Available-to-promise calculated from a nightly snapshot is not availability. It is a guess that the sales desk is contractually committing to.
A customer asks whether you have forty units. The sales desk checks a number, says yes, and the order is accepted. The warehouse discovers on Thursday that eighteen of those units were committed to another order on Tuesday.
Everyone involved behaved correctly. The number was wrong before anybody looked at it.
On hand is the easy part and the part most systems show. Real availability is on hand, minus committed, minus allocated, plus inbound within the promise window, across every location including stock in transit.
A distributor quoting from on-hand alone will oversell whenever demand is concentrated — which is to say, on exactly the lines that matter.
A single overselling incident is not one cost. It is the expedited freight to cover the shortfall, the partial shipment and its administration, the credit note, the customer call, and the goodwill nobody puts a number on.
In thin-margin distribution, one of these consumes the profit on several good orders. It is worth calculating your own figure before deciding this is a minor problem.
The fix is architectural rather than procedural. Quoting has to read live availability rather than a periodic copy.
Because it is where the promise is made. Improvements downstream — better picking, faster replenishment — help, but they cannot repair a commitment that was wrong when it was given.
Connecting Dynamics 365 Sales to live availability and contract pricing changes the quality of the promise, and everything downstream inherits that.
Fill rate and order accuracy are the obvious ones. The more revealing measure is the number of orders that required an intervention after acceptance — a short shipment, a substitution, an expedite, a credit.
Most distributors have never counted it. The number is usually higher than expected and it drops fast.
Send us an anonymised order file and your pricing rules for one customer segment, and we will demonstrate quoting against live availability using your product data.
If this describes your situation, tell us where it hurts most. We will tell you what it would realistically take to fix in your environment, what we would measure, and whether we think it is worth doing at all.
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Gross margin by product is known in every distribution business. Cost to serve by customer is known in very few, and it is the more decision-useful number.
Describe the situation in your own words.
