Should analytics drive category planning?
Recent studies indicate artificial intelligence has not yet delivered the promised time and labor savings benefits to the space and assortment optimization process.
According to Symphony RetailAI’s “Retailers’ Views of Modern Planning Tools & Solutions” study, macro space planning was cited by 72 percent of grocery retailers as critical to category planning needs, followed closely behind by assortment optimization, 67 percent; and micro space planning, 65 percent.
The study, conducted by RSR Research, found nearly 40 percent agreed assortment optimization was the most urgent system to be replaced. Thirty-one percent cited a desire to utilize cloud-based solutions for store clustering and planogram automation.
“The grocery industry has never been more complex, and the stakes are high to get category planning processes right to keep pace with change, grow sales and margins and outpace the competition,” said Cheryl Sullivan, general manager and chief product officer, Symphony RetailAI, in a statement.
IDC’s “Next-Gen Merchandising Solutions” study, which came out in January, said merchants and category managers are facing new pressures, including space constraints caused by the rise of small-format stores and the scaling of omnichannel services.
IDC’s accompanying survey found that, for 42 percent of retailers, space and assortment is their top priority for investment in merchandising technology. While 65 percent consider artificial intelligence (AI) to be essential for merchandise analytics applications, half said the primary intent of investing in AI for merchandise analytics is to drive efficiency through automation.
In a column for the Harvard Business Review, Marshall Fisher, UPS Professor of Operations and Information Management at the University of Pennsylvania’s Wharton School, wrote that techniques he helped develop with several retailers over the last few years show analytics are providing “tremendous opportunity” to improve revenues and profits, including helping identify substitutes and figuring out the right metrics to use in clustering stores.
He wrote, ”Assortment-planning processes vary greatly across retailers and product segments but have one thing in common: They rely too much on human judgment and not enough on hard data that might allow a retailer to predict how customers will react to a change in the assortment.”
- Space Planning Solutions Top-of-Mind for 68 percent of Retailers, Survey Finds – Symphony RetailAI
- IDC Research: Next-Gen Merchandising Solutions: New approaches to meet the coming challenges of retail – Hivery
- Don’t Trust Your Gut With Assortment Planning – Harvard Business Review
DISCUSSION QUESTIONS: Are merchants still relying too much on intuition rather than analytics to guide assortment and space planning? What’s holding back progress — or is a data-first approach overrated?