just developing software and implementing Microsoft technologies. “I saw an opportunity to build an amazing organisation that provides real value to our customers through our people and innovative solutions,” Degregori explains. “While the cloud didn’t exist in 2007, development, automation, and security were already crucial.”
Degregori founded Bravo on core values that remain the cornerstone of the company today. “Our vision is to attract and create kind leaders who make an impact on our customers, partners, and communities,” he explains. “We lead with empathy, embracing kind leadership. This means prioritising the growth and wellbeing of our team members and clients. We view every interaction from a win-win perspective with a strong sense of accountability.
“It’s not just about implementing technology in your organisation; it’s about truly advancing the mission. Collaborating with great people enables us to deliver outstanding results,” he emphasises. Degregori also hosts The Kind Leader Podcast where he discusses empathetic leadership with industry leaders, embodying the values Bravo champions.
By fostering a culture of empathy and innovation, Bravohas established itself as a leader in cloud services, application modernization, and cybersecurity. Degregori’s commitment to building a people-centric organisation ensures that Bravo not only meets but exceeds the expectations of its clients, driving meaningful and impactful results.
Strategic partnership with AvePoint
Bravo’s commitment to collaborating with exceptional partners has been the cornerstone of its longstanding relationship with AvePoint. For 15 out of its nearly 17 years of existence, Bravo has partnered with AvePoint—a testament to the enduring strength and value of this collaboration. When Bravo first started, the Microsoft ecosystem was rapidly evolving, with many businesses transitioning away from legacy systems. AvePoint’s advanced SharePoint migration and administration tools played a pivotal role in this transition, enabling Bravo to assist over 100,000 users across various verticals in successfully migrating and managing their content and data.
“Our partnership with AvePoint allowed us not only to migrate vast amounts of content and data efficiently but also to reduce costs, which we passed on to our customers,” says Degregori. “It was a phenomenal opportunity to leverage AvePoint’s tools for seamless content and data migration. We recognized early on that AvePoint was poised for significant success, and from then on, our collaboration deepened, enabling us to develop even better solutions.”
This partnership is a key reason customers choose Bravo. By integrating Bravo’s expertise in the Microsoft ecosystem with AvePoint’s suite of tools, Bravo delivers a unique value proposition centred on data management, compliance, and AI-driven solutions. Customers benefit from a holistic approach that not only prepares them for new technologies but also ensures regulatory compliance, cost efficiency, and superior results.
Together, Bravo and AvePoint empower organisations to confidently navigate their digital transformation. Leveraging Microsoft’s advancements in AI and AvePoint’s robust data management tools, they offer cutting-edge solutions that address the evolving needs of modern businesses. This collaboration enables organisations to optimise their data, maintain stringent compliance standards, and harness the power of AI to drive innovation and efficiency.
Expanding horizons through collaboration
For the first decade, Bravo focused exclusively on the federal sector. Recently, Degregori made the strategic decision to expand Bravo’s services into the commercial sphere. “Our strong partnership with AvePoint was instrumental in this successful expansion,” he says. “AvePoint is a global organisation, and through our collaboration, we developed a strategy to penetrate the commercial market. We leveraged our combined services, expertise, and certified professionals at Bravo to build trust and confidence with the AvePoint commercial folks.”
The unique relationship between Bravo and AvePoint has facilitated this long-standing and successful collaboration. Degregori attributes their success to three key factors: communication, clarity, and trust.
“First, strong communication ensures continuous understanding. Second, clarity about our collective goals – focusing not just on our objectives but also on AvePoint’s – allows us to align our efforts effectively. Lastly, trust is paramount. We need to rely on each other through both successful projects and challenging ones. This mutual trust ensures we can support each other through thick and thin,” Degregori explains.
“We are always learning. When things don’t go as planned, we sit down, discuss the lessons learned, and find ways to improve. This continuous learning and mutual support strengthen our partnership and drive our shared success.”
Future growth
The future of Bravo and AvePoint is exceptionally promising as technology evolves at an unprecedented pace. Both organisations are at the forefront, leveraging the Microsoft ecosystem. With Microsoft’s substantial investments in generative AI, their reach is set to expand even further into the Fortune 500 globally.
“This momentum allows us to continuously leverage advanced tools, integrating them to deliver unparalleled value to our customers,” says Degregori. This focus on the human element—the customer—ensures that Bravo remains true to its core values.
“I am immensely grateful for the opportunity to lead an incredible organisation like Bravo and to maintain a long-term partnership with AvePoint. Ultimately, while we discuss technology and solutions, it’s all about people. We’re constantly seeking ways to connect better as partners and employers. This human-centric approach is what drives us to deliver superior solutions.”
This vision and commitment to both technological excellence and human connection make Bravo and AvePoint’s partnership not only resilient but also highly impactful for their clients. Together, they are poised to lead the way in digital transformation, ensuring that organisations are not only equipped with the latest innovations but also supported by a team that values their success.
Sejal Mehta and Andrew Rodgers from Odgers Berndtson’s Global FinTech Centre of Excellence and Randy Bean, a Senior Advisor to Odgers Berndtson and industry author, explore the dynamics shaping leadership in the UK fintech sector
SHARE THIS STORY
The UK FinTech sector is undergoing a significant transformation, marked by maturation, consolidation, and a more selective investment landscape. Funding is increasingly funnelled towards profit-generating scale-ups, and away from newer entrants.
At the same time, the sector is shaped by a multi-generational workforce with varied perspectives. Meanwhile rapid advancements in AI foster apprehension and excitement. These converging factors make FinTech one of the most dynamic and competitive spaces to work in today. This presents both challenges and opportunities for its leaders.
From our perspective as global FinTech executive search and leadership advisors at Odgers Berndtson these shifts are reshaping the demands placed on leadership. They are also influencing what it takes to lead effectively in this fast-changing sector. Here, we explore the leadership trends that are emerging as a result.
Ethical FinTech leadership
Venture capital funding is now more selective and private equity investors are increasingly targeting fintechs with solid exposure. This is creating a difficult environment for new start-ups. Those attracting funding are typically cash-positive scale-ups.
Amidst these challenges, more FinTech firms are opting to list on the NASDAQ rather than the London Stock Exchange, as the UK navigates more stringent regulation. The need for payments licences, extensive reporting, and compliance demands weigh heavily on FinTech leaders.
In this landscape, we’re seeing leaders with experience in regulated financial services bring a valuable skillset. The ability to operate within defined regulatory frameworks while generating growth. FinTech boards are looking for leaders with high authenticity and who can make ethical decisions. And while balancing ambition and growth with the realities of working in a highly regulated space.
Founder replacements
We are in the midst of the FinTech sector’s maturation. Start-ups are transitioning into scale-ups, requiring different leadership competencies. For many, this requires the founder to step down or step into a board role and appoint a CEO who can take the business through its next stage of growth.
This requires leaders who are commercially driven, capable of shaping market strategies, and adept at understanding customer needs and product-market fit. Navigating risk and regulation becomes crucial, while the founder’s creative, opportunity-led approach typically no longer dominates the new operational and strategic demands.
Boards and investors are looking for CEOs with a broader skillset and deep regulatory expertise. These leaders must also be able to attract and retain the type of talent that can sustain growth and innovation, while maintaining the ‘DNA’ that made the business so attractive in the first place.
A multi-generational workforce
Intergenerational divides are becoming more pronounced for all businesses and noticeably in sectors like FinTech. Here, younger generations with fresh perspectives are working alongside older, more experienced professionals – often from traditional financial services backgrounds.
This diversity in age, experience, and approach can be a powerful asset, but only if integrated effectively. Typically, Gen Z and Millennials prioritise flexibility, technological integration and experimentation. Meanwhile, Boomers bring valuable expertise in regulatory environments and operational effectiveness, but may be more accustomed to traditional structures and leadership styles.
Increasingly, we see FinTech leaders attempt to bridge these divides by emphasising open communication, promoting mentorship opportunities, and encouraging cross-generational collaboration. With less funding and more regulation, FinTech leaders recognise the need to identify and capitalise on the strengths of a multigenerational workforce if they are to succeed.
Leadership team dynamics
As FinTech companies scale, leadership is no longer just about the capabilities of individual leaders but about the dynamics of the entire executive team. Successful scale-ups understand the importance of assembling a leadership team that brings a diverse mix of skills, and generational perspectives to the table.
We are starting to see FinTech companies think about leadership team dynamics as they scale up. Boards are looking for a blend of strategic, operational and ethical considerations. As well as how well team members work together. Do they solve problems cohesively? Are there any unresolved tensions or conflict? Are they aligned and equipped to collectively deliver on the leadership mandate?
Many leadership teams are not optimising their potential due to misalignment of strengths. For example, we recently worked with a FinTech creating an executive team profile to identify the leadership competencies needed to deliver their mandate. This exercise enabled the team to reallocate executive responsibilities for strategic initiatives based on the required strengths, regardless of traditional job roles.
Polarising views on Gen AI
Leading organisations are experiencing a transformational moment due to accelerated interest in AI and Generative AI. 89.6% are increasing their investments in AI, while 64.2% of companies have indicated that AI will be the most transformational technology in a generation. In response, organisations are hiring for the data and AI leadership roles required to prepare their companies for an AI future.
However, this integration of Gen AI has sparked both excitement and nervousness, particularly around issues of data protection and privacy. Generational differences are especially noticeable. Younger professionals are often less concerned about data privacy, while older generations remain cautious about the security implications.
This divergence in attitudes can create tension within the organisation, as leaders grapple with how best to leverage Gen AI while ensuring compliance with stringent data protection regulations. For some FinTechs, AI is seen as a specialised area requiring dedicated focus. Meanwhile, others believe AI represents a fundamental shift in how business can be conducted and AI strategy should be woven into the fabric of every leader’s responsibilities.
This divide in attitudes reflects the broader challenges we see FinTech companies face in incorporating AI. Leaders must now navigate the balance between embracing innovation and safeguarding sensitive information. They must also ensure AI is not seen as a siloed function. It must be an integral part of their commercial and strategic vision. Given the fundamental changes in the sector, the emphasis on leadership capabilities is changing for both the individual and executive team.
Hugo Farinha, Co-founder and CTO at Virtuoso QA on why AI is driving organisational change across financial services
SHARE THIS STORY
We’ve seen an enormous amount of discussion concerning all aspects of AI since the emergence of Chat GPT made it headline news. However, most articles and conversations focusing on its business impact seem to wilfully ignore the ‘elephant in the room’. Namely, the inevitable organisational change AI will usher in, especially for employees.
AI technology driving change
To ignore change is folly, and likely to have the exact opposite effect that businesses and AI technology vendors want. We can’t pretend workforces won’t be disrupted by such a seismic technological advance. Certain job roles will become obsolete. Business leaders can’t run the risk of creating a culture of fear and uncertainty among employees who are unlikely to be fooled.
It’s true AI could lead to leaner operations, particularly in insurance and finance companies, with fewer employees needed for routine tasks, but only half the story. Smart businesses will almost certainly reinvest cost savings into new growth areas that require specific human talent. Companies that maintain a strong human element in customer service and personalised offerings will differentiate themselves in a crowded market. The rise in AI-driven, agile companies will create faster market shifts and greater competition.
While AI has the potential for productivity and efficiency gains, and even to do the same with less if needed, I actually don’t predict major job culls in the next few years. AI is particularly good at data processing and data analytics, in insurance for example. So, when more data can be processed and analysed, human intervention can make better informed decisions as a result. In the short to medium term, data analysis and decision making will remain firmly in the human realm. But powered by AI.
The Future for Artificial Intelligence
Meanwhile, the technology is still evolving, and organisations need to build a model that layers over the top of AI – powered by it, rather than replaced by it. Despite the hype, we are still a long way from AI becoming an entity that can lead, implement and operate itself to a purposeful end. But it will increasingly power applications overlaid by strategic, human-led frameworks.
To achieve this, leaders must bring their teams with them on the journey. In the field of testing for example, developers have traditionally written code as part of their role. This is a very time consuming and laborious task. Historically skills gaps have led to delays in progress. But the ability to ‘outsource’ to AI has freed up the time of those developers to focus on the purpose of that code in relation to the product. And, ultimately, the customer. Similarly, leaders in all fields need a broader understanding of AI use cases such as these to make effective strategic decisions. For example, on hiring. Understanding when to bring in more people and when to bring in new technology to complement the skills of your existing team means understanding AI’s strategic implications, technical capabilities and limitations.
An Evolving Job Market
From the perspective of the employee, the job market will continuously evolve alongside AI advancements. It will require ongoing adaptation and learning to stay relevant. Skills such as empathy, communication, and negotiation will remain vital. These are differentiators and difficult for AI to replicate. Understanding AI tools and data analysis will be increasingly important, even for non-technical roles. The ability to adapt to new technologies and continuously learn will be essential. Moreover, as AI becomes more integrated, the need for professionals who understand the ethical implications and regulatory requirements will grow exponentially.
Driving growth and job creation in this new world will require a different mindset to the current received wisdom. From both employees and leaders. In addition to the advances and changes already discussed, AI also has the potential to level the playing field, enabling smaller or newer companies to compete more effectively with, and even seriously threaten, established players. With many traditional barriers to entry such as burdensome start-up costs removed, new business models are likely to emerge. In much the same way as they did in the early days of the internet. Investors will be on the lookout for the next ‘giant killer’.
This will create opportunities for those with the foresight to upskill, as well as for those looking to start their careers. Although those opportunities and the jobs of tomorrow may not yet be completely clear. What is clear, however, is that established businesses cannot afford to be complacent. Change is inevitable and empires can be toppled overnight by technology as disruptive as AI. By embracing it early, leaders in those businesses will have the opportunity to spot and fix the gaps and redundancies in their business models that the technology and its capabilities exposes before the market does so more painfully and publicly.
Our mission is to enable and lead the world’s quality-first revolution. QA tools haven’t kept up with the demands of the testing world. Virtuoso is here to deliver with AI-powered, low-code/no-code test automation to support the modern business.
“Virtuoso technology represents the foundation for software quality in the digital world, and we are proud to be a critical, guiding force in the era of AI.”
Cullen Zandstra, CTO at FloQast on mitigating the risks of AI to deliver benefits to financial services
SHARE THIS STORY
There’s a lot of buzz around Generative AI (GenAI). What’s not always heard beneath the noise are the very real and serious risks of this fast-developing AI tech. Let alone ways to mitigate these emerging threats.
Currently, one quarter (26%) of accounting and bookkeeping practices in the UK have now adopted GenAI in some capacity. That figure is predicted to grow for many years to come.
With this in mind, and as we hit the crest of the GenAI hype cycle, it’s critically important that leaders focus closely on the potential risks of AI deployment. They need to proactively prepare to mitigate them, rather than picking up the pieces after an incident.
Navigating the risky transition to AI
The benefits of AI are well-proven. For finance teams, AI is a powerup that unlocks major performance and efficiency boosts. It significantly enhances their ability to generate actionable insights swiftly and accurately, facilitating faster decision-making. AI isn’t here to take over but to augment the employees’ capabilities. Ultimately improving leaders’ trust in the reliability of financial reporting.
One of the most exciting aspects of AI is its potential to enable organisations to do more with less. Which, in the context of an ongoing talent shortage in accounting, is what all finance leaders are seeking to do right now. By automating routine tasks, AI empowers accountants to focus on higher-level analysis and strategic initiative, whilst drawing on fewer resources. GenAI models can help to perform routine, but important tasks. These include producing reports for key stakeholders and ensuring critical information is effectively and quickly communicated. It enables timely and precise access to business information, helping leaders to make better decisions.
However, GenAI also represents a new source of risk that is not always well understood. We know that threat actors are using GenAI to produce exploits and malware. Simultaneously levelling up their capabilities and lowering the barrier of entry for lower-skilled hackers. The GenAI models that power chatbots are vulnerable to a growing range of threats. These include prompt injection attacks, which trick AI into handing over sensitive data or generating malicious outputs.
Unfortunately, it’s not just the bad guys who can do damage to (and with) AI models. With great productivity comes great responsibility. Even an ambitious, forward-thinking, and well-meaning finance team could innocently deploy the technology. They could inadvertently make mistakes that cause major damage to their organisation. Poorly managed AI tools can expose sensitive company and customer financial data, increasing the risk of data breaches.
De-risking AI implementation
There is no technical solution you can buy to eliminate doubt and achieve 100% trust in sources of data with one press of a button. Neither is there a prompt you can enter into a large language model (LLM).
The integrity, accuracy, and availability of financial data are of paramount importance during the close and other core accountancy processes. Hallucinations (another word for “mistakes”) cannot be tolerated. Tech can solve some of the challenges around data needed to eliminate hallucinations – but we’ll always need humans in the loop.
True human oversight is required to make sure AI systems are making the right decisions. We must balance effectiveness with an ethical approach. As a result, the judgment of skilled employees is irreplaceable and is likely to remain so for the foreseeable future. Unless there is a sudden, unpredicted quantum leap in the power of AI models. It’s crucial that AI complements our work, enhancing rather than compromising the trust in financial reporting.
A new era of collaboration
As finance teams enhance their operations with AI, they will need to reach across their organisations to forge new connections and collaborate closely with security teams. Traditionally viewed as number-crunchers, accountants are now poised to drive strategic value by integrating advanced technologies securely. The accelerating adoption of GenAI is an opportunity to forge links between departments which may not always have worked closely together in the past.
By fostering a collaborative environment between finance and security teams, businesses can develop robust AI solutions. They can boost efficiency and deliver strategic benefits while safeguarding against potential threats. This partnership is essential for creating a secure foundation for growth.
AI in accountancy: The road forward
The accounting profession stands on the threshold of an era of AI-driven growth. Professionals who embrace and understand this technology will find themselves indispensable.
However, as we incorporate AI into our workflows, it is crucial to ensure GenAI is implemented safely and does not introduce security risks. By establishing robust safeguards and adhering to best practices in AI deployment, we can protect sensitive financial information and uphold the integrity of our profession. Embracing AI responsibly ensures we harness its full potential while guarding against vulnerabilities, leading our organisations confidently into the future.
Founded in 2013, FloQast is the leading cloud-based accounting transformation platform created by accountants, for accountants. FloQast brings AI and automation innovation into everyday accounting workflows, empowering accountants to work better together and perform their tasks with greater efficiency and accuracy. Now controllers and accountants can spend more time delivering greater strategic value while enjoying a better work-life balance.
Russ Rawlings, RVP, Enterprise, UK&I at Databricks, on the future of AI in FinTech
SHARE THIS STORY
Strict regulation, along with time and cost restraints, means financial services must take a measured approach to technological advancements. However, with the emergence of GenAI, particularly large language models (LLMs), organisations have an opportunity to maximise the value of their data to streamline internal operations and enhance efficiencies.
Embracing GenAI has never been more important for organisations looking to stay ahead of the curve. 40-60% of the global workforce will be impacted by the growth of AI. Moreover, global adoption of GenAI could add the equivalent of $2.6tn to $4.4tn in value annually to global industries. The banking sector stands to gain between $200-340 billion.
But whilst the financial services industry can gain incredible benefits from GenAI, adoption is not without its challenges. Financial organisations must prioritise responsible data management. They must also navigate strict privacy regulations and carefully curate the information they use to train their models. But, for companies that persevere through these obstacles, the benefits will be substantial.
Building customised LLMs for financial services
Consumer chatbots have brought GenAI to the mainstream. Meanwhile, the true potential of this transformative technology lies in its ability to be tailored to the unique needs of any organisation, in any industry. Including the financial sector.
Risk assessment, fraud prevention, and delivering personalised customer experiences are some of the use cases of custom open source models. Created using a company’s proprietary data, these models ensure relevant and accurate results. And are more cost-effective due to their smaller datasets. For instance, banks can use a customised model to seamlessly analyse customer behaviour and flag up any suspicious or fraudulent activities. Or, a model can leverage sophisticated algorithms to assess an individual’s eligibility for a loan.
Another huge benefit of these tailored systems is trust and security. Deploying a custom open-source model eliminates the need to share sensitive information with third parties. This is crucial for organisations operating within such a highly regulated industry. This approach also democratises the training of custom models. Furthermore, it allows organisations to harness the power of GenAI whilst retaining control and compliance.
Using data intelligence to boost AI’s impact
To truly harness the power of GenAI, organisations must cultivate a deep understanding of data across the entire workforce. Every employee, regardless of how technical they are, must grasp the importance of proper data storage. Also how data can be used to improve decision-making.
Organisations can use a data intelligence platform to help implement this. Built on a lakehouse architecture, a data intelligence platform provides an open, unified foundation for all data and governance. It operates as a secure end-to-end solution tailored to the specific needs of the financial services industry. By adopting such a platform, businesses can eliminate their reliance on third party solutions for data analysis. They can create a streamlined approach to data governance and accelerate data-driven outcomes. Users across all levels of the business can navigate their organisation’s data, using GenAI to uncover important insights.
The future of AI in the financial sector
The path to success lies in embracing GenAI as a canvas for crafting bespoke solutions. Whilst no two financial institutions are exactly the same, the industry’s tools must strike a delicate balance between supporting specific use cases and addressing broader requirements, Customised, open source LLMs and data intelligence platforms hold the key, sparking transformative change across the sector. These tailored solutions will empower financial businesses to integrate cutting-edge innovations and ensure security, governance and customer satisfaction. Organisations that embrace this change will not only gain a competitive edge, but also pave the way for larger transformations, re-shaping the financial landscape and setting new standards for the industry.
Databricks is the data and AI company with origins in academia and the open source community. Databricks was founded in 2013 by the original creators of Apache Spark™, Delta Lake and MLflow. As the world’s first and only lakehouse platform in the cloud, Databricks combines the best of data warehouses and data lakes to offer an open and unified platform for data and AI.
Pat Bermingham, CEO of B2B digital payment specialist Adflex, asks what impact will Artificial Intelligence really have on B2B payments?
SHARE THIS STORY
Visit any social media newsfeed and countless posts will tell you AI means “nothing will ever be the same again”. Or even that “you’re doing AI wrong”. The volume of hyperbolic opinions being pushed makes it almost impossible for businesses to decipher between hype and reality.
This is an issue the European Union’s ‘AI Act’ (the Act), which came into force on 1 August 2024, aims to address. The Act is the world’s first regulation on artificial intelligence. It sets out how to govern the deployment and use of AI systems. The Act recognises the transformative potential AI can have for financial services, while also acknowledging its limitations and risks.
Within the debate about AI in financial services, B2B payments are an area where AI has huge potential to accelerate digital innovation. Let’s go beyond the hype to provide a true perspective on what AI really means for B2B payments specifically.
Understanding what AI is, and what it isn’t
AI is a system or systems that can perform tasks that normally require human intelligence. It incorporates machine learning (ML). ML has been used by developers for years to give computers the ability to learn without being explicitly programmed. In other words, the system can look at data and analyse it to refine functions and outcomes.
