Raise the bar with accounts receivable automation to release cash

Thanks to pioneering technology, there is now a golden opportunity for financial controllers to free enormous sums of tied-up working capital. This will empower employees and enable them to drive value and strategy, writes Kevin Kimber, Managing Director, Global AR, BlackLine

The coronavirus crisis has prompted most organisations worldwide to spend big on automating their financial services – but only a tiny fraction have upgraded their accounts receivable processes. Today, with the advanced technology and pioneering tools available, those who fail to automate their AR processes miss a golden opportunity to empower the finance teams and unlock the cash held hostage.

In November 2019, months before the pandemic hit Europe, PricewaterhouseCoopers calculated that a staggering $1.2 trillion of excess working capital was tied up on global balance sheets. While there is clearly a latent opportunity to free this enormous amount of cash, ahead of the coronavirus crisis automating AR operations was not a priority for businesses.

Back then, the reluctance to focus on upgrading AR processes for the digital age was, to an extent, understandable, given the ease of borrowing for businesses. Now, though, organisations realise that optimising these processes has never been more critical. A recent Institute of Finance and Management survey suggests 55% of finance leaders are less than satisfied with how their company’s AR procedures have performed during the recession. And over half (52%) say that too many manual processes are the biggest weakness.

The combination of the lines of credit being significantly compressed and the increased demand to have cash more readily available – to drive innovation, boost agility and strengthen resilience – has elevated the need to embrace AR automation.

Historically, solution vendors possibly didn’t know how best to position the value and business benefits of automating AR processes. It’s so easy to pigeonhole AR automation as a single process primarily about headcount reduction and driving efficiencies. While these points are valid, there is so much more from which to benefit. 

Articulating the benefits of automating the AR process

Presenting the point that “if you deploy a technology like ours, you can reduce your headcount from, say, 16 to five people” does not go far enough – there are so many additional advantages now. However, if we reframe the case for AR automation, it becomes so much more compelling.

For example, a large, global B2B manufacturer with a high volume of low-value invoices might offer 30-day payment terms. Each day is worth $150 million, so customers paying 63 days late means $9.5bn late and at risk.

Not only is this woefully inefficient, but there is also friction generated between the increasingly frustrated finance team and the customers whom they are chasing for payment.

Deploying technology like BlackLine enables that cash to be collected and applied much faster, giving access to cash quicker, reducing the need to borrow to cover working capital exposure and tightening customer relationships. Ultimately, through artificial intelligence and machine learning, automating that process will enable businesses to unlock the cash held hostage.

More than that, investment in AR solutions starts a virtuous circle: the business becomes more agile, innovative, and resilient – all essential elements for organisations seeking to thrive in the coming months and years – because the cash is available. 

Looking at the broader picture, it’s a fallacy that robots are taking our jobs. On the contrary, they are enhancing and improving them. Humans are empowered to make smarter, data-driven decisions. And at BlackLine, we are transforming the relationship finance teams have with technology.

According to Adobe’s Future of Time study, published in late August, UK business employees waste more than a day a week on low-value tasks that should be automated. So much so that almost two-thirds (59%) of respondents are seeking new jobs with better technology to reclaim work-life balance.

Automation propels finance teams from the back office to driving strategy 

Indeed, the reduction of repetitive manual tasks transforms finance departments to be more human and less robotic – they become enablers rather than blockers. Automating the AR process means that risk is easier to manage. 

For instance, BlackLine AR Automation solutions put key information at the fingertips of organisations – from live payment data to debtor performance – so teams can quickly identify customer trends and maximise cash and debtor performance metrics.

It also helps to optimise relationships with customers. Access to and analysis of the data provides a markedly better understanding of customer behaviours, allowing the finance team to be more proactive, and helpful, when engaging. For example, how and when are they paying? What levels of credit are they on? With managing existing customers and looking for new customers crucial for growth, deepening these relationships is vital. 

Further, when supported by automation and data-hungry AI algorithms, finance teams are propelled from the “back office” to the heart of the business, driving both value and strategy.

Automated solutions, such as BlackLine’s, instantly improve a business’s cash flow, better protect revenue, and boost working capital and customer-centricity. We know what customers need to thrive in the digital age. Armed with our expert help and pioneering tools, they can unlock the cash held hostage while empowering their finance teams. Organisations that prioritise automating AR processes today will win tomorrow.

Small steps to accounts receivable automation – but large rewards

1. Understand that business outcomes are being challenged, unnecessarily. In 2019 PricewaterhouseCoopers estimated that $1.2 trillion of excess working capital was tied up on global balance sheets. A more recent IOFM survey suggests days sales outstanding (DSO) has increased by 59%. Additionally, PYMNTS’s B2B Payments Innovation Readiness Playbook shows businesses that rely on manual AR processes often have a 30% longer average DSO.

2. Most AR processes are not fit for purpose – so say finance leaders. The IOFM survey finds that 55% of respondents are less than satisfied with their AR operation. Over half (52%) report that too many manual processes are the biggest weakness. Further, only 23% have utilised some kind of cash application automation. Notably, the lowest number of days taken to collect debt for those businesses using AR automation is 12.

3. Realise the potential of automating AR processes. Organisations that have upgraded to BlackLine’s AR automation solutions all report huge – and immediate – benefits. “You can reduce your costs by at least 75%,” says the head of credit, Atkins Group. Meanwhile, Veolia’s UK credit manager says the solution “has allowed the credit controllers to focus on collecting cash and managing risk”.

4. BlackLine AR Intelligence delivers real-time insight into customer financial behaviour to mitigate financial risks and improve cash flow and working capital performance. With cash flow vital to every business, AR automation is a future-proofed solution.

This article first appeared in BlackLine’s special report, Optimising the accounts receivable department, published by Raconteur in November 2021

Five ways automation enables finance teams to be more human

As we stride into the fourth industrial revolution, finance teams can work alongside machines to drive strategy and value. And, as the war for talent rages investing in technology is crucial to attract and retain skilled workers

The argument that robots will replace human jobs misses the crucial point that machines empower workers with a pulse. It has been this way for hundreds of years – since the original industrial revolution in the mid-18th century when the Luddites, led by Ned Ludd, a Leicester weaver fearful of change, attacked factories and their owners. However, it soon became obvious man worked much better alongside machine.

Now, as we stride into the fourth industrial revolution, which uses modern smart technology to automate traditional manufacturing and industrial practices, robots are taking over more menial, repetitive tasks. This capability frees up workers to be more human. For finance teams especially, this automation of processes enables them to be more human and drive value and strategy – here follow five ways how.

1. Paper processes are old news

In the finance world, paper has been essential for centuries – but in the digital age, we can speed up processes, and save the trees, argues Nitin Purwar, India-based industry practice director of banking at UiPath. “Within finance, data-intensive and repetitive tasks are commonplace,” he says. “Often further weighed down by legacy systems, paper-based documents and unstructured data, these processes can take up a large proportion of a professional’s day.”

Purwar argues that “this work isn’t what humans are best at and often isn’t what we enjoy doing. By automating these processes, finance professionals can be freed to spend more time on value-added, strategic activities that require judgement and skill, thus enhancing the employee experience all while saving the department time, money and improving the accuracy of processes.”

2. Manual ways of working are highly inefficient – and a turn off for talent

Businesses that embrace automation stand to gain a competitive advantage – not least when it comes to attracting and retaining talent. Adobe’s Future of Time study, published in late August, finds that UK business employees waste more than a day a week on low-value tasks that should be automated. Tellingly, almost two-thirds (59%) of respondents are seeking new jobs with better technology to reclaim work-life balance.

Purwar from UiPath uses an example to explain the benefits of automation in this regard.“One infrastructure solutions firm we work with used to process all invoices manually, printing, signing, scanning and uploading 400,000 invoices a year. Now, a robot affectionately named Archie processes all invoices digitally, freeing up on average 11 minutes per invoice of time that employees can now spend focusing on value-added tasks instead. That amounts to thousands of hours per year saved.” 

There is more potential to realise, which is why organisations should double down on automated solution. Kevin Kimber, managing director of global accounts receivable at BlackLine, suggests that while many businesses seek robotic process automation, now “advancements in artificial intelligence and machine learning take what is possible to the next level”.

3. Financial leaders can show their human skills and improve collaboration

Ash Finnegan, digital transformation officer at Conga, which provides commercial operations transformation solutions, points out that the pandemic has forced financial leaders to show their human sides and manage change.

“Out of necessity, most digital transformation journeys have been accelerated, with artificial intelligence being a major focus,” she says. “Financial leaders have invested heavily in AI and wider automation technology, entirely restructuring their back office to deliver their services remotely.”

Neil Murphy, global vice president at ABBYY, a digital intelligence company, posits workers who embrace automation can “work more efficiently, collaborate better, and ease the burden of administration in their day-to-day roles. Deploying AI-powered robots gives this opportunity, gifting finance teams more time to focus on more creative, problem-solving tasks and alleviate the pressure. Now more than ever, it’s time to put the human touch back into the finance.” 

4. Automation elevates financial professionals to become trusted advisors

Glen Foster, director of small business and partners at accounting software company Xero, says “time truly is money” for financial professionals. Xero data shows these workers can use up to 30% of their time on manual data entry – equivalent to 1.5 days a week.

By contrast, automation and digital software can free up most of that time. “Cloud accounting tools allow you to automate time-consuming tasks like data entry, bank reconciliation and payments so that you can spend more time advising, analysing data and focusing on growth,” he says. 

“Providing advice and insights on financials is more valuable to clients and businesses than manual, repetitive data entry skills. This ultimately sets accountants and finance professionals up as trusted advisors.”

5. Improve relationships with customers – and add value

FreeAgent survey from 2020 calculated that 81% of accountants have discovered that using automated software has freed up an average of two working hours a week. The same report states that this time saved could generate an additional £68,000 in revenue a year.

John Miller, chief operations officer of Addition, a London-based financial services firm, adds: “Automation has allowed humans to do what they do best: offer advice to the client, knowing that the routine tasks are done robustly and accurately.”

This article first appeared in BlackLine’s special report, Optimising the accounts receivable department, published by Raconteur in November 2021

Will the new national strategy make the UK an AI superpower?

Westminster’s new AI strategy is a step in the right direction, but there are hurdles – particularly concerning regulation, data-sharing and skills – that could hinder the UK’s progress

In the global AI investment, innovation and implementation stakes, the UK lies in a creditable third place. Trailing the US and second-placed China, it holds a slight lead over Canada and South Korea, according to the Global AI Index published in December 2020 by Tortoise Media. The moral of Aesop’s most famous fable involving a tortoise may be ‘more haste, less speed’, but Westminster is seeking to hare ahead in this race over the coming decade. Its national AI strategy, published in September 2021, is a 10-year plan to make the country an “AI superpower”. But what does that mean exactly?

Although Westminster has already poured more than £2.3bn into AI initiatives since 2014, this strategy will accelerate progress, promises Chris Philp, minister for technology and the digital economy at the Department for Digital, Culture, Media and Sport. 

“It’s a hugely significant vision to help the UK strengthen its position as a global science superpower and seize the potential of modern technology to improve people’s lives and solve global challenges such as climate change,” he declares.

The Croydon South MP explains that the strategy has three main aims. These are to ensure that the country invests in the long-term growth of AI; that the technology benefits every sector of the economy and all parts of the country; and that its development is governed in a way that protects the public and preserves the UK’s fundamental values while encouraging investment and innovation. 

