Mike Graen, one of the industry’s foremost experts on on-shelf availability, shares his perspective on why OSA is not a single metric, but rather a series of interconnected layers that the retail and CPG industry too often treats as interchangeable.
In a recent article, on-shelf availability expert Mike Graen highlighted a simple but powerful reality: the supply chain routinely operates at 98 to 99%, yet on-shelf availability often falls to 90 to 93% during the final few feet to the shelf.
The article below is Mike's perspective on why availability is not a single metric, but rather a series of interconnected layers that the Retail-CPG industry too often treats as interchangeable. His point is simple: products can be successfully produced, shipped, and received, yet the shopper ultimately experiences only one thing: whether the product is available when and where they want to buy it.
Walk any store with a scorecard in hand and the same conversation happens. The system says the item is in stock. The buyer's report says the item is in stock. The shelf says otherwise. Everyone in that room is telling the truth, because they are each measuring something different.
Availability comes in layers, and commercial organizations routinely treat those layers as interchangeable when they are not.
Supply chain availability means stock exists somewhere in the network, whether in a distribution center, in transit, or on order. In-store availability means stock is physically inside the building, including the back room, top stock, and the pallet nobody has broken down yet. On-shelf availability means the product is in position, shoppable, and available at the exact moment a customer reaches for it.
Only the third layer converts availability into revenue. It is also the layer most measurement systems see least clearly, because most dashboards were built to answer the first two questions, not the third. The research community documented the shape of this gap years ago, and the finding continues to hold true. ECR Europe's Optimal Shelf Availability research, conducted with Roland Berger, found service levels of 98 to 99% from the manufacturer's warehouse through the retailer's stockroom, falling to 90 to 93% over the final meters from the stockroom to the shelf.
The industry hits its targets almost everywhere except the one place the shopper ever visits. NielsenIQ later put a dollar figure on the same pattern, finding that 7.4% of U.S. CPG sales went unrealized in 2021 due to out-of-stock and out-of-shelf conditions, representing an $82 billion opportunity lost in a single year.
That gap is expensive at every scale it has been measured.
IHL Group's research puts the global cost of inventory distortion, the combined impact of out-of-stocks and overstocks, at $1.73 trillion annually, equal to 6.5% of global retail sales. Of that total, $1.2 trillion is attributed to out-of-stocks alone.
Research from ECR Retail Loss found that 43% of shelf out-of-stock incidents result in less money in the till once substitutions are accounted for. Shopper behavior explains why these losses compound. By the third time a shopper encounters a gap on the same item, the probability they switch stores entirely reaches 70%.
The impact concentrates in exactly the moments when brands can least afford it.
Research by Gruen and Corsten across the fast-moving consumer goods industry found average out-of-stock rates around 8%, a figure ECR Retail Loss's 2025 analysis still found sitting at 8.6%, with promoted items running at roughly double the average. That detail deserves more attention than it usually receives. A brand funds the promotion, negotiates the feature, activates the media, and drives the traffic. Yet availability is most likely to fail during exactly those days, when conversion was the entire point of the investment.
A team measuring only promotional lift and ROI after the event closes may conclude the promotion underperformed. The promotion may have performed exactly as planned. The shelf did not.
For most of retail history, an empty shelf disappointed one person at a time.
Online fulfillment from stores changed that equation. The same gap now fails both the customer walking the aisle and the picker filling an order on behalf of a customer who is not there. The picker's version of the failure is often worse because it ends with a substitution decision made by someone else, or an item refunded entirely.
Harvard Business Review put a number on what improving that second failure is worth. It reported an Instacart experiment in which customers steered toward delivery windows with stronger stock positions increased average daily spending by 4.6%, with fewer substitutions and refunds.
That lift came from one thing: availability at the moment of picking.
Every retailer operating store fulfillment today generates the same signal at scale, whether or not anyone is using it. Pick rates, substitution rates, and refund rates provide a continuous, order-by-order audit of on-shelf availability that simply did not exist when many of today's measurement habits were created.
The solution starts with being honest about what each metric actually measures.
A perpetual inventory figure is not an on-shelf availability number. A distribution center fill rate is not an on-shelf availability number. On-shelf availability must be measured from the shopper's perspective, whether through store audits, computer vision, RFID, or the fulfillment signals already flowing through the picking operation.
The opportunity then belongs to everyone who touches the shelf, because no single party controls the last fifty feet. Retailers own the replenishment processes and labor models that move products those final steps. Suppliers own the forecast quality, case pack decisions, and promotional volumes that determine what those processes must absorb. Brokers and field teams are often the only people physically standing at the shelf with the ability to identify and fix what they see.
When these groups manage to a shared on-shelf availability metric through joint planning, the gap closes. When each manages only its own layer, the gap persists, and each party's numbers can honestly say the problem belongs somewhere else.
The moment a shopper reaches for a product is what researchers call the moment of truth. The finding underneath that phrase is consistent across every study: everything upstream of that moment may have performed at 98%. The shopper never sees the 98.
They see a gap, or they see the product, and they decide from there.