A newer part of this is ‘deep learning’, which leverages multi-layered neural networks. This simulates the complex decision-making power of our brains. The deep learning benefits outlined later in this article are based on Large Language Models (LLMs). LLMs are pre-trained on representative data (such as payment/transaction/tender data). Deep learning AI does not just look at and learn patterns of behaviour from the data. It is becoming capable of making informed decisions based on this data.
Before we explore what this means for B2B payments, let’s make one caveat clear: human supervision is still needed to ensure the smooth running of operations. AI is a supporting tool, not a single answer to every question. The technology is still maturing. You cannot hand over the keys to your B2B payments process quite yet. Manual processes will retain their place in B2B payments. AI tools will help you learn, adapt and improve more quickly and at scale.
The AI Act – what you need to know
The Act attempts to categorise different AI systems based on potential impact and risk. The two key risk categories include:
Unacceptable risk – AI systems deemed a threat to people, which will be banned. This includes systems involved in cognitive behavioural manipulation, social scoring, and real-time biometric identification.
High risk – AI systems that negatively affect safety or fundamental rights. High-risk AI systems will undergo rigorous assessment and must adhere to stringent regulatory standards before being put on the market. These high risk systems will be divided into two further categories:
AI systems that are used in products falling under the EU’s product safety legislation, including toys, aviation, cars, medical devices and lifts.
AI systems falling into specific areas that will have to be registered in an EU database.
The most widely used form of AI currently, ‘generative AI’ (think ChatGPT, Copilot and Gemini), won’t be classified as high-risk. However, it will have to comply with transparency requirements and EU copyright law.
High-impact general-purpose AI models that might pose systemic risk, such as GPT-4o, will have to undergo thorough evaluations. Any serious incidents would have to be reported to the European Commission.
The Act aims to become fully applicable by May 2026. Following consultations, amendments and the creation of ‘oversight agencies’ in each EU member state. Though, as early as November 2024, the EU will start banning ‘unacceptable risk’ AI systems. And by February 2025 the ‘codes of practice’ will be applied.
So, with the Act in mind, how can AI be used in a risk-free manner to optimise B2B payments?
Today’s B2B payment platforms are not one-size-fits-all solutions; instead, they provide a toolkit for businesses to customise their payment interactions.
AI-based LLMs and ML can be used by payment providers to rapidly understand and interpret the extensive data they have access to (such as invoices or receipts). By doing this, we gain insights into trends, buyer behaviour, risk analysis and anomaly detection. Without AI, this is a manual, time consuming task.
One tangible benefit of this data analysis for businesses comes from combining payment data with knowledge of a wide range of vendors’ skills, products and/or services. AI could then, for example, identify when an existing supplier is able to supply something currently being sourced elsewhere. By using one supplier for both products/services, the business saves through economies of scale.
Another benefit of data analysis comes from payment technology experts. Ours have been training one service to extract data from a purchase order or invoice, to flow level 3 data, which is tax evident in some territories. This automatically provides the buyer with more details of the transaction, including relevant tax information, invoice number, cost centre, and a breakdown of the products or service supplied. This makes it easy and straightforward to manage tax reporting and remittance, purchase control and reconciliation.
AI-driven data analysis isn’t just a time and money-saver, however. It also adds new value by enabling providers to use the data to create hyper-personalised payment experiences for each buyer or supplier. For example, AI and ML tools could look out for buying and selling opportunities, and perform a ‘matchmaking supplier enablement service’ that recommends the best payment methods – and the best rates – for different accounts or transactions. The more personalised a payment experience is, the happier the buyer and more likely they are to (re)purchase.
Efficient data flows mean stronger cash flows
Another practical application of AI is to help optimise cash management for buyers. This is done by using the data to determine who is strategically important and when to pay them. It could even recommend grouping certain invoices together for the same supplier, consolidating them into one payment per supplier, reducing interchange fees and driving down the cost of card acceptance.
AI can also perform predictive analysis for cash flow management, rapidly analysing historical payment data to predict cash flow trends, allowing businesses to anticipate and address potential challenges proactively. This is particularly valuable in the current economic climate where cashflow is utterly vital.
By extracting value-added, tax evident data from a purchase order or invoice, AI can rapidly analyse invoices and receipts to enable efficient, accurate automation of the VAT reclaims process. Imagine: the time comes for your finance team to reclaim VAT on recent invoices and receipts, but they don’t have to manually go through every receipt or invoices and categorise them into a reclaim pile or not reclaimable. It sounds like a dream but it will be the reality for business everywhere: AI does the heavy lifting and humans verify it, saving significant time and resources.
The third significant benefit of AI is automated invoice reconciliation. By identifying key information from an invoice and recognising regular payees, AI can streamline and automate the review process. This has the potential to significantly speed up transactions and enable more efficient payment orchestration.
Binding together all supporting paperwork, such as shipping, customs, routes, and JIT (just-in-time) requirements can also be done by AI, and it’s likely to be less prone to human error.
This provides an amazing opportunity to make B2B payments faster, reduce costs and increase efficiency. Businesses know this: 44% of mid-sized firms anticipate cost savings and enhanced cash flow as a direct result of implementing further automation within the next three years. According to American Express, 48% of mid-sized firms expect to see payment processes accelerate, with more reliable payments and a broader range of payment options emerging.
When. Not if.
There are significant opportunities to leverage AI in B2B payment processes, making it do the heavy lifting. It is, however, essential to view these opportunities with a balanced understanding of the limitations of AI.
While all the opportunities for AI in B2B payments outlined here are based on relatively low-risk AI systems, human oversight of these systems is still essential. However, with all the freed-up time and resource achieved through the implementation of AI, this issue can be avoided.
AI in B2B payments is not an if, but a when. The question is, when will you make the jump, hand in hand with technology, rather than fearing it or passing full control over to it.
In order to grow, it is essential for users to see the tangible benefits. For example, by enhancing efficiencies in account payable (AP), businesses can reallocate time and resource previously spent in AP to other areas. Early adopters are starting to test the water but only time will tell how much of an impact AI will make.
Most businesses will likely wait for the early adopters to fail, learn and progress. If something goes wrong in B2B payments, it can have a huge impact on individuals, businesses and economises. Only when the risk is clearly defined and manageable will AI truly become the gamechanger in B2B payments that all the hype claims.
“Adflexhas been at the heart of the B2B fintech revolution from the beginning. We are known for fostering innovation and helping companies harness the power of digital payments. Our technology and expertise bring together buyers and suppliers to make transactions fast, cost-effective and straightforward to manage. We take the pain out of the supply chain by delivering seamless and secure payment integration that adds value to both buyers and merchants.”
Michael Donnelly, Head of Client Success at BlueFlame AI, on how to prepare your firm to attract and retain the next generation of AI talent
SHARE THIS STORY
In the fast-paced world of financial services, a new generation is stepping in with high expectations for generative artificial intelligence (AI) in the workplace. Recently, BlueFlame AI conducted a specialised training session for one of our private equity clients, aimed at their newly hired summer intern class. The experience was eye-opening for us. Furthermore, it also provided a great lesson in the growing importance of AI in the industry and the expectations today’s young professionals have as they enter the workforce
AI & LLMs
The comprehensive training session covered vital areas such as AI and Large Language Models (LLMs), a review of the most popular use cases the industry has adopted, and hands-on practical training in prompt engineering. Moreover, our goal was to show this next generation the skills they’ll need to leverage these tools effectively. New roles could revolutionise alternative investment management processes like due diligence, market analysis, and portfolio management.
We also used this as an opportunity to survey the group about their experience of and expectations for AI use in the workplace – and it yielded some striking insights. A significant 50% of the interns reported using ChatGPT daily, with 83% utilising it at least weekly. Furthermore, these numbers suggest young professionals expect these tools to be available to them in their professional lives. In the same way they are available in their personal lives and set to become as commonplace as traditional software in the workplace. The interns’ expectations regarding AI’s impact on their work efficiency are even more telling. An overwhelming 94% believe these tools will enhance their productivity, indicating strong faith in the technology’s potential to streamline tasks and boost performance.
These high expectations have key implications for employers. A significant 89% of interns expect their employers to provide enterprise-grade AI/LLM access. This statistic is a wake-up call for companies that have yet to invest in AI technologies, highlighting the need to stay competitive not just in terms of products and services but also in workplace technology provision.
Talent Acquisition & Retention
Perhaps most important is AI’s potential impact on talent acquisition and retention. One-third (33%) of interns surveyed indicated they would reconsider their choice of employer if they didn’t offer access to enterprise-grade AI/LLM tools. A response that could throw a serious wrench into any Financial Services firm’s hiring plans.
The message is clear for businesses looking to stay ahead of the curve when it comes to supporting their employees. Investing in AI technologies and training is no longer optional. Firms must be ready to meet the expectations of the incoming workforce. They need to provide them with the best technology to maintain a competitive edge in an increasingly AI-driven business landscape. Companies that embrace AI and provide their employees with the tools and training to harness its power will likely see significant productivity, innovation, and talent retention advantages.
AI Revolution
Private and public investment firms stand to benefit greatly from this AI revolution. As this new generation brings its enthusiasm and expectations for technology tools into the workplace, firms that are prepared to meet these expectations will be better positioned to tap into fresh perspectives, drive innovation and reap significant efficiency and productivity gains. And if firms can take a proactive approach to training and commit to developing a forward-thinking, AI-enabled workforce, they will be able to enhance their teams’ capabilities and shape the future of work in the financial sector.
Generative AI and the workplace expectations it has created mark a new paradigm in the market. The next generation of professionals is not just ready for AI – they’re demanding it. Firms that recognize and act on this trend will be well-positioned to lead the pack when it comes to innovation, efficiency and talent acquisition.
Founded in 2023 BlueFlame AI is the only AI-native, purpose built, LLM-agnostic solution for Alternative Investment Managers.
Our cover star, EY’s Global Chief Data Officer Marco Vernocchi, tells Interface why data is a “team sport” and reveals…
SHARE THIS STORY
Our cover star, EY’s Global Chief Data Officer Marco Vernocchi, tells Interface why data is a “team sport” and reveals the transformation journey towards realising its potential for one of the world’s largest professional services organisations.
Welcome to the latest issue of Interface magazine!
Global Chief Data Officer, Marco Vernocchi, reflects on the data transformation journey at one of the world’s largest professional services networks.
“Data is pervasive, it’s everywhere and nowhere at the same time. It’s not a physical asset, but it’s a part of every business activity every day. I joined EY in 2019 as the first Global Chief Data Officer. Our vision was to recognise data as a strategic competitive asset for the organisation. Through the efforts of leadership and the Data Office team, we’ve elevated data from a commodity utility to an asset. Our formal data strategy defined with clarity the purpose, scope, goals and timeline of how we manage data across EY. Bringing data to the centre of what we do has created a competitive asset that is transforming the way we work.”
PivotalEdge Capital
Sid Ghatak, Founder & CEO of asset management firm PivotalEdge Capital, spoked to us about the pioneering use of “data-centric AI” for trading models capable of solving the problems of trust and cost.
“I’ve always advocated data-driven decision-making throughout my career,” says Ghatak. “I knew when I started an asset management firm that it needed to be data-centric AI from the very beginning. A few early missteps in my career taught me the importance of having a stable and reliable flow of data in production systems and that became a criterion.”
LSC Communications
Piotr Topor, Director of Information Security & Governance at LSC Communications, discusses tackling the cyber skills shortage, AI, and bringing together the business and IT to create a cyber-conscious culture at a global leader in print and digital media solutions.
Topor tells Interface: “The main challenge we’re dealing with is overcoming the disconnect between cybersecurity and business goals.”
América Televisión
Interface meets again with Jose Hernandez, Chief Digital Officer at América Televisión, who reveals how the company is embracing new business models, and maintaining market leadership in Peru.
“Launching our FAST channel represents a pivotal step in diversifying our content delivery and monetisation strategies. Furthermore, aligning us with global trends while catering to the changing viewing habits of our audience,” says Hernandez.
Also in this issue of Interface, we hear from eflow about new approaches to Regtech; get the lowdown on bridging the AI skills gap from CI&T; and GCX on the best ways to navigate changing cybersecurity regulations.
Financial institutions are increasingly turning to artificial intelligence (AI) to gain a competitive edge. AI tools streamline operations, improve customer…
SHARE THIS STORY
Financial institutions are increasingly turning to artificial intelligence (AI) to gain a competitive edge. AI tools streamline operations, improve customer support, and automate processes, making banks more efficient and customer-focused.
Research by McKinsey shows that over 20 percent of an organisation’s digital budget goes towards AI. The study links significant investments in AI to a 10-20 percent increase in sales. AI will play a central role in boosting efficiency, customer service, and overall banking productivity.
Introduction to AI in Personalised Banking
Delivering personalised experiences is crucial for customer satisfaction and retention. AI helps banks achieve this by collecting and analysing customer data. This data is then used to create recommendations, product offerings, and even financial advice tailored to each customer’s needs.
AI tools can optimise workflows through a technique called prescriptive personalisation, using past data to predict future behaviour. Real-time personalisation takes this further, incorporating current information alongside historical data.
This allows banks to deliver highly customised virtual assistants and real-time recommendations powered by natural language processing (NLP) models. These AI-powered assistants not only build trust and user engagement but also simplify interactions with the bank.
Tool 1: Predictive Analytics
Predictive analytics, powered by AI tools, unlock a new level of customer personalisation in banking. These tools analyse data to uncover hidden patterns and trends that traditional methods might miss. This knowledge reveals sales opportunities, possibilities for cross-selling, and ways to improve efficiency.
Predictive analytics use past data to forecast customer behaviour and market trends. This foresight allows banks to tailor marketing strategies and sales approaches to meet changing customer needs and capitalise on emerging opportunities.
Tool 2: Chatbots and Virtual Assistants
One key advantage of chatbots is their constant availability. This is especially helpful for customers who need assistance outside of regular operating hours.
AI chatbots learn from every interaction, improving their ability to understand and meet individual customer needs. By integrating chatbots into banking apps, banks can provide personalised banking experiences and recommend financial products and services that fit a customer’s specific situation.
Erica, a virtual assistant developed by Bank of America, handles tasks like managing credit card debt and updating security information. With over 50 million requests handled in 2019 alone, Erica demonstrates the potential of chatbots as efficient assistants for customers.
Tool 3: Recommendation Engines
Banks use AI tools to analyse vast amounts of customer data, including purchases, browsing habits, and background information. This deep understanding helps banks recommend products that truly fit each customer’s needs.
These personalised recommendations extend beyond credit card suggestions. AI can identify potential investments or loans that align with a customer’s financial goals. By providing customers with relevant information, banks allow them to make informed financial decisions.
Tool 4: Sentiment Analysis with AI
AI sentiment analysis translates written text into valuable insights. AI uses NLP to understand emotions and opinions in written communication. By examining things like customer feedback, emails, and social media conversations, banks gain a much clearer picture of customer sentiment.
Tool 5: Voice Recognition
AI-powered voice assistants offer a convenient way to handle everyday banking tasks. From checking balances to paying bills, all a customer needs are simple voice commands.
These assistants use NLP to understand customer requests and respond accurately. Voice authentication adds another layer of security by verifying customer identity during transactions.
Tool 6: Process Automation
Robotic Process Automation (RPA) automates repetitive tasks, boosting operational efficiency. It tackles up to 80 percent of routine work and frees up workers for more valuable tasks requiring human judgement.
RPA bots can handle tasks like issuing and scheduling invoices, reviewing payments, securing billing, and streamlining collections – all at once. NLP empowers these bots to extract information from documents, simplifying application processing and decision-making.
Tool 7: Facial Recognition with AI
Facial recognition helps banks verify customer identities during tasks like opening accounts, accessing information, and making transactions. Compared to traditional passwords, facial recognition offers stronger security and greater convenience. It eliminates the need for remembering complex passwords or worrying about stolen credentials, making banking interactions smoother and less error-prone. This technology also helps prevent fraud by identifying attempts to impersonate real customers.
Capital One AI Case Study
Capital One demonstrates how AI can personalise banking. Their AI assistant uses NLP to understand customer questions and provide immediate answers. Capital One also incorporates AI into fraud detection. Machine learning and predictive analytics help pinpoint suspicious credit card activity to strengthen security measures.
Conclusion
AI tools offer a significant opportunity for banks to improve customer experiences and achieve long-term success. By personalising banking services with AI, banks can better meet individual customer needs. This leads to higher satisfaction and loyalty, which enhances the bank/customer relationship.
AI has the potential for an even greater impact. As banks integrate more advanced AI capabilities, they can create even more engaging and personalised interactions. This focus on ‘hyper-personalisation’ could be the next big step for financial institutions to set them apart in a competitive market.
Banks are adopting artificial intelligence (AI) technology to provide more personalised experiences. A study by the AI Development Company projects…
SHARE THIS STORY
Banks are adopting artificial intelligence (AI) technology to provide more personalised experiences. A study by the AI Development Company projects that 75 percent of financial institutions will invest $31 billion in integrating AI into their existing systems by 2025. The trend is driven by customer demand for faster and more convenient banking options.
AI excels at analysing enormous amounts of data. This lets banks find patterns and trends to personalise customer service and boost efficiency. For example, AI-powered chatbots offer 24/7 help with basic questions, freeing up customer service staff for trickier issues. AI can also analyse customer behaviour to predict their needs and suggest relevant services or support, from personalised investment options to flagging suspicious account activity.
Benefit 1: Increased Efficiency
Long wait times and impersonal interactions often leave customers frustrated with traditional bank customer service. Fortunately, AI streamlines the experience by providing quick and accurate answers. It eliminates the need to navigate complex phone menus.
AI personalises interactions and saves customers from endless button-pressing and long hold times. AI in customer service can also analyse vast amounts of customer data. The data helps banks anticipate customer needs and recommend tailored solutions, preventing problems before they arise. This results in higher customer satisfaction and a smoother banking experience.
Benefit 2: Personalisation
AI can analyse vast amounts of customer data, including purchases and browsing habits, to create detailed customer profiles. These profiles help banks recommend relevant products and services that fit individual needs.
For instance, a customer who often pays bills online might be recommended a new budgeting tool. Similarly, someone who regularly saves for travel could receive information about travel insurance or currency exchange. These personalised suggestions can come through various channels, like the bank’s website, email alerts, or chatbots.
Benefit 3: Cost Savings
Cost savings are a major advantage of AI-powered customer service in banking. One key way AI achieves this is through automation. Chatbots powered by AI can handle many routine customer inquiries, freeing up human agents for complex issues. This reduces labour costs while also improving response times.
AI also helps with better staffing management. It can analyse past data to predict how many calls are coming in. Banks can then ensure they have the right number of agents available, avoiding overstaffing or understaffing that can significantly impact costs.
Benefit 4: 24/7 Support
Traditionally, reaching a support agent often meant waiting on hold during peak hours. However, AI in customer service is transforming the industry by offering immediate assistance through chatbots. These virtual assistants provide instant support the moment a customer reaches out.
Unlike human agents with limited working hours, chatbots are available 24/7. This ensures customers get help whenever they need it, regardless of location or time zone. This is especially valuable in the globalised world, where customers might need support outside of regular business hours.
A great example of this success is Photobucket, a media hosting service. After implementing a chatbot, they offered 24/7 support to international customers. This results in a three percent increase in customer satisfaction scores along with a 17 percent improvement in resolving issues on the first try.
Benefit 5: Multilingual Support
AI-powered chatbots offer multilingual support, breaking down language barriers and creating a positive banking experience. These chatbots can figure out a customer’s preferred language at the start of a conversation. This ensures clear communication, no matter what language the customer speaks.
Conclusion
A study by Global Market Insights predicts the conversational AI market will reach $57.2 billion by 2032. This technology is making big strides in banking, particularly by automating routine tasks and inquiries. By taking care of these repetitive tasks, AI frees up human agents to focus on more complex customer issues. This improves efficiency and helps banks manage their operating costs. A streamlined customer service experience builds trust and loyalty, which can lead to business growth for financial institutions.
McKinsey & Co. is seeing an increase in the number of clients seeking artificial intelligence-linked projects, reports Bloomberg. Faster adoption…
SHARE THIS STORY
McKinsey & Co. is seeing an increase in the number of clients seeking artificial intelligence-linked projects, reports Bloomberg. Faster adoption of the technology is helping the consulting titan and its peers boost revenue, across industries like Insurtech, following a period of tumult.
About 40 per cent of the New York-based firm’s client projects involve the technology. The number of AI-related customers in the past 12 months is approaching 500, Rodney Zemmel, senior partner and head of the firm’s digital business, said in an interview.
“We believe the long- or the medium-term economic implications are very real,” Zemmel said. He was a final candidate in the recent global managing partner leadership elections at the firm. According to people familiar with the matter, who asked not to be identified discussing confidential information.
Though there’s some degree of hype around AI, “we’re seeing the organisations that are doing that are getting value from it,” Zemmel said. “It’ll be a little longer, and maybe, a little harder than people think, but we’ve got no doubt that the value is there,” he added.
AI adoption across Insurtech
Among those deploying automation rapidly are the traditional and regulated industries such as banking and insurance, Zemmel said. In a June report, Citigroup Inc. said AI is poised to upend consumer finance and make workers more productive. Additionally, with a high potential for 54 per cent of jobs across banking to be automated. Citi also said that the technology could add $170 billion to the industry’s coffers by 2028.
JPMorgan Chase & Co. Chief Executive Officer Jamie Dimon has called AI “critical” to his company’s future success. He also noted the technology can be used to help the firm develop new products, drive customer engagement, improve productivity and enhance risk management.
The surge in automation has come as a relief for the broader consulting industry. It has been battling a slowdown in demand for its traditional services. McKinsey, Ernst & Young and PricewaterhouseCoopers have been cutting jobs to weather the slump. Furthermore, Accenture Plc shares tumbled in March after the company warned it’s seen financial-services customers, including Insurtech, rein in spending on its software.
AI’s rise is also diverting some budgets toward specialist consultancies. Although AI-focused units like McKinsey’s QuantumBlack are growing rapidly, according to Zemmel.
McKinsey – QuantumBlack
McKinsey, which has advised everyone from the U.S.’ Pentagon to China’s Ping An Insurance Group Co., currently has about 2,000 people working across QuantumBlack. It has 7,000 staff in total in tech-related fields, according to Zemmel’s estimates. McKinsey’s headcount stood at about 45,000 globally as of 2023 and revenues were at a record $16 billion.
Zemmel said that the firm is still evaluating how the use of AI will impact its own headcount over the longer run. McKinsey had earlier warned about 3,000 of its consultants that their performance was unsatisfactory and will need to improve.
“We’re certainly planning on being agile about it,” Zemmel said. “One thing that’s clear is everybody in our organization’s going to need to know how to use AI and incorporate in their day-to-day work if they’re going to remain relevant to their clients.”