“We have heard repeatedly from people working in and around AI that these issues are entirely connected,” says Philp, hinting at the complexity of the task at hand.

What will life be like for people living and working in an AI superpower? “There are huge opportunities for the government to capitalise on this technology to improve lives,” he says. “We can deliver more for less and give a better experience as we do so. For people working in the public sector, it could mean a reduction in the hours they spend on basic tasks, which will give them more time to find innovative ways of improving public services.” 

Philp continues: “For businesses, we want to ensure that there are clear rules, applied ethical principles and a pro-innovation regulatory environment that can create tech powerhouses across the country.”

AI will also be crucial in helping the UK to meet its legal obligations to achieve net-zero carbon emissions by 2050. Pleasingly for Philp, progress is already being made in this field. He notes that the Alan Turing Institute has been “exploring AI applications that could help to improve power storage and optimise renewable energy deployment by feeding solar and wind power into the national grid”.

The artificial elephant in the room is human resistance to data-sharing

The strategy has been generally well-received in the tech world, with most people acknowledging that it’s an important step in the right direction. But some experts have identified a few potential shortcomings.

Peter van der Putten is assistant professor of AI and creative research at Leiden University and director of decisioning and AI solutions at cloud software firm Pegasystems. He is “encouraged to see a shift from broad strategic statements to more concrete, action-oriented recommendations”, but he would have preferred to see a more complete ethical framework for AI application. 

“A large portion of the document focuses on AI governance, but it appears that a lot of the emphasis is still on analysis, discussion and policy-making. There is less on proposing hard legislation or determining which authority will be accountable for governance,” van der Putten explains. “This is an area in which the UK will need to accelerate, given that both the EU and China have made relatively concrete proposals for the regulation of AI recently.”

Liz O’Driscoll is head of innovation at Civica, a supplier of software designed to improve the efficiency of public services. She believes that the UK has “made great progress so far, with many organisations starting to embrace data standards and invest in data skills. But the artificial elephant in the room is human resistance to data-sharing. Privacy remains crucial, especially when it comes to citizens’ information, but wider uncertainty about issues such as regulation, public perception and peer endorsement will also prompt many in the public sector to play it safe with AI.”

There are some encouraging signs that people’s general reservations about data-sharing are softening, thanks to the success of collaborative AI solutions during the Covid crisis, O’Driscoll adds. 

“Sharing data has been essential in our defence against the virus. It has enabled key public services to stay focused on people who are most at risk,” she says. “Success stories have entered the public domain, so we need to make the most of these cases and continue driving further positive change.”

It’s clear that more education about the benefits of data-sharing and work on AI ethics are required, but could a shortage of recruits prove to be the most significant challenge for the national AI strategy? A survey published by Experian in September indicates that more than two-thirds (68%) of UK students wrongly believe that they would need to earn a STEM qualification to stand a chance of landing a data-related job.

Dr Mahlet Zimeta, head of public policy at the Open Data Institute, thinks that the widely held view that “the UK needs to produce more people who can code” is unhelpful at best. 

“Although improving data literacy is important, we’re going to need a much broader range of skills, including critical thinking,” she argues. “Leaders require a change of mindset to maximise the potential of AI. At the moment, it feels as though no one wants to be the first mover, but this is why experimenting and being transparent about the results will drive progress.”

From the government’s perspective, Philp urges both “students and businesses to equip themselves with the skills they’ll need to take advantage of future developments in AI”. For employers, this will include ensuring that their staff “have access to suitable training and development opportunities”, he adds, pointing out that the government’s online list of so-called skills bootcamps is an excellent place to start. Tortoise Media’s Global AI Index ranks the UK fourth in the world on its supply of talent and third for the quality of its research. The country is a relative laggard in terms of both infrastructure (19th) and development (11th), so there is plenty of ground to make up on both the US and China. The national AI strategy suggests that some haste will be required if the UK is to even keep these rivals within its sights. Ultimately, though, if all goes to plan, humanity stands to win.

This article was first published in Raconteur’s AI for Business report in October 2021

Is China dominating the West in the artificial intelligence arms race?

The US has warned that it is behind its historical foe in the East, and the European bloc is also concerned, but there are ways in which the UK, for example, could catch up, according to experts

If you ask technology experts in the West which country is winning the artificial intelligence arms race, a significant majority will point to China. But is that right? Indeed, Nicolas Chaillan, the Pentagon’s first Chief Software Officer, effectively waved the white flag when, in September, his resignation letter lamented his country’s “laggard” approach to skilling up for AI and a lack of funding. 

A month later, he was more explicit when telling the Financial Times: “We have no competing fighting chance against China in 15 to 20 years. Right now, it’s already a done deal; it is already over, in my opinion.”

The 37-year old spent three years steering a Pentagon-wide effort to increase the United States’ AI, machine learning, and cybersecurity capabilities. After stepping down, he said there was “good reason to be angry.” He argued that his country’s supposed slow technological transformation was allowing China to achieve global dominance and effectively take control of critical areas, from geopolitics to media narratives and everywhere in between.

 Chaillan suggested that some US government departments had a “kindergarten level” of cybersecurity and stated he was worried about his children’s future. He made his outspoken comments mere months after a congressionally mandated national security commission predicted in March that China could speed ahead as the world’s AI superpower within the next decade.

 Following a two-year study, the National Security Commission on Artificial Intelligence concluded that the US needed to develop a “resilient domestic base” for creating semiconductors required to manufacture a range of electronic devices, including diodes, transistors, and integrated circuits. Chair Eric Schmidt, the former Google CEO, warned: “We are very close to losing the cutting edge of microelectronics, which power our companies and our military because of our reliance on Taiwan.”

Countering the rise of China

Jens Stoltenberg, the Nato Secretary-General since 2014, echoed the US concerns about how China is galloping away from competitors due to its investment in innovative technology, which other countries have embraced. The implicit – yet hard-to-prove – worry is that the ubiquitous tech is a strategic asset for the Chinese government. But is this a case of deep-rooted, centuries-old mistrust of the East by the West?

 The former Norwegian Prime Minister, ever the diplomat, was at pains to stress that China was not considered an “adversary.” However, he did make the point that its cyber capabilities, new technologies, and long-distance missiles were on the radar of European security services. 

 In late October, Stoltenberg admitted that Nato would expand its focus to counter the “rise of China” in an interview with the Financial Times. “Nato is an alliance of North America and Europe,” he said, “but this region faces global challenges: terrorism, cyber but also the rise of China.”

 Ominously, Stoltenberg continued: “China is coming closer to us. We see them in the Arctic. We see them in cyberspace. We see them investing heavily in critical infrastructure in our countries. They have more and more high-range weapons that can reach all Nato-allied countries.”

 But is China truly so far in front of others? According to the venerated Global AI Index, calculated by Tortoise Media, the US leads the race, with China second. In late September, the UK – currently third in the rankings, slightly ahead of Canada and South Korea – unveiled its National AI Strategy, which sets out a 10-year plan to make it a “global AI superpower”.

 UK plans to become global AI superpower

Some £2.3 billion has already been poured into AI initiatives by the UK government since 2014, though this document – the country’s first package solely focused on AI and machine learning – will accelerate progress, enthuses the Department for Digital, Culture, Media and Sport’s digital minister, Chris Philp. 

“The UK already punches above its weight internationally, and we are ranked third in the world behind the US and China in the list of top countries for AI,” he said. “AI technologies generate billions [of pounds] for the economy and improve our lives. They power the technology we use daily and help save lives through better disease diagnosis and drug discovery.”

A self-styled AI champion and World Economic Forum AI Council member, Simon Greenman, states that the UK is home to the most significant number of AI companies and start-ups (8%) aside from the US (40%). Additionally, venture capital investment in UK AI projects was £2.4bn in 2019. 

“Money isn’t the issue,” says the Checkit Non-Executive Director, when discussing the perceived lack of progress being made by the UK. “The problem is we don’t have enough good commercial AI skills, such as product management and enterprise sales, to put the theory, research, and vision into practice.

“For instance, the ‘Office of AI’ doesn’t have an AI implementation budget. If we’re going to realise the potential that AI can bring to the UK, the government needs to put its money where its mouth is and appoint somebody who has a central budget to implement large-scale AI deployments when it comes to public policy.”

Greater collaboration needed

Fakhar Khalid, Chief Scientist of London-headquartered SenSat, a cloud-based 3D interactive virtual engineering platform, is more optimistic about the UK’s chances of becoming an AI superpower and calls for patience. While he agrees that “the US and China are the leading nations in terms of AI innovation and commercialisation,” he notes that China published its first AI strategy in 2017. The US followed with equivalent plans two years later. 

 “Although these strategies have recently started to emerge in the public and policy domain, these countries have been investing healthily in their ecosystems since the early 1990s,” he says. “In the 90s, the US was not only the leading country for AI education, but its academic innovation also had strong ties with the industry, ensuring a direct impact on the growth of their economy.”

Hinting at the different types of government that enable more collaboration in China compared to the US, the UK, and even Europe as a bloc, he continues: “China, on the other hand, has been radical and ambitious in building its technology capabilities by strongly linking government, academia, and industry to show the beneficial impact of AI on their economy. The government centrally controls China’s AI strategy with hyperlocal implementation.

“The UK’s long overdue AI strategy is a clear indication that we are here to declare ourselves as the key leader in this field, yet we have much to learn from these nations about commercialising our research and creating a strong and impactful link between academia and industry.”

For Dr Mahlet Zimeta, Head of Public Policy at the Open Data Institute in the UK, while China and the US are ahead in the AI race, there are ways in which her country can catch up. “The territories that are lined up to be global AI superpowers are China, US, and the European Union,” she says, “because the great access to and availability of data means the analysis is better. They have massive advantages of scale, but the UK could show international leadership around AI ethics.”

With a greater focus on data skills, standards, and sharing, and encouraging an international collaborative ecosystem driving AI innovation, the West can leap ahead of China. And perhaps, in time, all AI superpowers will work together, in harmony, to the benefit of humanity.  

FSA CIO on her career in tech: ‘It’s where the future is already happening’

The FSA’s groundbreaking CIO talks the future of technology careers, data openness and going beyond the status quo

What makes a successful chief information officer (CIO) in 2021? Ask Julie Pierce, the trailblazing director of openness, data and digital at the Food Standards Agency (FSA), who ranked fifth overall and was the highest-placed woman in the venerated CIO 100 list for 2019. 

Having learnt the news about the CIO 100, which recognises the UK’s “most transformational and disruptive” CIOs, Pierce recalls feeling “happy [and] honoured”. Following a pause, she adds: “And surprised.” Why? “If someone had told me I would be recognised at this level back when I was, say, 30, I would have thought it impossible, for so many reasons. So my reaction was: ‘Oh my God!’”

To an extent, her reaction to the accolade is understandable in an industry dominated by men. But the recognition is also a cause for celebration. Given that only one in six technology specialists in the UK are female and just 10% are IT leaders, the Bristol-based Pierce proudly serves as a role model for other women seeking to reach the top in tech.

The incredulity is misplaced, though, when one considers her groundbreaking 41-year career. After starting off with a misstep in oil exploration – more of which below – she enjoyed 13 years as a consultant at PwC, where she was one of the first female partners. Her CV also includes stints with the Home Office and the Metropolitan Police Service.

