What June’s supermarket fridge failures revealed about FMCG stock data

June’s heatwave closed chilled aisles across UK grocery. The real story is not the weather – it is how long the brands in those fridges took to find out.

June’s heatwave pushed UK temperatures to a provisional 37.3°C at Santon Downham – the third consecutive day the June record fell.

It also closed chilled and frozen aisles in stores run by Tesco, Sainsbury’s, M&S, Morrisons and Waitrose, from Essex and Bristol to Newcastle, Carlisle and the Isle of Man. Milk, meat, ready meals, fresh produce, ice cream – cordoned off, or pulled for disposal, as reported by The Grocer. The retailers handled it. Aisles reopened, stock was replaced, the news cycle moved on. Here is the question nobody asked while it was happening: how long did it take the brands whose products were in those fridges to find out?

The heatwave was the visible version of an invisible problem

Most coverage filed this under weather. It was more useful than that – a dated, photographed, nationally reported version of something that happens quietly every week of the year, with no heatwave anywhere near it.

The uncomfortable part is not that fridges failed. What is less discussed is the supplier side. For most FMCG brands, the mechanism for finding out their chilled products had been pulled was the same as always: wait for the weekly data file, or wait for someone to tell you. Availability data in this industry is overwhelmingly a lagging indicator dressed up as a live one.

That gap has a name: phantom inventory. Stock that exists in the record and not in reality. The file shows 100% in stock, no alert is raised, no replenishment triggered – while the shelf facing has been empty for days.

A heatwave makes it visible because it is photogenic and reportable. A quiet Tuesday gap in Stevenage does not make the news. It costs the same.

How much of this is actually happening?

More than most commercial teams assume. Average UK grocery on-shelf availability sits at 89.7%, with around £2.1bn of sales at risk from stock gaps each year and one in five shopping trips involving an out-of-stock. When a product is not there, 31% of shoppers buy a different brand and 26% leave the store entirely – for a share of them, that is a permanent switch. Sources: Retail Economics and DHL, “The Availability Effect” 2026; ECR Retail Loss.

Across the UK grocery accounts examined at GrowSights, the avoidable share – fixable execution failures, not genuine demand movement – typically runs 5-8% of addressable sales. On a mid-sized account, that is a six-figure annual number sitting inside data the brand already receives every week. No new technology needed. Nobody had built the layer that turns a raw stock feed into a signal somebody could act on.

What share of that loss is actually recoverable?

Not all of it. A genuine demand spike or an upstream supply failure is not fixable in-quarter, and pretending otherwise is how availability programmes lose credibility.

But across the UK grocery accounts examined at Growsights, the avoidable share – caused by fixable execution failures rather than real demand movement – typically runs 58% of addressable sales. On a mid-sized account that is comfortably a six-figure annual number, sitting inside data the brand already receives every week.

No new integration. No new technology. No new data source. The information was already in the business. Nobody had built the layer that turns a raw stock feed into a signal somebody could act on.

What the brands getting this right are doing differently

Not buying more dashboards. Changing what the data is asked to do.

The first shift is classification – telling apart three things that look identical in a weekly file. A genuine stockout needs action today. A reporting delay looks the same but the product is on shelf and the data has not caught up – ignore it. A post-promotional dip shows a sharp sales fall but is an expected pantry-loading effect – also ignore. Without classification logic, teams chase issues that resolved themselves and stop believing the alerts.

The second shift is ranking by money, not severity. A 6% gap across 400 stores costs around £4,200 a day. A 40% gap across 12 stores costs around £380. Sorting by severity puts the cheapest problem first every time.

The third shift is resolution – which store, which SKU, which week, who at the retailer fixes it. That collapses a multi-day diagnostic into something that happens the same day. And none of it requires a store visit. The store-level availability data the retailer already sends you covers every store you sell into. The constraint was never access – it was that nobody had made the file legible.

Four questions worth asking your team this week

1. How many days does it typically take us to notice a stockout, versus fix one? 

If nobody can answer this, that is the finding.

2. Is our availability data blended at national level, or can we see it store by store?

National averages routinely mask serious regional failure.

3. Can we tell a real stockout apart from a reporting delay – or do we treat them the same?

If it is the latter, your team is spending time on gaps that fixed themselves.

4. If a fridge failed in one of our accounts tomorrow, would we know before the buyer told us?

If the answer is “the buyer would tell us” – that is not a heatwave problem. That is a Tuesday problem.

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About the Author 

Riddhi Parekh is founder of Growsights, which helps UK FMCG brands turn the retailer data they already receive into ranked, store-level availability signals – identifying where revenue is being lost, in which stores, and why. You can connect with her here or visit them online here.