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Episode 25: Callum Staff (Marks & Spencer) + Key Takeaways

To kick off Season 3 of the Leading Analytics Podcast, I sit down with Callum Staff who leads food analytics at the global retail brand Marks & Spencer based in London. Sitting beneath the in-store customer experience and the rich product offerings, sits a growing analytics capability crucial to growing the enterprise in the future. Callum also mentions a few must read book titles that you won’t want to miss.

Key Takeaways

Describe your title and role. Where does your function report within the organization?

My title is head of data science and analytics within the food business at Marks and Spencer (M&S). I'm responsible for teams that govern and utilize data to support operations within M&S food. We're embedded within food business operations, much like a lot of banks have their quants and their tech teams embedded within the financial product teams. We have data quality and governance, data science, and within that, a commercial analysis function that does research, and a technology and modeling function that takes the research and creates software. We don't focus on the customer. That's handled by a separate function.

What are the most important application areas at M&S? Which business partners do you work with most?

My observation is that the retail industry has traditionally been fragmented in the way it works. You get what's called local optimization. You might optimize metrics best in one part of the supply chain, but the global optimum value, profit, and customer loyalty is not optimized as a result. So, it's a real value destroyer. With any of the data pipelines, models, and processes that we build, we aim to globally optimize them across the entire value chain. Right now, our efforts are very much about joining the dots in supply chain: demand forecasting, and optimizations around inventory, range (or assortment), and shelf space.

In addition, we focus on sustainability and nutrition, which are key business values for us. We have a sustainability plan, called Plan A. A key part of that is the ability to make well-informed decisions and have visibility, and have what we call a culture of measurement—if I do this, it's going to do that—and the ability to test things and understand the impact across the value chain.

What is your talent strategy for data and analytics personnel?

The one word we always come back to is "specialism." We've got a myriad of roles within each team, each with their own specialisms. This has allowed us to deliver a higher quality of project because team members use their time to master one role, and they're not spread across a number of specialisms like generalists. The risk comes when someone leaves, so to counter that we've tried to make the projects interesting. We've also created a progression framework that allows people to progress both technically and managerially in their careers.

To what extent does M&S use advanced technologies such as AI and machine learning?

I mentioned inventory optimization being one area where we've worked to reduce our waste. Part of our long-term strategy for engaging teams across the business is, first of all, exploring how we can improve the quality of their data. Fix the operational data we've got, then put reporting on top of that to improve efficiency and grow the culture of using data. Then, once we have done that, look for opportunities to bring in data science and machine learning to develop the culture of insight and measurement.

Getting that culture of measurement has been something of a journey. What we have brought to the table is more robust analytical techniques, such as A/B testing, and applying that to retail. There are definitely more opportunities to do that as we experiment and bring in new interventions, but, step by step, we've managed to take people on the journey to the point that we're looking at building in-house software to support the culture of measurement.

What advice would you give to aspiring analytics professionals?

  1. Don't rush progression. Spend time learning the technical ropes before you move up. This will pay dividends in terms of your reputation, and also, it's really interesting to spend time doing analysis.
  2. Have a professional development plan. Write one and keep it live. I have a reminder on Outlook every week to check my plan and to take one action from it so I'm keeping things ticking along and constantly developing.
  3. Be aware of culture and change management. That is, when you are delivering a project, it's not just about making sure that it's good technically. Make sure that you can embed it. Thinking about how complex systems fit together is important. It helps you think about how people are going to react to it.
  4. Thinking Fast and Slow by Daniel Kahneman. The behavioral economics and psychological phenomenon described here have stuck with me as related to how people react.
  5. The Humans by Matt Haig. A novel but fascinating for depicting observations about humans and all their quirks. In a weird way, a lot of that sort of stuff struck me in the same way I was talking about complex systems.

For more insights from Callum, listen to the full podcast.