More recently, Pierce has excelled as CIO at the Animal and Plant Health Agency and the Department for Environment, Food and Rural Affairs (Defra). In August 2015, she moved from Defra to the FSA, a non-ministerial government department which monitors risks and issues of concern regarding food.

The case for data openness

As director of openness, data and digital (“a long but pretty cool title”) at the FSA, she performs a raft of duties. These include the CIO role, while also covering science and Wales. 

Importantly, Pierce is a fervent advocate of open and transparent data. Indeed, in the public sector, and further afield, the FSA is often held up as an exemplar of what is possible through opening up data. This progressiveness is in no small part thanks to Pierce.

“Being open and transparent [with data] is so important to me,” she says. “And at the FSA it is fundamental to our core being; we are here to be open and transparent on behalf of the consumer.” 

Pierce explains that her agency raises the alarm when “things are not quite right for consumers concerning food safety and authenticity”. As an example, she points to a recently implemented service that uses predictive analytics and machine learning to monitor global risks. 

The FSA publishes 70% of its datasets. Pierce argues convincingly that fellow CIOs should push to open data and drive collaboration internally and externally. The FSA has been trying to persuade businesses to be open and publish their data, she says.

At the FSA it is fundamental to our core being; we are here to be open and transparent on behalf of the consumer 

“We can see the large amount of data collected about food in public and private sector. For instance, we can see the opportunities from data-rich digital platforms where they may be sitting on real insights as to food risk, allowing us all to take action before something goes wrong.”

Under Pierce’s direction, the FSA has “put as much effort as possible in the last few years” to develop the infrastructure necessary to open data and make it “easier for businesses to consume that data”.

Beyond the status quo

Pierce believes in “transformation through the application of modern digital technology and insights from predictive analytics to business problems”. And in a clarion call for fellow CIOs, she has urged on LinkedIn: “Let’s be really different; let’s go beyond merely automating the status quo.”

Pierce has always sought to go beyond the status quo, but she originally had little interest in technology. Having graduated from the University of Wales, Bangor, in 1980 with a first-class degree in mathematics and physical oceanography, Pierce sought a hands-on role in the oil-exploration industry. The fact that it was “completely male-dominated” made it more attractive because of the challenge.

Ironically, she switched directions and flourished when the path was blocked in her chosen profession because of her gender. As a woman, she was forbidden to step foot on either the boats or the rigs. Pierce’s impressive career in tech can be traced back to that early change of tack. 

Let’s be really different; let’s go beyond merely automating the status quo

However, the combination of fierce ambition and talent has elevated her. It is this desire that modern CIOs must possess to excel, she suggests.

“My FSA role includes the CIO and a lot more. That in itself is one of the things I’m most proud of: that I have risen and gone above the CIO role into other aspects of the business.” Indeed, to secure a place in the boardroom, CIOs must demonstrate the many different ways they can add value. 

Pierce says there has never been a more exciting time to embark on a career in tech and climb the ranks to CIO and above. “It’s an absolutely fascinating sector, as it’s moving and evolving so quickly,” she says. “It’s becoming more relevant, ubiquitous, and essential to everything we do. Therefore, you can choose any sector to work in – food, healthcare, financial services, whatever.

“What makes a career in tech so attractive nowadays is that it is accessible in so many more ways compared to when I began. You can come in through some of the more innovative data ideas, such as artificial intelligence or robotics, or via looking at accessibility and the way users engage with the tech, or the hardware route.”

After a final pause, she adds: “It’s the place really where I think the future is already happening.”

This article originally appeared in Raconteur’s Future CIO report in September 2021

Five ways to better manage supply chain disruption

The fallout from the pandemic exposed deep-rooted issues and a worrying lack of visibility, but these practical insights will help in case of future crises 

1. Don’t focus on cost alone

The countless stock delays and shortages over the past 18 months caused by a lack of preparedness and agility for the coronavirus-induced disruption have, for the first time in decades, called into question the running of lean supply chains designed to boost efficiencies and profits. They have laid bare a fragile and complex system that “has ultimately morphed into an investment plan focused on quick fixes and last-minute saves”, according to Patrick Van Hull, industry thought leader at Kinaxis, a global supply chain management company. 

Malcolm Harrison, group chief executive of the Chartered Institute of Procurement and Supply, agrees that many had seemingly dialled-up risk in the hunt for greater financial rewards. “Ensuring resilience and achieving value have always been the overarching objectives for procurement and supply professionals,” he says. “Focusing on cost alone is a risky strategy for any organisation. We’ve had decades of strong, lean and sometimes single-sourced supply chains working so efficiently that we hardly noticed them.”

The pandemic, he says, has encouraged supply chain managers to renew their focus on multi-supply strategies, local sourcing and best value in the supply chain, including working with competitors.

2. Invest in technology

Dirk Holbach, chief supply chain officer of laundry and home care at Henkel, says it was a tremendous advantage that his organisation was already far along its digital transformation journey before the pandemic. “The real-time visibility along our supply chain, which is a result of deploying Industry 4.0 technologies, allowed us to focus on the right challenges and to make the best decisions,” he says.

Van Hull points out that companies invested in digital transformation pre-pandemic were financially outperforming industry averages and surged further ahead of rivals over the past 18 months. “These types of results present a significant opportunity for supply chains, which historically have struggled with translating operational capabilities and digital transformation into financial success,” he says. 

3. Develop supplier relationships

While investment in technology is vital to increase supply chain resilience, old-fashioned human-to-human talking to solve problems is just as important when disruption inevitably strikes. Developing and nurturing supplier relationships accumulates mutual trust that can be cashed in when required, whether that buys favourable prices, shorter lead times or extra stock.

And, as the idiom suggests, a problem shared is a problem halved. “Embrace collaborative supply chain risk management,” urges Dr Alireza Shokri, associate professor in operations and supply chain management at Northumbria University. “Invest time in a collaborative culture, build trust and use these relationships to strengthen prevention and mitigation strategies.”

Shelley Harris, commercial director of IPP, which pools and provides pallets and boxes across Europe, agrees. “Our partner relationships are key, helping us to face new challenges as well as to work as efficiently and productively as possible,” she says.

The strength of its supplier relationships has allowed IPP to continue to fulfil its customer deliveries, despite the challenges the wider industry is facing, notably driver shortages. “We’re stronger because of long-standing relationships – we’ve seen a minimal impact on our operation and resulting service to our customers,” she says.

4. Improve transparency

The number-one way to manage disruption, according to Harrison, is a deep understanding of your supply chain and a focus on transparency. While this requires the right technology, as businesses have had to operate more efficiently in the digital space with more automation, it starts with understanding the different tiers of the supply chain. 

“Transparency across all tiers of the supply chain is a challenge,” he acknowledges, “but that visibility contributes to value in that it [helps to] remove fraud and corrupt practices and [helps businesses] look for signs of modern slavery among their suppliers.” 

Harrison stresses it is important to understand the robustness of different suppliers – and their suppliers. Transparency allows a business to identify potential problems, for example if a component is sourced from a single country or location and to track shipments.

This chimes with Van Hull’s thoughts. “Increased transparency is highly desirable for supply chains to sense disruptions as they are happening and respond immediately,” he says. “That is even more useful when it can be tied to financial outcomes, such as reduced inventory and cash buffers, improved capacity utilisation and lower cost resolution of demand-supply mismatches.”

5. Get the training right

Holbach believes training is imperative to maximise the potential of technology solutions. Empowering local teams and using their expert knowledge will strengthen the supply chain. They will flag potential issues early, giving the network a better idea of where to go for help with routing or stock if required. 

“We’ve had to react with agility during the pandemic and that was only possible by trusting our teams worldwide,” says Holbach. “It created the freedom to act fast, find the best solutions and keep our customers and consumers supplied with essential products.”

He believes a progressive approach to training starts from the top of an organisation. “As leaders, you should never stop learning,” he says. “To prepare for the unknown, you have to have the right mindset when confronted with new and difficult situations.”

Harrison echoes this insight, saying that supply chain professionals need to be equipped with the right skills and commercial judgement, which can only be achieved through training and development. This means being up to date, qualified, informed and skilled.

“What this pandemic has shown is that you need to invest in both technology and people to ensure supply chains are resilient, then we will manage better through the next global shock,” he says.

This article was first published in Raconteur’s Supply Chain Resilience report in September 2021

‘Just do it’: digital transformation lessons from Estonia

The Baltic state is a digital trailblazer, having made 99% of its public services available online. The government’s CIO, Siim Sikkut, offers his advice for businesses contemplating their own transformations

The smallest of the Baltic states by both area and population, Estonia has served as a political pawn in the hands of several neighbouring powers over the centuries. Since regaining its independence after the collapse of the Soviet Union 30 years ago, this republic has been punching massively above its weight in one respect: technological innovation.

In 2005, for instance, it was the first country to enable online voting. In 2012, it was the first to use blockchain technology for governance. By the time that Wired magazine named Estonia the “most advanced digital society in the world” in 2016, almost all public spaces in the country had been served by free Wi-Fi for a decade. Today, under the government’s so-called e-Estonia programme, 99% of government services are accessible online, while 70% of the country’s 1.3 million citizens regularly use digital ID cards. 

“We joke that our e-services are impossible only for marriages and divorces – you still have to leave the house for those,” says the man in charge of e-Estonia, Siim Sikkut, who has been the government’s CIO since 2017. 

He explains that the country desperately needed a technological “reboot” after gaining its freedom from the debilitating grip of Russian rule in 1991. With this in mind, the state committed itself to electronic governance – a decision that established a digital-first approach on which the country’s pioneering innovations have been based ever since. 

Sikkut, who also chairs the national task force on artificial intelligence, graduated from Princeton University with a degree in public and international affairs in the same year that online voting started. He initially joined the Ministry of Finance before becoming a digital policy adviser at the Ministry of Economic Affairs and Communications, when he co-founded Estonia’s ground-breaking e-residency scheme. Among other things, this offers entrepreneurs based anywhere in the world a digital ID granting them and their businesses remote access to markets in the EU.

Spearheading the world’s digital revolution

Sikkut, 38, is modest about the role he has played in creating what the e-Estonia website calls “an efficient, secure and transparent ecosystem”.

“I stand on many shoulders,” he says. “When I moved to my current role, it wasn’t a question of what to digitise next. All the low-hanging fruit had been picked. It has been about how to keep going to the next level of digitisation. We need to keep everything running while innovating and iterating.”

I hope that our experience in Estonia shows that it’s not rocket science. With commitment, anyone can achieve a digital transformation 

What might have been classed as a risky commitment to technology three decades ago has fostered a more progressive and open society, both online and offline, according to Sikkut. A Eurobarometer survey in 2018 found that 49% of Estonians trusted their government, compared with the EU-wide average of 34%, for instance. 

Indeed, it is said that in Estonia you are only two calls away from the prime minister – the implication being that people in this small country are community spirited and willing to help each other out.

Size matters: but trust trumps all

“It does help that there are few degrees of separation here,” Sikkut says. “With our small population, we get things done – both the connection and decision cycles are much shorter here than in other countries. But our talent pool is much smaller too, so our size is both a constraint and an opportunity.”

