Sainsbury’s: Balancing data governance with value creation
As the Brexit vote has undermined the value of sterling, many UK retailers have been dealing with a sharp rise in the cost of imported goods. At the country’s second largest supermarket, Sainsbury’s, that has started to squeeze profits even as revenues at the £29 billion ($38.6bn) company have continued to rise. Dealing with exceptional market conditions requires new approaches, and that has set Sainsbury’s chief data officer (CDO) Andrew Day the challenge of extracting even greater value from the vast volumes of data the company gathers on both the products that move through its 600 supermarkets and 800 convenience stores and the patterns of customer purchases.
For decades Sainsbury’s has used data to understand customer behavior — at both a macro and individual level — ensuring it can make better decisions on the products it stocks and the offers it makes to consumers based on their purchase history. But with its main competitors pursuing similar data strategies, the company has decided it needs to move the sophistication of its analytics up a notch.
The significance placed on data as a valuable asset is clear to see at Sainsbury’s. While the focus of many retail sector CDOs is on the world of data regulation and governance, Andrew Day highlights that his role is predominantly on value creation.
|Andrew Day, CDO of Sainsbury’s|
“The aim is to do all we can with data to make a difference. It’s about how to create better products and the right prices, optimize store layouts, work with farmers to get better crops, manage our logistics better, and much more. It’s about supporting people with commercial goals to hit their targets and drive the best outcomes across the organization,” he explains.
Like many businesses, Sainsbury’s tries to strike a balance in its use of customer data. It seeks to demonstrate to customers how its use of their data can be helpful to them without being too intrusive or compromising the customer experience, while at the same time maximizing the business benefits derived from that data. Day believes that value exchange always needs to be evident: “We should see ourselves as part-time custodians of our customers’ data, not owners, as they’re giving us permission to do smart and sensible things with it that also benefit them. We always put ourselves in our customers’ shoes and if we don’t see a customer benefit or if we think it would be unreasonable to do something with the data, we don’t do it,” he says.
To help make decisions about the specific ways it should use customer data the retailer runs ‘customer data clinics’ consisting of teams from legal, regulatory, business and customer management communities.
Prepping for GDPR
While focused on maximizing the value derived from such data, there are other challenges that need to be addressed. The incoming EU General Data Protection Regulations (GDPR), which comes into force in May 2018, have prompted a reassessment of processes for monitoring data use and storage.
Over the past year the company has been working through a major program to prepare itself for GDPR, which Day highlights as a major step beyond existing data protection legislation. “It’s clearly more onerous from a penalties perspective and it will also be more important to enact the chapter and verse of the regulations,” he says.
As part of that change program, Day’s team have been working out how Sainsbury’s can become increasingly transparent with customers about the data it holds. “The lion-share of the data is simply details of the items customers have bought from stores and they would just get bored of reading lists of those. But we are looking at smart ways of making that even more transparent,” he states.
Consumer data is only part of the story. Day emphasizes that its data about the products it sells can be more interesting. “It’s quite easy for people to jump to the conclusion that customer data is of most value to retail organizations, but there is as much, if not more, value to be had for the analysis of product data – something that doesn’t come with all of the challenges of consent or GDPR,” he explains.
Next-gen analytics tookit: AI, NLP and robots
Day is also looking to cutting-edge digital approaches to create even greater value from data, with machine learning and AI already on his radar.
One of the most exciting areas draws on natural language processing (NLP). “The ability to process and playback natural language, coupled with augmented reality and intelligent robots, has the potential to dramatically change the in-store experience,” he says. “For example, a customer could ask a robot where to find a particular item, with the robot understanding the words or an image the customer presents, and then take the customer to the relevant area of the store,” he says. “That kind of application is not a pipe dream, it’s reality.”
But it’s not just technology that is driving this business change. Day believes there is a cultural shift where the role of data specialists will be moved out of the back office so they will increasingly be challenging business colleagues to more actively engage with and exploit data.
“It is important that the business — including the C-suite — learns about and can talk the language of analytics, data science and AI as these will change the way the entire organization works,” he says. Applying new technology to solve business problems is not a new concept, he says. “When you have a problem to solve you use smart people, data and technology – this hasn’t changed, but the technology we can use is absolutely changing.”