AI-powered threat detection, automation, and data analysis are empowering fintech cybersecurity teams to more effectively meet the challenges of an evolving world.
SHARE THIS STORY
Artificial intelligence (AI) is driving a new generation of modern cybersecurity solutions. The technology is transforming how organisations protect against evolving digital threats, as predictive and big data analytics bring new benefits to the sector.
How is AI transforming cybersecurity for fintech teams?
AI’s importance in cybersecurity lies in its ability to provide advanced threat detection, automate responses, and adapt to evolving threats. It can also handle large amounts of data, making monitoring networks and detecting issues easier without increasing risks.
AI learns from past experiences, recognising patterns and improving over time. This makes it good at spotting weak passwords and alerting the right people. AI can also block harmful bots that try to overload websites. AI automates large amounts of tasks, allowing for 24/7 monitoring and quicker responses to security threats.
Its machine learning algorithms analyse vast datasets in real-time, identifying patterns and anomalies to detect emerging threats. As AI excels in behavioural analytics, it establishes a baseline of normal behaviour to spot deviations that indicate security threats.
Unlike traditional methods that rely on predefined signatures, AI can identify zero-day threats—new and previously unknown vulnerabilities—promptly. This proactive approach allows organisations to respond swiftly, preventing potential breaches before they occur.
AI also enhances threat intelligence by automating the analysis of code and network traffic, freeing up human analysts for more complex tasks. It, in turn, facilitates automated incident responses, rapidly mitigating attacks and minimising damage.
Predictive AI in Fraud Detection
AI is revolutionising fraud prevention by using predictive and behavioural analysis to detect and prevent fraudulent activities. By analysing historical data, AI identifies patterns that often precede fraud. This approach not only enhances detection accuracy but also reduces false alarms, distinguishing between normal and suspicious behaviours with greater precision.
In real-time, AI monitors multiple transactions simultaneously, flagging suspicious activities as they happen to mitigate risks promptly. It learns individual customer behaviours to detect anomalies, such as large transactions or unusual patterns. These triggers prompt alerts for investigation or automated protective measures, such as account freezing.
Despite challenges such as data privacy and the need for extensive datasets, AI’s advancements in machine learning promise increasingly effective solutions for protecting financial systems.
Industry case studies: Vectra and Kasisto
Fintech companies like Vectra use AI-powered technologies such as Cognito to automate threat detection and response. These systems analyse vast datasets to detect and pursue cyber threats swiftly, ensuring comprehensive security measures against malicious activities.
Tools like Kasisto’s KAI enhance customer experiences by providing personalised financial advice through AI-driven chatbots. This demonstrates AI’s versatile applications in improving both security and service delivery within the fintech sector.
AI’s use cases in cybersecurity are expected to increase. AI will revolutionise how users are authenticated. It will use advanced biometric analysis and behaviour tracking to make it harder for unauthorised users to gain access while ensuring a smooth experience for legitimate users.
This approach strengthens security by verifying identities with methods like fingerprints or facial recognition and detects unusual behaviours for added protection. AI’s ability to learn continuously from new data means cybersecurity systems will become smarter and more effective over time, adapting quickly to new threats.
The growing complexity of financial markets presents new challenges for asset and wealth managers. Therefore, to navigate this evolving environment,…
SHARE THIS STORY
The growing complexity of financial markets presents new challenges for asset and wealth managers. Therefore, to navigate this evolving environment, many are embracing artificial intelligence (AI) for assistance with investment decisions. AI acts as a powerful tool, improving efficiency and effectiveness across various aspects of asset management.
From analysing market trends to building diversified portfolios, AI’s strength lies in processing massive amounts of data. Furthermore, it uncovers hidden patterns empowering managers to make data-driven investment choices across financial services.
Introduction to AI in Asset Management
Asset management involves managing investment portfolios for individuals, institutions, and businesses. This includes stocks, bonds, real estate, and other financial assets. The main goal is to grow value over time while minimising risk and meeting client goals.
AI is transforming asset management with its data processing and analytics capabilities. Additionally, AI algorithms can quickly analyse massive amounts of financial data, market trends, and economic indicators. This helps uncover hidden patterns and connections that human analysts might miss. A data-driven approach empowers asset managers to make better investment decisions and develop more accurate market forecasts.
Portfolio Management
AI is transforming asset management by offering powerful tools for better decision-making. Moreover, machine learning (ML), AI analyses vast amounts of historical market data to identify patterns and predict future trends, providing valuable insights for building portfolios.
Natural language processing (NLP) lets computers understand human language. NLP can unlock information from unstructured sources like news articles, social media, and analyst reports. The algorithms then analyse sentiment and extract key information that feeds into portfolio decisions.
AI optimisation algorithms help construct optimal portfolios. These algorithms consider risk tolerance, return goals, and investment limitations. By using these tools, portfolio managers can create portfolios designed to maximise returns while minimising risk.
Risk Management
AI is changing how investment decisions are made. The AI algorithms can analyse massive amounts of historical market data and complex risk models.
The analysis provides a deeper understanding of individual asset risk and the overall portfolio’s exposure. With this knowledge, investment managers can proactively identify potential risks and develop strategies to lessen them.
AI offers real-time risk monitoring. An AI-powered system continuously tracks portfolio performance, alerting managers to any significant changes in risk. This allows for swift adjustments as market conditions evolve.
Automated Trading
Traditional automated trading tools execute trades based on pre-programmed instructions from human traders. These tools function within the parameters set by the user and can’t analyse markets on their own.
AI offers truly independent systems with tools that can analyse markets using technical and fundamental analysis with minimal human input.
AI uses sentiment analysis, ML, and complex algorithms to process vast amounts of information and identify trends. This data-driven approach removes the emotional bias that can affect human traders.
Case Studies
The asset management industry is seeing a rise in firms using AI to improve performance. A recent example isDeutsche Bank’s collaboration with NVIDIA. This multi-year project aims to integrate AI across their financial services. This includes virtual assistants for easier communication and AI-powered fraud detection. The bank expects faster risk assessments and improved portfolio optimisation.
Morgan Stanley is also making strides in AI adoption. Partnering with OpenAI, their financial advisors now have access to a massive research library at high speed. Advisors can explore client portfolio strategies and find relevant information in seconds, leading to better-informed advice.
Future Prospects
APwC report predicts artificial intelligence will significantly boost global GDP, contributing up to $15.7 trillion in 2030. This advancement could reshape asset management in the coming years, leading to entirely new business models and investment strategies.
One future possibility involves fully automated investment platforms powered by AI. These platforms would manage investment portfolios with minimal human involvement and use real-time data analysis to create personalised investment plans.
Moreover, AI could pave the way for more dynamic investment strategies that respond to market changes. By constantly analysing market conditions, AI can automatically adjust investment portfolios to optimise returns and minimise risks. This could lead to more resilient and adaptable investment systems that are better equipped to navigate various market environments.
We chatted to Gabe Perez from RiseNow about prioritising humans during technological transformation.
SHARE THIS STORY
RiseNow, as a procurement and supply chain strategy and design firm, is firmly plugged into the needs of the sector’s functions as they evolve. Its growth has been organic thanks to customers demanding exactly what they want. They can’t simply implement tech with the goal of ‘go live’ anymore. They need expert help to define the real outcomes.
RiseNow provides end-to-end guidance for customers. This ensures that when they implement new systems, they explore the whole picture from the beginning. It was a topic discussed in detail at DPW NYC in June, where we met up with Gabe Perez, Chief Strategy Officer.
“What we’re seeing in the market is that people are asking for guidance around operating models,” says Perez. “Our focus right now is trying to keep up with demand. There are a lot of different service providers out there.
“We’re showing RiseNow’s clients how to design, execute, and operate. So we’re really focused on helping customers end-to-end, whether they’re optimising what they currently have, or starting from a new platform.”
Humans first, then technology
As procurement continues to digitise, roadblocks that hinder technology’s effectiveness and promise of value become more apparent. One of these is implementing technology for technology’s sake. Or, simply using tech to digitise already-existing processes versus examining the why behind those processes.
“As David Rogers from Columbia Business School said, the best technology is not the most important part of digital transformation,” says Perez. “People are at the core of it. Procurement has to start focusing more on outcomes and let that drive technology. People are running to technology for answers, but they don’t have the right operating model set up by the right people. Plus, there’s a huge talent shortage.”
Addressing the talent shortage
Outside of technology, the talent shortage across procurement was a repeated topic of conversation during DPW NYC. Just as it is during CPOstrategy’s general conversations with leaders. Procurement has been too vague a concept for too long, and overlooked in the grand scheme of many businesses for decades.
“One of the issues is making roles attractive,” Perez states. “I recommend proposing the problems you’re trying to solve and asking whoever you’re interviewing: ‘how would you solve this?’ Because with all the cool tech we now have at our fingertips, they’re going to come up fresh ideas. The talent exists – they’re just not being engaged and attracted. That’s where tech comes into play.”
And technology moulded by a people-centric focus was another major theme of the day at DPW NYC. “While AI in procurement is a huge topic right now, creativity is still going to come from humans – not artificial intelligence,” Perez points out.
“You need human minds to see the value of things. This is to figure out how money can be driven out of the bottom line and into the top line. Humans are still needed for proving that procurement needs to take risks to be better. AI is a great tool, but it still needs us.”
Customer service significantly influences the overall customer experience and brand reputation. Artificial intelligence (AI) has taken customer service to new…
SHARE THIS STORY
Customer service significantly influences the overall customer experience and brand reputation. Artificial intelligence (AI) has taken customer service to new heights, including in the insurance industry.
Financial technology development has offered a better customer experience with enhanced accessibility and convenience. Mobile banks and digital wallets make it possible to contact the customer service team through online platforms. With the help of AI, FinTech companies escalate their services by offering more personalised, prompt, and efficient service.
AI Chatbots and Virtual Assistants
Conversational AI, which focuses on creating human-like interactions like chatbots and virtual assistants, improves customer service efficiency.
Chatbots are automated programmes that promptly address customer service queries. They can assist customers with inquiries and provide support for product information, account balances, or transaction details. AI-powered chatbots can give an immediate response and handle multiple customers at the same time.
Meanwhile, virtual assistants are voice-activated apps that can comprehend and carry out tasks based on users’ commands. These assistants offer personalised support by understanding the customers’ needs. For instance, they can deliver investment guidance tailored to customers’ risk tolerance and financial objectives.
These AI solutions can also assist human assistants by handling routine tasks, allowing them to focus on more complex work. Thus, the employment of AI assistants can reduce operational costs and effectively allocate resources to more important tasks.
Personalised interactions with AI
This approach can provide more personalised interactions by using algorithms and predictive tools to understand and respond to each customer’s preferences. AI algorithms can analyse large datasets of customers’ past interactions, browsing behaviour, and demographic information.
Meanwhile, predictive analytics tools can be used to anticipate customer needs and offer relevant financial products or services. These recommendations are constantly updated based on real-time client interactions and feedback.
24/7 Support
AI-powered customer service has the benefit of around-the-clock availability. It can operate continuously without being bound by office working hours like human-based customer service. Faster response times and enhanced availability help FinTech companies improve overall customer satisfaction.
Case Studies
Paypal, a digital wallet company, is one of the FinTech companies that has successfully used AI to improve its customer service. After implementing chatbots, PayPal experienced a 20 percent decrease in customer support costs and a 25 percent increase in user engagement. These chatbots can handle routine inquiries, resolve issues, and make personalised product recommendations.
Another example is Citi, a US retail bank that developed an AI-powered Customer Analytic Record (CAR). This programme can consolidate customer data, including financial records, used products, and interactions across online banking. The data is linked to automated decision-making AI software for analysis. The system can then recommend personalised offers to customers via text and mobile banking.
Future prospects
According to David Griffiths, Citigroup’s chief technology officer, AI has the potential to revolutionise the banking industry and improve profitability. With the continuous development of AI technology, the fintech industry can further improve its customer service.
Ronit Ghose, another executive at Citigroup, predicts that in the future, every client will have an AI-powered device in their pocket. This innovation will improve their financial lives with enhanced AI in customer service.
However, there are still concerns about AI’s scalability limitations in handling vast amounts of tasks. In addition, AI’s access to customers’ data makes security an important area to ensure its credibility. FinTech companies should ensure digital compliance to earn customers’ trust.
FinTech Strategy and Interface joined Publicis Sapient at Money20/20 in Amsterdam for the launch of its third annual Global Banking Benchmark Survey and spoke with Head of Financial Services Dave Murphy about its findings
SHARE THIS STORY
The third annual Global Banking Benchmark Study from Publicis Sapient draws on insights from 1000+ senior executives in financial services across global markets. The study focuses on the goals, obstacles, and drivers of digital transformation in banking.
Global Banking Benchmark Study
The study was launched during Money20/20 Europe in Amsterdam last month. Eoghan Sheehy, Associate MD, and Grace Ge, Senior Principal, highlighted the banking industry is focused on improving existing processes rather than introducing new ones. Data Analytics and AI are identified as key priorities for digital transformation. Additionally, there is a focus on internal use cases and efficiency.
Eoghan and Grace also discussed the challenges faced by the banking industry. These include regulation, competition from companies like Amazon, and the need to attract talent. They emphasised the importance for financial institutions of modernising core infrastructure. Also, building cloud infrastructure to support ongoing digital transformation. Moreover, the study notes the prevalence of the development of custom-made tools and internal use cases for AI implementation. Furthermore, Eoghan and Grace provided examples of repeatable use cases and discussed the success factors for Data Analytics and AI.
Four key takeaways from Publicis Sapient
Four key tracks came out of the study…
Modernising the core will always be important. But modernising the core for its own sake and also building the cloud infrastructure that supports it or allows for it to be modern. A decent chunk of the survey responders are still very focused on this. Executives are stating they want to make sure their people can make the best use of the beautiful core they’ve now built.
GenAI is an area of thoughtful experimentation for the Neobanks. We’re talking about scaled microservices here. Instances where, across Neobanks, you’ll have the same machine learning model and the same GenAI text generator facilitating retail and SMEs. That’s pretty sophisticated and something everyone has to contend with.
Data Analytics transformation is a key priority using GenAI to do so along with bringing new talent into the game.
Payments has been a big theme at Money20/20… We’re seeing lots of activity around ancillary individual product areas.
“The study focuses on how to think about solving problems end-to-end. Banks are dealing with legacy issues and taking a customer first view into solving the challenges. The practical application of AI across the banks is a significant theme as they look to automate decision-making and deliver better credit risk models. AI is finally delivering a set of use cases that truly can impact the way banks operate and build their own technology.” Dave Murphy, Head of Financial Services, EMEA & APAC
Be among the first to receive the study by signing up here
This month’s cover story sees our sister brand Fintech Strategy reporting from Money20/20 Europe in Amsterdam – a pivotal event…
SHARE THIS STORY
This month’s cover story sees our sister brand Fintech Strategy reporting from Money20/20 Europe in Amsterdam – a pivotal event in the fintech calendar, drawing over 8,000 participants from 2,300 companies worldwide.
Welcome to the latest issue of Interface magazine!
The RAI Amsterdam Convention Centre was the location for the world’s leading fintech conference. Money20/20 Europe offered a unique blend of insightful keynotes, panel discussions, and networking opportunities that underscored the transformative power of emerging technologies in financial services. We met with SC Ventures, Lloyds Banking Group, OSB Group, AirWallex, Plaid, Paymentology, Episode Six, Mettle (Nat West Group) and more to take the pulse of the latest trends across the fintech landscape.
Under the theme of ‘Human X Machine’, Money20/20 Europe explored the relationship between humans and intelligent machines, focusing on how the partnership between artificial and human intelligence will forge a new era in finance…
Publicis Sapient: Global Banking Benchmark Study
Interface was also proud to partner with Publicis Sapient at Money20/20 Europe for the launch of its third annual Global Banking Benchmark Survey. The survey draws on the insight of over 1000 senior executives in financial services across various global markets and focuses on the goals, obstacles, and drivers of digital transformation.
We spoke with Head of Financial Services Dave Murphy about its findings. “The survey focuses on how to think about solving problems end-to-end. Banks are dealing with legacy issues and taking a customer first view into solving the challenges. The practical application of AI across the banks is a significant theme as they look to automate decision-making and deliver better credit risk models.”
At the launch event for the study, Eoghan Sheehy, Associate MD, and Grace Ge, Senior Principal, highlighted that banks are primarily focused on improving existing processes rather than introducing new ones. Data Analytics and AI are identified as key priorities for digital transformation, with a focus on internal use cases and efficiency.
Eoghan and Grace also discussed the challenges faced by banks, including regulation, competition from companies like Amazon, and the need to attract talent. They emphasised the importance for financial institutions of modernising core infrastructure and building cloud infrastructure to support ongoing digital transformation. The study also notes the prevalence of the development of custom-made tools and the prioritising of internal use cases for AI implementation. Eoghan and Grace also provided examples of repeatable use cases and discussed the success factors for Data Analytics and AI.
STO Building Group: Enabling and Empowering People
Claudia Healey, Chief Human Resources Officer at STO Building Group, spoke to Interface about the HR platform empowering its people in pursuit of a strategic vision… “Culture is the number one priority in a people business like STO Building Group (STOBG). If you’re not nurturing and inspiring your folks, well, they can just vote with their feet. They don’t have to stay. Or they could do worse, they could quit and stay. And that’s something we would never want. Meeting your people where they’re at, understanding their goals and aspirations, and how you can help them reach their potential is vital. Realising how you can really see your people and truly understand what matters to them, is an incredible priority.”
Also in this issue, AI hype has previously been followed by an AI winter, we hear from Scott Zoldi, Chief Analytics Officer at FICO who asks, ‘Is the AI bubble set to burst?’ Elsewhere, we round up the top events in tech and learn how businesses can ensure their cloud storage is more sustainable in an age of rising demand for data and AI. Cloud storage without the climate cost is possible explains Fasthosts CEO Simon Yeoman.
Our cover story this month focuses on the work of Arianne Gallagher-Welcher. As the Executive Director for the USDA Digital…
SHARE THIS STORY
Our cover story this month focuses on the work of Arianne Gallagher-Welcher. As the Executive Director for the USDA Digital Service, in the Office of the OCIO, her team’s mission is to drive a tech transformation at the USDA. The goal is to better serve the American people across all of its 50 states.
Welcome to the latest issue of Interface magazine!
Welcome to a new year of possibility where technology meets business at the interface of change…
“We knew that in order for us to deliver what we needed for our stakeholders, we needed to be flexible – and that has trickled down from our senior leaders.” Arianne Gallagher-Welcher, Executive Director for the USDA Digital Service reveals the strategic plan’s first goal. Above all, the aim is to deliver customer-centric IT so farmers, producers, and families can find dealing with USDA as easy as using an ATM.
BCX: Delivering insights & intelligence across the Data & AI value chain
We also sat down with Stefan Steffen,Executive Leader for Data Insights & Intelligence at BCX. He revealed how BCX is leveraging AI to strategically transform businesses and drive their growth. “Our commitment to leveraging data and AI to drive innovation harnesses the power of technology to unlock new opportunities, drive efficiency, and enhance competitiveness for our clients.”
Momentum Multiply: A culture-driven digital transformation for wellness
Multiply Inspire & Engage is a new offering from leading South African insurance provider Momentum Health Solutions. Furthermore, it is the first digital wellness rewards program in South Africa to balance mental health and physical health in pursuing holistic wellness. CIO, Ndibulele Mqoboli, discusses re-platforming, cloud migrations, and building a culture of ownership, responsibility, and continuous improvement.
Clark County: Creating collaboration for the benefit of residents
Navigating the world of local government can be a minefield of red tape, both for citizens and those working within it. Al Pitts, Deputy CIO of Clark County, talks to us about the organisation’s IT transformation. He explains why collaboration is key to support residents. “We have found our new Clark County – ‘Together for Better’ – is a great way to collaborate on new solutions.”
Also in this issue, we hear from Alibaba’s European GM Jijay Shen on why digitalisation can be a driving force for SMEs. We learn how businesses can get cybersecurity right with KnowBe4 and analyse the rise of ‘The Mobility Society’.
Doug Laney is Innovation Fellow at West Monroe and a leading Data & Analytics strategist. We caught up with the author of Infonomics and Data Juice to talk tech and how companies can measure, manage and monetise to realise the potential of their data
SHARE THIS STORY
Our cover story explores the rise of data and information as an asset.
Welcome to the latest issueof Interface magazine!
Interface showcases leadersaiming to take advantage of data, particularly in a new world of AI technologies where it is the fuel…
How to monetise, manage and measure data as an asset
Our cover star is pretty big in the world of analytics… We meet the guy who defined Big Data. Doug Laney is Innovation Fellow at West Monroe and a leading Data & Analytics strategist. We caught up with the author of Infonomics and Data Juice to talk tech and learn how companies can measure, manage and monetise to realise the potential of their information. In his first book Laney advised companies to stop being fixated on hindsight-oriented analytics. “It doesn’t actually move the needle on the business. In the stories I’ve compiled over the last decade, 98% have more to do with organisations using data to diagnose, predict, prescribe or automate something. It’s not about asking questions about what happened in the past.”
Canvas Worldwide: A data-driven media business
Continuing this month’s data theme, we also spoke with Alisa Ben, SVP, Head of Analytics at full-service media agency Canvas Worldwide. Data has transformed the organisation, and what its clients do. “We look holistically at the client’s business and sometimes the tools we have might be right for them, sometimes not. It’s more about helping our clients achieve their business outcomes.”
TUI Musement: from digital transformation to digital pioneer
At travel giant TUI, handling data effectively is paramount when communicating consistently and meaningfully with up to 25 million customers annually. David Garcia, CIO for TUI Musement, talks about the tech evolution driving the travel giant’s provision of experiences, transfers and tours. It’s a big part of its operational shift from local to global. “As a CIO, I’ve always been interested in how the tech innovations we drive can support the business and add value.”
Hiscox: making cybersecurity more accessible
Liz Banbury, CISO at Hiscox and president of (ISC)² London Chapter, talks to us about how cybersecurity can become a more accessible, realistic career path for almost anybody. “When I was at school, topics like computer science didn’t even exist,” Banbury explains. “In one of my first jobs, over in Hong Kong, we were still using a typewriter! A lot has changed. My key point here is that there’s a lot of cybersecurity professionals who are really good at their job. They are inspiring, and have come from all walks of life. Crucially, they don’t have a maths, computer science, or technological background at all. But they still make great cybersecurity professionals.
Portland Community College: Risk vs Speed in Cybersecurity
Reet Kaur, former Chief Information Security Officer at Portland Community College, discusses the organisation’s transition to the cloud amid a digital transformation journey. “I don’t want to work with people who just say yes all the time. I want my ideas challenged to help forge the excellence in the security programmes I help build.”