It’s no coincidence that the capital, Tallinn – where Sikkut lives with his wife and their three young children – is often referred to as Europe’s Silicon Valley. Estonia is estimated to have produced more start-ups per capita than any other European country in recent years. According to Startup Estonia’s online database, 1,104 enterprises have been established in the country since 2013 – including Uber rival Bolt and payment company Wise (TransferWise until it was renamed at the start of this year).

Any entrepreneur seeking to up the pace of their business’s digital transformation has much to learn from Estonia’s experience. Sikkut believes that strategic partnerships are key in this respect. He points to e-Estonia’s soon-to-be-launched digital testbed framework, a collaboration model that will offer free access to the government’s tech stack, on which any business worldwide can build new products or services and gain proofs of concept.

“I’d say to business leaders: ‘You have to be open for innovation and open to partnership,’ like we’re trying to be with our testbed framework. If someone comes to you with a good idea, take it on board, try it out and then perhaps you can move more quickly,” he says. “We’re looking to increase the speed of innovation in Estonia again by being open and encouraging experimentation with new ideas. The emergence of AI has been a game-changer, for instance, as we embark on this new stage of digitisation.”

Taking people with you

What other advice would Sikkut offer business leaders looking to introduce new digital tools and services? 

“If you build something that saves people time, money or effort and offers them value, they are likely to use it and refer it to others,” he says, adding that “you still might want to throw in incentives for people to start using them. For example, we offer much quicker tax reimbursements to those who complete their forms online rather than on paper.”

Sikkut stresses that it’s essential to spend an adequate amount on training people in how to use new digital tools. “We’ve invested in infrastructure and worked on skills to ensure that people can use our online services. You have to take care of your users so that you can bring them along with you,” he says.

His advice for any entrepreneur who may be approaching digital transformation with trepidation is to learn from his country’s success and stop dithering. 

“Just do it,” Sikkut says. “You’ll never have a perfect plan. Take an engineer’s attitude: try things out, fix them if they fail and try them again before scaling up your operations. I hope that our experience in Estonia shows that it’s not rocket science. With commitment, anyone can achieve a digital transformation. You don’t have to build everything from scratch. There are solutions that you can reuse and you can partner with people who’ve gone through it already – including us here in Estonia.” 

He continues: “The latest technology will probably not solve all your problems. What matters most is being open to possibilities and open to partnerships. If you give bright people a conducive environment, magic will happen.”

This article was first published in Raconteur’s Business Transformation report, published in June 2021

Mastercard cyber chief on using AI in the fight against fraud

Ajay Bhalla, Mastercard’s president of cyber and intelligence solutions, thinks innovations like AI can tackle cybercrime – and help save the planet

The fight against fraud has always been a messy business, but it’s especially grisly in the digital age. To keep ahead of the cybercriminals, investment in technology – particularly artificial intelligence – is paramount, says Ajay Bhalla, president of cyber and intelligence solutions at Mastercard. 

Since the opening salvo of the coronavirus crisis, cybercriminals have launched increasingly sophisticated attacks across a multitude of channels, taking advantage of heightened emotions and poor online security.

Some £1.26 billion was lost to financial fraud in the UK in 2020, according to UK Finance, a trade association, while there was a 43% year-on-year explosion in internet banking fraud losses. The banking industry managed to stop some £1.6 billion of fraud over the course of the year, equivalent to £6.73 in every £10 of attempted fraud.

If you don’t test things to break them, you can be sure their vulnerabilities will be discovered down the line

The landscape has rapidly evolved over the past year, says Bhalla, due to factors like the rapid growth of online shopping and the emergence of digital solutions in the banking sector and beyond. These changes have broken down the barriers to innovation, driving an unprecedented pace of change in the way we pay, bank and shop, says the executive, who’s responsible for deploying innovative technology to ensure the safety and security of 90 billion transactions every year. 

“Against that backdrop, cybercrime is a $5.2 trillion annual problem that must be met head-on. Standing still will mean effectively going backwards, as fraudsters are increasingly persistent, agile and well-funded.”

AI: the new electricity

It isn’t just the growing number of transactions that attracts criminal attention, but the diversity of opportunity, according to London-based Bhalla, who has held various roles at Mastercard around the world since 1993. 

“As the Internet of Things becomes ever more pervasive, so the size of the attack surface grows,” he says, noting that there will be 50 billion connected devices by 2025. 

Against this backdrop, AI will be essential to tackle cyber threats. 

“AI is fundamental to our work in areas such as identity and ecommerce, and we think of it as the new electricity, powering our society and driving forward progress,” says the 55-year-old.

Mastercard has pioneered the use of AI in banking through its worldwide network of R&D labs and AI innovation centres, and its AI-powered solutions have saved more than $30bn being lost to fraud over the past two years. 

In 2020, it opened an Intelligence and Cyber Centre in Vancouver, aimed at accelerating innovation in AI and IoT. The company filed at least 40 AI-related patent applications last year; it has developed the biggest cyber risk assessment capability on the planet, according to Bhalla. 

“We are constantly testing, adapting and improving algorithms to solve real-world challenges.”

Turning to examples of the company’s work, Bhalla says Mastercard has built an ability to trace and alert on financial crime across its network, a world first. He also points to the recently launched Enhanced Contactless, or ECOS, which leverages state-of-the-art security and privacy technology to make contactless payments resistant to attacks from quantum computers, using next-generation algorithms and cryptography. 

“With ECOS, contactless payments still happen in less than half a second, but they are three million times harder to break.”

Building security through biometrics


Such innovations are transforming customers’ interactions with financial services providers. For example, Mastercard has combined AI-powered technologies with physical biometrics – like face, fingerprint and palm – to identify legitimate account holders. These technologies recognise behavioural traits, like the way in which customers hold their phone or how fast they type, actions that can’t be replicated by fraudsters. 

“We see a future where biometrics don’t just authenticate a payment; they are the payment, with consumers simply waving to pay.”

Excited by developments in this area, Bhalla says Mastercard recently detected an attack that involved hundreds of devices attempting to log in from a phone that had reported itself as lying flat on its back. “Given the speed at which the credentials were typed, we knew it was unlikely it could be done with the phone flat on a surface,” Bhalla says. “In this way, a sophisticated attack that looked otherwise legitimate was detected before any fraud losses could occur.”

Cybercrime is a $5.2 trillion annual problem that must be met head-on. Standing still will mean effectively going backwards, as fraudsters are increasingly persistent, agile and well-funded

Mastercard might boast an impressive list of successful fraud-fighting solutions, but wrong turns are vital for the journey, Bhalla admits. “If you don’t test things to break them, you can be sure their vulnerabilities will be discovered down the line,” he says. “At Mastercard, trust in and reliance on our services is far too important to take that risk, so rigorously testing solutions before they get anywhere near the end user is our standard operating procedure.”

Trust is a must

A keen rower and golfer, Bhalla volunteers as an executive-in-residence at the University of Oxford’s Saïd Business School. He has a bachelor’s degree in commerce from Delhi University and a master’s degree in management from the University of Mumbai. 

Even with his experience and tech knowledge, Bhalla insists that Mastercard and others within the industry must go back to basics and focus on customer experience. The company’s leadership in standards has been core to earning and retaining the trust of its customers, he notes. 

The technology may be evolving quickly, but one core principle remains, says Bhalla. “Our business is based on trust, which is hard-won and easily lost.”

The correct operating processes and standards must be in place from the outset so that both customers and businesses can have confidence in the technology and trust that it will be useful, safe and secure. 

“What has changed is the sharp focus now placed on developing leading-edge solutions that prevent fraud and manage its impact, which is not surprising given that the average cost of a single data breach has now grown to $3.86 million,” Bhalla says.

Providing a blueprint for business leaders, Bhalla strongly believes that “innovation must be good for people … and address their needs at the fundamental design stage of the systems and solutions we create.”

“We see a future where biometrics don’t just authenticate a payment; they are the payment, with consumers simply waving to pay

Bhalla is using tech to fight fraud and drive financial inclusion, with Mastercard aiming  to connect 1 billion people globally to the digital economy by 2025. His ambitions are wider still, with much of his work focused on “protecting the world we have”. 

Mindful that climate change is high on the agenda, especially for younger generations, Mastercard has launched a raft of programmes in the area, including this year’s Sustainable Card Badge, which looks to identify cards made more sustainably from recyclable, recycled, bio-sourced, chlorine-free, degradable or ocean plastics.

Much like fighting fraud, global warming is reaching a crucial stage. Thanks to the efforts of industry leaders like Bhalla, the world stands a better chance of ultimate triumph on both fronts.

This article was originally written for Raconteur’s Fighting Fraud report, published in June 2021

The worrying rise of ransomware as a service

The Colonial cyberattack that cost a US fuel pipeline $4.4m in May highlights why businesses need to treat the fast-emerging threat of ‘ransomware as a service’ more seriously

A wry observation doing the rounds among cybersecurity experts is that the hackers who’ve transformed ransomware attacks into a multibillion-dollar industry are more professional than their high-profile corporate victims. 

It was certainly no laughing matter for the CEO of the Colonial Pipeline, one of the largest fuel-distribution networks in the US, when an attack in early May disabled the 5,500-mile system, triggering fuel shortages and panic-buying at filling stations. Within hours of the breach, Joseph Blount controversially paid a $4.4m (£3.1m) ransom to DarkSide, the Russian hacking group that mounted the attack, on the basis that it was “for the good of the country”. Despite this, the network was still out of action for a week.

The Colonial Pipeline case is one of many similar incidents, which have increased sharply in number since the pandemic started but have tended to go under the radar, as the victims are understandably reluctant to publicise their security failings. This high-profile example has exposed the rise of so-called ransomware as a service (RaaS), which DarkSide and various other professional hackers are now offering. 

Ethically speaking, you have to consider that you are enabling cybercrime by paying a ransom

The number of cybercrimes committed worldwide in 2020 was 69% higher than the previous year’s total. Ransomware was involved in 27% of these and a total of $1.4bn was demanded, according to a report published in May by US data security company Zscaler. In the UK, cybersecurity specialist Mimecast believes that as many as 60% of companies suffered a ransomware attack during the year. 

Ransomware is on the rise (Soumil Kumar from Pexels)

“Covid-19 has driven a huge ransomware surge,” reports Deepen Desai, Zscaler’s chief information security officer. “Our researchers witnessed a fivefold increase in such attacks starting in March 2020, when the World Health Organization declared the pandemic.”

Criminals seeking to exploit the network vulnerabilities created by the general shift to remote working during the Covid crisis either developed more sophisticated hacking methods or, seeking a shortcut, paid for RaaS. 

RaaS business model rings alarm bells

“RaaS has enabled even the least technically advanced criminals to launch attacks,” says George Papamargaritis, director of managed security services operations at Obrela Security Industries. “Gangs are advertising their services on the dark web, collaborating to share code, infrastructure, techniques and profits.” 

The RaaS model means that the spoils are split among three partners in crime: the programmer, the service provider and the attacker. “This is a highly structured and organised machine that operates much like many other legitimate organisations,” he adds.

The earliest reference to RaaS can be traced back to 2016. But, as Jen Ellis, vice-president of community and public affairs at Rapid7 and co-chair of the Ransomware Task Force, notes: “There are indications that it’s on the rise as more criminals take the chance to make a quick, easy and relatively risk-free profit by entering the ransomware market.”

