Store Stock Data Matches Shelves Only 46% of Time
A Scandit survey of 2,200 store associates finds most do not fully trust retail inventory systems, with UK staff the least confident.
Updated on Nov. 10, 2026 in Economic Indicators
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Do you trust the stock information at the stores you shop in?
Research from Scandit found that stock information in store systems matches what associates find on the shelf 46% of the time. Only 8% of store associates trust store data completely, falling to 3% among UK associates.
Why it matters
Retailers are increasingly planning to rely on AI for decisions based on store data, which depends on accurate stock records. The survey suggests that unreliable data is currently being corrected by staff through informal workarounds.
Scandit commissioned a survey of 2,200 store associates at retailers with more than 1,000 employees across seven countries, finding stock data matches shelf findings 46% of the time. The survey does not say how the 46% figure was measured or whether it varies by retail category.
The players
Scandit
Scandit is a enterprise computer vision and barcode scanning company that commissioned the research on store stock data.
Sapio Research
Sapio Research is a market research firm that conducted the online survey of store associates for Scandit.
The details
Store associates in the US, Germany, UK, France, Italy, Canada, and Poland reported using paper notes, team chats, personal phone photos, apps, or memory to track stock outside official systems. Among UK associates who take corrective action, 36% bypass the official system entirely, and UK associates estimate they could each reclaim 3.96 hours a week with trustworthy data.
Timeline
September: Scandit surveyed 2,200 store associates online.
Wednesday, 4 November: The 2026 RTIH Innovation Awards ceremony was held at The HAC in London.
Market Landscape
Retailers are moving toward AI-driven decisions on store data at the same time that the underlying inventory records remain unreliable. The Scandit findings suggest that adoption of automated stock management depends on closing the gap between system records and physical shelves first.
Shoppers may experience out-of-stock or incorrect availability information if store records diverge from shelves. Store staff spending hours on manual stock checks can affect how quickly customer questions are answered.
The takeaway
Accurate store data is a prerequisite for trustworthy AI in retail, and staff workarounds are a signal that the data is not yet ready. Retailers planning automation should audit shelf-level accuracy before expanding automated decision-making.
Further reading
For related context on measurable retail and business activity, see Economic Indicators.
Source note: This article includes information reported by Retail Technology Innovation Hub.
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Do you trust the stock information at the stores you shop in?