DBHDS: Cybersecurity in healthcare
The Virginia Department of Behavioral Health and Developmental Services (DBHDS) exists to create ‘a life of possibilities for all Virginians’ and transform behavioural health. Its focus is on supporting people across the entire commonwealth. It helps them get the support they need in order to take wellness and recovery into their own hands. In an area like healthcare, sensitive information is all over the place, meaning cybersecurity is a priority – and this is where Glendon Schmitz, CISO at DBHDS, comes in. “The security team exists to help the wider organisation achieve its objectives with data. We’re there to protect the business, not the other way around.”
Also in this issue, we schedule the can’t miss tech events and get the lowdown on IoT security from the Mobile Ecosystem Forum.
This month’s cover story sees us speak with Brad Veech, Head of Technology Procurement at Discover Financial Services.
Having been a leader in procurement for more than 25 years, he has been responsible for over $2 billion in spend every year, negotiating software deals ranging from $75 to over $1.5 billion on a single deal. Don’t miss his exclusive insights where he tells us all about the vital importance of expertly procuring software and highlights the hidden pitfalls associated.
“A lot of companies don’t have the resources to have technology procurement experts on staff,” Brad tells us. “I think as time goes on people and companies will realise that the technology portfolio and the spend in that portfolio is increasing so rapidly they have to find a way to manage it. Find a project that doesn’t have software in it. Everything has software embedded within it, so you’re going to have to have procurement experts that understand the unique contracts and negotiation tactics of technology.”
There are also features which include insights from the likes of Jake Kiernan, Manager at KPMG, Ashifa Jumani, Director of Procurement at TELUS and Shaz Khan, CEO and Co-Founder at Vroozi.
This month’s exclusive cover story features a fascinating insight into the procurement function at lighting giant, Signify.
A forward-thinking enterprise constantly reevaluating and adapting its operations against an ever-changing landscape, Signify has recently transformed its procurement function. And so we join Luc Broussaud, Global Head of Procurement/CPO and Arnold Chatelain, Transformation Program Director for Signify’s Procurement Organization to see why, and how, they have evolved procurement at the company.
Signify is a global organisation spread over all continents and Luc heads up the procurement function. According to Luc, he and his team no longer engage in traditional transactional procurement, but instead leverage digitalisation to deliver competitive prices as well as what they call ‘concept saving’, “Which is how we redesign or improve our product; leveraging the knowledge of our suppliers to make it cheaper, more efficient, easier to manufacture and install, and more sustainable for the planet.”
Luc joined Signify in 2018, after being the CPO of Nokia (based in Shanghai) and has always been working within procurement. He joined Signify with a broad skillset and a wealth of experience. “I joined because the people I talked to, from the COO to the CEO and CFO were all incredibly knowledgeable and passionate about procurement,” he reveals. Read the full story here!
Not only that, but we also have some incredible insights from procurement leaders at Heijmans, Datadog, HICX, DPW, ProcureCon Asia and SourcingHaus Research! Plus, the very best procurement events of 2023.
Amit Thawani, CIO for Consumer Data & Engagement Platforms at Wells Fargo, on the journey towards becoming a customer-centric company
SHARE THIS STORY
This month’s cover story reveals how a customer-centric approach to technology is helping Wells Fargo deliver stable, secure, scalable, and innovative services.
Welcome to the latest issueof Interface magazine!
It’s our biggest issue yet! The common theme this month is the focus on the creation of customer-centric technologies that offer reliable, secure and helpful user journeys from travel and banking to health and business.
Interface dives deep for insights on understanding, planning, implementing and communicating change across industries.
Amit Thawani, Chief Information Officer (CIO) for Consumer Data & Engagement Platforms (CDEP) on the technology journey at Wells Fargo: “All tech employees at Wells Fargo are tasked with working towards delivering stable, secure, scalable, and innovative services at speed that delight and satisfy our customers while unleashing the skills potential of our employees.”
TUI: Developing a technology ecosystem
Kristof Caekebeke, CIO for Product & Engagement, is a member of the leadership team that is driving the transformation of the TUI technical ecosystem which has seen Master Domain Owners taking different blocks of the ecosystem under their control to roll out across the organisation.
TUI Group
Responsible for product and engagement, Caekebeke’s focus is on building products out of the thousands of hotels, flights, experiences and cruises TUI is offering. “I’m responsible for every contact point between the customer and TUI. The websites, the mobile apps, the retail systems – any contact point we have between the customer and TUI. It’s a large team of 1,100 tech people.
A digital bank transformation journey with Banco PAN
“Until 2018 Banco PAN was very much an analogue company reliant on legacy paper processes,” recalls Leandro Marçal. Joining the bank in December 2020, to become Technology & Operations Director (CIO/COO), Marçal was tasked with accelerating a digital transformation journey.
“Banco PAN invested in innovation before I arrived,” says Marçal. “It is my team’s job to formalise the path towards becoming a digital bank. Our legacy operation was digitalising. It was an opportunity to improve the customer experience with our checking account and credit card systems.”
Pohlad Companies: The power of people
A pillar of the community in Minneapolis, Pohlad Companies is well known to Minnesotans for its influence, its charity work, and the opportunities it has created for people since the 1950s.
Alongside significant commercial real estate investments, Pohlad Companies owns a custom engineering and robotics company, a group of automotive dealerships specialising in luxury vehicles, a film production studio, and many more businesses. Famously, the Pohlad family also owns the Minnesota Twins, a Major League Baseball team.
This variety is part of what makes Rachel Lockett’s job so exciting. She’s Pohlad Companies’ CIO and has spent a decade in her current role. Lockett began her career as a programmer over 25 years ago and quickly moved into IT leadership management.
Coalfire: Embracing change in cybersecurity
If you wait for something to happen, then it’s often too late. The art of having a finger on the pulse is an essential ingredient to success. Failure to manage change and implement cybersecurity protocols could mean leaving an organisation vulnerable to hackers.
Sreeveni Kancharla, Coalfire’s first Chief Information Officer, is leading the company’s digital transformation with unwavering determination. As a cybersecurity advisor, Coalfire assists private and public sector organisations in managing threats, closing gaps, and mitigating risks. Kancharla ensures that her team stays up-to-date with the latest technologies to guard against zero-day attacks.
Uni of Kansas Health: Cybersecurity at the heart
Speed versus safety. The two topics are intrinsically linked and vital in their own individual way. But can you have both in healthcare when the risks are so great? Ultimately, there is no higher stake than saving people’s lives – it goes above everything and is why cybersecurity is so vital.
Protecting the healthcare system
“There’s nothing more important to me than patient care,” affirms Michael Meis, Associate Chief Information Security Officer at The University of Kansas Health System. “It is one of the highest callings you can imagine, to be able to help people. While the cybersecurity team and me, individually, do not directly care for patients, we enable a lot of that patient care to continue and to be able to achieve some of the goals that the health system has set to provide that healing, research, and innovation within the healthcare space.”
Also in this issue, we ask ChatGPT what the future holds for AI and learn from Zoom how businesses can leverage analytics for insights from their hybrid events.
Mike Randall, CEO at Simply Asset Finance, discusses how to build a people-first strategy that enables growth.
SHARE THIS STORY
As the UK economy continues to balance on the edge of a recession, employee retention is quickly being pushed to the top of CEOs’ lists. Over the past couple of years, the job market has shifted dramatically with previously unheard terms such as ‘the great resignation’, ‘quiet quitting’ and ‘hybrid working’ becoming commonplace. People are rightly prioritising their working situation and job satisfaction levels, questioning whether they believe in the organisations they are committing so much time to.
Consequently, there has been a power dynamic shift in favour of the workforce. Reportedly in the third quarter of 2022 businesses witnessed over 365,000 job-to-job resignations across the UK. In similar fashion, the phenomenon of ‘quiet quitting’ – doing the bare minimum required of a job – has become a growing concern but its rise is prompted by a growing number of employees feeling disengaged in their roles.
Against this backdrop of a highly turbulent job market, and increasingly difficult macro-economic pressures, it’s vital for CEOs to prioritise a people-first strategy to ensure healthy growth for their business in 2023. Data from Deloitte has even revealed that experts believe how engaged a workforce feels can directly correlate to overall business output, with 93% of HR and business leaders in agreement that building a sense of belonging is crucial for organisational performance.
Mike Randall, CEO at Simply Asset Finance
However, creating the right environment and recruiting, maintaining and nurturing the right talent to ensure a people first approach can be daunting. With this in mind, here are four learnings CEOs might want to consider when approaching this challenge:
1. Define your beliefs
Before CEOs and founders can hope to attract the right talent, it is critical to first distil and translate the business vision into something that can be understood by employees. Put simply, this means defining the business’ beliefs.
Some business leaders may already refer to this as an ‘employer brand’, and it can be key to not only securing better talent, but also saving a business money in the long-term. Data from LinkedIn for example, recently found that a strong employer brand can help to reduce employee turnover by as much as 28% and cost-per-hire by 50%. Defining these beliefs – or the tenets a business does and doesn’t stand for – is therefore the perfect exercise to put a vision onto paper, and clearly communicate it to its prospective talent.
2. Build a solid culture
Once these beliefs have been defined, they must be reflected, and built into a strong culture. A business’ beliefs should permeate through the whole organisation – from customer communications, to how staff are treated, to how leaders run the business. Culture should essentially be a representation of a business’ beliefs being put into practice.
Building a strong culture in a business, however, is not solely about these beliefs but also extends into how employees are equipped with the tools they need to succeed. Companies that invest in learning and development for example, have been found to benefit from a 24% higher profit margin than those that don’t, according to the Association of Talent Development. Training and development should therefore be seen as a worthwhile and necessary investment that can solidify your culture and ensure profitability, not just an unavoidable cost.
3. Invest in retention
With research from Oxford Economics estimating the average turnover per employee earning £25,000 a year to be £30,000 plus, there is an evident cost to businesses that fail to invest in retention. Tackling this will mean regularly taking the time to truly understand what makes employees tick – and more specifically, understanding their motivations, attitudes, behaviours, strengths and weaknesses.
As the past few years have evidenced, individuals are no longer deciding where they work solely based on salary, but are also thinking about employer values, flexibility, and benefits. To avoid employee churn, businesses should regularly take time to understand what drives their employees and implement retention strategies to address these drivers. Gathering and analysing employee data will play an important role here over the coming years, and should be built into a long-term strategy to optimise employee satisfaction.
4. Build for the future
A common challenge encountered by modern businesses and startups wanting to take a people first approach, can be their ability to stay committed to it. As a business grows in size and becomes successful, it can be all too easy to let external factors dictate its purpose and for it to lose sight of what it initially stood for. The reality is that when this happens, a business is in its most vulnerable state – as its beliefs become increasingly distant, and worse, employees no longer understand what it stands for.
When creating a people-first strategy its therefore important to think long-term. If there are external factors that will potentially put this strategy at risk in future, it’s crucial to identify them, and put in practical steps to mitigate them where possible. The pandemic, for example, is a prime example of an external factor that interrupted the status quo of many businesses – disrupting employees, customers and operations in general. While they can be unpredictable in nature, having a plan to get through these times can help to get you back on track and reassure talent that a solution is in place.
In this economic climate, defining beliefs, building a solid culture, and retention plan should be at the core of every business’ strategy. It’s only when these things are in place that a business can hope to attract and retain talented people that exude the same passion and values built into the heart of a business. As while a business’ growth may be defined by its leaders, it is delivered by its people who are putting that vision into practice.
Procurement is in a state of flux. Against a backdrop of economic uncertainty, the procurement landscape is volatile and requires…
SHARE THIS STORY
Procurement is in a state of flux.
Against a backdrop of economic uncertainty, the procurement landscape is volatile and requires agility to navigate turbulent waters. But, despite significant disruption could there still be opportunity?
Simon Whatson, Vice President of Efficio Consulting, is optimistic about the future of digital procurement and despite a challenging few years he is confident of a successful bounce back. He gives us the lowdown on the direction of travel for digital procurement in 2023.
As an executive with considerable experience in the space, we’d love to learn more about your background and how you ended up in procurement. Why was this the specialism for you and how did you get involved to begin with?
Simon Whatson (SW): “I think the one-word answer of how I came into procurement was accidental. I studied maths at university, with a year in France, before I began looking for different roles to apply for.
“Eventually, I was offered a position with a big plumbing and heating merchant with global operations. I worked in that supply chain team for two and a half years. Although it was called supply chain, a lot of the work was procurement, which involved negotiating with suppliers. It was after that stint there, that I discovered consulting and joined a boutique procurement consultancy. Now I am onto my third consultancy and I’m very happy here!
“In terms of why I’ve stayed, one of the success factors in procurement is being able to work cross-functionally. Procurement doesn’t own any of the spending that it is responsible for helping to optimise. It must work with other functions and the spend owners. I quite like the people side of that, building relationships, almost selling internally to bring teams together. That really appeals to me and is a key reason why I’ve been very happy in procurement.”
As we move into exploring procurement today in 2023. The space is filled with challenges and complexities. You only need to look at the last few years. Covid, war in Ukraine, inflation – how would you describe the world’s recent challenges and their effect on the industry and what do you feel CPOs and leaders can do to combat these issues?
SW: “I would flip it around and say that these are not so much challenges but rather opportunities for procurement. When I started my career 18 years ago, procurement was often fighting to get a voice and there were complaints that procurement was not represented at the top table, but the war in Ukraine, inflation, COVID and ESG, these are things which are now on the C-suite agenda and procurement is ideally positioned to help companies face those challenges. If you think about COVID and the war in Ukraine, procurement is in a privileged position to help with this.
“I see some procurement functions that prefer to do what they know, which focuses on the process and transactional side. However, there are also many forward-thinking CPOs and procurement professionals out there, that have really seized this opportunity of being on the C-suite agenda and drive the thinking and the solutions to some of these big challenges we’re seeing.”
Although new technology in procurement has been around for well over a decade, digitalisation has become so much more of an important topic. How would you sum up where procurement and supply chain are in terms of digital transformation today?
SW: “It’s a bit laggard, but digital transformation is difficult, and we have to recognise there are some real trailblazers. There are some firms doing some fantastic things in digital to produce better outcomes. If you contrast your experience when you’re buying something in your private life, it’s much easier than 20 years ago. You can get access to a wealth of pre-sourced things, whether it’s food, a holiday, a car, or a book. You can see reviews of what other people think of these things.
“But when you go into your workplace as a business user and you want to buy something, it doesn’t quite work like that yet. You often have to fill in a form, send it off and wait for them to come back to you. They might come back a little bit later than you were hoping and might tell you that they don’t have that part on the supply frameworks. I think people sometimes get confused about how it can be so easy to buy something as large as a car or a holiday on their sofa at home, but when they want to buy something at work, it seems to be quite cumbersome. Digital can help a lot with that, but it is incumbent on organisations and procurement functions to figure out how to recreate that customer experience that we’ve become accustomed to in our private lives.”
With a new generation of leaders growing up with technology, some might say that it could be a key driver in helping to speed the adoption in procurement along. Is this something you would agree with or what would you point to as a key driver?
SW: “I do think that it will act as one of the catalysts for further digital transformation in organisations, because if procurement doesn’t manage to recreate that customer experience that the new generation expects, then they won’t use procurement going forward and will look to bypass it.
“The analogy that I’ve used previously in this case is one of travel agents. I remember as a child, my parents were able to take us on holiday and I remember the whole process. We would walk into town to the travel agent, and look at some of the brochures of options. They often then had to phone the various airlines or resorts on our behalf. They might not be able to get through, so we’d have to come back the next day. I remember as a child being quite excited by the whole process but actually, thinking back, it was quite cumbersome. You compare that to now, with being able to review online, and you can get instant answers to your questions. It’s not a coincidence that travel agents don’t really exist anymore.”
How much of a challenge is it to not get caught leveraging technology for technologies sake? How important is it to stay true to your approach and be strategic?
SW: “We conducted a study of many procurement leaders and CPOs a few years ago, and one of the things that we found was that about 50% of procurement leaders admitted to having bought technology just on the basis of a fear of missing out, without any real understanding of the benefits that technology was going to bring. That was a real shock and a revealing find because technology is not cheap, and its implementation is quite disruptive. If you’re purchasing a system because everybody else is using it, then there could be some pretty costly mistakes. It is really important to make sure that when buying technology, it is because the benefits are fully understood.
“My advice to companies when looking to digitalise is own your data, visualise that data, and manage your knowledge. If you can focus on getting those things right in that order, and make your technology decisions to support that goal, then that’s a much better way of thinking about it rather than just jumping in and buying a piece of technology.”
It’s clear that the procurement space is an exciting, but challenging, place to be. What do you think will play a key role in the next 12 months to push the digital conversation further to take procurement to the next level?
SW: “Looking forward, one thing that procurement needs to do and continue to do is attract the best people. Ultimately, people are what makes an organisation, and it is what makes a function successful. I think procurement has often not looked for the right skills in the people that it employs. Traditionally, it’s looked for people with procurement experience and while they are valuable and required, we also need leadership potential. People who think a bit more outside the box and aren’t so process driven. A lot of what procurement has done in previous years has been process driven, so if you’re just limiting your search of people to those that have had procurement experience, you’re inevitably going to end up with a lot of people who are process driven.
“I think being bolder and recruiting people from different backgrounds with different skill sets is the way to go. If procurement can ‘own’ the ESG space, that will help with the younger generation see procurement make a difference. I think that’s one thing that will be key to success going forward.”
Check out the latest issue of CPOstrategy Magazine here.
Paul Farrow, Vice President of Hilton Hotels’ Supply Management, sits down with us to discuss how his organisation’s procurement function has evolved amid disruption on a global scale
SHARE THIS STORY
The hospitality industry has endured a rough ride over the past few years.
Following the COVID-19 pandemic which stopped the world in its tracks and now with millions facing a cost-of-living crisis, it’s been a period of unprecedented disruption for those involved in the space and beyond.
But it’s a challenge met head-on by Paul Farrow, Vice President of Supply Management at Hilton Hotels, and his team who have been forced to respond as the world continues to shift before their eyes.
Farrow gives us a closer look into the inner workings of his firm’s procurement function and how he has led the charge during his time with Hilton Hotels.
Could we start with you introducing yourself and talking a little about your role at Hilton Hotels?
Paul Farrow (PF): “I’m the Vice President of Hilton’s Supply Management, or HSM as we call it. I’ve been with Hilton Hotels for 12 and a half years, and my role is to head the supply chain function for our hotels across Europe, the Middle East and Africa.
“Over the past few years, Hilton has grown rapidly and has now got 7,000 hotels in over 125 countries globally. What is really exciting is Hilton Supply Management doesn’t just supply Hilton Hotels and the Hilton Engine because we also now supply our franchisees and competitive flags. While we have 7,000 hotels globally, Hilton Supply Management actually supplies close to 13,000 hotels. That’s an interesting business development for us, and a profit earner too.”
You’re greatly experienced, I bet you’ve seen supply chain management and procurement change a lot in recent years?
PF: “The past two to three years have been tremendously challenging on so many industries but I’d argue that hospitality got hit more than most as a result of the Covid pandemic. Here at Hilton, supply management was really important just to keep the business operational throughout that tough time, but I’m delighted to say we’re fully recovered now.
“Looking back, it was undoubtedly difficult, and you only have to look at the media to see that we’re now going through a period of truly unprecedented inflation. On top of the normal day job, it’s certainly been a very busy time.”
Hospitality must have been under an awful lot of pressure during the pandemic…
PF: “Most of our teams as a business and all functions have worked together far more collaboratively than ever before through the use of technology and things like Microsoft Teams and Zoom. Trying to work remotely as effectively as possible changed the way we all had to think and the way we had to do. Now we’re back in the workplace and in our offices, we’re actually looking to take advantage of that new approach.”
Inflation, rising costs, energy shortages, as well as drives towards a circular economy means it’s quite a challenging time for CSCOs and CPOs right now, isn’t it?
PF: “Those headwinds have caused and created challenges of the like that we’ve not seen before. The war in Ukraine and Russia has meant significant supply chain disruption and supply shortages of some key ingredients and raw materials. China is a significant source of materials and they’re still having real challenges to get their production to keep up with demand.
“All the local and short-term challenges are around energy and fuel pricing, so throughout the supply chain that’s been a major factor to what we’ve had to deal with. On top of that is the labour shortages. We rely heavily throughout the supply chain and within our business to utilise labour from around the world. In my region, particularly from say Eastern Europe as well as other businesses all fighting for a smaller labour pool than we had before. We are fighting with the likes of the supermarkets, Amazon’s, not just other hotel companies to capture the labour pool we need both in our properties but also within our supply chain supplies themselves.
Hilton operates a rather unique procurement function, doesn’t it?
PF: “We trade off the Hilton name because our brand strength is something that we are able to utilise and we’re very proud of, but we’ve also got additional leverage by having that group procurement model.
“We’ve got essentially two clients. We’ve got our managed estate which is when an owner chooses to partner with Hilton, they’re signing a management agreement because they want the benefit and value of the Hilton engine. That could be revenue management, how we manage onboarding clients and customers through advertising, as well as the other support we give in terms of finance, HR, marketing and sales as well as procurement.”
HSM is a profit centre and revenue driver through its group procurement model but how does this work?
PF: “Our secret sauce is our culture. It’s our people and that filters across all of our team members and indeed all of our functions. The key strategic pillars are the same for health and supply management around culture, maximising performance and so on as they are across the overall global business.
“Across our 7,000 plus hotels, the majority are actually franchised hotels because that’s the legacy of what still is the model in the US. When I joined Hilton 12 and a half years ago, the reverse is true where nearly all of our hotels in Europe, Middle East and Africa, and indeed in Asia Pacific, were and are managed. In the Europe, Middle East and Africa regions right now we’re building up close to a 50/50 split between managed, leased and franchised.”
What has pleased you most about the roll-out of the HSM?
PF: “It’s certainly not been easy because we’ve got 70 countries that sit within our region here in EMEA and Hilton’s penetration in those individual countries is very different. We may have 100 hotels in one of those markets and only one or two in specific countries. Our scale and our ability to get logistics solutions is different by market.
“Getting everyone on board to what we want to achieve to our guests and to our owners means we have to pull different levers. We have very effective brand standards. If you’re signing up to Hilton, you’re signing up to delivering against those brand standards that we believe are right for our organisation.”
What kind of feedback have you had from your clients?
PF: “Integrity is in our DNA, and we work very closely with our suppliers who we value as partners. These are long-term relationships, and we work hand in hand because we have to see that they’re successful so that we can be successful – it’s really important to what we do and we constantly look for feedback.
“With our internal and our external customers, we’ll have quarterly business reviews and so we’ll get that feedback through surveys where we are asking them to tell us what we do well and what we could do better. Our partners are now asking what additional value can you do to bring support to our organisation through ESG? So that’s what’s on the table now when it wasn’t before. But it’s not just that – it’s about the security of supply competitiveness, competitiveness of pricing, and a whole bunch of other very important things as well.”