This collaborative approach to ransomware attacks is terrible news for businesses, warns Ian Pratt, global head of security for personal systems at Hewlett-Packard. “Once, it was the preserve of opportunistic individuals who targeted consumers with demands of a few hundred pounds. Today, criminal gangs operating ransomware make millions from corporate victims in so-called big-game hunts,” he says. “This should have the alarm bells ringing in boardrooms.”

By educating themselves and their employees, business leaders can improve company-wide security protocols and so minimise the risk of ransomware attacks. Pratt explains that “users are the point of entry for most attacks”, accounting for 70% of successful network breaches. Malware is “almost always delivered via email attachments, web links and downloadable files”.

Prevention better than cure

Michiel Prins, co-founder of HackerOne, a vulnerability-disclosure platform connecting businesses with penetration testers, agrees. “Difficult as it may seem to prevent these attacks, prevention is always better than cure when it comes to ransomware,” he says. “This means maintaining a nimble and adversarial approach to cybersecurity that takes into account the perspective of an attacker, getting beyond traditional solutions that miss more elusive vulnerabilities.”

Prins argues that working with ethical hackers will “strengthen an organisation’s overall security posture”, as potential weak spots are reported and fixed “before serious damage is done”. Additionally, establishing a so-called bug-bounty programme, which rewards people for highlighting faults in the coding, “signals a high level of security maturity,” meaning that the criminals might look for easier prey.

If they do fall victim to an attack, should organisations accede to ransomware demands? CrowdStrike estimates that just over a quarter of victims end up paying the hackers to unlock their systems. Nearly 60% of UK businesses would enter negotiations, according to Sam Curry, chief security officer at Cybereason. 

Gangs are advertising their services on the dark web, collaborating to share code, infrastructure, techniques and profits

“We’d advise against paying ransoms. But in extreme situations, where lives are at risk or a national emergency is likely, it could be better to pay,” he says. “Before making that decision, it’s essential to notify your legal counsel, your insurer and the relevant law-enforcement agencies.”

Even when a business does cough up, there’s no guarantee that this will put an end to its problems. Peter Yapp, former deputy director at the UK’s National Cyber Security Centre and now a partner at law firm Schillings, cites the Travelex attack in December 2019 as an example. Many of the company’s web pages were still out of action two months later and a $2.3m ransom was eventually paid to the hackers. Later in 2020, Travelex sank into administration, “partly due to the losses and reputational damage caused by the attack”, he says.

Charles Brook, threat intelligence specialist at cybersecurity company Tessian, acknowledges that it’s a tough decision. “Ethically speaking, you have to consider that you are enabling cybercrime by paying a ransom,” he says. “But I can sympathise with organisations that may have no other option.”

There are other considerations, Brook adds. “If you pay, you could put a target on your back for further attacks. And, even after your files are decrypted, there may still be something malicious left behind.”

With the hackers in the ascendancy, Yapp believes that the government needs to step up its efforts to combat ransomware. “This has become such a serious problem that perhaps it’s time to lobby for the UK’s new National Cyber Force to fight back against these criminals in a different, military, way,” he suggests.

Perhaps the hackers won’t have the last laugh, after all.

This article was originally written for Raconteur’s Connected Business report, published as a supplement in The Times in June 2021

Is your business harnessing the power of conversational search?

The proliferation of smart devices and the improving capabilities of AI-powered voice assistants mean that voice search-ability is no longer a mere ‘nice to have’

Hey, Siri. Are marketers and their businesses investing enough time, money and effort in improving their conversational search rankings? 

Given that Juniper Research forecasts that consumers will be using voice assistants on more than 8.4 billion devices by 2024, while MarketsandMarkets predicts that the global conversational AI market will grow from £3.4bn in 2020 to £9.8bn in 2025, there’s a strong case that they should be doing more.

Consumers embrace new technology if it makes life simpler and more effortless for them. Otherwise, what’s the point?

Firms that have already invested in achieving higher voice search rankings are benefiting from it. For instance, translation service Lionbridge started optimising for voice search in July 2019. Twelve months later, it had almost 47 times more ‘featured snippets’ – the short text at the top of a page of Google search results. This improvement aided a 127% year-on-year increase in traffic to the firm’s website.

“Businesses should view optimising for conversational search as mandatory,” argues Olga Andrienko, head of global marketing at Semrush, which manages Lionbridge’s marketing analytics. “We have already seen the dramatic effect it can have on businesses’ search results. As voice assistants are further integrated into people’s everyday lives, this influence will grow.”

Nick McQuire, chief of enterprise research at tech consultancy CCS Insight, agrees. “As one of AI’s most important areas of development, conversational search is progressing rapidly,” he says.

Bringing AI to the masses

Conversational search development has accelerated “because it sits at the centre of two important trends”, McQuire suggests. First is the improvement in AI speech technology. Second is the need to improve information search in businesses. “This area”, he says, “is often listed as ‘broken’ by customers owing to information silos, especially across several data stores, documents and applications.”

McQuire continues: “The fact that all the big tech firms have started to tackle this area with products and tools demonstrates the scale of the customer need.”

Conversational search is a more complex matter than people simply using their voices instead of keyboards, though. For instance, on what smart device is the search being conducted – a screen-less Apple HomePod, a Google Nest Hub Max or an in-car Amazon Alexa?

While companies can pay to appear on the first page of a conventional typed search on a computer screen, mastering conversational search is not so straightforward. For one thing, marketers don’t always have the same real estate for advertising. 

If a device being used for voice search has no screen, how likely is it that a business will pull traffic to its website if it ranks outside the top three search results? Equally, if the device has a screen, a more visual response is presumably better. Notably, the average answer length for the three most popular voice assistants – Siri, Alexa and Google Assistant – is 23 words, according to Semrush.

Convenient and contextualised answers

Semantics aside, the crucial point for marketers is that consumers want their problems solved quickly. So says Kashif Naqshbandi, CMO at IT recruiter Tenth Revolution Group, who adds: “Most of the time they are not just looking for a ‘what’, but also a ‘how’ and ‘why’. This is why question-driven conversational search has spiked.”

Naqshbandi explains that few people are now searching online for, say, a “mountain bike” and then clicking through web pages of information. Instead, they are asking specific questions – for instance, “what sort of mountain bike should I buy?” – to seek a contextualised answer.

“Consumers are more accustomed to these fast, personalised interactions that help them cut through the digital noise and find a solution,” he says. “Marketers have to evolve to deliver interactive, dialogue-based experiences to stay competitive.”

Euan Matthews, director of AI and innovation at ContactEngine, a developer of conversational AI systems, agrees that people ultimately want to save time wherever possible and are happy to pay for convenience. 

“Consumers embrace new technology if it makes life simpler for them. Otherwise, what’s the point?” he says, attributing Amazon’s continuing ascendancy to the time it saves customers. But he adds that a “big pitfall” for marketers is to focus only on the search element.

To illustrate his point, Matthews says that some devices, when asked about the best local Indian restaurant, say, will now offer a follow-up option of booking a table through Google, and – if the user accepts – they will add this booking to the digital calendar. 

“This time saving is not because of the conversational search,” he says. “It’s more because that search has been seamlessly married with the ability to execute a transaction on your behalf. Marketers must consider how to marry conversational search and the transactional capability of the voice assistant, because this is what saves consumers time and makes it more likely that they’ll progress down the sales funnel.”

The direction of travel is clear, so marketers must alter their course accordingly. “We will see more advances in the ability for conversational search to end in a transaction – and this will drive uptake,” Matthews predicts. 

Will it ever replace keyed search? “I doubt it,” he says. “Some searches are best not voiced aloud.”

This article was originally published in Raconteur’s Future of Marketing and CX report in June 2021

Hyperautomation will revolutionise work – but what exactly is it?

Experts agree that the growing maturity of a cluster of technologies has transformative potential, but businesses must act fast if they’re to gain a competitive edge

Hyperautomation has been thrust into the spotlight for the second time in six months by Gartner. In October 2020, the research giant named it as one of its top strategic technology trends for 2021. Its latest report on the subject, published at the end of April, forecasts that the global market that enables hyperautomation will be worth almost £430bn in 2022 – a 24% increase on the previous year’s figure. 

“Hyperautomation has shifted from an option to a condition of survival,” says Fabrizio Biscotti, research vice-president at Gartner. 

But what is hyperautomation, why is it generating such interest now, and – most crucially – how can businesses best harness its potential? 

In essence, hyperautomation is a strategy that enterprises adopt to quickly identify, vet and automate as many processes as possible, applying a disciplined, holistic approach and mix of technologies. It spans the whole spectrum of operations, using digital tools to simplify many time-consuming tasks. These tools include AI systems, robotic process automation (RPA), low-code application platforms and virtual assistants. 

The concept is becoming increasingly relevant, Biscotti says, because organisations will “require more IT and business process automation as they are forced to accelerate their digital transformation plans in a post-Covid, digital-first world”. 

Gartner’s October 2020 report had noted: “Many organisations are supported by a patchwork of technologies that are not lean, optimised, connected, clean or explicit. At the same time, the acceleration of digital business requires efficiency, speed and democratization. Organisations that don’t focus on efficiency, efficacy and business agility will be left behind.”

Tackling low-hanging fruit

Peter van der Putten is director of AI solutions at cloud software firm Pegasystems and an assistant professor of AI at Leiden University in the Netherlands. He suggests that the drive towards hyperautomation has been “gathering pace for a while as the technologies have matured”. 

Their simultaneous emergence has created far-reaching possibilities. There is low-hanging fruit to be gobbled by business leaders, he says, although those who invest heavily in hyperautomation stand to gain the most from it.

“There is more to hyperautomation than streamlining workflows to save time and reduce cost,” van der Putten stresses. “There are strategies that businesses can use to link automation with business outcomes more directly. Realising the potential of hyperautomation hinges on robust governance and the quality of executive-level support – how it is implemented across an organisation and not in narrow niches.”

Hyperautomation will do to the knowledge worker what the industrial revolution did to the manual worker

For instance, the ability to manage exceptions through AI enables finance, IT and governance experts to deliver value for industries that already use new networks or decentralised cloud services. A recent global survey of 1,300 business leaders by Pegasystems identified key areas where hyperautomation has already been benefiting financial services providers. Respondents reported achieving quick wins in a number of functions, including finance, data management and production. They expect to see significant advances in areas such as supply chains and “partner ecosystems” over the next five years.

As an example of what’s possible with hyperautomation, take credit broker Loan.co.uk. The business, which has been building intelligent systems since 2014, has transformed mortgage lending from a process that’s traditionally been opaque, complex and painfully slow. The total automation improvements to date have “saved our 40 advisers and processors on average three hours and 45 minutes a day”, reports CEO Paul McGerrigan.

The company’s AI helper, Albot, can search thousands of lenders’ offers in less than a second while matching more than 10,000 criteria, delivering the lowest rate appropriate for the applicant’s circumstances. 

“Our smart AI underwriter can fully underwrite about 100 cases in 30 seconds, including credit searches,” McGerrigan says. “Previously, it would have taken an adviser 20 minutes to underwrite one complex case.” 

A workplace revolution

The company’s new approach has significantly increased transparency and, in turn, engendered greater trust among its customers. McGerrigan urges other companies to embrace hyperautomation, which, he says, “will do to the knowledge worker what the industrial revolution did to the manual worker. We are seeing the largest shift in how we work in 100 years. Most firms have been taken by surprise at the speed of change, while some are still asleep.”

