Europe’s Top Data Innovators Discuss the Challenges They’re Facing in 2022
Six of our 2022 Global Top 100 Innovators in Data and Analytics share some of the biggest challenges they are facing today in this recent panel discussion
Securing executive support, optimizing data governance processes and scaling AI initiatives are among the top challenges facing the European executives in our 2022 Top 100 Innovators in Data and Analytics list.
Six of the European data and analytics leaders named in this year’s list discussed these challenges and more in a recent virtual discussion we held to celebrate their achievements.
Securing Executive Support Remains a Priority
Convincing decision makers about the importance of data is still one of the biggest obstacles that many data-focused executives face, according to Sameer Rahman, CEO and Founder at DataMonet.
“The challenge for us in the data community is getting data in the boardroom,” he said. “Everybody understands that data is important, but nobody understands how data can give them commercial and distinct competitive advantage, which is why the data community has lagged behind other communities in getting to the boardroom.
“We as business leaders have to have that conversation, a very commercial conversation, that illustrates the importance of data in the boardroom. How data at the very highest level can develop businesses, not just optimize marketing, but genuinely develop businesses.”
Ross Simson, Global Chief Data Officer at environmental charity CDP, agreed. He said this was often because leaders were guilty of overcomplicating things when explaining the benefits of data. He added that one thing which helped when he gave a presentation to the board at Thames Water was to use Lego to demonstrate the points he was making visually.
“The challenge that we face isn’t as a function,” he said. “It’s that we make [data] very complex and we don’t simplify it.”
Enterprises Must Improve Data Governance Processes
One of the key issues raised during the live LinkedIn webinar was the need to automate processes and improve efficiency while still ensuring data governance is maintained.
As Jean Perez, Director of Data and Analytics at Collinson – Valuedynamx, put it: “Even though I’m banging on at every single meeting about data governance, it always becomes second on the list of priorities and I actually never get to it.”
The problem, she said, was carving out the time and putting the processes in place to ensure data governance is always given the proper consideration.
“We’ve moved from having two to three scheduled releases a month to two a week,” Perez said. “Having two releases a week and managing governance has become a challenge.
“It’s about trying to tackle it and put more automation into the process. It’s about what we can establish in a way that is less resource-intensive that will help us achieve that governance throughout and keep the agile environment.”
Balancing Personalization with Data Privacy
Delivering customer insights to fuel customer experience personalization initiatives is a priority for many data-focused executives. But for businesses operating in regions with relatively robust data privacy laws, executives must ensure they do this in a way that respects consumers’ rights.
“Data privacy is top of mind for me”, said Harvinder Atwal, Chief Data Scientist at price comparison specialist MoneySuperMarket Group. “There’s this paradox where customers want you to use their data to help them, but equally they want their data to be as private as possible.
“With the changes happening on the web with the death of things like third-party cookies and tracking, it is about how we earn the trust of users and show them that we are using their data in a very responsible way.
“Obviously we are a price comparison website and, since our mission is to help our customers save money, the more data they give us, the more we can help them do that.”
Scaling AI Projects will be a Key Focus for 2022
Our 2022 ‘top 100’ data innovators have enjoyed a great deal of success with AI over the past 12-24 months. But in many cases, these successes have been limited to specific use cases for specific parts of their businesses. In the months ahead, many will be implementing new processes and technologies geared towards scaling their organizations’ AI capabilities.
Thierry Grima, Group Chief Data Analytics Officer at ENGIE, said that the company does AI – but not at a ‘global scale’, adding that he thought this was an area it needed to work on. He also acknowledged that ENGIE could “certainly use data more efficiently.”
Sarah Gadd, Global Head of Data and Analytics at Credit Suisse, added: “We need to be able to be agile with our development process so we can scale and scale fast.
“We don’t release things every two weeks or every month, now. We release them potentially every day. You need to be able to do that in a very secure fashion. You need to be able to operate data with security, kind of real-time, built into the process so the whole pipeline is fully automated – and that is a challenge.”