How to build a warehouse-to-store delivery plan: delivery days, vehicle fill and store capacity
Who it is forGrocery chains, logistics and distribution managers, replenishment planners, area and store operations
Searches such as "supermarket delivery days" and "delivery tracking schedule" show how much the delivery calendar shapes a grocery store: goods receipt time sets the staff plan, the delivery interval sets the shelf layout and the dispatch quantity sets how full the backroom gets. In grocery, warehouse-to-store distribution is not a one-off decision but a flow repeated every day. This guide covers how the delivery day calendar is built, how frequency affects stock and shrink, how to balance vehicle fill against store capacity and which measures track deliveries.
How is the delivery day calendar built?
The calendar is a three-way matrix: store, product group and day. Product groups are split by temperature regime, because each needs its own vehicle or compartment: ambient grocery, chilled products, frozen products, fruit and vegetables, and bread. The delivery frequency for each group is set separately according to shelf life and the store's sales volume.
Four principles build the calendar. Higher-turnover stores receive more frequent deliveries. Stores on the same route are grouped on the same day. Goods receipt time does not clash with the store's peak hours. The order cut-off is set before delivery by the warehouse preparation time plus travel time.
The calendar is not written once and left. It is recalculated when a store's turnover, capacity or route structure changes; new store openings and closures change routes directly.
- Delivery interval (days)
7 ÷ Deliveries per week- Order cut-off time
Delivery time − (Warehouse preparation time + Travel time)
| Store | Turnover class | Ambient | Chilled | Fruit and veg | Route |
|---|---|---|---|---|---|
| Store A | High | Mon, Wed, Fri | Daily | Daily | Route 1 |
| Store B | Medium | Tue, Fri | Mon, Wed, Fri | Daily | Route 2 |
| Store C | Low | Thu | Tue, Fri | Mon, Wed, Fri | Route 2 |
The days in the calendar are illustrative. B and C share a route; C's ambient day falls on a day when B has no delivery, so the vehicle is balanced between the two stores.
How does delivery frequency affect store stock and shrink?
The delivery interval directly sets the stock held in store. At each delivery the store receives what it will sell until the next one, and that stock runs down between deliveries. Average stock is close to half a delivery plus safety stock. The longer the interval, the larger each delivery and therefore the average stock.
The benefits of more frequent delivery lie in three places: less store stock, fresher product and less need for backroom space. So do the costs: more trips, more handling and less load per vehicle. The right frequency balances the two and is set separately by product group; in fresh food the shrink benefit dominates, in ambient grocery the transport cost.
Safety stock changes with the interval too: in a periodic review system, safety stock has to cover the order interval as well as the lead time. That calculation is covered in the safety stock guide.
- Dispatch quantity
Forecast sales to next delivery + Safety stock − Store stock − Goods in transit- Average store stock
Daily sales × Delivery interval ÷ 2 + Safety stock
When vehicle fill and store capacity conflict, which comes first?
In its 2024 integrated annual report, BİM states as a logistics principle that its vehicles run at 100 per cent fill. Fill is the largest lever on delivery cost: a half-loaded vehicle carries the same road, fuel and driver cost with half the load. The lever grows with scale — in the same report BİM describes 68+2 logistics centres in Türkiye and a fleet of 1,358 vehicles; ŞOK Marketler served 11,057 stores from 51 warehouses as at 30 September 2025; and Migros opened 10 new distribution centres in 2025, taking its total distribution centres and warehouses to 73.
The conflict starts when more goods are sent than a store needs, in order to fill the vehicle. The surplus does not fit the shelf and waits in the back room; on fresh food it turns into shrink, on dry goods into count variance and back-room clutter. The warehouse's cost has been moved to the store, and in the report logistics looks good while the store looks bad.
The rule is clear: store capacity is the constraint, vehicle fill is the target. Fill is raised by pulling forward the next delivery's requirement, and only with long-shelf-life products that fit the back room. Where that is not enough, routes are combined or the delivery day is shifted. A vehicle is never filled with fresh food.
- Vehicle fill rate
Loaded volume (or pallets) ÷ Vehicle capacity × 100- Quantity eligible as filler
min(Free volume on the vehicle, Free back-room capacity at the store)Applied only to long-shelf-life products.
| Order | Constraint | Why |
|---|---|---|
| 1 | Shelf life | The quantity of fresh food is limited by its selling window; the surplus turns into shrink |
| 2 | Store shelf and back-room capacity | Goods that do not fit turn into shrink or count variance |
| 3 | Minimum delivery pack | Cases and pallets are not split; quantity is rounded to a multiple of the pack |
| 4 | Vehicle fill | First pull forward long-shelf-life requirements, then combine routes or shift the day |
Which measures track delivery performance?