Guy Kirkwood, chief evangelist at UiPath, an RPA software provider, agrees that the potential for hyperautomation is huge. “In the US alone, 2.6 trillion hours of work a year are automatable,” he says, noting that the pandemic-induced lockdowns have added impetus to the trend. 

“Work will be revolutionised,” Kirkwood predicts. “Almost over night, employees were expected to work from home, deal with unfavourable economic conditions and handle a huge rise in their workloads in areas such as customer service and data entry. Many turned to automation to adapt.”

He points to a firm providing smart infrastructure that used to print, sign, scan and upload 400,000 invoices a year manually. The business “now has a robot that performs these tasks digitally. This means that no employee needs to physically be in the office to process an invoice.”

Now that businesses have been catapulted into the digital age, regardless of their industry, we are on the verge of a new era of work in which hyperautomation will play a much greater role. Companies that make the leap today and go big on automation will be winners tomorrow. 

This article was originally published in Raconteur’s AI for Business report in May 2021

Trust is a must: why business leaders should embrace explainable AI

The EU’s proposed regulation on artificial intelligence has earned widespread praise. The prospect of harmonised rules presents an ideal opportunity for firms to improve transparency and reduce bias in their processes by investing in AI that’s easier for humans to understand 

The European Commission vice-president responsible for media and information matters, Margrethe Vestager, neatly summarised the founding philosophy of the EU draft legal framework on AI at the time of its publication in April. 

“Trust is a must,” she said. “The EU is spearheading the development of new global norms to make sure AI can be trusted. By setting the standards, we can pave the way to ethical technology worldwide.” 

Trust is a must (Anna Shvets from Pexels)

Any fast-moving technology is likely to create mistrust, but Vestager and her colleagues decreed that those in power should do more to tame AI, partly by using such systems more responsibly and being clearer about how these work. 

The landmark legislation – designed to “guarantee the safety and fundamental rights of people and businesses, while strengthening AI uptake, investment and innovation” – encourages firms to embrace so-called explainable AI.

If we want AI to play a role in decision-making, then we have a right to understand how the AI came to a decision, regardless of its complexity

Most business leaders have welcomed the initiative, understanding that the goal is to increase public trust in AI by promoting the use of more transparent systems. 

Peter van der Putten is director of AI solutions at cloud software firm Pegasystems and an assistant professor of AI at Leiden University in the Netherlands. He believes that the EU has produced a “sensible, risk-based framework” that distinguishes “prohibited, high-risk and low-risk” AI applications from each other.

“This is a significant step forward for both EU consumers and companies that want to reap the benefits of AI but in a truly responsible manner,” he says.

The end of ‘computer says no’ 

Given that many organisations are using opaque algorithms to make significant decisions – sometimes with disastrous results – the creation of a legal framework that would encourage them to adopt explainable AI is welcome. So says Matt Armstrong-Barnes, chief technologist at Hewlett Packard Enterprise. 

“If we want AI – constructed using complex mathematics – to play a role in decision-making, then we, as citizens, have a right to understand how the AI came to a decision, regardless of its complexity,” he argues. “Explainable AI can answer the fundamental question: why? Once we know this, the decision can be evaluated to ensure that it’s made without bias. ‘Computer says no’ is no longer acceptable or desirable.”

Pip White, MD of Google Cloud in the UK and Ireland, agrees. “Your ability to understand your AI and machine-learning models entirely is key to your ability to roll out the technology confidently, particularly in regulated industries where trust is critical,” she says. “It’s also paramount in helping to unpick bias and other gaps in data or models. Ultimately, the more informed you are about the ‘why’ of AI-driven decisions, the more useful and responsible your AI deployments will be.”

But not all experts believe that that the draft law, which proposes fines of up to 6% of a company’s global revenue for the most severe breaches, will have a sufficiently positive effect if enacted in its current form. 

By setting the standards, we can pave the way to ethical technology worldwide

“You have to admire the EU for arriving late to the party and telling everyone to turn the music down,” says Mark K Smith, founder and CEO of ContactEngine, a conversational AI company. “I agree that AI needs regulation, but a regulation that stifles innovation would be unhelpful and lead only to developments being encouraged elsewhere.”

A well-timed reset

Van der Putten, who stresses that AI was never intended to replace human intelligence, believes that the proposed law will serve as a “reset moment” for the technology and its proponents, because it will help to improve trust. 

The EU’s intervention is timely, concurs Joe Baguley, EMEA vice-president and chief technology officer at enterprise software firm VMware. A survey by his company at the start of this year found that only 43% of Britons trust AI.

“This absence of trust can be attributed to AI’s perceived lack of transparency, which must be a key consideration for business leaders,” Baguley says. “There is no doubt that AI has the potential to revolutionise the workplace and society, but the need for explainable AI will become more pressing, as fears about the technology remain high.”

He continues: “If developers themselves don’t know why and how AI is thinking, this creates a slippery slope, as algorithms keep becoming more complex. Offering the public more insight into how AI makes decisions will give them more confidence and, in turn, help them feel more secure about the organisations that use the technology.”

The legal implications for AI in other jurisdictions

Kasia Borowska, managing director of AI consultancy Brainpool, believes that the rest of the world needs to catch up with the EU in regulating the technology. 

“The next step needs to involve making these regulations international, because uneven laws between different blocs could have catastrophic consequences in the long term,” she warns. “International leaders should look at this urgently. We know that AI will give unparalleled advantages to those in less controlled countries.”

How should businesses in the UK respond to the lead that Brussels is taking? “Be more guide dog than guard dog,” advises Caroline Gorski, group director of R² Data Labs at Rolls-Royce. “Create your own simple framework that meets the EU requirements. Focus on defining what can be done rather than what can’t, then break it down into steps, with auditable standards for each step. Join them all up and create a procedure.”

Simon Bullmore, co-founder and CEO of data-literacy consultancy Mission Drive, suggests that firms seeking guidance on explainable AI should engage the Open Data Institute, the Alan Turing Institute and the Office for Artificial Intelligence.

He urges business leaders to treat the EU’s initiative as a chance to invest in explainable AI – and to educate both themselves and their employees in the technology. 

“Regulators step in when they lose trust in the market’s competence and desire to self-regulate,” Bullmore says. “Part of the challenge of using AI is the disconnect between what leaders know about AI and what their organisations are doing with it.” 

Now that the rules of the game are changing, it will be the proactive leaders that gain the competitive edge by going back to basics with AI. 

This article first appeared in Raconteur’s AI for Business report in May 2021

Could the pandemic have been predicted?

Governing in advance may seem like something from science fiction, but by using artificial intelligence and predictive analytics, experts say it’s possible

When the coronavirus pandemic hit UK businesses in the spring, forcing organisations to lock down, it required open minds to grasp technology and reimagine ways of working. Government and the public sector sought to solve challenges old and new, including rushing through essential financial support to companies and their furloughed staff, and improve service delivery and data-driven decision-making by dialling up investment in tech, especially artificial intelligence (AI).

After all, with predictive analytics, governments can conceivably prevent, rather than cure, issues or respond to citizens’ needs before they arise. But how far off are we from governing in advance? And what are the ethical implications of such a system?

Around the world, there are numerous narrow-scope use cases of authorities using predictive analytics to life-saving and life-enhancing effect. In Durham, North Carolina, the police department reported a 39 per cent drop in violent crime from 2007 to 2014 after using AI to observe patterns and interrelations in criminal activities and to identify hotspots, thus enabling quicker interventions.

Also in the United States, AI has helped reduce human trafficking by locating and rescuing thousands of victims. Knowing that approximately 75 per cent of child trafficking involves online advertisements, the Defense Advanced Research Projects Agency developed a platform using software that monitors suspicious online ads, detects code words, and infers connections between them and trafficking rings.

Further afield, the Indonesian government has partnered with a local tech startup to better predict natural disasters. By analysing historical flood data, collected from sensors, and accessing citizen-complaint data, prone areas can now be quickly identified, speeding up the emergency response and improving management.

Actionable intelligence and data scientists needed

In the UK, the public sector has much work to do, and requires people to do it, if governing in advance is to become a reality, says David Shrier, adviser to the European Parliament in the Centre for AI. “More investment in predictive analytics will help with risk mitigation, although this exacerbates the already extant shortage of data scientists who can develop and manage these models.”

Predicting trends through data analysis is vital for governments and has been for some time. “Forecasting approaches using historical data to build mathematical predictive models have been core to government economic policy for decades,” says Andrew Hood, chief executive of Edinburgh-headquartered analytics consultancy Lynchpin. “Whether those models allow governments to govern in advance effectively depends on to what extent they have enough political motivation and capital to apply the model outputs directly.

It’s too tempting to see predictive analytics as a magical answer, a black box that can solve all our challenges

“Arguably, there has been no shortage of predictive models kicking around as the pandemic took hold. However, the pandemic also points to the reality of a lot of prediction and forecasting: it is not about having one crystal ball to rely on, rather a set of predictions based on the best data to hand that need to be reviewed constantly, updated and critically applied.”

Hood stresses that skilled humans must remain in the driving seat and warns of the dangers of solely relying on technology to steer choices. “As with any application of predictive analytics,” he says, “it is the integration of those models within the context of governing and the processes of human decision-making that is the critical success factor.”

Public trust in AI must be won

Futurist Tom Cheesewright, whose job is to predict trends, posits that predictive analytics is “one subset of a wider array of foresight tools for scanning near and far horizons”. Should governments be making better use of such tools? “Absolutely,” he answers. “But I think it’s too tempting with predictive analytics to see this as a magical answer, a black box that can solve all our challenges. It’s not like Minority Report-style predictive justice. It’s about pulling policy levers in time to dodge obstacles or maximise opportunities.”

Echoing Hood’s advice, Cheesewright adds: “Foresight needs time and investment of cash and political capital, both of which are in short supply in our volatile, post-austerity era.”

Nick McQuire, of specialist technology market intelligence and advisory firm CCS Insight, says: “Historically, the public sector has been behind most sectors in terms of maturity in deploying and investing in AI,” but senses the purse strings are being loosened. “We are starting to see more AI applications in the public sector: chatbots, contact centre assistance and demand forecasting,” says the senior vice president and head of enterprise research.

AI has been excoriated in the UK media this year, though, making citizens and politicians wary of the tech and by extension predictive analytics. “Public confidence in AI is not high,” McQuire concedes. “To build trust in AI, organisations are now having to double-down on areas like data governance and security, privacy, explainability and ethics.”

It didn’t help that prime minister Boris Johnson, the most powerful politician in the UK, blamed the Ofqual exam-marking fiasco in August on “a mutant algorithm”, says Dr Jeni Tennison, vice president and chief strategy adviser at the Open Data Institute. “We have to recognise people are at the heart of designing algorithms; it’s not that algorithms go off and mutate on their own and we have no control over them,” she says. “We need to ensure there is a good end-to-end process that recognises the AI isn’t always going to get things right.”

Tennison, a fervent supporter of open data, believes those in the public sector must take care of how they deploy the technology. And, as such, predictive analytics, if applied, should be closely managed. “Algorithms that are used by the public sector have a much bigger impact on people’s lives. Government has a particular responsibility to make sure it uses AI and data well,” she says.

“Right now we’re operating from a position where people distrust the use of algorithms. The public sector has to be very proactive and win that trust.”

