On-Shelf Availability in Saudi Retail: How to Measure It and Close the Gap
On-shelf availability is the percentage of time a shopper can actually buy your product when they reach for it. It is the most direct measure of whether your route to market works, and the one most brands get wrong — because the number they quote comes from inventory systems, and inventory systems describe warehouses, not shelves.
A product can be in stock at the distributor, in stock at the store, in the back room, and still unavailable. The shopper does not distinguish. They buy a competitor.
This article covers how to measure on-shelf availability properly in the Saudi market, how to establish a benchmark you can trust rather than borrowing one, how to diagnose which of the several possible causes is driving your gaps, and what actually closes them.
A note on benchmarks
Published on-shelf availability benchmarks circulate widely and should be treated carefully. They vary enormously by category, channel, market and — most importantly — by measurement method. An availability figure measured on a scan-data proxy is not comparable to one measured by physical audit, and the two can differ by a wide margin on the same shelf.
Rather than anchoring on someone else’s number, the useful exercise is to measure your own with a defined method and then improve against it. A brand that knows its true availability in its own top 200 Saudi outlets, measured consistently, is in a far stronger position than one quoting an industry average.
Everything below is oriented toward getting you that number.
Why the Saudi market makes this harder
Two channels, two measurement problems
Saudi modern trade gives you some visibility — scan data from the larger banners, planograms to measure against, and store systems that record inventory. Traditional trade gives you almost none: thousands of independent groceries with no data, no planogram and no obligation to share anything. If a meaningful share of your volume moves through traditional trade, most of your availability picture is currently an estimate. We covered the operating split in combating out-of-stock across channels.
Distributor-owned replenishment
Where a distributor owns the route and the ordering decision, availability failures may originate outside your visibility entirely — a distributor allocation decision, a van that skipped a route, a credit hold on an outlet. You will see the symptom on the shelf and have no access to the cause.
Extreme seasonal demand swings
Ramadan and Eid compress a disproportionate share of annual volume into a short window. Replenishment cycles built for normal demand fail under peak demand, and availability collapses precisely when the commercial cost of failure is highest. The same is true to a lesser degree of back-to-school and National Day.
Geographic spread
Riyadh, Jeddah and the Eastern Province plus a long tail of secondary cities means route frequency varies widely across the estate. Availability in a store visited weekly and a store visited monthly are not comparable problems, and a national average obscures both.
How to measure on-shelf availability
There are three methods, and the difference between them is not academic — they produce materially different numbers on the same shelf.
Method 1: Physical audit
A field rep checks whether each planned SKU is physically present and purchasable at the moment of visit.
OSA = SKUs present and purchasable ÷ SKUs planned for that store × 100
This is the ground truth. Its limitation is that it is a snapshot: it tells you availability at 11am on Tuesday, not across the week. A product that is out of stock every Saturday will look fine if you always visit on Tuesdays.
Method 2: Scan-data proxy
Where you have store-level scan data, a SKU that normally sells and records zero sales for a period is inferred to be unavailable.
This covers all days rather than visit days, which is its main advantage. It is also systematically imperfect: slow-moving SKUs generate false positives, and it cannot detect a product that is present but unfindable — wrong location, blocked by a competitor, or on a shelf the shopper does not reach.
Method 3: Combined
Scan-data proxy for continuous coverage in modern trade, physical audit for ground truth and for the whole of traditional trade, with the audit used to calibrate the proxy. This is what most mature operations converge on.
Defining the denominator
This determines your number more than the method does, and it is where most inconsistency comes from. SKUs planned for that store means the agreed assortment for that specific outlet, not your full national range. Measuring a 60-SKU portfolio against a store that only lists 20 produces a meaningless figure. Get the outlet-level assortment right first; it is a master data exercise and it gates everything else.
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Diagnosing the cause
An availability gap is a symptom with at least six distinct causes, and they require completely different fixes. Treating them as one problem is why availability programmes stall.
True stockout
No stock in the store at all. Cause sits upstream: forecast error, distributor allocation, delivery failure, credit hold. The fix is in the supply chain, not the field.