Looking to the future, what’s on the agenda for the next few years?
PF: “We’re out there meeting and greeting people in person and there’s always new opportunities that make things exciting in what we do and how we work. Innovation’s very high on our agenda and we’re very proud of what we do in food and beverage. In non-food categories, it’s about how we support our owners and our hotel general managers to find that competitive edge and do the next big thing ahead of our competitors.”
Anything else important to know?
PF: “One thing we’ve been able to take full advantage of is how we’ve been able to grow our business by bolting on new customers. I think it’s fantastic that our competitors choose to use Hilton Supply Management because they benchmarked what our capabilities are and how competitive we are.
“Another key part of the agenda is environmental, social and governance (ESG) sustainability. Responsible sourcing and everything that sits within that is front and centre of what we do. Within that you’ve got human rights, animal welfare, single use plastics as well as general responsible sourcing like managing food waste. The list is very long, but they’re all very important.”
Check out the latest issue of CPOstrategy Magazine here.
Here are 10 of the most important leadership skills that CEOs need to demonstrate in 2023.
SHARE THIS STORY
In today’s world, a CEO needs to be lots of things to different people. The importance of having the leadership skill to being able to lead through unprecedented disruption was highlighted by the COVID-19 pandemic and helped to define what makes a good CEO.
Here are 10 of the most important leadership skills that CEOs need to demonstrate in 2023.
1. Clear communication
Communicating effectively with employees is one of the most vital skills any leader can have. By adopting a transparent mindset, it leaves little room for miscommunication or misunderstandings. But rather than just being eloquent, CEOs should deliver meaningful content too. A CEO needs to be able to communicate the essence of the business strategy and the methodology for achieving it.
2. Strong talent management strategy
People are the most important component of all businesses. CEOs who are able to recruit and retain key employees have a greater chance of increasing productivity and efficiency. After recruiting good people, the key to retaining them is by harnessing a positive work environment that empowers employees to succeed.
3. Decision-making
As a leader, thinking strategically to make effective decisions is vital to the success of an organisation. Making decisions is a key part of leadership as well as having the conviction to stand by decisions or agility to adapt when those decisions don’t have the required outcome. While all decisions might not be favourable, making unpopular but necessary calls are important characteristics of a good leader.
4. Negotiation
Negotiation is a fundamental part of being a CEO. In a top leadership position, almost every business conversation will be a negotiation. Good negotiations are important to an organisation because they will ultimately result in better relationships, both with staff inside the company and externally. An effective leader will also help find the best long-term solution by finding the right balance and offering value where both parties feel like they ‘win’.
5. Creativity and innovation
Being quick-thinking and ready to explore new options are great skills of a CEO. Creative leadership can lead to finding innovative solutions in the face of challenging and changing situations. It means in the midst of disruption, of which it has been increasingly prevalent, leaders can still find answers for their teams. Creative CEOs are those who take risks and empower employees to drop outdated and overused practices to innovate and try new things that could lead to greater efficiency.
6. Agility
Without agility over the past few years, businesses would have failed. CEOs were forced to embrace remote working following the advent of the COVID-19 pandemic whether they liked it or not. Now, faced against a potential recession, these macroeconomic events are unavoidable and have to be managed carefully. Effective leaders will have their fingers on the pulse and ready to respond to changes.
7. Strategic forecasting
Creating a clear path forward is essential to achieving uninterrupted success. The ability to look into the future and identify trends and issues to then react to is vital. Good CEOs are able to plan strategically and make informed decisions to set goals and plan for the future easily.
8. Delegation
CEOs can’t do everything. A leader tends to be pulled in a number of different ways every day and it is impossible to be on top of everything. This means the importance of bringing in a team of people who are trusted and skilled in their respective areas of expertise. Successful CEOs are expert delegators because they recognise the value of teamwork and elevating those around them.
9. Approachability
An approachable CEO who welcomes conversation and is an active listener will help employees feel at ease raising issues or concerns. This approach will help build strong relationships with staff and customers and encourage a healthy culture which is beneficial to employee retention. Leaders with strong, trusting and authentic relationships with their teams know that investing time in building these bonds which makes them more effective as a leader and creates a foundation for success.
10. Growth mindset
If a CEO arms themselves with a growth mindset it allows them to meet challenges head-on and evolve. This shines a light on improving through effort, learning and persistence. As others may back down in the face of adversity and upheaval, successful CEOs will strive to move forward with confidence. Those with a growth mindset are unlikely to be swayed as they have the tools needed to reframe challenges as opportunities to grow.
In McKinsey’s latest report ‘Actions the best CEOs are taking in 2023’, we examine three of the biggest trends on the c-level agenda
SHARE THIS STORY
Anyone can sail a ship when things are going well. But it takes a strong, robust and characterful CEO to steer a business through choppy waters and out the other side.
In McKinsey’s latest report ‘Actions the best CEOs are taking in 2023’, the research and advisory firm uncovered which trends are set to have the biggest impact on how CEOs lead their business throughout the year.
McKinsey’s CEO Excellence Survey surveyed 200 of the best corporate CEOs of the past 15 years. This was completed by whittling down a list of all the current and former CEOs of the 1,000 largest public companies during that timeframe. The list was subsequently filtered based on tenure, including only those who had completed at least six years in the role. From there, the CEOs were continuously shortlisted until the best 200 were determined.
Each CEO was asked to identify the top three trends that are set to determine how leaders tackle the future. Here is an insight into those findings.
1. Actions to deal with digital disruption
CEOs are targeting digital trends in three key ways: developing advanced analytics, enhancing cybersecurity and automating work. OpenAI’s launch of ChatGPT has accelerated the demand of companies looking to embrace advanced analytics for a competitive advantage. Improving cybersecurity is another key action for CEOs with the importance of guarding against external threats paramount amid strengthening and more mature cyberattacks. Lastly, automating work is another key priority to scale efficiency and eliminate boring and manual tasks which free up people’s time.
2. Actions to deal with the risk of high inflation and economic downturn
One CEO who is worried about economic uncertainty told McKinsey: “Act early to lower costs and protect the balance sheet so that you are stronger and leaner when the economy begins to turn more favourably.” McKinsey found that companies that outperformed the 2008 financial crisis cut operating costs by 1% before the downturn while the others expanded costs by the same percentage. The best performers reduced their debt by $1 for every $1 of book capital before the downturn. This can be done by reducing operating expenses, redesigning products and services as well as reassessing strategic and economic assumptions.
3. Actions to deal with the escalation of geopolitical risk
According to McKinsey, there are three actions to help manage the escalation of global and national crises. CEOs are targeting building robust compliance capabilities, creating resilience in supplier networks and investing in monitoring and response capabilities. These actions come following the challenges presented by COVID-19, the war in Ukraine and now inflation concerns. Many firms are choosing to build their trade compliance organisations and improve how they screen different customers and companies. While a defensive approach is the way forward for many, some companies see the turbulent times as an opportunity.
What does today’s CEO need to do to accelerate an organisation’s digital transformation journey?
SHARE THIS STORY
Digital transformation journeys are no one-size-suits-all. There is no singular way to welcome a new wave of technology into operations.
Since the turn of the century, digitalisation has had an increasingly influential impact on the way CEOs make decisions. Today’s world is full of disruption and potential risk. And with technology growing in complexity it can be challenging to lead such a revolution against a backdrop of economic uncertainty.
Embracing digital
According to KPMG 2022 CEO Outlook, which draws on the perspectives of 1,325 global CEOs across 11 markets, 72% of CEOs agree they have an aggressive digital investment strategy intended to secure first-mover or fast-follower status.
Advancing digitalisation and connectivity across the business is tied (along with attracting and retaining talent) as the top operational priority to achieve growth over the next three years. This digital transformation focus could be driven as a result of increasingly flexible working conditions and greater focus on cybersecurity threats.
However, the prospect of recession is threatening to halt digital transformation in the short-term. KPMG research found that four out of five CEOs note their businesses are pausing or reducing their digital transformation strategies to prepare for the anticipated recession.
This is reinforced further when 70% say they need to be quicker to shift investment to digital opportunities and divest in those areas where they face digital obsolescence.
When a company’s digital transformation ambition is mismatched to its readiness, it is the CEO’s responsibility to close the gap. According to Deloitte, in order to do this successfully, the CEO must assess the current level of organisational readiness for change.
This covers four key pillars that are mixed together to work out an organisation’s overall readiness: leadership, culture, structure and capabilities.
How CEOs can close the gap
Leadership: CEOs need to ensure their c-suite and other key executives are motivated and equipped to execute the vision. CEOs interviewed by Deloitte in a recent study emphasised the importance of the leadership team supporting the transformation vision and having a positive attitude and willingness to transform.
Culture: A large potential barrier to readiness in the organisation is down to culture. Low cultural readiness takes the form of bureaucratic, reactive and risk-averse ways of working that are at against the collaborative, proactive learning mindset needed for ambitious transformation.
Structure: If a company hopes to operate differently, it could mean the need for organising in an alternative way. CEOs will often need to lead the reorganisation of teams, assignment of new roles, revision of incentives, strategies to collapse organisational hierarchies or layers to increase agility.
Capabilities: CEOs need to equip their organisation with four key capabilities to harness digital for a superior capacity for change. These are nimbleness, scalability, stability and optionality which are often enabled or supercharged by digital technologies which are critical factors for competing in an increasingly disrupted world.
For now, one of the CEOs most important roles when steering the ship through disruption is to be ahead of the latest trends and tackle change head-on. By embracing a new digital future that will provide the company with long-lasting benefits, it will help create a brighter and future-proofed firm for years to come even after the CEO is gone.
Expert analysis of the tech trends set to make waves this year
SHARE THIS STORY
Digital transformation is a continuing journey of change with no set final destination. This makes predicting tomorrow a challenge when no one has a crystal ball to hand.
After a difficult few years for most businesses following a disruptive pandemic and now battling a cost-of-living crisis, many enterprises are increasingly leveraging new types of technology to gain an edge in a disruptive world.
With this in mind, here are what experts predict for the next 12 months…
1. Process Mining
Sam Attias, Director of Product Marketing at Celonis, expects to see a rise in the adoption of process mining as it evolves to incorporate automation capabilities. He says process mining has traditionally been “a data science done in isolation” which helps companies identify hidden inefficiencies by extracting data and visually representing it.
“It is now evolving to become more prescriptive than descriptive and will empower businesses to simulate new methods and processes in order to estimate success and error rates, as well as recommend actions before issues actually occur,” says Attias. “It will fix inefficiencies in real-time through automation and execution management.”
2. The evolution of social robots
Gabriel Aguiar Noury, Robotics Product Manager at Canonical, anticipates social robots to return this year. After companies such as Sony introduced robots like Poiq, Aguiar Noury believes it “sets the stage” for a new wave of social robots.
“Powered by natural language generation models like GPT-3, robots can create new dialogue systems,” he says. “This will improve the robot’s interactivity with humans, allowing robots to answer any question.
“Social robots will also build narratives and rich personalities, making interaction with users more meaningful. GPT-3 also powers Dall-E, an image generator. Combined, these types of technologies will enable robots not only to tell but show dynamic stories.”
3. The rebirth of new data-powered business applications
Christian Kleinerman, Senior Vice President of Product at Snowflake, says there is the beginning of a “renaissance” in software development. He believes developers will bring their applications to central combined sources of data instead of the “traditional approach” of copying data into applications.
“Every single application category, whether it’s horizontal or specific to an industry vertical, will be reinvented by the emergence of new data-powered applications,” affirms Kleinerman. “This rise of data-powered applications will represent massive opportunities for all different types of developers, whether they’re working on a brand-new idea for an application and a business based on that app, or they’re looking for how to expand their existing software operations.”
4. Application development will become a two-way conversation
Adrien Treuille, Head of Streamlit at Snowflake, believes application development will become a two-way conversation between producers and consumers. It is his belief that the advent of easy-to-use low-code or no-code platforms are already “simplifying the building” and sharing of interactive applications for tech-savvy and business users.
“Based on that foundation, the next emerging shift will be a blurring of the lines between two previously distinct roles — the application producer and the consumer of that software.”
He adds that application development will become a collaborative workflow where consumers can weigh in on the work producers are doing in real-time. “Taking this one step further, we’re heading towards a future where app development platforms have mechanisms to gather app requirements from consumers before the producer has even started creating that software.”
5. The Metaverse
Paul Hardy, EMEA Innovation Officer at ServiceNow, says he expects business leaders to adopt technologies such as the metaverse in 2023. The aim of this is to help cultivate and maintain employee engagement as businesses continue working in hybrid environments, in an increasingly challenging macro environment.
“Given the current economic climate, adoption of the metaverse may be slow, but in the future, a network of 3D virtual worlds will be used to foster meaningful social connections, creating new experiences for employees and reinforcing positive culture within organisations,” he says. “Hybrid work has made employee engagement more challenging, as it can be difficult to communicate when employees are not together in the same room.
“Leaders have begun to see the benefit of hosting traditional training and development sessions using VR and AI-enhanced coaching. In the next few years, we will see more workplaces go a step beyond this, for example, offering employees the chance to earn recognition in the form of tokens they can spend in the real or virtual world, gamifying the experience.”
6. The year of ESG?
Cathy Mauzaize, Vice President, EMEA South, at ServiceNow, believes 2023 could be the year that environmental, social and corporate governance (ESG) is vital to every company’s strategy.
“Failure to engage appropriate investment in ESG strategies could plunge any organisation into a crisis,” she says. “Legislation must be respected and so must the expectations of employees, investors and your ecosystem of partners and customers.
“ESG is not just a tick box, one and done, it’s a new way of business that will see us through 2023 and beyond.”
7. Macro Trends and Redeploying Budgets for Efficiency
Ulrik Nehammer, President, EMEA at ServiceNow, says organisations are facing an incredibly complex and volatile macro environment. Nehammer explains as the world is gripped by soaring inflation, intelligent digital investments can be a huge deflationary force.
“Business leaders are already shifting investment focus to technologies that will deliver outcomes faster,” he says. “Going into 2023, technology will become increasingly central to business success – in fact, 95% of CEOs are already pursuing a digital-first strategy according to IDC’s CEO survey, as digital companies deliver revenue growth far faster than non-digital ones.”
8. Organisations will have adopted a NaaS strategy
David Hughes, Aruba’s Chief Product and Technology Officer, believes that by the end of 2023, 20% of organisations will have adopted a network-as-a-service (NaaS) strategy.
“With tightening economic conditions, IT requires flexibility in how network infrastructure is acquired, deployed, and operated to enable network teams to deliver business outcomes rather than just managing devices,” he says. “Migration to a NaaS framework enables IT to accelerate network modernisation yet stay within budget, IT resource, and schedule constraints.
“In addition, adopting a NaaS strategy will help organisations meet sustainability objectives since leading NaaS suppliers have adopted carbon-neutral and recycling manufacturing strategies.”
9. Think like a seasonal business
According to Patrick Bossman, Product Manager at MariaDB corporation, he anticipates 2023 to be the year that the ability to “scale out on command” is going to be at the fore of companies’ thoughts.
“Organisations will need the infrastructure in place to grow on command and scale back once demand lowers,” he says. “The winners in 2023 will be those who understand that all business is seasonal, and all companies need to be ready for fluctuating demand.”
10. Digital platforms need to adapt to avoid falling victim to subscription fatigue
Demed L’Her, Chief Technology Officer at DigitalRoute, suggests what the subscription market is going to look like in 2023 and how businesses can avoid falling victim to ‘subscription fatigue’. L’Her says there has been a significant drop in demand since the pandemic.
“Insider’s latest research shows that as of August, nearly a third (30%) of people reported cancelling an online subscription service in the past six months,” he reveals. “This is largely due to the rising cost of living experienced globally that is leaving households with reduced budgets for luxuries like digital subscriptions. Despite this, the subscription market is far from dead, with most people retaining some despite tightened budgets.
“However, considering the ongoing economic challenges, businesses need to consider adapting if they are to be retained by customers in the long term. The key to this is ensuring that the product adds value to the life of the customer.”
11. Waking up to browser security
Jonathan Lee, Senior Product Manager at Menlo Security, points to the web browser being the biggest attack surface and suggests the industry is “waking up” to the fact of where people spend the most time.
“Vendors are now looking at ways to add security controls directly inside the browser,” explains Lee. “Traditionally, this was done either as a separate endpoint agent or at the network edge, using a firewall or secure web gateway. The big players, Google and Microsoft, are also in on the act, providing built-in controls inside Chrome and Edge to secure at a browser level rather than the network edge.
“But browser attacks are increasing, with attackers exploiting new and old vulnerabilities, and developing new attack methods like HTML Smuggling. Remote browser isolation is becoming one of the key principles of Zero Trust security where no device or user – not even the browser – can be trusted.”
12. The year of quantum-readiness
Tim Callan, Chief Experience Officer at Sectigo, predicts that 2023 will be the year of quantum-readiness. He believes that as a result of the standardisation of new quantum-safe algorithms expected to be in place by 2024, this year will be a year of action for government bodies, technology vendors, and enterprise IT leaders to prepare for the deployment.
“In 2022, the US National Institute of Standards and Technologies (NIST) selected a set of post-quantum algorithms for the industry to standardise on as we move toward our quantum-safe future,” says Callan.
“In 2023, standards bodies like the IETF and many others must work to incorporate these algorithms into their own guidelines to enable secure functional interoperability across broad sets of software, hardware, and digital services. Providers of these hardware, software, and service products must follow the relevant guidelines as they are developed and begin preparing their technology, manufacturing, delivery, and service models to accommodate updated standards and the new algorithms.”
13. AI: fewer keywords, greater understanding
AI expert Dr Pieter Buteneers, Director of AI and Machine Learning at Sinch, expects artificial intelligence to continue to transition away from keywords and move towards an increased level of understanding.
“Language-agnostic AI, already existent within certain AI and chatbot platforms, will understand hundreds of languages — and even interchange them within a single search or conversation — because it’s not learning language like you or I would,” he says. “This advanced AI instead focuses on meaning, and attaches code to words accordingly, so language is more of a finishing touch than the crux of a conversation or search query.
“Language-agnostic AI will power stronger search results — both from external (the internet) and internal (a company database) sources — and less robotic chatbot conversations, enabling companies to lean on automation to reduce resources and strain on staff and truly trust their AI.”
14. Rise in digital twin technology in the enterprise
John Hill, CEO and Founder of Silico, recognises the growing influence digital twin technology is having in the market. Hill predicts that in the next 20 years, there will be a digital twin of every complex enterprise in the world and anticipates the next generation of decision-makers will routinely use forward-looking simulations and scenario analytics to plan and optimise their business outcomes.
“Digital twin technology is one of the fastest-growing facets of industry 4.0 and while we’re still at the dawn of digital twin technology,” he explains. “Digital twins will have huge implications for unlocking our ability to plan and manage the complex organisations so crucial for our continued economic progress and underpin the next generation of Intelligent Enterprise Automation.”
15. Broader tech security
With an exponential amount of data at companies’ fingertips, Tricentis CEO, Kevin Thompson says the need for investment in secure solutions is paramount.
“The general public has become more aware of the access companies have to their personal data, leading to the impending end of third-party cookies, and other similar restrictions on data sharing,” he explains. “However, security issues still persist. The persisting influx of new data across channels and servers introduces greater risk of infiltration by bad actors, especially for enterprise software organisations that have applications in need of consistent testing and updates. The potential for damage increases as iterations are being made with the expanding attack surface.
“Now, the reality is a matter of when, not if, your organisation will be the target of an attack. To combat this rising security concern, organisations will need to integrate security within the development process from the very beginning. Integrating security and compliance testing at the upfront will greatly reduce risk and prevent disruptions.”
16. Increased cyber resilience
Michael Adams, CISO at Zoom, expects an increased focus on cyber resilience over the next 12 months. “While protecting organisations against cyber threats will always be a core focus area for security programs, we can expect an increased focus on cyber resilience, which expands beyond protection to include recovery and continuity in the event of a cyber incident,” explains Adams.
“It’s not only investing resources in protecting against cyber threats; it’s investing in the people, processes, and technology to mitigate impact and continue operations in the event of a cyber incident.”
17. Ransomware threats
As data leaks become increasingly common place in the industry, companies face a very real threat of ransomware. Michal Salat, Threat Intelligence Director at Avast, believes the time is now for businesses to protect themselves or face recovery fees costing millions of dollars.
“Ransomware attacks themselves are already an individual’s and businesses’ nightmare. This year, we saw cybergangs threatening to publicly publish their targets’ data if a ransom isn’t paid, and we expect this trend to only grow in 2023,” says Salat. “This puts people’s personal memories at risk and poses a double risk for businesses. Both the loss of sensitive files, plus a data breach, can have severe consequences for their business and reputation.”
18. Intensified supply chain attacks
Dirk Schrader, VP of security research at Netwrix, believes supply chain attacks are set to increase in the coming year. “Modern organisations rely on complex supply chains, including small and medium businesses (SMBs) and managed service providers (MSPs),” he says.
“Adversaries will increasingly target these suppliers rather than the larger enterprises knowing that they provide a path into multiple partners and customers. To address this threat, organisations of all sizes, while conducting a risk assessment, need to take into account the vulnerabilities of all third-party software or firmware.”
19. A greater need to manage volatility
Paul Milloy, Business Consultant at Intradiem, stresses the importance of managing volatility in an ever-moving market. Milloy believes bosses can utilise data through automation to foresee potential problems before they become issues.
“No one likes surprises. Whilst Ben Franklin suggested nothing can be said to be certain, except death and taxes, businesses will want to automate as many of their processes as possible to help manage volatility in 2023,” he explains. “Data breeds intelligence, and intelligence breeds insight. Managers can use the data available from workforce automation tools to help them manage peaks and troughs better to avoid unexpected resource bottlenecks.”
20. A human AI co-pilot will still be needed
Artem Kroupenev, VP of Strategy at Augury, predicts that within the next few years, every profession will be enhanced with hybrid intelligence, and have an AI co-pilot which will operate alongside human workers to deliver more accurate and nuanced work at a much faster pace.
“These co-pilots are already being deployed with clear use cases in mind to support specific roles and operational needs, like AI-driven solutions that enable reliability engineers to ensure production uptime, safety and sustainability through predictive maintenance,” he says. “However, in 2023, we will see these co-pilots become more accurate, more trusted and more ingrained across the enterprise.
“Executives will better understand the value of AI co-pilots to make critical business decisions, and as a key competitive differentiator, and will drive faster implementation across their operations. The AI co-pilot technology will be more widespread next year, and trust and acceptance will increase as people see the benefits unfold.”
