Study: Retailers lose labor hours to inaccurate shelf data
Store employees report significant discrepancies between stock information and what they find on shelves — and that gap helps drives up labor costs.
Stock information matches products displayed on store shelves only 46% of the time, according to a new survey of store associates from Scandit. The firm's “The Store Truth Gap" also reveals that only 8% of respondents trust store data completely. In addition, only one-in-four respondents say store data is accurate more than 70% of the time.
Among respondents who put accuracy anywhere up to 50%, roughly one-in-four report high trust, and that trust figure remains consistent until accuracy passes 70%, when it rises sharply.
Respondents estimate they would each get back more than 4.4 hours a week — nearly six working weeks a year — if they had store data they could trust. They report spending an average of 4.1 hours each week handling customer questions that store technology should be able to answer and are asked to physically check whether an item is in stock 5.85 times a week on average. More than one in five say they make those checks more than 10 times a week.
Nearly half (49%) of respondents will correct the record themselves when encountering a stock-store information discrepancy and 44% will raise a stock adjustment. But among respondents who take action, 42% bypass the official system entirely, while 68% use at least one informal method, including paper notes, team chats, personal phone photos and apps or memory.
The survey also reveals that associates should be involved in any effort to roll out shelf-tracking technology or AI systems. Associates who participated in a pilot reported using most store tools at a rate of 74%, compared with 61% among those who were consulted before rollout and those who were never asked. Half of pilot participants reported high trust in their stock data, compared with 25% of those who were never asked for input.
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“Retailers do not have an AI adoption problem as much as a store truth problem,” said Samuel Mueller, CEO and co-founder of Scandit. “Associates are spending valuable time repairing these gaps, yet much of that work disappears into unofficial tracking systems. Before retailers ask AI to make more decisions based on inaccurate store data, they need a shared, accurate view of what is actually happening on the shelf and across their stores.”
Scandit commissioned Sapio Research to survey 2,200 store associates online in September 2026. All worked in physical stores for retailers with more than 1,000 employees across the U.S., Germany, U.K., France, Italy, Canada and Poland. The research covered grocery, mass merchant and department store, hypermarket and supercenter, DIY and home improvement, convenience, and drugstore and pharmacy formats.
