WPP’s Community-Led Approach to Data and Analytics

Di Mayze, Global Director of AI and Data at WPP, outlines why she’s adopted a people-first approach to data and analytics strategy at the advertising giant

One in four of the world’s adverts are made by WPP, it’s safe to say the organization is a hotbed of data-driven innovation. But with more than 100,000 staff spanning more than 400 companies, keeping everyone abreast of what’s going on is a huge challenge.

As Di Mayze, WPP’s inaugural Global Director of AI and Data, says in this week’s Business of Data podcast, this is the thinking behind the group’s people-first, community-led data and analytics strategy.

“I absolutely believe in people and the power that is in the application of what these great people do to the data,” she says. “I’ve been able to carve out my dream job, because I’ve just made it about data people and us investing in people.”

“We share licenses with our agencies, but we say, ‘Come on. You had your data. You tell us how you’re using it and then we can continue to support it’”

Di Mayze, Global Director of AI and Data, WPP

Given the vastness of the organization, any attempt to centralize WPP’s data architecture was bound to run into difficulties. Instead, Mayze’s team is focusing on cataloging what data the group has and creating organizational structure that showcases the latest innovations from across the group.

In this way, WPP’s data function is building awareness of what data the organization has and how it might be used. To illustrate this, she talks about telling a colleague about a ‘velociraptor’ dataset that lets people enter their postcode and reveals their chances of being killed by a velociraptor.

“I said, ‘Well obviously [that’s] totally useless,’” she recalls. “[But they] turned around and said, ‘Oh that’s brilliant! We’re working with Jurassic Park right now!’”

The Power of Data and Analytics Communities

WPP’s enablement program is the second string to its data strategy bow. The group is training 5,000 data scientists in its AI academy and is upskilling 50,000 staff members through its Demystify AI program.

The agency also launched its data and AI community in July 2020. The community now has 2,700 active members and provides a forum for presentations and panel discussions showcasing recent case studies and exploring the future of data-driven innovation. Meanwhile, WPP has an 88-member ‘CDO group’ that meets regularly to discuss strategic issues such as executive sponsorship.

“It’s [taken] a lot of energy,” says Mayze. “For anybody looking to set up a community, I will say, however much time you’ve allocated, you [probably] need to times that by 10. But that’s been really rewarding, and I get so much feedback from that that makes it all worthwhile.”

She adds: “There’s a real breadth of skills, from people who are just wanting to learn more about data to scientists who are sharing code [and] thinking about how you might answer some particular challenges.”

These organizational structures allow WPP staff to network across companies, markets and regions, and Mayze puts the success of these communities down to WPP’s data champions.

“We have about 15 data champions that I asked to work with us,” she concludes. “They will help get interest [from] in their agency. They will help drive up users. [And] they will help post content.”

Key Takeaways

  • Data communities can be extremely powerful. Creating structures that connect data and analytics leaders help inform everyone about what’s being done and what’s possible with data
  • Allocate time to community-building initiatives. Working out who to include and how to ensure ‘wins’ are shared freely across the organization takes a great deal of planning
  • Find data champions to fuel the conversation. WPP’s network of around 15 data champions helps to promote its data communities and ensure they are valuable forums for idea sharing

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