Co-operating to manage data scientists

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The remit of Lindsay Pellow, head of member data and insight at The Co-op, has expanded. She works alongside two other heads of data and insight. They specialise in marketing and the retail business, while Pellow focuses on member data. The three of them manage and prioritise the work of a pool of data scientists, but from the start of this year Pellow has also been covering the Co-op’s funeral and life planning business.
She spends her days working with the membership team, discussing the analysis and reporting they require to understand members of The Co-op. She is also the product owner of the membership database and plans the ongoing development of it. On top of that, she also produces analysis to inform business decisions.

“As managers we can work with everyone in the team.”

Pellow finds this set up works well for both her fellow heads of data as well as the data scientists. She said: “Having a pool of data scientists means my colleagues can choose to specialise in one area or have exposure to multiple areas of work, and as managers it allows us to work with everyone in the team rather than just those we line manage.”
Pellow and her fellow heads of data work alongside teams responsible for CRM and marketing as well as colleagues across the various Co-op businesses such as proposition managers and food buyers. “This is to ensure we’re close to business priorities and can help make sure data is at the heart of decision making,” Pellow explained.
Last year, Pellow and her team launched an interactive dashboard in PowerBI which helps colleagues see how members are trading with The Co-op. With this new tool, they have enabled over 150 colleagues to do self-serve reporting. It has freed up time and resource as they now spend less time dealing with ad-hoc requests.
The key ingredient for a successful project in her view is simply team work. When implementing the dashboard, Pellow’s team worked closely with the membership team to understand the user needs and then planned an iterative delivery with the data engineering team, who they worked very closely with throughout.

“The most successful combine data knowledge with business acumen.”

Pellow acknowledges there is a widely-held perception of data professionals as nerdy and geeky people who lack social skills, but finds that those who do well do not adhere to that stereotype. “The most successful are those with great interpersonal skills who can combine data knowledge with business acumen,” she said.
Pellow really enjoys the logic and reason offered by working with data as it reduces the reliance on gut feeling. “Fact backed up by data is real, and should transcend opinion, though sometimes it’s still a challenge to make that happen. But that’s getting better as more and more people are taking data seriously and becoming more data savvy.”
Though pleased with her career path, Pellow wishes she had cultivated self-belief from an earlier age. “I’d have taken more risks, put myself forward for more responsibility and promotion earlier than I did, so probably believed in myself a bit more earlier on,” she said.



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