Should Retail Tech Be Judged by How Much Complexity It Removes From Stores?

Retail technology, particularly around AI tool integration, has revolutionized the in-store experience for both shoppers and associates.

One recent case study in an Oct. 14 Target press release makes this quite clear: The retailer has enhanced its myDay store operations app to include a customized informational panel available to store leaders – “from fulfillment orders and truck unloads to team members’ schedules” – and associates are provided with a “clear, prioritized to-do list, helping them know what to work on next.”

“The impact is already clear. These latest enhancements are helping team members work more efficiently and helping leaders make faster, more confident decisions — spending less time at a computer pulling together information and more time on the sales floor supporting their teams and serving guests. Across Target stores, these efforts add up to more than 2 million team member hours saved annually,” the press release continued.

The thrust for Target remains squarely on saving labor hours and also upping efficiency (and minimizing headaches) for store associates and management. Other retailers appear to be heading in a similar direction with their retail tech pushes:

• Kroger partners with Deloitte on My Day and Store Walk: Kroger worked with Deloitte and Google Cloud to produce My Day for night shift store workers to help them better direct tasks related to stocking, and Store Walk for managers to smoothen daily store operations. “Kroger can measure its success by pallets—or rather, the absence of them on store floors. It can also look to the shelves, which are typically fully stocked by the time customers arrive,” a Deloitte paper reported.

• Lowe’s Mylow AI based on real-world insight: In a recent Retail Dive piece, Lowe’s SVP of stores, data, AI and innovation Chandhu Nair called the company’s Mylow assistant “a critical part of how we work,” incorporating real-world store data based on store walks and associate feedback. Employees deing with pro desk clients are now having Mylow condense information and personalized recommendations within minutes, which formerly would have taken them hours to compile.

• Walmart uses AI-powered tools to streamline frontline operations: Walmart last year introduced its AI-based tool suite to frontline associates nationwide. It, too, began with overnight stocking pilots. “Initially available for overnight stocking, this AI-directed workflow tool ensures associates have clear guidance on where to focus their efforts. Based on early results, team leads and store managers estimate that the tool has reduced the time team leads spend planning shifts — from 90 minutes to 30. The tool is now in pilot for other shifts in select locations,” a press release detailed.

Deloitte pointed to the inevitability of “the connected store” featuring a virtual store manager overtop for intelligent orchestration and real-time monitoring and advice, stating that “evolution is not optional; it is the difference between leading and falling behind.”

On the other hand, offering a counterpoint was Nikki Baird, vice president of strategy and product at Aptos Retail. While Baird acknowledged that AI was suitable in many use cases – albeit less impressive than what many grandiose claims might put forth – there were several instances where it could actually work to the detriment of the in-store experience, both for customers and for associates.

“Delivering consumer-grade tools straight to store associates is not a good idea because they’re way more time crunched and they’ve got to serve multiple customers, sometimes with multiple competing objectives,” Baird said, as Retail Dive’s Bryan Wassel reported. Baird also pointed out that customers had the benefit of being able to extensively research a product with AI assistance before even entering the store – something associates may not be able to replicate on the fly.

Also, as Baird underscored, AI is more prone to errors than its proponents might admit – and this could lead to frustration and further time wastage. Beyond that, if associates begin to feel that the AI tools are getting in the way of their day-to-day tasking – being a hindrance rather than a help – the expensive integrations could end up being ignored.

“I’ve seen lots of in-store technology get stuffed in a drawer because of the unreliability of the experience for the store associate. If an AI tells a store associate very confidently that there’s 10 of these in aisle five, and they go to aisle five and there aren’t any there, it’s going in a drawer,” Baird concluded.

Questions for further discussion:

• Should new retail tech tools or implementations be judged primarily on how much complexity or frontline labor is removed? Why or why not?

• Do you believe it is inevitable that heavy engagement with AI tools will become table stakes for the average retail worker or manager in terms of day-to-day operations? What friction points need to be addressed in full before this happens across the board?