Given the public scepticism around AI, and the paucity of data scientists to make best use of predictive analytics, it seems we are some way off the UK governing in advance. Ethically, perhaps that is no bad thing.

This article was originally published in Raconteur’s Public Sector Technology report in December 2020

Fighting fraud in times of crisis

Cybercrime is always distressing for those affected, but when the resultant losses come from the public purse, it must be taken even more seriously

Coronavirus has coursed through every facet of our lives, and society and business have already paid a colossal price to restrict its flow. We will be counting the cost for years, if not decades. And while people have become almost anaesthetised to the enormous, unprecedented sums of support money administered by the government, it was still painful to learn, in October, that taxpayers could face losing up to £26 billion on COVID-19 loans, according to an alarming National Audit Office report.

Given the likely scale of abuse, it raises the question of how authorities should go about eliminating public sector fraud? Could artificial intelligence (AI) fraud detection be the answer?

Admittedly, the rapid deployment of financial-aid schemes, when the public sector was also dealing with a fundamental shift in service delivery, created opportunities for both abuse and risk of systematic error. Fraudsters have taken advantage of the coronavirus chaos. But their nefariousness is not limited to the public sector.

Ryan Olson, vice president of threat intelligence at American multinational cybersecurity organisation Palo Alto Networks, says COVID-19 triggered “the cybercrime gold rush of 2020”.

Indeed, the latest crime figures published at the end of October by the Office for National Statistics show that, in the 12 months to June, there were approximately 11.5 million offences in England and Wales. Some 51 per cent of them were made up of 4.3 million incidents of fraud and 1.6 million cybercrime events, a year-on-year jump of 65 per cent and 12 per cent respectively.

Cybercrime gold rush – counting the cost

Jim Gee, national head of forensic services at Crowe UK, a leading audit, tax, advisory and risk firm, says: “Even more worryingly, while the figures are for a 12-month period, a comparison with the previous quarterly figures shows this increase has occurred in the April-to-June period of 2020, the three months after the COVID-19 health and economic crisis hit. The size of the increase needed in a single quarter to result in a 65 per cent increase over the whole 12 months could mean actual increases of up to four times this percentage.”

In terms of eliminating public sector fraud, Mike Hampson, managing director at consultancy Bishopsgate Financial, fears an expensive game of catch-up. “Examples of misuse have increased over the last few months,” he says. “These include fraudulent support-loan claims and creative scams such as criminals taking out bounce-back loans in the name of car dealerships, in an attempt to buy high-end sports cars.”

AI fraud detection and machine-learning algorithms should be put in the driving seat to pump the brakes on iniquitous activity, he argues. “AI can certainly assist in carrying out basic checks and flagging the most likely fraud cases for a human to review,” Hampson adds.

John Whittingdale, media and data minister, concedes that the government “needs to adapt and respond better”, but says AI and machine-learning are now deemed critical to eliminating public sector fraud. “As technology advances, it can be used for ill, but at the same time we can adapt new technology to meet that threat,” he says. “AI has a very important part to play.”

Teaming up with technology leaders

Technology is already vital in eliminating public sector fraud at the highest level. In March, the Cabinet Office rolled out Spotlight, the government grants automated due-diligence tool built on a Salesforce platform. Ivana Gordon, head of the government grants management function COVID-19 response at the Cabinet Office, says Spotlight “speeds up initial checks by processing thousands of applications in minutes, replacing manual analysis that, typically, can take at least two hours per application”. The tool draws on open datasets from Companies House, the Charity Commission and 360Giving, plus government databases that are not available to the public.

“Spotlight has proven robust and reliable,” says Gordon, “supporting hundreds of local authorities and departments to administer COVID-19 funds quickly and efficiently. To date Spotlight has identified around 2 per cent of payment irregularities, enabling grant awards to be investigated and payments halted to those who are not eligible.”

We need to watch how the technology fits into the whole process. AI doesn’t get things right 100 per cent of the time

She adds that Spotlight is one of a suite of countermeasure tools, including AI fraud detection, developed with technology companies, and trialled and implemented across the public sector to help detect and prevent abuse and error.

Besides, critics shouldn’t be too hard on the public sector, argues David Shrier, adviser to the European Parliament in the Centre for AI, because it was “understandably dealing with higher priorities, like human life, which may have distracted somewhat from cybercrime prevention”. He believes that were it not for the continued investment in the National Cyber Security Centre (NCSC), the cost of fraudulent activity would have been significantly higher.

Work to be done to prevent fraud

Greg Day, vice president and chief security officer, Europe, Middle East and Africa, at Palo Alto Networks, who sits on Europol’s cybersecurity advisory board, agrees. Day points to the success of the government’s Cyber Essentials digital toolkit. He thinks, however, that the NCSC must “further specialise, tailor its support and advice, and strengthen its role as a bridge into information both from the government, but also trusted third parties, because cyber is such an evolving space”.

The public sector has much more to do in combating cybercrime and fraud prevention on three fronts, says Peter Yapp, who was deputy director of incident management at the NCSC up to last November. It must encourage more reporting, make life difficult for criminals by upping investment in AI fraud detection and reallocate investigative resources from physical to online crime, he says.

Yapp, who now leads law firm Schillings’ cyber and information security team, says a good example of an initiative that has reduced opportunity for UK public sector fraud is the NCSC’s Mail Check, which monitors 11,417 domains classed as public sector. “This is used to set up and maintain good domain-based message authentication, reporting and conformance (DMARC), making email spoofing much harder,” he says. Organisations that deploy DMARC can ensure criminals do not successfully use their email addresses as part of their campaigns.”

While such guidance is welcome, there are potential problems with embracing tech to solve the challenge of eliminating public sector fraud, warns Dr Jeni Tennison, vice president and chief strategy adviser at the Open Data Institute. If unchecked, AI fraud detection could be blocking people and businesses that are applying for loans in good faith, or worse, she says.

“We need to watch out how the technology and AI fit into the whole process,” says Tennison. “As we have seen this year, with the Ofqual exam farrago, AI doesn’t get things right 100 per cent of the time. If you assume it is perfect, then when it doesn’t work, it will have a very negative impact on the people who are wrongly accused or badly affected to the extent they, and others, are fearful of using public sector services.”

There are certainly risks with blindly following any technology, concurs Nick McQuire, senior vice president and head of enterprise research at CCS Insight. But the public sector simply must arm itself with AI or the cost to the taxpayer will be, ultimately, even more significant. “Given the scale of the security challenge, particularly for cash-strapped public sector organisations that lack the resources and skills to keep up with the current threat environment, AI, warts and all, is going to become a crucial tool in driving automation into this environment to help their security teams cope.”

This article was originally published in Raconteur’s Public Sector Technology report in December 2020

Taking a peek at the new retail calendar

What happens to Black Friday when customers can’t jostle in the aisles? Or Christmas shopping season when we can’t hit the high street? Experts think these dates will become part of a whole new online retail calendar

Will it be a happy Christmas for UK retailers? After the coronavirus pandemic squeezing the life out of the high street, they certainly deserve some cheer. Data shows their fortunes could be resurrected by ecommerce. But given the shift to online, and the evolution of shopping habits, what does it mean for the traditional retail calendar?

New data from Adobe indicates activity around key retail dates will begin earlier, and peak retail occasions will be higher and more prolonged. According to the software giant’s international president Paul Robson, online holiday sales will “shatter all previous records”.

This is supported by Adobe’s projections that, in America alone, Black Friday will generate $10 billion (£7.5 billion) in online sales. “That’s a 39 per cent year-on-year increase,” says Robson. “Cyber Monday will remain the biggest online shopping day of the year,” he continues, adding that $12.7 billion (£9.6 billion) is expected to be spent in the United States, up 35 per cent on last year.

Robson says: “Our research into the online shopping habits of UK consumers during lockdown found that while they were up to four times more likely to buy from marketplaces like Amazon, it’s not always at the expense of smaller independent retailers. Where marketplaces may have the edge when it comes to convenience and speed, shoppers have also shown they are keen to support local, independent retailers where they can.

“The extended shopping period, coupled with the ability of independent retailers to deliver great, personalised digital experiences, could see them have a happier Christmas period than many might expect.”

Looking beyond traditional retail peaks

Google data also implies the retail calendar needs updating. “As a direct result of COVID-19, we have witnessed heightened search queries for online retail this year that will lead to a new baseline for Black Friday,” says Becky Power, director of consumer retail and technology at Google UK. “Google searches for ‘early Black Friday deals’ were up by 150 per cent versus November 2019.” Further, Google searches for “Christmas shopping” are up 1,800 per cent compared to the same period last year.

“The message is clear: consumers are looking beyond traditional peaks in the retail calendar as they continue to enjoy the flexibility of browsing online,” says Power, who points out that Enders research estimates there will be an additional £4.5 billion-worth of online sales in 2020.

Retail owners must keep pace with customer expectations and arm themselves with technology that enables multi-channel personalisation and improves data analysis. “Given that a continually growing number of consumers are already shopping online for traditional peaks, retailers will have to adapt to be ready for this rise in demand,” says Power. “Digital tools are imperative for applying product promotions easily and quickly, boosting retailers’ visibility to new customers, and can uncover meaningful insights from their performance.”

Kyle Harbinson, of global technology consultants REPL Group, agrees. “To reduce the impact of the troughs, retailers need to connect with and understand the circumstances of their customers, in a dynamically changing environment,” the consulting partner says. “We are in uncharted territory, so retailers need to pivot from instinct-driven decision-making to a data-driven culture.”

Taking steps to bolster the online offering

Warnings are being heeded. Capgemini’s annual Holiday Shopping Survey reports that while more than a third (36 per cent) of UK retailers expect an increase in holiday sales compared to previous years, 91 per cent have taken deliberate steps to bolster their online offering. Almost half (47 per cent) have improved their ecommerce propositions and 52 per cent will offer more generous discounts both online and in-store.

The benefit ecommerce brings allows you to create and build your own peak retail event

However, Dr Rajesh Bhargave, associate professor of marketing at Imperial College Business School, cautions that one issue retailers will face post-COVID-19 is the dilemma of “sticky prices”. “Consumers tend to remember what they would have paid previously for a product, so would view price increases as unjust in poor economic conditions,” he says. “Similarly, cutting prices would erode pricing power.”

No retailers should be discouraged from embracing ecommerce, however, stresses author and business consultant Erica Wolfe-Murray. “The hype surrounding traditional retail peak days has a halo effect across the board whether you are actively marketing or not,” she says. “But the benefit ecommerce brings allows you to create and build your own peak retail event. Think ‘Founder’s Day’, ‘Dress-Up Day’, or whatever.”

Embracing technology is business-critical

Technology can also help with the morphing of traditional peak retail periods, from dealing with stock management and the supply chain, to predicting when more staff might be required. Or with improving the delivery process, posits Mike Hancox, chief executive of UK couriers Yodel. “The five months stretching from November to the end of March have long been the busiest period for those in logistics as they encompass retail’s traditional peaks of Black Friday, Christmas, Valentine’s Day and Mother’s Day,” he says.

“This year we’re expecting Christmas to be higher in intensity and longer in duration than previous years, but a greater increase in overall volumes means the fluctuations seen in previous years could be less pronounced in the future.”

