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The European Data Leaders Making AI-Led Innovation a Reality

CDAO Europe 2020 highlighted the visionary leaders from companies including BT, Opel Vauxhall, Three and WPP who are paving the way for a new era of AI-led business innovation

The past 12 months have been transformative for European data and analytics. COVID-19 woke many businesses up to the necessity of being data-centric. But it also prompted some data leaders to look again the core assumptions behind their strategies.

“We managed to convince executives that data is a must,” explains Lukasz Kozielski, Transformation Lead Business Intelligence and Analytics at Opel Vauxhall Finance. “It’s not a competitive advantage anymore.”

“It happened during the corona crisis, when everything sped up,” he continues. “With Tableau and other technologies, we were able to answer questions in real-time.”

“There was [historically] a conception that, once you have a lot of data, you can answer all questions,” adds ZestMoney CDO Natalia Lyarskoya. “With the recent COVID-19 situation, many companies, especially in the financial sector, realized that’s the wrong strategy.”

Of course, neither of these realizations will surprise the most forward-thinking minds in data and analytics. In fact, some of the expert speakers at this month’s CDAO Europe 2020 virtual conference have been preparing their organizations for a new era of AI-led innovation for years.

What BT Learned from Two Decades of AI Innovation

It may surprise some to learn that BT has the UK’s largest AI patent portfolio. But given that the telecoms giant has been developing AI tools for more than 20 years, it stands to reason.

As BT Head of AI and Data Science Detlef Nauck says, the firm has picked up a thing or two about delivering successful AI projects in that time.

“AI is different from standard software of automation projects, because it’s based on data,” he says. “So, you need to make sure you have high-quality data available. This is where you start.”

“When you then have something that works, the [next] challenge is, ‘Does it scale in operation?’” he continues. “Getting data out of your systems [and] training something up is easy. But making sure it runs in operation is another challenge.”

“The other thing you need to prepare for is the ‘hooks’ into your operations,” he concludes. “You have to have ‘hooks’ back into your operation to actually execute something automatically that has been done manually before.”

To illustrate these ideas, Nauck gives the example of using natural language processing to develop a chatbot for customers.

A chatbot like this will only work if it has access to natural language data that can be used to train the AI to identify the context and intension behind customer queries and surface the information they need.

Then, the responses it gives must gel with the company’s existing business processes, automating simple tasks while handing ones that require a human touch seamlessly over to a customer services agent.

What’s Driving Opel Vauxhall and Three’s AI Transformations

Just like people, companies only change if they want to or have to. Getting stakeholders outside the data and analytics team to adopt new, data-driven practices has been a key challenge for data-focused executives at legacy organizations for many years.

But as Kozielski says, COVID-19 has been a wakeup call for executives that were previously ‘data laggards’. This in turn has provided data leaders with a fresh mandate to accelerate key initiatives.

He recalls: “When COVID-19 started, executives started to ask questions about delinquencies. So, ‘Which customers don’t pay?’”

“We started our journey with Tableau and, actually, it was spot on, because at that point, we could answer executives’ questions right away,” he adds: “They saw the benefit and they imposed that change on employees.”

Of course, winning company-wide support for this kind of change is important to ensure these initiatives lead to real business transformation. As such, Three CDO Gillian Tomlinson has adopted a two-pronged approach to influencing employees to adopt data-driven tools.

“It’s [about ensuring] they don’t feel that technology is being done ‘to’ them,” she says. “They’ve got to be involved in the project upfront.”

“Being a data-driven business [means] using datapoints upfront as well,” she adds. “So, do you have KPI measurements from an ‘outcomes’ perspective that you’re tracking and measuring?”

Bringing staff along on a data-driven transformation is about setting expectations and developing strong relationships. But it’s also important to deliver projects that feed into a ‘big picture’ plan for the future. That’s why Three’s data strategy is divided into ‘short-term’ and ‘long-term’ strands.

She concludes: “On that basis, we’re able to consistently prioritize and understand where the biggest value is, whether that’s activities that are protecting revenue, increasing revenue or reducing costs.”

A WPP Leader’s Vision for a Data-Led Future

The global data landscape today is radically different from how it was 10 years ago, and it will have transformed again by 2030. Given the pace of innovation in the market today, forward-thinking data leaders are already thinking about what the next big shift will mean for their AI and analytics strategies.

“Data volumes are going to skyrocket,” predicts Di Mayze, Global Head of Data and AI at advertising giant WPP. “As a consequence of this, companies will stop hosting their own data. They will think about hosting less data.”

As the amount of data organizations capture continues to rise, Mayze believes companies will reevaluate what data they really need. Storing customer data to create personalized customer experiences may be reserved for people in high-value audience segments.

“Companies will start to look at how much it costs to maintain customer records and whether it’s worth it,” she predicts. “The customer may always be right. But they’re not necessarily equal, and they’re not equally valuable.”

At the same time, Mayze thinks new technologies will automate many aspects of data cleaning, transformation and integration. As a result, data scientists will be free to focus on driving business value and a new class of professional data storytellers will emerge.

“These people will really think creatively on how to story-tell, how to bring data to life, how to bring it to every part of every role,” she says. “It will be like digital is, now. You don’t really shout out that something’s digital, because everything is.”

To prepare for this future, WPP is scaling up its analytics university to provide thousands of its staff members with enhanced data fluency and skills.

“Everybody recognizes with our training programs that there’s something in there for everybody,” Mayze concludes. “We’re just wanting to make sure that WPP and its clients are all well-protected.”

European data and analytics has come a long way in recent years. But stories like these show that the region’s data-led transformation is far from over. If anything, the pace of innovation could be accelerating.

The investments innovative data leaders at WPP, Three, Opel Vauxhall and BT highlighted at CDAO Europe 2020 should be a shining example to other data-focused leaders as they plan for the years ahead.


To discover even more insights from the industry leaders who spoke at CDAO Europe 2020, register to view the on-demand sessions here.