Back-room stock
Stock is in the store but not on the shelf. This is frequently the largest single category in modern trade and the most fixable, because the stock has already been paid for and delivered. The fix is a replenishment prompt to store staff, which a field visit can trigger immediately. Our note on optimising stock replenishment covers the mechanics.
Phantom inventory
The store system says stock exists, so no reorder triggers, but the shelf is empty. Caused by shrinkage, mis-scanning at receipt, or misplaced stock. Self-perpetuating until someone physically counts, which is why it can persist for months.
Planogram gap
The SKU has no assigned space, so it cannot be available regardless of stock. This is a compliance failure presenting as an availability failure, and it is the most commonly misdiagnosed of the six. Worth reading alongside planogram compliance measurement, since the two problems compound: a stockout causes facing loss, and facing loss causes future stockouts.
Present but unfindable
Physically on the shelf, in the wrong location, behind a competitor, or at a height the shopper does not scan. Available by any audit definition and unavailable in practice. Only detectable by physical observation.
Delisted without notice
The store has stopped carrying the SKU. Not an availability problem but a distribution one, and it will sit in your availability reporting as a permanent failure until someone reconciles the assortment.
Why the split matters commercially
Back-room stock and planogram gaps are field problems, fixable this week at close to zero marginal cost. True stockouts and phantom inventory are supply chain and retailer systems problems requiring different owners and longer timelines. A brand reporting a single availability number cannot tell which it has, and will typically respond by adding field visits — which fixes only two of the six causes.
Closing the gap
In rough order of return on effort.
- Fix the outlet-level assortment master. Unglamorous and gating. Until the denominator is right, every subsequent number is disputed and the reporting gets ignored.
- Add a back-room check to every visit. One question — is there stock behind the shelf — converts an availability observation into an immediately actionable prompt. Cheapest high-return change available.
- Separate the six causes in your reporting. Requires only a cause field on the availability check. Changes what the organisation does with the data more than any other single change.
- Move from reporting to alerting. An availability failure detected today and routed to someone today is worth many times a weekly report. This is where field capacity produces the most value in dense urban estates.
- Prioritise by volume, not by percentage. A 5% gap in your top 20 Saudi outlets costs more than a 25% gap across 300 small groceries. Weight the reporting accordingly.
- Build a peak-season replenishment plan explicitly. Ramadan availability should be planned as a distinct operating mode with higher visit frequency and pre-agreed stock cover, not as normal operations under strain.
- Feed the causes back upstream. Phantom inventory and true stockouts need to reach supply chain and the retailer. Availability data that only circulates within commercial teams cannot fix its own largest causes.
Point four deserves emphasis. Most availability programmes produce a weekly report that a brand manager reads and cannot act on, because by the time it arrives the situation has changed. The shift from periodic reporting to same-day exception alerting is what turns availability measurement into availability improvement. We covered the field-side implications in on-shelf availability metrics and strategies.
What to track
Four measures cover most of what a commercial team needs.
- Weighted OSA by channel and banner. Weighted by outlet volume, split modern and traditional trade. The headline number.
- Cause breakdown. The share of gaps attributable to each of the six causes. Tells you who owns the problem.
- Time to correction. From detection to resolution. The metric that best reflects whether your operation is responsive or merely observant.
- Repeat-offender outlets. Stores failing across multiple cycles. Usually a small set, usually a specific fixable cause, and usually invisible in aggregate reporting.
The last one is consistently the highest-value report and the least commonly built. Chronic availability failure concentrates in a minority of outlets, and identifying them turns a broad problem into a short, addressable list.
Availability in traditional trade
Most on-shelf availability methodology assumes modern trade, because that is where the data is. In Saudi Arabia a substantial share of volume moves through independent groceries and convenience outlets where none of it applies, and this is where availability programmes usually stop short.
What is different
No scan data, so the proxy method is unavailable. No planogram, so there is no agreed assortment to measure against. Low individual outlet volume, so an audit programme has to be cheap per visit to be viable. Ordering often decided by the shopkeeper on the spot rather than by a replenishment system.
