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.
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.
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.
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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
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.
29 March 2023
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Here are 10 of the most important leadership skills that CEOs need to demonstrate in 2023.
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.
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.
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.
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.
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.
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.
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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
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.
3 February 2023
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What does today’s CEO need to do to accelerate an organisation’s digital transformation journey?
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.
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.
24 January 2023
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Expert analysis of the tech trends set to make waves this year
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.”
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The digital landscape is changing day by day. Ideas like the metaverse that once seemed a futuristic fantasy are now…
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:
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.”
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?”
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.
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.
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.
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.”
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
2 November 2022
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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
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.
Enjoy the issue!
Dan Brightmore, Editor
6 September 2022
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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
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.”
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.
Enjoy the issue!
Dan Brightmore, Editor
17 February 2021
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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.
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.
2 January 2021
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Gurpreet Purewal, Associate Vice President, Business Development, iResearch Services, explores how organisations can overcome the challenges presented by AI in 2021.
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.
18 December 2020
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With virtually all companies looking at AI, what are some of the key risks they need to consider before implementation?
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.
18 July 2020
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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…
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.
30 April 2020
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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.
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.
31 March 2020
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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
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 Guillen Zandman
22 February 2020
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Mauro Guillén Zandman, Professor of International Management, The Wharton School, University of Pennsylvania, USA Srikar Reddy, Managing Director and Chief…
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.
6 February 2020
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Peltarion, leading AI innovator and creator of an operational deep learning platform, today announced the findings of a survey of…
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.
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
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.”
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.
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
21 October 2019
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AI is no longer science-fiction writers dream, it’s being implemented in industries all over the world. We look at 5…
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
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
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
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.
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.
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.
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.
5 October 2019
Estimated Read time
The uptake of artificial intelligence by industry will drastically change the UK job market in the coming years – with…
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
IT Service Management
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 (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.
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 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
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
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
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
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.
22 July 2019
Estimated Read time
Everyone wants to implement Artificial Intelligence (AI) and Business Intelligence (BI) solutions. AI alone is anticipated to generate $15.7 trillion…
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.
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.
don’t trust their own data.*
sink in for a moment.
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.
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
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?
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.
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.
equally bleak in the US, where Gartner’s Data Quality Market Survey puts the
average cost to US business at $15 million per year.
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.
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
Intelligence and Analytics Capabilities Report
businesses, where data streams are blended from many sources, machine learning
can help data scientists monitor figures to flag outliers, irregularities and
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.
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.”
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
learning can automate this based on product description and image.”
before we can walk
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
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.
brings us back to the question of trust. What needs to happen for CEOs to trust
their own data?
there’s no single answer to this question, a master data management (MDM)
solution is a good place to start.
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
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. 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.
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.
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.
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.
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
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.
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
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.
26 June 2019
Estimated Read time
Companies that use voice plus touch interactions with their products and services are actually seen as less trustworthy and less…
Companies that use voice plus touch interactions
with their products and services are actually seen as less trustworthy and less
engaging by their users, according to new research from emlyon business school.
The research, conducted by Margherita Pagani,
Director of the AIM Research Center on AI in Value Creation and Professor of
Digital Marketing at emlyon business school, and colleagues from ESSCA School
of Management and Florida State University, College of Business, analysed the
impact and differences between ‘touch’ interaction and ‘touch and voice’
interaction on personal consumer engagement and brand trust.
The researchers created two separate experiments,
focused on a utilitarian product and then a hedonic product, both of which had
over 90 participants belonging to generation Y, which is commonly equipped with
the latest smartphones and frequently use them for business interactions. For
both experiments, participants had to interact with the brand using their
smartphone including a phone call to the company to ask a specific set of
One group was required to interact with the brand
through the smartphone using a touch-only interaction, and the other used both
touch and voice interaction – either Apple’s Siri or OK Google. After
interacting with the company, participants were asked to rate their customer
experience. The participant’s answers were then measured to evaluate personal
engagement with the tasks, their level of trust with the brand and their
The researchers found that participants who used
the touch-only interaction experienced a much higher level of personal
engagement with the brand compared to those who used the touch plus voice
Prof. Pagani says,
“Many companies have introduced new AI products
that use voice-activation such as Amazon’s Alexa, Google’s Home Assistant or
Apple’s Siri. These have been introduced in order to increase customer
experiential engagement, stimulate the interaction and collect more data that
allow to better personalise the experience through machine learning.
However, our study shows that in the initial phase of adoption, adding
voice recognition actually has the opposite desired effect. Even if voice may
be considered as a way to develop a much more natural interaction, the level of
cognitive efforts required to the brain using two sensory modes (voice and touch)
are higher. Therefore, consumers find it harder to completely engage with the
product and can easily be distracted”.
The researchers also found that participants who
used the touch-only interaction felt as though they had more control over the
information they shared and therefore had greater confidence in the brand.
