Why Retailers Fail to Adopt Advanced Data Analytics

Advanced analytics have been available to businesses for years and are getting better all the time, but with a few big exceptions most retailers still use very basic tools. They do this even though they understand the advantages that analytics have given their competitors. What is holding them back from more fully embracing analytics? To find out, the authors interviewed 24 global retail executives in the Americas, Europe, and Asia and found that six factors are the primary sticking points. In this article they discuss those six factors and offer retailers some suggestions for how to move forward and profit from what advanced analytics have to offer.

For years now, executives have been told that advanced analytics can provide better answers to almost every business question. Yet in retail, at least, surprisingly few companies have taken full advantage of the opportunity.

Even as Walmart, Amazon, and a few other leading retailers operate at the leading edge of the analytics frontier, making many important decisions based on an ever-growing supply of real-time and historical data, most of their competitors still use very basic tools that are far better able at tracking where they’ve been than where they should be going.

This is already having real consequences for the industry. During the pandemic, McKinsey estimates, the 25 top-performing retailers — most of whom are digital leaders — were 83% more profitable than laggards and took home more than 90% of the sector’s gains in market capitalization. Although you cannot prove a negative, it does seem likely that laggards are leaving a lot of money on the table. In grocery retail, for instance, McKinsey estimates that implementing advanced analytics would add 2% to grocers’ earnings — a potential windfall for a tough, low-margin business.

This won’t come as news to most people. The executives of even the slowest-moving company must be aware at some level that they are missing out. Yet despite understanding the advantages that analytics have given their competitors, and despite knowing that academics and consultants keep developing more and more advanced analytics solutions, most laggards seem unlikely to catch up with the leaders anytime soon.

Why are so many companies having such a hard time making this leap forward? What is holding them back?

To find out, we interviewed a diverse set of global retail executives (senior executives of retailers, distributors, consulting firms, and analytics providers active in the Americas, Europe, and Asia). The 24 business leaders we interviewed, whose companies varied in their analytics maturity, cited six factors as the primary sticking points:

Culture. Most companies suffer from risk aversion and have no clear goals for an analytics project. “Is data important?” one interviewee told us. “Everyone says yes. If you ask why, many don’t know.” Others look down on analytics, considering their work to be more art than science. One department store executive recalled a buyer asking, “Will an algorithm tell me what dresses to buy? I know what dresses to buy.”

Organization. Many noted that their companies struggle to maintain a balance between centralization and decentralization, both of which are essential: centralization for efficiency, economies of scale, and consistency; and decentralization for flexibility, a greater ability to adapt to local environments, and receptivity to a wider range of ideas.

People. The larger problem, however, respondents suggested to us, is perhaps this: The analytics function is often run by people who do not really understand the business. As one executive wrote, “When during an interaction with the problem owners someone from analytics gives the impression (s)he does not understand the business at all, something happens that I’d like to call organ withdrawal: they stop taking this person serious[ly] altogether.