What should an inventory report show before you place an order?
Stock on hand is only part of the picture. Before ordering, review available stock, sales pace, inbound deliveries and lead times together.
One stock balance can hide several different situations
A warehouse holds 100 units of a product. Another order may not look urgent. But some units may already be reserved, others may be unavailable for sale, and the supplier may need two weeks to deliver the next batch.
An ordering decision needs more than a physical balance. Read several measures together: what can be sold now, how quickly it is selling and when the next delivery will arrive.
The numbers in this article are illustrative. Each company needs an ordering policy that reflects its demand, supply conditions and service targets.
1. Separate the stock that is actually available
Show physical stock, reserved quantities and stock available for sale separately. Put inbound goods in another column with their expected receipt date. They are not stock available today.
For example, physical stock is 100 units, with 20 reserved and eight blocked for a quality check. If these groups do not overlap, 72 units are available in this example. First check the meaning of the fields in your actual system: an “available” quantity may already account for restrictions, so do not subtract them twice.
With multiple warehouses, a sufficient company-wide balance can hide a shortage at a particular branch. Review stock at the location where demand occurs.
2. Put the sales pace in context
Average sales over the past 30 days are a useful starting point, but not an exact forecast. Promotions can temporarily increase sales. A stockout can reduce recorded sales even when customers still want the product.
Alongside the average, show the selected period, promotion dates and days when the product was unavailable. If you calculate the pace using only days with stock available, state that in the definition. Seasonal products often need another comparison, such as the equivalent period in the previous year.
3. Compare days of cover with lead time
If 72 units are available and the selected period shows average sales of six units a day, a simple estimate gives 12 days of cover: 72 ÷ 6 = 12. This assumes the sales pace stays constant and does not add inbound stock.
Suppose supplier lead time is ten days and the company has chosen an additional three-day buffer for this product. In this simplified example, 12 days is below the 13-day reference threshold. Flag the product for review. This is not an instruction to order a particular quantity: check inbound deliveries, expected receipt dates, minimum order quantities and expected demand first.
When sales are zero, avoid displaying infinite cover. A label such as “No sales recorded in the period” is more useful, followed by a check of whether the product is new, seasonal or no longer moving.
4. Look for ageing stock as well as shortages
An ordering view should not focus only on fast-selling products. Separate goods with no sales in the selected period and balances that are high relative to normal demand.
Useful fields include the last sale date, batch receipt date and, where relevant, expiry date. These fields are not interchangeable. A sale yesterday does not mean that an old batch has left the warehouse. Batch age and time since the last sale answer different questions.
5. Build a working list for the team
After the overview, a Power BI page should let the reader inspect individual products. The person responsible needs to see the reason behind a warning, not just a colour. These fields provide a useful starting point for a working list.
- Product, warehouse and the last data refresh time.
- Available, reserved and blocked quantities with clear definitions.
- Sales pace, its calculation period and days of cover.
- Inbound quantity and expected receipt date.
- Lead time and the reason for review.
- A responsible person and a short note on the next action.
Start with one product group and validate the result
Before automating the full assortment, choose one product group and compare the report with the warehouse and purchasing teams' knowledge. Define available stock, how inbound quantities are represented and when the information refreshes. A few known shortages make useful cases for checking whether warnings appear in the right places.
These questions are a practical starting point for planning inventory analytics with DataStudio. The aim is a working list the team can use to plan orders, transfers and stock checks.