Users stated that they found it much simpler to input information using only
one sensory method; touch.
“The lack of familiarity with how these digital
voice interactions actually work is likely to be the reason as to why consumers
are less trusting of brands that use both touch and voice. Whilst the use of
touch also garners much more control for a consumer, as opposed to voice”.
study, published in the ‘Journal of Interactive Marketing’ is the first of its
kind to explore the effects of new voice-based interface modes on marketing
relationships. Whilst technology multiplies the way that consumers can interact
with brands, this study shows that too much interaction can actually harm a company,
and offers managers guidance on how to increase personal engagement and brand
13 June 2019
Estimated Read time
Welcome to the June issue of Interface Magazine! Read the latest issue now! This month’s cover features Gary Steen, TalkTalk’s…
This month’s cover features Gary Steen, TalkTalk’s
Managing Director of Technology, Change, and Security, Gary Steen regarding the
telco’s commitment to thinking, and acting, differently in a highly competitive
TalkTalk is an established telecommunications company that fosters a youthful, pioneering spirit. “I like to think of TalkTalk as a mature start-up,” says Managing Director of Technology, Change and Security, Gary Steen. “We are mature in terms of being in the FTSE 250, with over four million customers, relying on our services every day through our essential, critical national infrastructure. But that said, I definitely think we start our day thinking as a start-up would. What can we do differently? How do we beat the competition? How do we attract great talent? We’ve got to come at this in a different way if we are going to succeed in the marketplace. We are mature, but we think like a start-up.”
Elsewhere we speak to Natalia
Graves, VP Head of Procurement at Veeam Software who reveals the secrets to a
successful procurement transformation. Graves
was tasked with looking at the automating, simplifying, and accelerating of
Veeam’s procurement and travel processes and systems around them, including
evaluating and rolling out a company-wide source-to-pay platform. “It has been
an incredible journey,” she tells us from her office in Boston, Massachusetts.
We also feature exclusive interviews with PTI Consulting and cloud specialists
we reveal 5 of the biggest AI companies in fintech and list the best events and
19 March 2019
Estimated Read time
IPsoft has introduced 1Bank, the first conversational banking solution featuring virtual agent Amelia. It has been rated the top virtual…
IPsoft has introduced 1Bank, the first conversational banking solution featuring virtual agent Amelia. It has been rated the top virtual agent in conversational AI by Everest Group.
Chetan Dube, CEO at IPsoft, commented: “With 1Bank we provide the most humanlike digital experience in the marketplace, built from the knowledge we’ve gained serving six of the world’s leading banks with conversational AI. We are giving banks the possibility of providing customers with their own personal banker around the clock.”
1Bank answers FAQs, but also resolves complex customer needs, by understanding customer intent. It can also switch context, mid-conversation. Its machine learning Learning (ML) abilities also mean that 1Bank can improve over time.
Some of the tasks 1Bank can carry out are:
advising on unpaid bills, proactively informing customers of an incoming bill and communicating any insufficient funds, making a money transfer and asking if the customer wants to set up payment for the bills when they are due.
recommending and setting up recurring payments, making payments from different accounts, opening and closing accounts.
helping customers locate transactions.
assisting with individual and potentially fraudulent charges on credit cards and disputing them, getting a new pin, getting a balance transfer or applying for a new credit card.
creating travel alerts after a customer made an airline purchase and proactively recommending the next step, such as, when traveling to exchange and withdrawing cash.
1Bank can integrate with existing tools and interfaces, and it can be added to existing applications to help customers quickly access the information and service they need. This includes mobile apps, desktop or kiosk apps, website modules, or within consumer chat applications, such as Facebook Messenger and Amazon Echo.
12 March 2019
Estimated Read time
It is a measure of how much we take sophisticated technology for granted that the appearance of a pop-up chatbot…
It is a measure of how much we take sophisticated technology
for granted that the appearance of a pop-up chatbot screen, asking questions
and providing sensible responses, is no longer considered remarkable.
Chatbots today inhabit websites, intranets, apps, and social
media platforms, and have become so ubiquitous as to become almost invisible.
Interacting with a text screen is a natural activity, and most users don’t seem
to care much about whether the other side of the conversation is a human or a
bundle of code.
From a corporate perspective, chatbots can be a win/win.
Increasingly reliable in their responses and cheap to operate, they are
available night and day and are instantly scalable. Whether your site or app
has one visitor a day or thousands, the bot is always eager to help.
We’ve come a long way from the disastrous early attempts at
providing AI assistance – remember Microsoft’s paperclip? – but what a good
chatbot does today is much the same as that much-loathed animated character:
identify what a user is trying to do, and offer appropriate help.
You will have heard of the Turing Test, which held that if a
computer could provide responses that were indistinguishable from those of a
human, the machine had to be considered intelligent. Are we there yet?
