Meet Bas

“No, not at all. Because it was such a greenfield environment, we got to do everything our way. That gave me far more opportunities to make a difference than in my previous role as an external consultant. I felt like a kid in a candy store. I got to fix everything the way I wanted, pick my own tools, and so on. For the first couple of years, I approached ‘project data’ like a consultancy job. For example, I put together roadmaps and developed maturity models. Even when the project team grew, we were still cowboys for a while. We’d work on whatever data projects looked the most attainable and quantified the added value in euros. Whenever we completed a project, we’d shine a spotlight on business colleagues to promote the new data-driven way of working.” Do you have an example? ”Sure, for one project we used customer behavior data to personalize e-mails for our loyalty program. That generated millions of euros in one fell swoop. And the fact that we operated under the wing of the CEO helped to stimulate adoption.”

“Quite a way. Company-wide, I’d give us a 3.5 on a scale to 5. Our team scores higher. It’s no accident that we won the Customer Data Award last year. The focus has gradually shifted from pioneering to managing and expanding. And from marketing to other domains, like sales and the supply chain. There’s a world to be won there, too. For example, we’re currently working on daily sales forecasting. So we can staff our distribution center appropriately, with the right number of people to pick all the articles for the day. That might not sound sexy, but it sure pays off. We used to base our predictions on historical data, say the same week in previous years, and I can confirm that ‘past results are no guarantee of future performance.’ Particularly not in our rapidly changing world. Take gloves: on the day first of frost, we instantly sell thousands of pairs. But you have to time it right. And have everything ready.”

“Data science and BI go hand in hand here! We need to look ahead, so we have five data scientists on the team. Plus analysts, product owners, and engineers. And traditional BI colleagues to help manage HEMA. Our favorite tools are Python, PySpark, Kubernetes, Git, Airflow, SQL, and Power BI. And by now, we can run any analysis we want because everything is new. We replaced the entire foundation. New BI platform. New data analytics platform. Also: we used to support 20,000 reports, and we’ve reduced that to a set of 20. One truth. And unprecedented clarity of vision: we can see things now that we were never able to detect! We also trained about 300 business colleagues – all volunteers – to make better use of our data in a span of three months. These trainings took eight hours, so commitment was a given. In short, we have a super sexy stack now, an organization that clamors for data insights, and a new data and analytics platform. So we’re ready to do some real data science! And we’re ready to take the next steps. You can work on anything you feel would add value. You won’t be toiling on ‘project make a green button for page X of the website,’ but contributing to genuinely impactful projects. For enthusiastic colleagues. For an increasingly data-savvy organization. And for millions of HEMA customers. And because literally everybody knows HEMA and has a soft spot for us, you’ll be a hit at parties, too.”