A delivery scorecard carries four measures. Vehicle fill and on-time delivery show the efficiency of logistics. Store receiving variance and capacity-breach rate show the health of the agreement between warehouse and store: did the right quantity arrive, and was the store in a position to take it?
Receiving variance is the most neglected of the four. Where goods receipt is not done by scanning, a shortage or surplus between warehouse and store is invisible on the day; months later it surfaces in the count as stock loss, and its cause can no longer be found.
Return legs belong in the plan as well. Store-to-store transfers and the crates, pallets and returns collected back to the warehouse are planned onto the return journey; a vehicle running back empty gives away part of the fill gained on the way out.
- On-time delivery rate
Deliveries within the delivery window ÷ Total deliveries × 100- Store receiving variance rate
|Dispatched − Received| ÷ Dispatched × 100- Capacity-breach rate
Delivery lines above store capacity ÷ Total delivery lines × 100
How does Mindpera run the delivery plan?
In Mindpera the delivery list is produced in Mind Send. Recent rate of sale, the history of comparable products and store cluster coefficients are read as the demand signal; the forward sales expectation comes from a forecasting model. Warehouse stock, store shelf capacity and the minimum delivery pack enter as constraints, the quantity per store is calculated, and every line carries the constraint that shaped it. The planner approves, rejects or changes the line; once approved, the list becomes a dispatch order in the ERP. On store-to-store transfer proposals, transfer cost is part of the calculation.
Store capacity is defined in Mind Space as selling area, shelf metres and back-room volume; the capacity constraint feeds straight into the delivery proposal and any line above capacity is flagged. Vehicle routing and load planning stay in the transport system; the job of Mindpera is that the list loaded onto the vehicle matches demand and store capacity. In Mind Stock, dispatch and goods-receipt movements are posted to the stock balance and the variance is tracked by product and location.
- Mind Send: demand signal, constrained delivery proposal, line-by-line approval and store-to-store transfer
- Mind Space: shelf and back-room capacity model, flagging of lines above capacity
- Mind Stock: dispatch and receiving movements, variance by product and location
- Agents find capacity breaches and receiving variances, open a task for the owner and follow it until it closes
Where dispatch, goods receipt and stock data are scattered between the warehouse system and the ERP, installation brings them into a single data model.
Frequently asked questions
- How are grocery delivery days set?
- With a store, product group and day matrix. Product groups are separated by temperature regime and each one's frequency is set from shelf life and store turnover. Stores on the same route are grouped onto the same day, the goods receipt slot is kept away from peak trading hours, and the order cut-off is set from warehouse picking time plus travel time.
- How many deliveries a week should a store get?
- There is no fixed number; it follows the product group and the store's turnover. As frequency rises, store stock and shrink fall while trip and handling costs rise. For example, in a store selling 60 cases of dry goods a day, average stock is 270 cases with one delivery a week and 130 cases with three. The decision comes from comparing carrying cost with transport cost.
- How is the delivery quantity calculated?
- Safety stock is added to the sales forecast up to the next delivery, then store stock and goods in transit are deducted. The result is capped by the store's shelf and back-room capacity and rounded to a multiple of a case or pallet. On fresh food, the part of store stock that will not sell by the next day is deducted as well.
- How is vehicle fill rate calculated?
- The volume or number of pallets loaded is divided by vehicle capacity and multiplied by a hundred. BİM's 2024 integrated annual report states as a logistics principle that its vehicles run at 100 per cent fill. When fill is raised, filler goods are limited to the store's free back-room space and chosen only from long-shelf-life products.
- Which comes first, vehicle fill or store capacity?
- Store capacity is the constraint, vehicle fill is the target. When goods that do not fit the shelf are sent to fill a vehicle, the surplus waits in the back room; on fresh food it becomes shrink, on dry goods a count variance. Fill is raised first by pulling forward long-shelf-life requirements, then by combining routes or shifting the delivery day.
- Which measures track delivery performance?
- Four: vehicle fill rate, on-time delivery rate, store receiving variance and capacity-breach rate. The first two show the efficiency of logistics, the last two the health of the agreement between warehouse and store. When fill is low and capacity breaches are happening at the same time, filler goods are going to the wrong stores and the filler rule needs correcting.