Callum Staff, Head of Data Science and Analytics at Marks &
Spencer, discusses his plan to build on his team’s successes
over the past 24 months and integrate data further with the
retailer’s business processes
At UK retailer Marks & Spencer, most conversations in the past two years
involving data and analytics have revolved around COVID-19.
For Callum Staff, Head of Data Science and Analytics at Marks & Spencer,
the global crisis meant putting major data science projects on ice to better
support the retailer’s supply chain. He considers the move ‘a real shift’ in the
relationship between business and data science at M&S.
“It showed the sort of support that we can provide; I want to further embed
the data and analytics team in key M&S functions,” he says. “We've got
tools that allow us to do that, and we want to turn them into fully fledged
software. It will help bake my operating model into any project.”
In this week’s Business of Data    podcast   , Staff talks about how he’s working
to build on the ties the pandemic-era has helped his team build with
business stakeholders to integrate data and analytics further into the
company’s operating model.
Making M&S Staff Sweet on Data
One of the ways Staff’s team is already helping to optimize M&S’s supply
chain is through space planning in stores. They provide insights to improve
demand forecasting and optimize inventory levels.
The data science team has also been involved in planning for a new law
regulating the sale of fatty, sugary and salty foods that will come into effect
in the UK this April. It will mean retailers can no longer place these foods at
store entrances and other main points. Advertising these products on TV
and online will also be restricted.


“Our data quality team's been involved in the conversations around this new
law from the start,” Staff says.
But Staff believes he must be mindful of his approach as he works towards
greater integration between data science and business teams. He wants to
ensure that the models and systems his team builds meet business needs
and integrate with staff workflows.
“It's all very well building a new dashboard or building a new machine
learning model,” he says. “But if you just plonk it somewhere and leave it,
it's never going to grow. We’re spending a lot of time thinking about how this
works day-to-day with people and where it impacts the steps they need to
take.”
Success will require constant communication and re-evaluation to ensure
Staff’s team’s priorities remain aligned with those of the wider business. But
Staff is confident that the greater cross-functional collaboration he’s seen
recently will help his team drive further organizational change in the coming
months and years.
“It’s really good to have the quants and the tech teams working alongside
sales and the traders,” he concludes. “It seems like a really good way of
working. COVID-19 showed me that, and hopefully it showed that to other
areas of the businesses as well.”
Key Takeaways
The pandemic has changed perspectives around data. COVID-19
helped Staff and his team show their colleagues how data science can
embed itself within the company and add value
Provide consultation on key business initiatives. M&S’s data team is
playing a strategic role as the organization reformulates thousands of
products to meet the UK’s new dietary regulations
Focus on alignment and adoption. Staff is keen to ensure his team is
developing the right tools and capabilities and that these can be integrated
effectively with staff workflows