What to measure instead
Compliance-based availability does not translate. Two measures that do:
- Coverage: the proportion of outlets in a territory carrying your must-stock list at all. A distribution measure more than an availability one, and usually the bigger commercial gap in traditional trade.
- Must-stock availability: of the outlets that do carry the SKU, the proportion where it is physically present and purchasable. Measured against a short must-stock list per outlet type rather than a full assortment.
A five-SKU must-stock list checked reliably across a wide estate is worth considerably more than a forty-SKU audit completed inconsistently. Keeping the check short is what makes the visit economics work at low outlet volume. Our note on merchandise tracking covers the field mechanics.
The van sales dimension
Where you reach traditional trade through van sales or direct store delivery, availability and ordering are the same event: the rep who finds the gap is the person who can fill it immediately. This makes traditional trade availability structurally more fixable than modern trade availability, provided the gap is detected. The constraint is visit frequency, not diagnosis.
The commercial case for closing the gap
Availability improvement competes for budget against activity that looks more like growth, so the case needs framing in terms a commercial director will act on.
Calculate your own loss, roughly
You do not need precision to make the case. A rough estimate from your own data:
Estimated annual loss = Annual volume ÷ (OSA rate ÷ 100) × (1 − OSA rate ÷ 100) × Substitution factor × Unit margin
The substitution factor is the share of shoppers who buy a competitor rather than deferring or switching pack size — the portion of the gap that is a genuinely lost sale rather than a delayed one. It varies by category and is worth estimating conservatively, because a conservative number that survives scrutiny is more useful than an aggressive one that does not.
Even at conservative assumptions, the arithmetic on a mid-sized Saudi portfolio typically produces a number large enough to fund the measurement programme several times over. Run it on your own figures rather than accepting the assertion.
Frame it as retailer revenue, not brand housekeeping
An out-of-stock costs the retailer a sale as well as you. Presenting your availability performance as category revenue protection changes the retailer conversation from a brand request into a shared operational interest, and it is considerably more persuasive in a category review. This is the same framing that works for portfolio visibility generally.
Expect the fixable share to be high
The reason availability programmes tend to pay back quickly is the cause breakdown. Back-room stock and planogram gaps — both field-fixable at near-zero marginal cost — usually account for a substantial portion of gaps in modern trade. Measuring the split is what lets you make a funding case on the cheap causes rather than the expensive ones.
Two questions worth settling early
How often should we measure?
Frequently enough that the data is actionable and consistently enough that the trend is real. For most Saudi portfolios that means a defined cycle per channel — higher frequency in key accounts where volume justifies it, lower in the traditional trade tail — with the same method every cycle. Varying the visit day within the cycle matters as much as the frequency, since a fixed weekday hides day-of-week patterns entirely.
Should availability be a field team KPI?
Carefully. Making availability a rep KPI creates an incentive to record favourable results, particularly where the rep both measures and is measured. The safer construction is to hold the field team accountable for detection and correction — visit completion, cause recorded, time to correction — and to treat the availability rate itself as an outcome measure owned further up. Holding someone accountable for a number they also report is the fastest way to lose the number’s credibility.
Establishing your own benchmark
A practical four-week exercise that produces a number you can defend.
- Week 1. Fix the assortment master for your top 100 Saudi outlets by volume. Confirm what each store should be carrying.
- Week 2. Define the method in writing: physical audit, presence and purchasability, cause captured on every gap. Vary the visit day across the sample so you are not measuring one day of the week.
- Week 3. Measure the full sample. Record cause on every failure without exception.
- Week 4. Report weighted OSA with the cause breakdown, split by channel. Identify repeat-offender outlets.
That figure is your baseline. It will very likely be lower than your assumption, and the cause breakdown will very likely show that more of it is fixable in the field than you expected. Repeat the identical measurement each cycle and the trend becomes the management tool.
Shelvz captures availability, cause, back-room stock and planogram gap in a single field check, weights reporting by outlet volume, and routes exceptions the same day rather than in a weekly report. To see it against your own Saudi outlet list, book a walkthrough.
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