Based on a press release sent to Daily Tech Times. Published after automated checks against the release; not read by an editor before publication. Corrections: editor@dailytechtimes.co.uk.
Stock records in shops match what staff actually find on the shelf just 46% of the time, according to global research published on 10 November 2026 by Scandit, the Zurich-based smart data capture company. Only 8% of store associates said they trust store data completely, a figure that falls to 3% in the UK.
Scandit calls the difference between what inventory systems say and what is physically in the store the “Store Truth Gap”. It argues that the gap hurts customers and threatens the return on retailers’ AI investment, because AI systems would be making decisions from the same flawed records.
The survey was carried out for Scandit by Sapio Research, which questioned 2,200 store associates online in September 2026. All worked in physical stores for retailers with more than 1,000 employees in the US, Germany, the UK, France, Italy, Canada and Poland, across grocery, department store, hypermarket, DIY, convenience and pharmacy formats.
The UK figures
- 3% of UK associates trust store data completely, against 8% globally.
- 41% correct wrong records themselves (global average 49%), and 35% raise stock adjustments (global 44%).
- Of UK associates who do act, 36% bypass the official system entirely and 58% use at least one informal method, such as paper notes, team chats, photos on their own phones or memory.
- UK associates say they could each win back 3.96 hours a week if they had data they could trust. Scandit puts that at a labour cost of £23 million a year for a retailer with 10,000 store associates.
- They are asked to check whether an item is in stock almost 7 times a week on average, and a third (33%) do so more than ten times a week. They spend 2.8 hours a week on customer questions, against a global average of 4.1 hours.
Shadow stores
Scandit describes the informal workarounds as a “shadow store”: information that lives on phones, in messages and in people’s heads, outside the records that head office, dashboards and AI systems rely on.
“Retailers do not have an AI adoption problem, as much as a store truth problem,” said Samuel Mueller, CEO and co-founder of Scandit. “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.”
Trust does not rise in a straight line
Globally, only one in four associates say store data is accurate more than 70% of the time. The research found that trust stays low until accuracy passes 70%, then rises sharply.
“Moving stock accuracy from 46% to 60% may look like progress in a board report and still change nothing on the floor,” said Andrew Smith, managing partner and co-founder of ThinkUncommon, who is quoted in Scandit’s release.
The full report, which also covers European and US figures, is on Scandit’s website.