David Ciancio, global head of grocery, dunnhumby

What are your key areas of focus for data and analytics in 2022?

I cannot recall a more difficult – or opportune - time in the industry in all my 52 years in the business, post-Covid and now with the highest inflation in most shoppers’ lives and our own professional careers. These extraordinary times call for an exceptional understanding of changing Customer needs, using data and analytics. 

Accordingly, the key focus areas for data science must be around: 

1. refreshing customer understanding and strategies;
2. focusing on the right categories, brands and products that drive value perception, according to shoppers;
3. rebalancing how prices and promotions work together to deliver real value; and 
4. helping shoppers find smarter, easier, and more sustainable alternatives.

Tell us what leadership means to you in the context of your role as a senior data leader.

A great data leader understands that data must translate into insights, and that insights must create actions that ultimately benefit customers. Insights should take the form of a common Customer language, in words that humans use every day, and spoken as simply as possible (think of a common customer language as the missing vocabulary in most businesses, where everyone speaks common product and store languages, automatically and almost unconsciously). 

Data leaders should avoid speaking jargon like AI, machine learning and algorithms in examples. Instead, they should speak of “what customers are telling us in the data". Great data leaders position data and analytics as organic and natural processes – human, not artificial - thereby winning more trust from the organisation.  

And what about the skills of your data teams and of your business stakeholders? How are you developing data literacy across the company/organisation?

I encourage analysts to think of themselves as scientists and translators who clarify and simplify from a kind of hieroglyphics to everyday vernacular, because this is how the organisation will better understand and activate the insights. Literacy is about sharing the insights broadly and frequently, giving access to any business stakeholder who wants it, and in a simple common Customer language as mentioned above. 

I encourage analysts to think of themselves as myth busters, who speak truth to power not from their own authority, but from that of thousands and millions of customers. And business stakeholders are encouraged to start with a kind of humility that admits, “we don’t know what we don’t know” (and how could we, really, in a world that is changing so rapidly), but which they can know by looking at the data. So, business stakeholders are recast as discoverers, pioneers, testers and learners. 

Finally, the common customer language and insights must even be shared with business partners outside the organisation, with suppliers and financiers, so that everyone becomes literate and fluent. This can be enabled via insight platforms but should also be spoken in everyday conversations like joint business planning discussions.