Callum Staff: Building on Pandemic-Era Data Science Successes at M&S

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