21. Building the right workplace culture
Harnessing a positive workplace culture is no easy task but in 2023 with remote and hybrid working now the norm, it brings with it new challenges. Tony McCandless, Chief Technology Officer at SS&C Blue Prism, is well aware of the role organisational culture can play in any digital transformation journey.
“Workers are the heart of an organisation, so without their buy in, no digital transformation initiative stands a chance of success,” explains McCandless. “Workers drive home business objectives, and when it comes to digital transformation, they are the ones using, implementing, and sometimes building automations. Curiosity, innovation, and the willingness to take risks are essential ingredients to transformative digitalisation.
“Businesses are increasingly recognising that their workers play an instrumental role in determining whether digitalisation initiatives are successful. Fostering the right work environment will be a key focus point for the year ahead – not only to cultivate buy-in but also to improve talent retention and acquisition, as labor supply issues are predicted to continue into 2023 and beyond.”
22. Cloud cover to soften recession concerns
Amid a cost-of-living crisis and concerns over any potential recession as a result, Daniel Thomasson, VP of Engineering and R&D at Keysight Technologies, says more companies will shift data intensive tasks to the cloud to reduce infrastructure and operational costs.
“Moving applications to the cloud will also help organisations deliver greater data-driven customer experiences,” he affirms. “For example, advanced simulation and test data management capabilities such as real-time feature extraction and encryption will enable use of a secure cloud-based data mesh that will accelerate and deepen customer insights through new algorithms operating on a richer data set. In the year ahead, expect the cloud to be a surprising boom for companies as they navigate economic uncertainty.”
23. IoT devices to scale globally
Dr Raullen Chai, CEO and Co-Founder of IoTeX, recognises a growing trend in the usage of IoT devices worldwide and believes connectivity will increase significantly.
“For decades, Big Tech has monopolised user data, but with the advent of Web3, we will see more and more businesses and smart device makers beginning to integrate blockchain for device connectivity as it enables people to also monetise their data in many different ways, including in marketing data pools, medical research pools and more,” he explains. “We will see a growth in decentralised applications that allow users to earn a modest additional revenue from everyday activities, such as walking, sleeping, riding a bike or taking the bus instead of driving, or driving safely in exchange for rewards.
“Living healthy lifestyles will also become more popular via decentralised applications for smart devices, especially smart watches and other health wearables.”
The digital landscape is changing day by day. Ideas like the metaverse that once seemed a futuristic fantasy are now…
SHARE THIS STORY
The digital landscape is changing day by day. Ideas like the metaverse that once seemed a futuristic fantasy are now coming to fruition and embedding themselves into our daily lives. The thinking might be there, but is our technology really ready to go meta? Domains and hosting provider, Fasthosts, spoke to the experts to find out…
How the metaverse works
The metaverse is best defined as a virtual 3D universe which combines many virtual places. It allows users to meet, collaborate, play games and interact in virtual environments. It’s usually viewed and accessed from the outside as a mixture of virtual reality (VR), (think of someone in their front room wearing a headset and frantically waving nunchucks around) and augmented reality (AR), but it’s so much more than this…
These technologies are just the external entry points to the metaverse and provide the visuals which allow users to explore and interact with the environment within the metaverse.
This is the ‘front-end’ if you like, which is also reinforced by artificial intelligence and 3D reconstruction. These additional technologies help to provide realistic objects in environments, computer-controlled actions and also avatars for games and other metaverse projects.
So, what stands in the way of this fantastical 3D universe? Here are the six key challenges:
Technology
The most important piece of technology, on which the metaverse is based, is the blockchain. The blockchain is essentially a chain of blocks that contain specific information. They’re a combination of computers linked to each other instead of a central server which means that the whole network is decentralised. This provides the infrastructure for the development of metaverse projects, storage of data and also allows them the capability to be compatible with Web3. Web3 is an upgraded version of the internet which will allow integration of virtual and augmented reality into people’s everyday lives.
Sounds like a lot, right? And it involves a great deal of tech that is alien to the vast majority of us. So, is technology a barrier to widespread metaverse adoption?
Jonothan Hunt, Senior Creative Technologist at Wunderman Thompson, says the tech just isn’t there. Yet.
“Technology’s readiness for the mass adoption of the metaverse depends on how you define the metaverse, but if we’re talking about the future vision that the big tech players are sharing, then not yet. The infrastructure that powers the internet and our devices isn’t ready for such experiences. The best we have right now in terms of shared/simulated spaces are generally very expensive and powered entirely in the cloud, such as big computers like the Nvidia Omniverse, cloud streaming, or games. These rely heavily on instancing and localised grouping. Consumer hardware, especially XR, is still not ready for casual daily use and still not really democratised.
“The technology for this will look like an evolution of the systems above, meaning more distributed infrastructure, better access and updated hardware. Web3 also presents a challenge in and of itself, and questions remain over to what extent big tech will adopt it going forward.”
Storage
Blockchain is the ‘back-end’, where the magic happens, if you will. It’s this that will be the key to the development and growth of the metaverse. There are a lot of elements that make up the blockchain and reinforce its benefits and uses such as storage capabilities, data security and smart contracts.
Due to its decentralised nature, the blockchain has far more storage capacity than the centralised storage systems we have in place today. With data on the metaverse being stored in exabytes, the blockchain works by making use of unutilised hard disk space across the network, which avoids users within the metaverse running out of storage space worldwide.
In terms that might be a bit more relatable, an exabyte is a billion gigabytes. That’s a huge amount of storage, and that doesn’t just exist in the cloud – it’s got to go somewhere – and physical storage servers mean land is taken up, and energy is used. Hunt says: “How long’s a piece of string? The whole of the metaverse will one day be housed in servers and data centres, but the amount or size needed to house all of this storage will beentirely dependent on just how mass adopted the metaverse becomes. Big corporations in the space are starting to build huge data centres – such as Meta purchasing a $1.1 billion campus in Toledo, Spain to house their new Meta lab and data centre – but the storage space is not the only concern. These energy-guzzlers need to stay cool! And what about people and brands who need reliable web hosting for events, gaming or even just meeting up with pals across the world, all that information – albeit virtual – still needs a place to go.
“The current rising cost of electricity worldwide could cause problems for the growth of data centres, and the housing of the metaverse as a whole. However, without knowing the true size of its adoption, it is extremely difficult to truly determine the needed usage. Could we one day see an entire island devoted to data centre storage? Purely for the purposes of holding the metaverse? It seems a little ‘1984’, but who knows?”
Identity
Although the blockchain provides instantaneous verification of transactions with identity through digital wallets, our physical form will be represented by avatars that visually reflect who we are, and how we want to be seen.
The founder of Saxo Bank and the chairman of the Concordium Foundation, Lars Seier Christensen, argues, “I think that if you use an underlying blockchain-based solution where ID is required at the entry point, it is actually very simple and automatically available for relevant purposes. It is also very secure and transparent, in that it would link any transactions or interactions where ID is required to a trackable record on the blockchain.”
Once identity is established, it is true that it could potentially become easier to assess creditworthiness of parties for purchasing and borrowing in the metaverse due to the digital identity and storage of each individual’s data and transactions on the blockchain. However, although it sounds exciting, there must be considerations into how it could impact privacy, and how this amount of data will be recorded on the blockchain.
Security
There are also huge security benefits to this set up. The decentralised blockchain helps to eradicate third-party involvement and data breaches, such as theft and file manipulation, thanks to its powerful data processing and use of validation nodes. Both of these are responsible for verifying and recording transactions on the blockchain. This will be reassuring to many, given the widespread concerns around data privacy and user protection in the metaverse.
To access the blockchain all we will need is an internet connection and a device, such as a laptop or smartphone, this is what makes it so great as it will be so readily available. However, to support the blockchain, we’re relying on a whole different set of technologies. Akash Kayar, CEO of web3-focused software development company Leeway Hertz, had this to say on the readiness of the current technology available: “The metaverse is not yet completely mature in terms of development. Tech experts are researching strategies and
testing the various technologies to develop ideas that provide the world with more feasible and intriguing metaverse projects.
“Projects like Decentraland, Axie Infinity, and Sandbox are popular contemporary live metaverse projects. People behind these projects made perfect use of notable metaverse technologies, from blockchain and cryptos to NFTs.
“As envisioned by top tech futurists, many new technologies will empower the metaverse in the future, which will support the development of a range of prolific use cases that will improve the ability of the metaverse towards offering real-life functionalities. In a nutshell, the metaverse is expected to bring extreme opportunities for enterprises and common users. Hence, it will shape the digital future.”
Currency & Payments
Whilst it’s only considered legal tender in two countries, cryptocurrency is currently a reality and there is a strong likelihood that it will eventually be mass adopted. However, the metaverse is arguably not yet at the same maturity level, meaning cryptocurrency may have to wait before it can finally fully take off.
Golden Bitcoin symbol and finance graph screen. Horizontal composition with copy space. Focused image.
There is no doubt that cryptocurrency and the metaverse will go hand-in-hand as the former will become the tender of the latter with many of the current metaverse platforms each wielding its native currency. For example Decentraland uses $MANA for payments and purchases. However, with the volatility of crypto currencies and the recent collapse of trading platform FTX indicating security lapses, we may not yet be ready for the switch to decentralised payments.
Energy
Some of the world’s largest data centres can each contain many tens of thousands of IT devices which require more than 100 megawatts of power capacity – this is enough to power around 80,000 U.S. households (U.S. DOE 2020) and is equivalent to $1.35bn running cost per data centre with the cost of a megawatt hour averaging $150.
According to Nitin Parekh of Hitachi Energy, the amount of power which takes to process Bitcoin is higher than you might expect: “Bitcoin consumes around 110 Terawatt Hours per year. This is around 0.5% of global electricity generation. This estimate considers combined computational power used to mine bitcoin and process transactions.” With this estimate, we can calculate that the annual energy cost of Bitcoin is around $16.5bn.
However, some bigger corporations are slowly moving towards renewable energy to power their projects in this space, with Google signing close to $2bn worth of wind and solar investments in order to power its data centres in the future and become greener. Amazon has also followed in their footsteps and have become the world’s largest corporate purchaser of renewable energy.
They may have plenty of time yet to get their green processes in place, with Mark Zuckerberg recently predicting it will take nearly a decade for the metaverse to be created: “I don’t think it’s really going to be huge until the second half of this decade at the earliest.”
About Fasthosts
Fasthosts has been a leading technology provider since 1999, offering secure UK data centres, 24/7 support and a highly successful reseller channel. Fasthosts provides everything web professionals need to power and manage their online space, including domains, web hosting, business-class email, dedicated servers, and a next-generation cloud platform. For more information, head to www.fasthosts.co.uk
John MClure, CISO at Sinclair Group – a diversified media company and America’s leading provider of local sports and news – talks about the evolution of cybersecurity and the cultural shift placing it at the forefront of business change
SHARE THIS STORY
This month’s cover story explores how Sinclair Broadcast Group is embracing the evolution of cybersecurity and placing the role of the CISO at the forefront of business transformation.
Welcome to the latest issueof Interface magazine!
Communication, secure and at speed, is a vital component of the transformation journey for both the modern enterprise and its relationship with stakeholders, be they customers or partners. Putting the right building blocks in place to deliver successful change management is at the heart of the inspiring stories in the latest issue of Interface.
Our cover star John McClure progressed from a career in the military and work as a consultant in the intelligence industry to fight a new kind of foe… As CISO for Sinclair Broadcast Group, a diversified media company and America’s leading provider of local sports and news, he talks about the evolution of cybersecurity, the battle to meet the rising velocity and sophistication of cyber-attacks and the cultural shift of the role of CISO placing it at the forefront of business change.
“Sinclair is unique in terms of its different business units and how it operates. It’s my job as CISO leading our cyber team not to be an obstacle for the business; we’re here to help it move faster to keep up with market forces, and to move safely. We’re here to engineer solutions that work for the enterprise but also help us maintain a positive security posture.”
State of Florida: digital government services
We also hear from CIO Jamie Grant who is leading the State of Florida’s Digital Service (FL[DS]) on its charge to transform and modernise the way government is accessed and consumed. He is building a team of talented, goal-oriented and customer-obsessed individuals to drive a digital transformation with innovation at its heart. “Leadership is really about developing the team and investing in the people. And it turns out that when you get their backs, they appreciate it and then you can achieve anything.”
ResultsCX: putting people first
Jamie Vernon, SVP for IT & Infrastructure at AI-powered customer experience solution specialist ResultsCX, discusses what drives customer care in the 21st century, and the part technology has to play.
“We are the custodians of our customers’ customers,” says Vernon. “In this increasingly tenuous relationship with their customers, they trust us. My leadership takes that responsibility very seriously, and charges each of us with doing everything we can to provide a perfect call, or email, or chat, every time, thousands of times a minute, around the clock and around the calendar.”
Jamie Vernon, SVP for IT & Infrastructure at AI-powered customer experience solution specialist ResultsCX, discusses what drives customer care in the 21st century, and the part technology has to play.
“We are the custodians of our customers’ customers,” says Vernon. “In this increasingly tenuous relationship with their customers, they trust us. My leadership takes that responsibility very seriously, and charges each of us with doing everything we can to provide a perfect call, or email, or chat, every time, thousands of times a minute, around the clock and around the calendar.”
Also this month, Sarita Singh, Regional Head & Managing Director for Stripe in Southeast Asia, talks about how the fast-growing payments platform is driving financial inclusion across Asia and supporting SMEs with end-to-end services putting users first, and we get expert advice for the modern CEO from the University of Oxford’s Saïd Business School.
Our cover story this month investigates how Fleur Twohig, Executive Vice President, leading Personalisation & Experimentation across Consumer Data & Engagement Platforms, and her team are executing Wells Fargo’s strategy to promote personalised customer engagement across all consumer banking channels
SHARE THIS STORY
This month’s cover story follows Wells Fargo’s journey to deliver personalised customer engagement across all its consumer banking channels.
Welcome to the latest issue of Interface magazine!
Partnerships of all kinds are a key ingredient for organisations intent on achieving their goals… Whether that’s with customers, internal stakeholders or strategic allies across a crowded marketplace, Interface explores the route to success these relationships can help navigate.
Our cover story this month investigates the strategy behind Wells Fargo’s ongoing drive to promote personalised customer engagement across all consumer banking channels.
Fleur Twohig, Executive Vice President, leading Personalisation & Experimentation across the bank’s Consumer Data & Engagement Platforms, explains her commitment to creating a holistic approach to engaging customers in personalised one-to-one conversations that support them on their financial journeys.
“We need to be there for everyone across the spectrum – for both the good and the challenging times. Reaching that goal is a key opportunity for Wells Fargo and I have the pleasure of partnering with our cross-functional teams to help determine the strategic path forward…”
IBM: consolidating growth to drive value
We hear from Kate Woolley, General Manager of IBM Ecosystem, who reveals how the tech leader is making it easier for partners and clients to do business with IBM and succeed. “Honing our corporate strategy around open hybrid cloud and artificial intelligence (AI) and connecting partners to the technical training resources they need to co-create and drive more wins, we are transforming the IBM Ecosystem to be a growth engine for the company and its partners.”
Kate Woolley, IBM
America Televisión: bringing audiences together across platforms
Jose Hernandez, Chief Digital Officer at America Televisión, explains how Peru’s leading TV network is aggregating services to bring audiences together for omni-channel opportunities across its platforms. “Time is the currency with which our audiences pay us, so we need to be constantly improving our offering both through content and user experiences.”
Portland Public Schools: levelling the playing field through technology
Derrick Brown and Don Wolf, tech leaders at Portland Public Schools, talk about modernising the classroom, dismantling systemic racism and the power of teamwork.
Also in this issue, we hear from Lenovo on how high-performance computing (HPC) is driving AI research and report again from London Tech Week where an expert panel examined how tech, fuelled by data, is playing a critical role in solving some of the world’s hardest hitting issues, ranging from supply chain disruptions through to cybersecurity fears.
Conventional robots, like giant industrial robots used in the car industry, are set to reach $14.9bn value this year, up from $12bn in 2018.
SHARE THIS STORY
Robotics play a huge role in the manufacturing landscape today. A growing number of businesses use manufacturing robots to automate repetitive tasks, reduce errors, and enable their employees to focus on innovation and efficiency, causing the entire sector’s impressive growth.
According to data presented by AksjeBloggen.com, the global market value of conventional and advanced robotics in the manufacturing industry is expected to continue rising and hit $18.6bn in 2021, a 40% increase in three years.
Market Value Jumped by $5.4B in Three Years
Robots have numerous roles in manufacturing. They are mainly used for high-volume, repetitive processes where their speed and accuracy offer tremendous advantages. Other manufacturing automation solutions include robots used to help people with more complex tasks, like lifting, holding, and moving heavy pieces.
Companies turn to robotics process automation to cut manufacturing costs, solve the shortage of skilled labor and keep their cost advantage in the market.
In 2018, the global market value of conventional and advanced robotics in the manufacturing industry amounted to $13.2bn, revealed the BCG survey. In 2019, this figure rose to $14.8bn and continued growing. Statistics show the market value of manufacturing robots hit $16.6bn in 2020. This figure is expected to jump by $2bn and hit $18.6bn in 2021.
Conventional robots, like giant industrial robots used in the car industry, are set to reach $14.9bn value this year, up from $12bn in 2018.
The market value of advanced manufacturing robots, which have a superior perception, adaptability, and mobility, tripled in the last three years and is expected to hit $3.7bn in 2021. Combined with big data analytics, advanced manufacturing robots allow companies to make intelligent decisions based on real-time data, which leads to lower costs and faster turnaround times.
The BCG survey also showed most manufacturers believe advanced robotic systems will have a massive role in the factory of the future and plan to increase their use. More than 70% of respondents defined robotics as a significant productivity driver in production and logistics.
European and Asian Companies Lead in the Use of Advanced Manufacturing Robots
Analyzed by regions, European and Asian companies lead in the use of advanced robots, while manufacturers from North America lag behind. However, the survey showed 80% of respondents from the US plan to implement advanced robotics in the next few years.
The survey also revealed that manufacturers in emerging markets, especially China and India, are more enthusiastic about using advanced robots than those in industrialized countries. These companies may be looking to automation as a way to overcome a skilled labor shortage and improve their ability to compete in international markets.
Germany had the largest robot density in the manufacturing industry among European countries, with 346 installations per 10,000 employees in 2019. Sweden, Denmark, and Italy followed with 277, 243, and 212 installations per 10,000 employees, respectively.
Statistics also show that companies in the transportation and logistics and technology sector lead in implementing advanced robotics, with 54% and 53% of manufacturers who already use such solutions. The automotive industry and consumer goods sector follow with 49% and 44% share, respectively.
Manufacturers in the engineered products, process, and health care industries lag behind, with 42%, 41%, and 30% of companies that use advanced manufacturing robots. However, around 85% of manufacturers in these sectors plan to start using advanced robotic systems by 2022.
Gurpreet Purewal, Associate Vice President, Business Development, iResearch Services, explores how organisations can overcome the challenges presented by AI in 2021.
SHARE THIS STORY
2020 has been a year of tumultuous change and 2021 isn’t set to slow down. Technology has been the saving grace of the waves of turbulence this year, and next year as the use of technology continues to boom, we will see new systems and processes emerge and others join forces to make a bigger impact. From assistive technology to biometrics, ‘agritech’ and the rise in self-driving vehicles, tech acceleration will be here to stay, with COVID-19 seemingly just the catalyst for what’s to come. Of course, the increased use of technology will also bring its challenges, from cybersecurity and white-collar crime to the need to instil trust in not just those investing in the technology, but those using it, and artificial intelligence (AI) will be at the heart of this.
1. Instilling a longer-term vision
New AI and automation innovations have led to additional challenges such as big data requirements for the value of these new technologies to be effectively shown. For future technology to learn from the challenges already faced, a comprehensive technology backbone needs to be built and businesses need to take stock and begin rolling out priority technologies that can be continuously deployed and developed.
Furthermore, organisations must have a longer-term vision of implementation rather than the need for immediacy and short-term gains. Ultimately, these technologies aim to create more intelligence in the business to better serve their customers. As a result, new groups of business stakeholders will be created to implement change, including technologists, business strategists, product specialists and others to cohesively work through these challenges, but these groups will need to be carefully managed to ensure a consistent and coherent approach and long-term vision is achieved.
2. Overcoming the data challenge
AI and automation continue to be at the forefront of business strategy. The biggest challenge, however, is that automation is still in its infancy, in the form of bots, which have limited capabilities without being layered with AI and machine learning. For these to work cohesively, businesses need huge pools of data. AI can only begin to understand trends and nuances by having this data to begin with, which is a real challenge. Only some of the largest organisations with huge data sets have been able to reap the rewards, so other smaller businesses will need to watch closely and learn from the bigger players in order to overcome the data challenge.
3. Controlling compliance and governance
One of the critical challenges of increased AI adoption is technology governance. Businesses are acutely aware that these issues must be addressed but orchestrating such change can lead to huge costs, which can spiral out of control. For example, cloud governance should be high on the agenda; the cloud offers new architecture and platforms for business agility and innovation, but who has ownership once cloud infrastructures are implemented? What is added and what isn’t?
AI and automation can make a huge difference to compliance, data quality and security. The rules of the compliance game are always changing, and technology should enable companies not just to comply with ever-evolving regulatory requirements, but to leverage their data and analytics across the business to show breadth and depth of insight and knowledge of the workings of their business, inside and out.
In the past, companies struggled to get access and oversight over the right data across their business to comply with the vast quantities of MI needed for regulatory reporting. Now they are expected to not only collate the correct data but to be able to analyse it efficiently and effectively for regulatory reporting purposes and strategic business planning. There are no longer the time-honoured excuses of not having enough information, or data gaps from reliance on third parties, for example, so organisations need to ensure they are adhering to regulatory requirements in 2021.
4. Eliminating bias
AI governance is business-critical, not just for regulatory compliance and cybersecurity, but also in diversity and equity. There are fears that AI programming will lead to natural bias based on the type of programmer and the current datasets available and used. For example, most computer scientists are predominantly male and Caucasian, which can lead to conscious/unconscious bias, and datasets can be unrepresentative leading to discriminatory feedback loops.
Gender bias in AI programming has been a hot topic for some years and has come to the fore in 2020 again within wider conversations on diversity. By only having narrow representation within AI programmers, it will lead to their own bias being programmed into systems, which will have huge implications on how AI interprets data, not just now but far into the future. As a result, new roles will emerge to try and prevent these biases and build a more equitable future, alongside new regulations being driven by companies and specialist technology firms.
5. Balancing humans with AI
As AI and automation come into play, workforces fear employee levels will diminish, as roles become redundant. There is also inherent suspicion of AI among consumers and certain business sectors. But this fear is over-estimated, and, according to leading academics and business leaders, unfounded. While technology can take away specific jobs, it also creates them. In responding to change and uncertainty, technology can be a force for good and source of considerable opportunity, leading to, in the longer-term, more jobs for humans with specialist skillsets.