Yodel has developed a parcel-scanning app to streamline the delivery process. “It gives more flexibility to the growing numbers of self-employed couriers out on the road who can download the app on their own devices rather than having to get up to speed with a handheld terminal.”

Striving to reduce touchpoints and frictions through tech is now business critical, argues Professor Laurent Muzellec, founder and director of Trinity Centre for Digital Business. “Big digital players such as Netflix, Amazon and Apple use artificial intelligence to produce an effortless experience; this should be a source of inspiration for all retailers,” he says.

Retailers that act on this advice and tailor their offerings, both online and offline, look set to have a happy Christmas and beyond.

This article was originally published in Raconteur’s Future of Retail report in November 2020

Should you bother with real-time data?

Real-time insights are essential to adapt to a changing consumer landscape, but companies that ignore trust and transparency as part of the process are risking it all


The advice that “trust takes years to build, seconds to break and forever to repair” is attributed to an anonymous sage, which is good news for the sage because the dearth of real-time data means they’ll escape an endless stream of personalised ads.

But it’s wisdom that brands would do well to heed. Now more than ever, given that consumer trust is so difficult to earn and easy to lose, and organisations are becoming increasingly reliant on customer data to manage sales.

The Edelman Trust Barometer Special Report, published in late-June, found that, after price, the most critical factor in a customer’s purchasing decision is trust. “If trust is a key consideration for consumers, it must be a key consideration for brands,” says Henk Campher, vice president of corporate marketing at social media management platform Hootsuite.

However, consumer trust has been eroded in the last six months if engagement from brands has been lacking, or tone deaf, according to new Pegasystems research, which reveals the extent of damage the coronavirus pandemic has caused for businesses’ relationships with their customers.

More than a third (36 per cent) of respondents say they lost existing customers during the pandemic due to failings in their communications. And a similar number (37 per cent) admit to communicating at least one message that was poorly received and dented brand reputation.

It’s not easy for brands, though. The January State of the Connected Customer report from Salesforce highlights a rise in consumer expectations, while stressing four in five consumers won’t buy from companies they don’t trust.

Timing is key to real-time data success

The research shows almost three quarters (73 per cent) of customers think companies should understand their needs and 78 per cent expect consistent interactions across departments. And to make that work, real-time data is required.

“Brands that deliver connected, multichannel and personalised experiences will earn consumers’ trust,” says Adam Spearing, Salesforce chief technology officer for Europe, Middle East and Africa.

Personalisation perhaps feeds from trust as much as it drives it

“Having a 360-degree customer view is crucial for enabling brands to have more personal and contextually aware interactions with customers. For retailers, this may be understanding the most appropriate time to offer customers in-store or online discounts. Whereas manufacturers can get ahead of demand based on what customers usually order at a specific time of the year, based on decades of data intelligence.”

And if companies can use real-time data to communicate with customers at particular times, and it feels sincere and authentic, then brownie points will be won. “Brands can build trust through meaningful interactions with their customers, anticipating their needs and delighting them,” says Spearing. As an example, he lauds Premier League football clubs that send personalised messages from star players to supporters on their birthdays.

Personalisation is a risky business

“The more valuable an interaction is for a customer, the more inclined they will be to continue to trust a brand to use their data appropriately,” he says, though warning there is “a fine line” to walk. “Only if brands use the data respectfully will they gain that trust.”

Andrew Hood, chief executive of data analytics consultancy Lynchpin, is equally ambivalent. “Personalisation perhaps feeds from trust as much as it drives it,” he says. “While I might be happier to share my data if I receive a better, more relevant experience in return, if I don’t trust you as a brand with my data in the first place, I might not feel confident enough to make the first move.”

M&C Saatchi’s senior art director Tom Kennedy is treading carefully and acknowledges the risk that comes with data-driven personalisation. “In January, Aviva addressed its whole email base as ‘Michael’, proving that with even the most basic data, mistakes can happen,” he says. “The assumptions, errors and insults will be amplified with each step more personal.”

Increased awareness of data privacy

Hunting for real-time data can be viewed as insidious and creepy, and there are many instances where organisations crossed the line. Cassandra Moons, data privacy officer at navigation technology firm TomTom, recalls how in 2012 American retailer Target supposedly worked out a teenager was pregnant before her parents through data mining. “Knowing intimate details about your customer that they have never told you can make people very uncomfortable,” she says.

More recently, consumer trust has been chipped away by serious data breaches. “Using data to personalise communications could be the tool that destroys people’s trust in advertising if not used smartly and respectfully,” says Megan Jones, senior planner at R/GA London. She points out that record numbers of people are using internet ad blockers and search engines protecting privacy, such as DuckDuckGo.

“This shift is symptomatic of greater public understanding around data due to Cambridge Analytica’s influence in the Vote Leave Brexit campaign, as well as greater awareness of data privacy through the launch of the General Data Protection Regulation two years ago,” says Jones.

Trust second only to price

Don’t rely too heavily on personalisation

Because customers arguably cherish personal data more than before, she questions a market strategy founded on real-time data. “Almost a decade ago, easyJet stopped investing in Google search terms and moved that budget into more traditional media to deliver phenomenal results. The company saved £6 million a year and there was a 95 per cent rise in seat sales,” says Jones.

“Similarly, last year adidas’ econometric analysis showed they’d been relying on ‘personalised’ communications too heavily as it was the broad brand-building communication that got them the majority – around 65 per cent – of their sales. And let’s not forget that Amazon, hailed as an exemplary data company, was the fifth-highest investor in traditional media in the UK in 2019, with a spend of £114 million, £26 million more than the year before.”

Lynchpin’s Hood concludes: “Ultimately, privacy and personalisation, using real-time data, go hand in hand. And brands that are transparent with the former are more likely to be able to deliver on the latter effectively to their, and their customers’, benefit.”

This article was originally published in Raconteur’s Future Customer report in September 2020

Grounding sci-fi ambitions in reality

Ridley Scott’s 1982 cult film Blade Runner, based on Philip K. Dick’s science-fiction classic Do Androids Dream of Electric Sheep?, came of age five months ago: its dystopian futurescape was Los Angeles ablaze in November 2019.

While some elements accurately hit today’s world, now stricken by the coronavirus pandemic, the planet is dangerously warm and computers can be commanded by a human voice for instance, other predictions fall short. High-collar, full-length trench coats are unfashionable, flying cars have failed to take off and, most pertinently, so-called ‘general’ artificial intelligence (AI) does not exist.

UK AI businesses

Sci-fi is increasingly becoming sci-fact, admittedly, but a technology that can replicate a range of highly advanced human characteristics – the basic definition of general AI – does not walk among us, yet. Moreover, the so-called singularity, when machines achieve sentience and technological growth becomes uncontrollable and irreversible, is some distance away, most experts say.

“Think of general AI as HAL from 2001: A Space Odyssey, or Skynet in the Terminator series,” suggests Bernd Greifeneder, founder and chief technology officer of leading automated-software organisation Dynatrace. “We’re currently nowhere near that becoming a reality, with estimates ranging from it being five years to a century away. Some even believe we’ll never see general AI step out of sci-fi and into the real world.”

Arguably that conclusion is good for the longevity of the human race, though not everyone agrees. “Unless humanity takes a wrong turn, general AI is likely to arrive around 2050, perhaps sooner,” says David Wood, chair of London Futurists. “General AI, handled wisely, can enable humanity to enter a profound new era that I call ‘sustainable superabundance’, in which we can transcend many of the cruel limitations of the human condition that we have inherited from our evolutionary background.”

Gorilla warfare in the technological jungle

Wael Elrifai, global vice president of solution engineering at Hitachi Vantara, pleads for greater caution. “When we achieve general AI, it will drastically transform our economy and society in ways we can’t even predict,” he says. “We’ll be faced with what Dr Stuart Russell, a pre-eminent thinker in the field, dubs ‘the gorilla problem’. Namely, human beings will be outmoded by machines in the same way we evolved to dominate our gorilla kin.

“Finding our place in that future isn’t a decision that can be left in the hands of a few. Technologists, educators, psychologists, policymakers and testing experts must put their heads together to consider how we measure human capital, improve human performance and ensure equity in a world where machine intelligence surpasses human capabilities.”

For the moment, though, narrow AI, which is programmed by humans to focus on a niche task, will have to suffice. The hype around AI has calmed recently, in part because business leaders have realised it is neither akin to the general AI of Blade Runner or Terminator nor a silver bullet. Narrow AI, however, is potent if pointed the right way; those who work out what direction to aim at will triumph.

Besides, as Dr Iain Brown, head of data science at SAS in the UK and Ireland, posits: “The machines have already taken over, to some extent, and with little resistance.” Our smartphones, smart speakers and driverless cars all rely on AI. “Self-learning machines are embedded in services or devices used by three quarters of global consumers,” says Brown, “and algorithms choose what news we read and the entertainment we consume.”

Canny members of the C-suite are beginning to realise the true potential of narrow AI. “General AI isn’t a pipe dream, but it is irrelevant,” says leading futurist Tom Cheesewright. “Focusing on it as a business leader is like seeing the wheel for the first time and spending your time dreaming about a Tesla. Make use of the wheel.”

AI adoption challenges

Targeting niche tasks with narrow AI

Indeed, according to Microsoft’s Accelerating Competitive Advantage with AI report, published in October, businesses in the UK already using AI at scale are performing 11.5 per cent better than those who are not, up from 5 per cent in 2018. Further, the study calculates the number of UK companies with an AI strategy has more than doubled, from 11 per cent two years ago to 24 per cent in 2019. The report also finds that more than half of organisations in the UK (56 per cent) are using AI to some extent, including a rise of 11 per cent in machine-learning from the previous year.

“Narrow AI is certainly a more rewarding prospect for businesses in the short term, as it has more specific applications and so can help to overcome the clearly defined challenges that exist today,” says Greifeneder. “It’s also easier to manage the risks and ethical implications associated with it.” As an example of granting too much autonomy to a machine, he points to Microsoft’s infamous AI chatbot Tay, which began tweeting racist and inflammatory remarks in March 2016, after just 24 hours of exposure to users on Twitter. And, like any tool, AI can be used for good or bad.

Focusing on general AI as a leader is like seeing the wheel for the first time and spending your time dreaming about a Tesla. Make use of the wheel

“We don’t need to wait for general AI to experience elements of AI utopia or dystopia,” says Peter van der Putten, assistant professor of AI at Leiden University in the Netherlands and director of decisioning solutions for cloud software company Pegasystems. “AI is used successfully to understand the structure and function of COVID-19 and to mine COVID-19 research articles. But bias has been creeping into models to determine credit card limits, decide who needs to await a court case in jail or who gets selected for preventive care programmes.”

Why general AI and man must work together

There may be justified concerns about algorithmic biases, how the associated technologies might develop and AI displacing human jobs. But it is critical for business leaders to understand what AI can achieve and it’s certainly not for every organisation.

“If you don’t understand what you are trying to solve first, you are carrying a hammer looking for a nail and AI is going to be of no real use,” says Nick Wise, chief executive of OceanMind, a not-for-profit organisation using AI to protect the world’s fisheries.

For now, the realm of sentient computers seems a long way off. And if we humans are prudent, if or perhaps when general AI becomes a reality, man and machine will augment one another. As Brown concludes: “The future belongs to the cyborg: humans working hand in glove with AI, rather than the android alone.”

This article was originally published in Raconteur’s AI for Business report in April 2020