SYNTHETIC DEMONSTRATION · WEB-076
See why a stock plan changes
Use one filter item at one location to separate demand, delivery time and the buffer you choose. These invented figures show arithmetic and tradeoffs. They are not customer results, a purchasing recommendation or a validated stock policy.
1. Check a simple forecast first
Invented demand for days 1–7 is 8, 12, 10, 9, 11, 10, 10 units. Its total is 70, so the average is ten a day. At the end of day 7, use that average to forecast ten units on each of days 8–11. Keep those forecasts fixed; do not use the later values to set them.
| Day | Forecast | Demand | Difference size |
|---|---|---|---|
| 8 | 10 | 12 | 2 |
| 9 | 10 | 8 | 2 |
| 10 | 10 | 14 | 4 |
| 11 | 10 | 10 | 0 |
The average size of the daily difference is (2 + 2 + 4 + 0) ÷ 4 = 2 units. Customers needed 44 units. The forecast was 40, which was four too low. Another simple forecast repeats day 7's demand on each future day. It also predicts ten a day, so its errors are the same. Neither wins here. Four invented days cannot show how accurate a real forecast would be or how demand changes through the year. They cannot support a service guarantee.
2. Keep the rule and assumptions visible
For the separate scenarios below, use ten units per day as the planning forecast. The order trigger is expected demand during the delivery wait plus the chosen safety stock: 10 × 4 + 10 = 50 units in the base case. This is when to order, not how many to buy.
The rule compares the trigger with inventory position: usable stock on hand, plus quantities already ordered, minus unfilled customer demand. Each example starts when stock reaches the reorder level. No earlier deliveries are due, no customer orders are waiting, and no stock has been set aside. The stock available at the start therefore matches the reorder level. A new supplier order is placed at that point. This example does not calculate how much to buy.
Stock is checked as it changes. In each example, it reaches the reorder level exactly. Every filter is the same item and can fill the same customer need. No returns, damage, transfers or earlier deliveries occur. In each case, customers need the same number of filters each day until delivery arrives. The delivery arrives after the stated number of full days. Each result shows the stock just before it arrives. Each case starts afresh; they do not follow one another. They also use different figures from the forecast check above.
Base case
Plan: ten/day, four days, buffer ten. Start: 50.
Actual: ten/day for four days → demand 40.
10 left; 0 unmet.
Higher demand
Same plan and starting stock: 50.
Actual: 14/day for four days → demand 56.
0 left; 6 unmet. Demand exceeded the forecast.
Unexpected supplier delay
Same plan and starting stock: 50.
Actual: ten/day for six days → demand 60.
0 left; 10 unmet. Daily demand matched; the wait changed.
Plan for a six-day wait
Plan: ten/day, six days, buffer ten. Trigger and start: 10 × 6 + 10 = 70.
Actual: ten/day for six days → demand 60.
10 left; 0 unmet. Earlier ordering would require that higher starting stock.
Choose a bigger buffer
Plan: ten/day, four days, buffer 30. Trigger and start: 10 × 4 + 30 = 70.
Actual: ten/day for four days → demand 40.
30 left; 0 unmet. Twenty more units remain than in the base case.
Slower demand: surplus to review
Original plan and starting stock: 50.
Actual: six/day for four days → demand 24.
26 left; 0 unmet. Sixteen more than the original ten-unit buffer. This is possible overstock to review, not proof those units have no future use.
For each case: demand before receipt = actual daily demand × actual days. Remaining stock = the larger of zero or starting stock minus demand. Unmet demand = the larger of zero or demand minus starting stock. Shortages are counted as unmet units; the example does not decide whether customers wait or sales are lost, or what happens after receipt.
3. Stop when an input is missing
Invalid example: ten/day, a blank delivery wait and buffer ten. Result: no trigger calculated. Ask purchasing to confirm the wait. Treating a blank as zero would incorrectly produce ten units. Correct quantities below zero or entries that are not numbers. This example also requires a delivery wait above zero and one consistent time unit. Zero demand or zero buffer is allowed as an explicit scenario, not a missing value.
This static page contains no input form or automatic validation. These are checks to apply in a real model. Count stock in the same unit throughout, and measure all waits in days. If a calculation gives part of a unit, agree how to round it before ordering. These examples use whole units.
4. Agree what the buffer should protect
The example chooses extra stock of ten or 30 filters. It does not calculate either amount from a target for filling customer orders. Your team needs to agree the availability it wants—for example, how often stock should last until the next delivery. That is different from the share of units supplied immediately. This example calculates neither the chance of avoiding a shortage nor the share of demand supplied immediately.
Check forecasts against demand across many real deliveries. Also review changing delivery times, seasonal or irregular demand, shelf life, minimum order sizes, storage and cash limits. If stock is checked weekly, the plan must cover the days until the next check as well as the delivery wait. This example assumes stock is checked as it changes. The example does not find the lowest-cost plan or the best amount of extra stock.