Automation is an example of helping people to do their jobs better, speeding up business processes and taking care of the time-intensive, repetitive tasks that could be completed far quicker by using technology. There remain just as many tasks within the workforce and the wider economy that cannot be automated, where a human being is required.
Businesses need to review and put initiatives in place to upskill and augment workforces. Reflecting this, a survey on the future of work found that 67% of businesses plan to invest in robotic process automation, 68% in machine learning, and 80% investing in perhaps more mainstream business process management software. There is clearly an appetite to invest strongly in this technology, so organisations must work hard to achieve harmony between humans and technology to make the investment successful.
6. Putting customers first
There is growing recognition of the difference AI can make in providing better service and creating more meaningful interactions with customers. Another recent report examining empathy in AI saw 68% of survey respondents declare they trust a human more than AI to approve bank loans. Furthermore, 69% felt they were more likely to tell the truth to a human than AI, yet 48% of those surveyed see the potential for improved customer service and interactions with the use of AI technologies.
2020 has taught us about uncertainty and risk as a catalyst for digital disruption, technological innovation and more human interactions with colleagues and clients, despite face-to-face interaction no longer being an option. 2021 will see continued development across businesses to address the changing world of work and the evolving needs of customers and stakeholders in fast-moving, transitional markets. The firms that look forward, think fast and embrace agility of both technology and strategy, anticipating further challenges and opportunities through better take-up of technology, will reap the benefits.
With virtually all companies looking at AI, what are some of the key risks they need to consider before implementation?
SHARE THIS STORY
Today virtually all companies are forced to innovate and many are excited about AI. Yet since implementation cuts across organisational boundaries, shifting to an AI-driven strategy requires new thinking about managing risks, both internally and externally. This blog will cover “the seven sins of enterprise AI strategies”, which are governance issues at the board and executive levels that block companies from moving ahead with AI. by By Jeremy Barnes, Element AI
1- Disowning the AI strategy
This is probably the most important sin. In this case, a CEO and board will say that AI is a priority, but delegate it to a different department or an innovation lab. However, success is not based on whether or not a company uses an innovation lab—it’s whether they are truly invested in it. The bottom line is that the CEO and board need to actively lead an AI strategy.
2- Ignoring the unknowns
This happens when companies say they believe in AI, but don’t reach a level of proficiency where it’s possible to identify, characterise and model the threats that emerge with new advances. Even if it is decided not to go all-in on AI innovation, it’s still important that there is a hypothesis for how to address AI within a company and an early warning system so the decision can be re-evaluated early enough to act. Being a fast follower requires as much organizational preparation and lead time as leadership.
3- Not enabling the culture
The ability to implement AI is about an experimentation mindset. That and an openness to failure need to be adopted across the company. Organisations need to keep in mind that AI doesn’t respect organisational boundaries. Most companies want high-impact, low-risk solutions that could simply lead to optimising, rather than advancing new value streams. It is hard to accept increased risk in exchange for impact but it will come as part of the continuous cultural enablement of an experimental mindset.
4- Starting with the solution
This is the most common sin. It’s important to be able to understand the specific problems you’re trying to solve, because AI is unlikely to be a solution for all of them, and especially not blindly implementing a horizontal AI platform. Have the conversation at board level to ensure that an overarching AI strategy, and not simply quick-fix solutions, is the priority.
5- Lose risk, keep reward
As mentioned in the third sin, it is natural for companies to want to implement AI without any risk. But there is no reward without risk. A vendor motivated to decrease risk will also decrease innovation and ultimately impact by making successes small and failures non-existent. AI creates differentiation only for companies that are willing to learn from both their successes and their failures. A company that doesn’t effectively balance risk in AI will ultimately increase its risk of disruption.
6- Vintage accounting
Attempting to fit AI into traditional financial governance structures causes problems. It doesn’t fit nicely into budget categories and it’s hard to value the output. The link between what you put in and what you get out can be less tangible or predictable, which often makes it harder to square with existing plans or structures. Model the rate of return on AI activities and all data-related activities. This demands that these activities affect profit (not just loss) and assets (not just liabilities).
7- Treating data as a commodity
The final sin concerns data and its treatment as a commodity. Data is fundamental to AI. If data is poorly handled, it can lead to negative impacts on decision-making. Data should be treated as an asset. The stronger, deeper and more accurate the dataset, the better models that you can train and more intelligent insights you can generate. But, at the same time, when personally identifiable information is stored about customers, it can be stolen, risking heavy penalties in some jurisdictions. You need to build towards data from a use case rather than invest blindly in data centralisation projects. So, now you know what not to do. Here are some of the simple things that you can do to move ahead. First, talk to your board about how long it will take to become an AI innovator, modelling it out, rather than simply discussing it conceptually.
Second, prepare for change and put in place monitoring. AI shifts all the time, so you’ll want to regularly check in to adjust and pivot your strategy. It’s important to develop a basic skill set so you can redo planning exercises with your board. Third, model out risks in both action and inaction. But don’t model them in a traditional approach, which is to push risk down to different business units and then compensate those units for reducing risk rather than managing trade-offs. Instead, view those trade-offs in terms of risks and rewards, and start to think about how you are accounting for the assets and liabilities of AI. Ultimately, you want to start to model what is the actual rate of return for all these activities that you are doing. Then benchmark it against what you see in other companies from across the industry, and that will give you a good picture of the current situation and where to go.
Understanding what it isn’t is just as important as understanding what it is, says Jim Logan who has nearly three decades of experience in financial services and technology…
SHARE THIS STORY
I’ve been working in the financial services space for close to thirty years now. I’ve seen many trends and technologies emerge. Some take hold, several are just a flash in the pan. Regardless of how long a concept sticks around, one thing remains: Terminology plays a material role in shaping perceptions. In a world where messaging tends to over complicate things, too many acronyms and too many buzzwords all work against what should be the primary objective: clearly illustrating value. I’ve found this to be equally true when it comes to artificial intelligence or ‘AI’.
Generally speaking, the word artificial doesn’t readily call to mind a positive image, does it? By definition, the word “artificial” has listed meanings of, “insincere or affected” and “made by humans as opposed to happening naturally.” It is the second part of this definition I’d like to explore a bit further.
Artificial Intelligence is, in fact, created by humans. And it isn’t a new fad or concept. Many don’t realize that the term was first coined by John McCarthy, Ph.D. and Stanford computer and cognitive scientist, back in 1955. AI has continued to evolve as a material concept, with practical applications across many industries, ever since.
For financial service professionals, particularly those of us involved with fighting financial crime and preventing money laundering, AI can have tremendous impact and practical application. Before we dive a bit deeper, I feel it’s important to first understand what AI isn’t.
AI is not intended to simply be a digital worker, certainly not within financial services and fighting financial crime. Yes, AI can automate various functions. We’re all familiar with the concept of ‘bots’ and virtual assistants. However, those are rudimentary examples of robotic process automation. True AI is human led and a continuous, instantaneous learning process that drives tangible value. AI is not merely a play to cut costs or replace human capital. Rather, AI enhances the bottom line by keeping compliance staff costs flat in the immediate term and enables our human experts to more appropriately manage their time, by focusing talent on investigations that matter the most.
One of the most valuable aspects of AI, in the context of anti money laundering and compliance, is the speed by which it can be deployed. We’re talking about time to market and time to value in a matter of weeks. Not months, not multiple quarters – simply weeks. But I don’t mean a generic, black box concept. I’m specifically referring to a highly precise, tailored AI solution that has extensive proof points and, more importantly, far-reaching global regulatory approval.
AI shouldn’t simply be an extension of legacy rules-based routines, nor a way to further automate the process of scoring or risk weighted alert suppression. That simply dilutes the true value of AI, and does not maximize the cost and efficiency benefits.
The cost of compliance continues to grow at a staggering pace, particularly for financial institutions and insurance companies. Equally of concern, the impact of fines for non-compliance has also skyrocketed in the last decade. Specifically to the tune of $8.4 billion last year across North America alone.
What if you could literally solve every single name screen, sanction, and transaction alert? What if you could achieve this without sacrificing any aspect of control and security? What if you could increase the throughput, efficiency and accuracy of your compliance operations without adding a single dollar of staff expense to your budget?
Let’s stop talking in terms of what if and have a meaningful conversation regarding how. I’m helping clients achieve all of these measures today and that is from a perspective proven in production. Here at Silent Eight we’re a team founded by engineers and data scientists, solving real world challenges in the anti money laundering and financial compliance market.
Artificial Intelligence isn’t scary…it isn’t a black box…and it isn’t the futuristic world of tomorrow – it is the here and now, and it’s battle tried and tested.
Temenos, the banking software company, partners with Microsoft to offer AI-driven Financial Crime Mitigation solution to help banks combat surge cybercrime during Covid-19 outbreak.
SHARE THIS STORY
Temenos, the banking software company, announced today a joint effort with Microsoft to enable access to its AI-powered, Financial Crime Mitigation (FCM) SaaS solution to allow banks to protect both their customers and their organization from financial crime increase during the pandemic, particularly as banks have moved to remote working to protect their staff. Temenos AI-powered, Financial Crime Mitigation SaaS solution based on Microsoft’s fast, scalable and secure Azure cloud platform can be deployed within weeks.
Temenos and Microsoft are opening up access to banks for a 14-day trial, available until 30 of June. As part of the collaboration with Microsoft, Temenos is offering system access and online tutorials for users to familiarize themselves with navigation of the system and learn how it can support them in a revised operating landscape. Temenos unveiled the open access initiative of its FCM software at its virtual event Temenos Community Forum Online, 29-30 April.
Temenos FCM provides enterprise-wide financial crime protection for a highly regulated and fast-changing environment. It allows banks’ operators to respond to alerts and collaborate with team members while working remotely. Throughout the Covid-19 crisis, Temenos customers from Tier 1 banks to regional banks and neobanks have continued to benefit from Temenos FCM’s comprehensive coverage regardless of the fact that their teams are working remotely.
Financial regulators worldwide and organizations such as the European Central Bank are warning that the Covid-19 pandemic may result in an increase in financial crime and other misconduct due to market disruptions, reduced staff, and other factors, as has been the case during past global crises. Opportunistic fraudsters and criminals are adapting their methods of targeting people and countries in distress as new threat vectors open up.
The Financial Actions Task Force (FATF), the global standard setter for combating money laundering and terrorism financing, warns businesses to remain vigilant for emerging money laundering and terrorist financing risks as criminals may seek to exploit gaps and weaknesses in Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT) systems under the assumption that resources are focused elsewhere. Fraudsters have already been very quick to adapt well-known fraud schemes to target individual citizens, businesses and public organizations. These include various types of adapted versions of telephone fraud schemes, supply scams and decontamination scams.
Jean-Michel Hilsenkopf, Chief Operating Officer, Temenos, said:“We are proud to be able to offer our cloud-native and AI technology to support banks in the fight against financial crime, which has increased as a result of the pandemic. As a strategic global banking software partner of Microsoft, we are pleased to join efforts to deliver Temenos Financial Crime Mitigation as SaaS on Microsoft Azure’s resilient, secure and proven cloud platform. We are committed to providing robust and up-to-date sanction screening, AML, KYC and fraud management protection combined with powerful AI-driven transaction monitoring and sanction screening to help banks worldwide.”
Marianne Janik, Country General Manager, Microsoft Switzerland, said: “We have been pioneering with Temenos in the cloud for a decade. We are proud to join forces to help banks use the power of Temenos’ market-leading Financial Crime Mitigation solution based on our secure, scalable and resilient global Azure cloud platform to combat financial crime surge due to Covid-19.”
More than 200 banks use Temenos FCM SaaS solution, which covers watch-list screening, anti-money laundering, fraud prevention – suspicious activity prevention – and KYC, delivering industry-leading levels of detection and false positives of under 2% vs industry average of 7% and above. Temenos FCM can be deployed as a standalone, or integrated into any banking or payments platform including cloud-native, cloud-agnostic Temenos Transact and Temenos Infinity. It provides unrivalled levels of detection and resilience against financial crime and Total Cost of Ownership (TCO) savings of more than 50%. Temenos FCM provides banks with the next generation of AI-driven FCM capabilities that can run on any public cloud, as a service or on premise.
The global developer of artificial intelligence solutions is releasing a free search platform to help clinical and scientific researchers find answers and patterns in research papers
SHARE THIS STORY
Information on COVID-19 is evolving fast and this AI-powered platform leverages a semantic search model that will allow users to quickly connect disparate information. The platform can execute searches based on specific inquiries, along with critical paragraphs copied from a relevant paper. Unlike keyword searches, the queries do not need to be specifically structured, and actually perform better in longer form. This initial version is configured to work with the COVID-19 Open Research Dataset (CORD-19) corpus. Element AI is looking for users and organizations from various groups to test the platform and suggest other data sets and features that could best fit their needs.
The group’s Element AI is looking to work with include:
Clinical researchers who need to incorporate many phenomena to make a rich model of the pandemic and its impacts.
Government, Public Safety and Public Health authorities looking to find best practices across different countries.
Pharmaceutical companies working on new therapies or vaccine trials, as well as identifying existing therapies that could provide immediate help.
-Scientific researchers and data scientists who are working on novel ways to connect research across the body of knowledge already available for COVID-19.
“Research data and reports are being published at an unprecedented pace as organizations scale up their efforts to respond to COVID-19. We want to contribute, and this free platform is our way to help the community locate and gather knowledge to find answers and patterns,” said Jean-François (JF) Gagné, CEO and Co-founder of Element AI. “We encourage the scientific and healthcare community to use this free platform and engage with our team to quickly ramp up and collaboratively meet the needs of the people working to slow down and contain COVID-19. We hope that their feedback and collaboration will help us quickly add features and datasets on top of what we already have made available” added Gagné.
The COVID-19 platform leverages technology from the Element AI Knowledge Scout product, which uses natural language techniques to tap into structured and unstructured sources of information. The first version will be progressively updated in coming weeks as additional datasets emerge. The site can be accessed at: https://www.elementai.com/covid-research.
Mauro Guillén Zandman, Professor of International Management, The Wharton School, University of Pennsylvania, USA Srikar Reddy, Managing Director and Chief…
SHARE THIS STORY
Mauro Guillén Zandman, Professor of International Management, The Wharton School, University of Pennsylvania, USA
Srikar Reddy, Managing Director and Chief Executive Officer, Sonata Software Limited and Sonata Information Technology Limited
Artificial intelligence (AI) relies on big data and machine learning for myriad applications, from autonomous vehicles to algorithmic trading, and from clinical decision support systems to data mining. The availability of large amounts of data is essential to the development of AI. But the scandal over the use of personal and social data by Facebook and Cambridge Analytica has brought ethical considerations to the fore. And it’s just the beginning. As AI applications require ever greater amounts of data to help machines learn and perform tasks hitherto reserved for humans, companies are facing increasing public scrutiny, at least in some parts of the world. Tesla and Uber have scaled down their efforts to develop autonomous vehicles in the wake of widely reported accidents. How do we ensure the ethical and responsible use of AI? How do we bring more awareness about such responsibility, in the absence of a global standard on AI?
The ethical standards for assessing AI and its associated technologies are still in their infancy. Companies need to initiate internal discussion as well as external debate with their key stakeholders about how to avoid being caught up in difficult situations.
Consider the difference between deontological and teleological ethical standards. The former focuses on the intention and the means, while the latter on the ends and outcomes. For instance, in the case of autonomous vehicles, the end of an error-free transportation system that is also efficient and friendly towards the environment might be enough to justify large-scale data collection about driving under different conditions and also, experimentation based on AI applications.
By contrast, clinical interventions and especially medical trials are hard to justify on teleological grounds. Given the horrific history of medical experimentation on unsuspecting human subjects, companies and AI researchers alike would be wise to employ a deontological approach that judges the ethics of their activities on the basis of the intention and the means rather than the ends.
Another useful yardstick is the so-called golden rule of ethics, which invites you to treat others in the way you would like to be treated. The difficulty in applying this principle to the burgeoning field of AI lies in the gulf separating the billions of people whose data are being accumulated and analyzed from the billions of potential beneficiaries. The data simply aggregates in ways that make the direct application of the golden rule largely irrelevant.
Consider one last set of ethical standards: cultural relativism versus universalism. The former invites us to evaluate practices through the lens of the values and norms of a given culture, while the latter urges everyone to live up to a mutually agreed standard. This comparison helps explain, for example, the current clash between the European conception of data privacy and the American one, which is shaping the global competitive landscape for companies such as Google and Facebook, among many others. Emerging markets such as China and India have for years proposed to let cultural relativism be the guiding principle, as they feel it gives them an edge, especially by avoiding unnecessary regulations that might slow their development as technological powerhouses.
Ethical standards are likely to become as important at shaping global competition as technological standards have been since the 1980s. Given the stakes and the thirst for data that AI involves, it will likely require companies to ask very tough questions as to every detail of what they do to get ahead. In the course of the work we are doing with our global clients, we are looking at the role of ethics in implementing AI. The way industry and society addresses these issues will be crucial to the adoption of AI in the digital world.
However, for AI to deliver on its promise, it will require predictability and trust. These two are interrelated. Predictable treatment of the complex issues that AI throws up, such as accountability and permitted uses of data, will encourage investment in and use of AI. Similarly, progress with AI requires consumers to trust the technology, its impact on them, and how it uses their data. Predictable and transparent treatment facilitates this trust.
Intelligent machines are enabling high-level cognitive processes such as thinking, perceiving, learning, problem-solving and decision-making. AI presents opportunities to complement and supplement human intelligence and enrich the way industry and governments operate.
However, the possibility of creating cognitive machines with AI raises multiple ethical issues that need careful consideration. What are the implications of a cognitive machine making independent decisions? Should it even be allowed? How do we hold them accountable for outcomes? Do we need to control, regulate and monitor their learning?
A robust legal framework will be needed to deal with those issues too complex or fast-changing to be addressed adequately by legislation. But the political and legal process alone will not be enough. For trust to flourish, an ethical code will be equally important.
The government should encourage discussion around the ethics of AI, and ensure all relevant parties are involved. Bringing together the private sector, consumer groups and academia would allow the development of an ethical code that keeps up with technological, social and political developments.
Government efforts should be collaborative with existing efforts to research and discuss ethics in AI. There are many such initiatives which could be encouraged, including at the Alan Turing Institute, the Leverhulme Centre for the Future of Intelligence, the World Economic Forum Centre for the Fourth Industrial Revolution, the Royal Society, and the Partnership on Artificial Intelligence to Benefit People and Society.
But these opportunities come with associated ethical challenges:
Decision-making and liability: As AI use increases, it will become more difficult to apportion responsibility for decisions. If mistakes are made which cause harm, who should bear the risk?
Transparency: When complex machine learning systems are used to make significant decisions, it may be difficult to unpick the causes behind a specific course of action. Clear explanations for machine reasoning are necessary to determine accountability.
Bias: Machine learning systems can entrench existing bias in decision-making systems. Care must be taken to ensure that AI evolves to be non-discriminatory.
Human values: Without programming, AI systems have no default values or “common sense”. The British Standards Institute BS 8611 standard on the “ethical design and application of robots and robotic systems” provides some useful guidance: “Robots should not be designed solely or primarily to kill or harm humans. Humans, not robots, are the responsible agents; it should be possible to find out who is responsible for any robot and its behaviour.”
Data protection and IP: The potential of AI is rooted in access to large data sets. What happens when an AI system is trained on one data set, then applies learnings to a new data set?
Responsible AI ensures attention to moral principles and values, to ensure that fundamental human ethics are not compromised. There have been several recent allegations of businesses exploiting AI unethically. However, Amazon, Google, Facebook, IBM and Microsoft have established a non-profit partnership to formulate best practices on artificial intelligence technologies, advance the public’s understanding, and to serve as a platform about artificial intelligence.
Peltarion, leading AI innovator and creator of an operational deep learning platform, today announced the findings of a survey of…
SHARE THIS STORY
Peltarion, leading AI innovator and creator of an operational deep learning platform, today announced the findings of a survey of AI decision-makers examining what they see as the impact of the skills shortage, and suggestions on how to overcome it. The research, ‘AI Decision-Makers Report: The human factor behind deep learning’, presents the findings of a survey of 350 IT leaders in the UK and Nordics with direct responsibility for shepherding AI at companies with more than 1,000 employees.
The
report finds that many AI decision-makers are concerned about the business
impact of the deep learning skills shortage. 84% of respondents said their
company leaders worry about the business risks of not investing in deep
learning, with 83% saying that a lack of deep learning skills is already
impacting their ability to compete in the market. These companies are exclusively
focusing on recruiting data scientists (71% of AI decision-makers are actively
recruiting to plug the deep learning skills gap), and this is already impacting
their ability to progress with AI projects:
Almost half (49%) say the skills shortage is causing delays to projects
44% believe the need for specialist skills is a major barrier to further investment in deep learning
However, almost half (45%) say they are struggling to hire because they don’t have a mature AI program already in place
“This
report shows that companies can’t afford to wait for data science talent to
come to them to progress their AI projects. The fact is, many organisations are
already starting to lose their competitive edge by waiting for specialised data
scientists. The current approach, which relies on hiring an isolated team of
data scientists to work on deep learning projects, is delaying projects and
putting strain on the talent companies do have,” explains Luka Crnkovic-Friis,
Co-Founder and CEO at Peltarion. “In order to solve the deep learning skills
gap, we need to make use of transferrable talent that can be found right under
companies’ noses. Deep learning will only reach its true potential if we get
more people from different areas of the business using it, taking pressure off
data scientists and allowing projects to progress.”
Less
than half (48%) of respondents said they currently employ data scientists who
can create deep learning models, compared to 94% that have data scientists who
can create other machine learning models. This shortage is having a direct
impact on teams: 93% of AI decision-makers say their data scientists are
over-worked to some extent because they believe there is no one else who can
share the workload. However, with the right tools, others can make a serious
impact on AI projects.
“Organisations
need to move projects forward by bringing on existing domain experts and
investing in tools that will help them input into AI projects. This will reduce
the strain on data scientists and lower deep learning’s barrier to
entry,” concludes Crnkovic-Friis. “We need to make deep learning more
affordable and accessible to all by reducing its complexity. By
operationalising deep learning to make it more scalable, affordable and
understandable, organisations can put themselves on the fast track and use deep
learning to optimise processes, create new products and add direct value to the
business.”
AI is no longer science-fiction writers dream, it’s being implemented in industries all over the world. We look at 5…
SHARE THIS STORY
AI is no longer science-fiction writers dream, it’s being implemented in industries all over the world. We look at 5 examples of how AI is revolutionising the retail experience Written by: Dale Benton
Marks and
Spencer
In early 2019, M&S announced a new
Technology Transformation Program, one that will allow M&S to become a
digital-first business and deliver key improvements in customer experience. As
part of this transformation, M&S has partnered with Microsoft to investigate
and test the capabilities of technology and artificial intelligence in a retail
environment. M&S will look to integrate machine learning, computer vision
and AI across every endpoint – both in its stores and behind the scenes. Every
surface, screen and scanner in its stores will create data – and enable
employees to act upon it. Every M&S store worldwide will be able to track,
manage and replenish stock levels in real time – and deal with unexpected
events.
