Inventory how-to

How to forecast sales when a product was out of stock for weeks

Exclude the out-of-stock days from your sales average instead of letting them drag it down.

Short answer: Exclude the out-of-stock days from your sales average instead of letting them drag it down. Calculate daily sales using only the days the product was actually available to buy, then apply that corrected rate to your reorder point and order quantity formulas.

Why the raw average is wrong

If you divide total units sold by total calendar days, every day the product was unavailable counts as a zero-sale day. That pulls the average down and understates real demand. The fix is simple: only count days when the product was actually orderable, and divide sales by that smaller number of days.

Watch for the restock spike

When a popular item comes back in stock, you often see a burst of catch-up orders from people who were waiting. That burst is not your normal daily rate either. If you include those spike days in your "in-stock" average, you will overstate demand. A reasonable approach is to exclude the first few days after restock from the calculation, then use the days after that settle down.

Check for a lasting effect

A long stockout can cost you customers who switched to a competitor or found another product. Sales after restock sometimes come back lower than before, at least for a while. Compare the sell-through rate in the two or three weeks after restock against the pre-stockout rate. If it is meaningfully lower, lean toward the newer, lower number rather than averaging it in with the old one.

Keep a record for next time

Note the stockout dates for each affected SKU somewhere you can find them later, such as a spreadsheet or a note in your supplier file. The next time you review that product's sales history, you will remember to exclude those dates again rather than repeating the same mistake.

Step by step

  1. List the exact dates the product was unavailable to buy.
  2. Count the number of days it was actually in stock during your sales window.
  3. Divide total units sold in that window by the in-stock days only, not the full calendar span.
  4. Exclude the first few days after restock if you see a catch-up order spike.
  5. Compare pre-stockout and post-restock sell-through rates to check if demand has shifted.
  6. Apply the corrected daily sales rate to your reorder point and order quantity formulas.
  7. Note the stockout dates somewhere you will see them next time you review this SKU.

Worked example

A supplement sold 180 units over 30 days, but it was out of stock for 10 of those days. Naive math gives 180 / 30 = 6 units a day, which is too low. Correct math uses only the 20 in-stock days: 180 / 20 = 9 units a day. With a 14-day lead time and 5 days of safety stock, the reorder point is 9 x (14 + 5) = 171 units, not the 114 units you would get using the naive 6-per-day figure.

How SteadyShelf helps

SteadyShelf's 28-day sales window will include zero-sale days from a stockout and understate the true daily rate, since it does not automatically detect or exclude out-of-stock periods. Work around this by manually raising the safety days or suggested quantity for that SKU for a cycle or two until the window rolls past the stockout, and watch the weekly reorder email closely during that stretch.

$29/month flat, unlimited products and suppliers, 30-day free trial. Run the numbers now with the free reorder point calculator.

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FAQ

Should I use the pre-stockout sales rate or the post-restock rate?

Yes, but treat it as a floor, not the real answer. If the product sold out fast once restocked, true demand is higher than the capped number shows. Watch sell-through speed after restock and adjust the next order up if it moves faster than the forecast assumed.

What if the product was out of stock for months, not weeks?

Set safety days higher for that SKU for a few cycles, and reorder before you hit zero again. If the stockout was caused by a slow supplier, also check whether you need a backup supplier or a longer lead time assumption for that item.

Let SteadyShelf do this math for every SKU

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