Despite some well-publicised claims, the answer is still,
probably, no. In 2014 a program called Eugene Goostman successfully tricked
Turing Test judges into believing it was a 13-year-old Ukrainian boy. This
controversial victory is still a failure, though, because nobody expects or
wants to find an adolescent behind a real-world help screen.
More relevant is the Loebner Prize for the most convincing
chatbot. This awards bronze medals each year to the best contenders, but has
never made a silver (text) or gold (audio visual) award – the equivalent of a
Turing Test pass.
A glance at the best entries from the 2018 competition shows
why. Eleven bots were asked 20 questions, winning two points for a human-like
answer and one for a plausible response. Out of a maximum of 40 points, the
winner scored 27 and the lowest just 12.
Even simple questions can make the tech fall over. The
winner, a chatbot called Tutor by Ron C Lee, answered “Do you know how to
make toast?” with “No, we haven’t”.
While there remain limits on what a chatbot can convincingly
do, this need not be a problem if it is deployed in the right way. Recent
research from Penn State University found that while many appreciate an
apparently empathetic response from a bot, those who believe machines are
actually capable of consciousness do not.
“The majority of people do not believe in machine
emotion, so took expressions of empathy and sympathy as courtesies,” said researcher
Bingjie Liu. “However, people who think it’s possible that machines could
have emotions had negative reactions from the chatbots.”
The answer is only to use them for things they are good at,
says James Williams, who leads the development of advanced chatbots with
Nottingham-based software company MHR. While chatbots are now common in
consumer interfaces, he notes, there is much potential in the enterprise space.
When applied within the company’s flagship human resources (HR) software, Williams says the conversational interface is an excellent way to simplify common transactions. “You’ll hear us talk a lot about reducing friction,” he says, which means anything that slows down a routine interaction.
An example is an employee submitting an expenses claim,
which MHR’s Talksuite does through an AI-driven chatbot. “Taking a picture
of a receipt is a natural thing to do, and the AI will recognise the image,
understanding the content as well as the context. Bots are really good for
processes with lots of rules or lots of steps, and here it just asks a few
questions and saves the employee a lot of hassle. Less friction.”
Knowing when not to deploy a bot can be just as valuable. Williams recounts one client which had deployed a complex chatbot for its newly joining employees, known in HR circles as the onboarding process. “The chatbot went through everything plus the kitchen sink, so the employee was there for 20 minutes or more being interrogated by a machine. It was just awful. A web-based form is a much better interface in this situation.”
His final advice is to consider the image the bot projects.
“Any personality in a chatbot tends to come accidentally, unlike a website
or an app. If you let software developers write the conversation, you might end
up with a bot that’s actually a bit of a dick. People make judgements on things
like language and punctuation. It’s fine to be personable and friendly, but it
should be clear when the user is talking to a bot and when any transition to a
human interaction takes place.”
7 March 2019
Estimated Read time
Quest Solution Inc, provides supply chain and artificial intelligence (AI) based machine vision solutions. It has been awarded a project by…
Quest Solution Inc, provides supply chain and artificial intelligence (AI) based machine vision solutions. It has been awarded a project by a leading supply chain and logistics provider in the US. The release doesn’t detail who the leading supply chain provider is, but it does reveal that the project is valued at around $US7 million.
that will allow for a robot to live at your home and handle your deliveries has
been filed by Amazon. The patent outlines plans for a robot that will
completely transform last mile delivery capabilities, even potentially
delivering packages in the early hours between 2am and 6am.
Back to AI, NFI Industries and Transplace are paying attention to
this technology through partnerships with firms that add AI capabilities to
transportation and distribution. Both companies have announced a partnership
with the goal of enhancing logistics services and technology capabilities.
In a video interview with CNBC, Lance
Fritz, the CEO of Union Pacific, is concerned that supply chain
disruption won’t return to normal. He believes the biggest concern lies in
trade and that the challenges with China should be resolved as soon as
In an interview with Sky News, Peter
Schwarzenbauer, BMW board member responsible for Mini and Rolls
Royce, has said that the firm will need to think about moving production from
the UK in the event of a no-deal Brexit. Remaining would be too costly for the
organisation and some production would move to countries like Austria. Toyota
shares similar concerns with Johan van Zyl, head of Toyota’s European
operations, telling the BBC that Brexit hurdles would ‘undermine Toyota’s
Blockchain remains an interesting solution for many in the supply chain and
Blockchain Labs for Open Collaboration (BLOC) has recently started working with
NYK, a Japanese shopping company, and BHP, a mining company, to establish a
sustainable biofuel supply chain using BLOC’s blockchain fuel assurance
Also in the news: HighJump,
a global supply chain solutions provider, awarded five women in its Top Women
Leaders in Supply Chain awards; Cryptobriefings
Kiana Danial examines whether VeChain can deliver a supply chain solution; Apple
releases a supply chain document that reveals how iPhone, airpods and other
products are all zero waste; and SIGTTO GM, Andrew Clifton, looks to the LNG
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