The John Lewis Partnership is currently
partaking in a three-year trial, deploying robots to one of its farms, which
grows produce for its Waitrose & Partners brand. The robots, named Tom, Dick and Harry, are delivered
in partnership with the Small Robot Company. Each will be equipped with a
camera and AI technology to gather topographical data, while autonomously
obtaining accurate, plant-by-plant data in order to enable higher farming
efficiency. The data will also be used
to develop further machine learning capabilities. The trial will also provide
the John Lewis Partnership’s Room Y innovation team with valuable insight to
support innovation and inform how robotics and Artificial Intelligence (AI)
could be used further in other areas of the business.
One of the biggest retail companies in the world has been piloting and implementing artificial intelligence solutions across its stores for a number of years. As part of a technology program, called Missed Scan Detection, Walmart has deployed AI-equipped cameras in more than 1,000 of its stores. These cameras, developed in part with Everseen, tracks and analyses activities at both self-checkout registers and those manned by Walmart employees. If an item isn’t scanned at checkout, the cameras will detect the and notify a checkout attendant of the problem. The AI technology allows Walmart to monitor its inventory product quantities, but also significantly reduce theft across its stores.
Amazon Go represents a whole n era of shipping.
The concept is simple, walk into an Amazon Go store, pick up whatever you want
and walk back out. The idea is to create
a “Just Walk Out” experience. Described as the “most advanced shopping
technology”, customers simply download the Amazon Go app. Powerful machine
learning and AI technology automatically detects when products are taken from
or returned to the shelves, keeping track of them all in a virtual cart. Once
customers leave, Amazon will collate all of the data and produce a receipt and
charge the customer’s Amazon account.
One of the UK’s largest food retailers with more
than 120,000 colleagues in 494 stores serving over 11 million customers every
week, Morrisons turned its attention to AI with JDA Software. Looking to vastly
improve the customer experience, Morrisons looked at reducing queues at
checkouts, and improving on-shelf availability. Morrisons
invested in Blue Yonder – a Demand Forecast & Replenishment solution from JDA,
which uses Artificial Intelligence (AI) technology to improve demand planning
and reinvigorate replenishment based on customer behaviour in every store. Over
a 12-month period, Morrisons was able to generate up to 30% reduction in shelf
gaps and a 2-3 day reduction in stockholding in-store. AI technology has also
enabled Morrisons to close the execution gap, optimizing availability while
reducing wastage, enhancing shelf presentation and meeting stockholding
targets.
By Craig Summers, Managing Director, Manhattan Associates Customer experience can be make or break for retailers. In fact, recent research…
SHARE THIS STORY
By Craig Summers, Managing Director, Manhattan Associates
Customer experience can be make or break for retailers. In fact, recent research shows that flawed customer experiences could be costing British retailers up to £102 billion in lost sales each year. This shouldn’t be news to retailers; the modern consumer demands a connected, consistent experience that is personalised to them, whether it’s online or instore. The same research found that running out of stock in-store was the biggest contributor to lost revenue, with 79 per cent of consumers saying they would not return to make a purchase if they found their desired item was out of stock. This frustration is only amplified if an out of stock product is marketed to the consumer.
Personalisation isn’t anything new but if the basics aren’t right, retailers risk not delivering on customer experience. Many retailers still aren’t getting it right – and, explains Craig Summers, Managing Director, Manhattan Associates, inept personalisation is affecting the bottom line.
Misplaced Personalisation
The way in which retailers can engage with customers has changed radically over the past decade, from social media onwards. Add in the compelling appealing of Artificial Intelligence (AI) and the promise of incredibly accurate and timely promotional offers, and personalisation has become a foundation of any retail strategy. Yet while the marketing activity is becoming ever more sophisticated, personalisation cannot be delivered by marketing alone.
Without integrating marketing activity to the core operation, retailers risk repelling rather than engaging customers. Product offers that are out of stock in the customer’s size. Promotions not on offer at the local store. Incentives to buy an item the customer has already purchased – not a problem for a standard food or household item, incredibly annoying if it’s an expensive mountain bike or cashmere jumper. Customers are becoming increasingly familiar with ostensibly personalised offers that fail to deliver a great experience.
What is the thinking behind a promotion that cannot be purchased by the customer? Why set such high expectations when they cannot be met? Enticing a customer to click through an emailed offer may be the measure of marketing success – but when that customer is unable to make a purchase because the desired item is not available in his or her size, that is at least one lost sale and a bottom line retail failure.
Complete Experience
Are retailers listening to what their customers want from personalisation? Great personalised offers will not deliver any value if they are not linked to the rest of the business. Smart technologies, such as AI, without any doubt have a role to play in delivering personalisation – but they are not the foundation. The foundation is getting the basics right. It is ensuring that when a customer wants to buy a product – online or instore – it is available. It is about providing Store Associates with the ability to track stock anywhere in the supply chain, reserve it for a customer to try on instore or have it sent direct to their destination of choice. It is about combining stock availability information with customer insight to make intelligent suggestions, both instore and via marketing promotions.
Bottom line success is, essentially, about the quality of the interaction. And that means considering not just the accuracy of the promotional offer but the complete customer experience. What is achievable today? What can be done well? If a product is being promoted to an individual, is it available in the right size? Is it available locally, or only in flagship outlets? It is these disconnected experiences that are fundamentally undermining customer experience and brand value.
Conclusion
The future of customer personalisation is incredibly exciting. AI promises the ability to predict a customer’s desires before the customer. Fabulous. But only fabulous if that product is available to buy, at a time and place to suit that individual. Right now personalisation is about the retailer; it is about being clever with promotions. It needs to be about the customer; it needs to be about delivering the quality of experience that drives sales.
Retailers need to go back to basics: use technology to recreate the ‘corner shop model’ of the past, at scale. By creating a truly immersive experience for their customers, retailers can find a way to make personalisation profitable again.
The uptake of artificial intelligence by industry will drastically change the UK job market in the coming years – with…
SHARE THIS STORY
The uptake of artificial intelligence by industry will drastically change the UK job market in the coming years – with 133 million new jobs expected to be created globally.
In the UK alone, up to a third of jobs will be automated or likely to change as a result of the emergence of AI – impacting 10.5 million workers.
Ollie Sexton, Principal at Robert Walters comments:
“As businesses become ever more reliant on AI, there is an increasing amount of pressure on the processes of data capture and integration. As a result, we have seen an unprecedented number of roles being created with data skill-set at their core.
“Our job force cannot afford to not get to grips with data and digitalisation. Since 2015 the volume of data created worldwide has more than doubled – increasing (on average) by 28% year-on-year.
“Now is the perfect time to start honing UK talent for the next generation of AI-influenced jobs. If you look at the statistics in this report we can see that demand is already rife, what we are at risk of is a shortage of talent and skills.”
Demand for Data Professionals
IT professionals dedicated to data management appear to be the fastest growing area within large or global entities, with volumes increasing ten-fold in three years – an increase in vacancies of 160% since 2015.
More generally speaking, data roles across the board have increased by 80% since 2015 – with key areas of growth including data scientists and engineers.
What has been the most interesting to see is the emergence of data scientist as a mainstream profession – with job vacancies increasing by a staggering 110% year-on-year. The same trend can be seen with data engineers, averaging 86% year-on-year job growth.
Professional Services Hiring Rapidly
The rise of cybercrime has resulted in professional services – particularly within banking and financial services – hiring aggressively for information security professionals since 2016, however since then volumes have held steady.
Within professional services, vacancies for data analysts (+19.5%), data manager (+64.2%), data scientist (+28.8), and data engineer (+62%) have all increased year-on-year.
Top Industries Investing in AI
Agriculture
Business Support
Customer Experience
Energy
Healthcare
Intellectual Property
IT Service Management
Manufacturing
Technical Support
Retail
Software Development
Tom Chambers, Manager – Advanced Analytics and Engineering at Robert Walters comments:
“The uptake of AI across multiple industries is bringing about rapid change, but with that opportunity.
“Particularly, we are seeing retail, professional services and technology industries’ strive to develop digital products and services that are digitally engaging, secure and instantaneous for the customer – leading to huge waves of recruitment of professionals who are skilled in implementing, monitoring and gaining the desired output from facial recognition, check-out free retail and computer vision, among other automation technologies.
“Similarly, experimental AI is making huge breakthroughs in the healthcare industry, with the power to replace the need for human, expert diagnoses.
“What we are seeing is from those businesses that are prepared to invest heavily in AI and data analytics, is they are already outperforming their competitors – and so demand for talent in this area shows no signs of wavering.”
In a world awash with a seemingly never-ending list of technology buzzwords such as automation, machine learning and Artificial Intelligence…
SHARE THIS STORY
In a world awash with a seemingly never-ending list of technology buzzwords such as automation, machine learning and Artificial Intelligence (AI) to name a few, AI is one such technology that is moving away from simple hype and stepping closer to reality in procurement.
Here, CPOstrategy looks at 5 ways in which AI is being utilised in procurement…
Procurement, by its very nature, is tasked with handling huge quantities of spend and with spend comes spend data. Often described by leading CPOs as a repetitive task, understanding and sorting that spend data is now being achieved through the implementation of AI.
Through the use of AI, procurement teams can remove human error, increase efficiency and realise greater value from spend data.
Chatbots
One of the biggest ways in which AI is being implemented around the world is in the customer interaction space. In telcos, for example, customer support can now be handled via a highly developed AI chatbot that uses legacy data and context to provide real-time, and unique, solutions for customers.
In procurement, chatbots follow a similar path for both internal and external customers. With tailored and context-aware interactions, chatbots create an omni-channel user experience for all stakeholders in the procurement ecosystem.
Supplier risk identification
Procurement and risk go hand in hand and one of the biggest risks is identifying and working with the right partner. Working in partnerships, which ultimately proves to be a failure, can be extremely costly and so AI is now being used to reduce the risk of failure.
Machine Learning technology, powered by AI, captures and analyses large quantities of supplier data, including their spend patterns and any contract issues that have emerged in previous partnerships, and creates a clearer picture of a supplier in order for the procurement teams to be able to identify whether this particular partner is right for them – without spending a penny.
Benchmarking efficiency
Benchmarking is key to any organisation’s ambition to measure and continuously improve its processes, procedures and policies. In procurement, organisations such as CIPS are used as examples of best practice in which procurement functions all over the world can benchmark against and identify any gaps.
Similar to supplier risk identification, AI can be implemented within ERP systems to analyse the entirety of data that passes through procurement and present this key data in easy to digest formats.
Examples include data classification, cluster analysis and semantic data management to help identify untapped potential or outliers in which procurement teams can improve their processes.
Purchase order processing/Approving purchasing
Procurement has evolved from its traditional role as simply managing spend into a strategic driver for a number of organisations all around the world.
As the role of the CPO has changed, technology such as AI has been implemented to free up their time from the menial tasks (such as PO processing and approving purchases), allowing them to spend more time in areas of growth.
AI software can be used to automatically review POs and match them to Goods Receipt Notes as well as combining with Robotics Process Automation (RPA) to capture, match and approve purchases through the use of contextual data. This contextual data allows AI to identify and make decisions based on past behaviour.
By Robert Douglas, Europe Planning Director at Adaptive Insights, a Workday company Now, more than ever, agility is the currency…
SHARE THIS STORY
By Robert Douglas, Europe Planning Director at Adaptive Insights, a Workday company
Now,
more than ever, agility is the currency of success. And while agility may be
about responding intelligently to the changing nature of the marketplace, those
responses must be rooted in a plan. Today, many organizations leverage newer
technologies in the cloud for planning, having moved away from manual
spreadsheets. And while the cloud offers greater collaboration and the ability
to easily combine both historical and real-time data, it’s just the beginning. Digital
transformation is changing and will continue to change the definition of best
practice planning in organisations. As such, the next step for business planning
revolves around two key areas—advancements in AI and machine learning, and
increased automation.
The power of ‘what if’
What-if scenarios are already incredibly
powerful for strategic decision-makers. Organisations can model different
versions of the future based on historical information and predictive analytics
before choosing the best path forward. Consolidating executional data within
organisations is the first step in capitalising on future AI opportunities. However,
there is a lot more to come. In fact, compared with what AI is going to make
possible, scenario planning is still in its infancy.
Today’s scenario planning is a good proof of
concept, but as long as humans are driving the creative process—it relies on
people to ask the right questions of the right data—what-if planning is going
to be constrained by available resources. The most advanced decision-making
today is typically supported by a few best-estimate scenarios—maybe four or
five at most. However, in truth, there are many more possible futures to
potentially prepare for, and what looks like best practice now is going to seem
vastly limited in scope before too long.
As the volume and variety of available data
grows, and access to that data gets easier, AI and machine learning algorithms
will make it possible to drill down, consolidate, and leverage incredibly
granular information at the highest levels.
AI and machine
learning use cases
To consider how these AI and machine learning
algorithms will work, let’s look at a use case of a CEO aiming to achieve a 40
percent growth target over a two-year period and wants to model what that looks
like to present at the annual executive offsite. AI and machine
learning-enabled planning could help to quickly and automatically find the
optimal growth path, while accommodating any conditions and assumptions on the fly.
Essentially, the planning system could measure
historical performance and recommend a market segment mix strategy, along with
the associated budget increases in the specific marketing and sales activities
needed to support it. If they then decide they need to cap growth in sales to
smaller businesses in order to also expand into enterprises and international
markets—while also maintaining expenses at a certain increase—an alternative,
optimised model could be quickly created without any manual lifting.
A future with machine
learning
The future of business planning is not just
about thinking bigger—it is about making better decisions and operationalising
them faster. That’s where machine learning comes in. Increased automation,
driven by algorithms, is going to blur the boundaries between planning,
execution, and analysis until planning cycle times have all but evaporated.
Planners will be able to ask deep, complex strategy questions and see the results modelled in real time. As the data becomes more trusted, they will be able to make significant, informed, “just-in-time” decisions, confident in the patterns surfaced in the data. And as the line between planning and transactions systems begins to blur and disappear, plans will automatically cascade down to operational departments—even down to individual workflows—in real time.
‘Strategy’ will become the province of human-driven
innovation while planning becomes an organic, ongoing exercise of continuous
improvement inextricably linked to the transactional systems that execute
plans.
Leading the change
Today finance acts as the central junction within business planning and is, therefore, a natural steward for change, helping normalise new habits and behaviours for the rest of the organisation. As such, there is a strong case to be made for finance teams to double down on their new position as stewards of change by acting as transformation leaders—both for existing processes, and for future, unknown developments.
Finance’s role will change significantly in
order to leverage technology developments in the data-driven, AI future.
Driving collaboration with business partners, breaking down data silos, and
embracing new technologies and processes to keep pace with today’s rapidly
changing business environment will be key. The result will be an augmented,
intelligent planning process that delivers true business agility.
Everyone wants to implement Artificial Intelligence (AI) and Business Intelligence (BI) solutions. AI alone is anticipated to generate $15.7 trillion…
SHARE THIS STORY
Everyone wants to implement Artificial Intelligence (AI) and
Business Intelligence (BI) solutions. AI alone is anticipated to generate $15.7
trillion in GDP by globally 2030, and as this market grows, AI and BI will
shift from industry buzzwords, to key market differentiators, before eventually
becoming the new normal in the corporate landscape.
Yet
bringing AI and BI on board is a big leap if it’s your first major data
project. Stibo Systems’ Claus Jensen, Head of Emerging Technology, comments
on the role of MDM as a vital foundation to implement emerging data technology.
Most CEOs
don’t trust their own data.*
Let that
sink in for a moment.
Almost
every business is looking to data solutions to fuel the next phase of growth
and innovation. AI and BI are firmly on the agenda, yet a report by Forbes
Insights and KPMG found 84% of CEOs are concerned with the quality of the data
they’re basing their decisions on.
That’s a
significant disconnect. Businesses at board level want to implement ‘next
generation’ data projects, but don’t trust
the data that will be fed into them. For CDOs and other data leads, this
presents a difficult situation. They need to meet demand for cutting-edge data
projects, knowing that there is a certain level of mistrust in the data at
their disposal.
For many
CDOs, that mistrust isn’t limited to the CEO. Think about the data you are
currently processing: how confident are you that it’s being accurately sourced,
entered, saved, stored, copied and presented? How well do you know that data
journey once it leaves your sphere of control? Are you certain that a
single source of truth is being maintained?
The
data gold rush
It may only
be major data breaches that make the headlines, but in the global gold rush for
data, too many businesses fail to accurately extract, store and interpret data.
Mistakes
are made at every stage in the process – in fact, so bad are we at processing
data, a report by Royal Mail Data Services claims that around 6% of annual
revenue is lost through poor quality data.
It’s
equally bleak in the US, where Gartner’s Data Quality Market Survey puts the
average cost to US business at $15 million per year.
Despite
this, we’re rapidly moving the conversation from data capture to artificial
intelligence (AI), business intelligence (BI) and connected devices (IoT) – and
for good reason.
Putting
aside the issue of bad data (we’ll come back to that), businesses now have
access to more data than they can handle – according to SAS’ Business
Intelligence and Analytics Capabilities Report, 60% of business leaders
struggle to convert data into actionable insights, and 91% of companies feel
that they are incapable to doing it quickly enough to make useful
changes.
Business
Intelligence and Analytics Capabilities Report
In large
businesses, where data streams are blended from many sources, machine learning
can help data scientists monitor figures to flag outliers, irregularities and
noteworthy patterns.
Once
flagged, business leaders can use BI to bring those patterns to life, helping
pave the way for the most appropriate, and profitable, action.
Stibo Systems’ Head of
Emerging Technology, Claus Jensen, believes it’s only a matter of time before
we see AI regularly used within business product features – with machine
learning automating tasks thanks to effective data interpretation.
Jensen and
his team are working at the forefront of data: building master data management
solutions in conjunction with AI and BI. “We’re entering into a new era of data
analytics,” says Jensen. “Data scientists aren’t going away, but they can do
more and more high-level work as certain use cases are solved by AI.”
One of
these use cases is machine learning-based auto classification. “For retailers
onboarding thousands and thousands of new products every month, it’s really
time consuming for them to have the vendor categorise the product into the
vendor taxonomy.
“Machine
learning can automate this based on product description and image.”
Running
before we can walk
As exciting
as this sounds, businesses eager to install new uses for data often face
significant challenges: their data isn’t watertight, or it’s siloed, often
both.
In a piece
penned for the Financial Times, Professor of Economics at Stanford Graduate School
of Business, Paul Oyer, wrote: “Smart managers now know that algorithms are as
good as the data you train them on.” In other words, AI (and analytics for that
matter) can only ever be as good as the date you feed it.
Which
brings us back to the question of trust. What needs to happen for CEOs to trust
their own data?
While
there’s no single answer to this question, a master data management (MDM)
solution is a good place to start.
“You can
think of MDM as the foundation, a layer, that provides a single source of the
truth for data,” explains Jensen. “Analytics and machine learning is only
useful if the data you’re working on is accurate. That’s where MDM comes in; it
ensures information presented, and actions taken, are based on fact and
reality.
“Otherwise,
business analytics is just a nice and colourful way to look at bad data, and
what’s the point in that?”
In today’s market expectations are growing and the stakes are high, with one mistake potentially costing a retailer their reputation….
SHARE THIS STORY
In today’s market expectations are growing and the stakes are
high, with one mistake potentially costing a retailer their reputation. Due to
this level of risk, brands find reducing their hands on approach to processes
difficult, but what they don’t realise is that technology such as Artificial
Intelligence and Machine Learning could prove to be their hero, not their
villain. Entrusting their data and brand values to such technologies may seem
like a scary step, but as David Griffiths, Senior Product Marketing &
Strategy Manager, Adjuno, discusses, it’s one that will free up
retail teams to add value and cut costs.
In AI
should we trust?
There is a great deal of obstacles to overcome when it comes to the stigma attached to AI. A key challenge facing the progression of this technology is that individuals simply do not trust it. The fear of the unknown is one concern that pops up most commonly, with people battling a perceived perception that those who use this technology will lack control.
But a new age
of retail is approaching and there is now an even greater need for brands to
define their processes in order to keep up. Consumers want to receive products
that are of a high-quality and they want to receive them now. These
expectations are taking us beyond the traditional methods of retailing and
leading us into a world immersed in technology, a world that benefits from the
helping hand of AI.
Informing
key decisions
With AI,
retailers will be able to gain valuable insights in warehouse management,
logistics and supply chain management, and make more informed and proactive
decisions. This technology makes it easier to analyse huge volumes of data in
an efficient fashion, helping to detect patterns and providing an endless loop
of forecasting. Using this knowledge to identify factors and issues impacting
the performance of the supply chain, such as weather events, retailers will be
able to take a forward-thinking approach to decision-making. An approach that
will lead to reduced costs and delays.
By extending
human efficiency in terms of reach, quality and speed, this technology can also
help to eliminate the more mundane and routine work that’s faced by employees
across the retail spectrum. From tackling flow management by assessing key
products to ensuring there is enough stock available to improving production
planning, a more informed use of time will help equip brands to face every
consumer request and demand.
This is
particularly important for those brands whose product line extends further than
apparel wear, and steps into the realm of hardware. With diversity comes a need
for more proof points and in turn, an extended volume of data. Retailers will
be battling to work across an even greater number of suppliers and distribution
centres, and accommodating the expectations of a larger customer base.
Considering this, it is fundamental that every last bit of data is refined and
utilised to streamline processes. AI is providing retailers with a platform to
do this, offering the potential for significant changes across the entire
product journey.
A data
conundrum
The benefits of
using AI to consolidate data are endless. Traditionally, teams have relied on
spreadsheets to collate information, hindering their ability to forward plan.
With AI this is no longer the case, a much more accurate picture of the hero
products, sizes and colours likely to sell, can be achieved by looking at
multiple scenarios in real time and pulling them together.
This doesn’t
mean that AI will replace creative buying teams. AI doesn’t forecast trends, it
can’t predict what consumers will be buying in 2020, it can only report on the
product lines. It can however help buying teams assess partners, analyse stock
patterns, track costs, enable capacity planning and help optimise shipments.
This data is invaluable to teams, especially for any new buyers who may need
extra guidance.
Conclusion
AI is set to
transform the retail scene as we know it. But in order to make implementation a
success, there shouldn’t just be a focus on the evolution of data management,
there must be an evolution of mindsets too. After all, if a retailer fails to
jump on board with AI and embrace a new era of change, then their customers
will be the ones who suffer.
