Start with something familiar
You might buy milk whenever the carton becomes low, or inspect the fridge every Sunday and buy enough for the coming week. Both habits can work, but the Sunday shopper must protect the time until the next shop as well as delivery time. Looking only at what is on the shelf can also mislead you if a delivery is already booked. A good shopping rule counts what is coming and what has already been promised.
Words to know: Inventory position, Review period, Lead time.
Use position for the order decision
For this lesson, inventory position is usable on-hand plus open supply minus backlog. It measures coverage already owned or ordered, not what can ship today. With twenty on hand, thirty on order, and five backlog, position is forty-five. Keep an event-date stock check as well, because the thirty may arrive too late for an immediate obligation.
A continuous-review rule checks after each relevant event. In our simplified rule, order a fixed lot when position is at or below the reorder point. Mean daily demand of ten and lead time of three days imply thirty units of mean lead-time demand. Add safety stock of ten to set a reorder point of forty. Position forty-five does not trigger a new lot.
Protect the review interval
A periodic-review rule checks only on scheduled review days. Its target must protect both lead time and the time until the next review. With review interval four days and lead time three, mean demand over the seven-day protection window is seventy. With a stipulated buffer of ten, the order-up-to target is eighty. At position forty-five, order thirty-five.
The same buffer was deliberately stipulated to isolate the effect of review frequency. In a real uncertainty calculation, a longer protection window may need a larger buffer. The order-up-to target is a position target, not an instruction to place eighty units every review. Subtract the existing position and round only after applying actual pack or minimum-order rules.
Test boundary cases
Document the equality rule at the reorder point. Different systems can use different triggers, and a hidden difference can explain one-day disagreements. Also document whether orders are permitted outside the review day when a serious risk appears. An exception process should say who can act and what evidence is needed.
A policy should be judged with a time sequence, not one snapshot. Simulate demand, receipts, position, and orders over several reviews. Avoid using the same arriving order twice, once in stock and again in open supply. On receipt, transfer the quantity from open supply to on-hand; position should not jump merely because ownership changes status.
- Define units and event
- Reconcile eligible inputs
- Apply the stated rule
- Check feasibility
- Explain the decision
Northstar worked decision
All quantities and costs below are fictional and self-contained. Apply the stated timing and unit conventions.
| Input | Value |
|---|---|
| On hand | 20 |
| Open supply | 30 |
| Backlog | 5 |
| Daily mean | 10 |
| Lead days | 3 |
| Review days | 4 |
- 1. Position = 20 + 30 - 5 = 45.
- 2. Continuous reorder point = 10 × 3 + 10 = 40; no order at position 45.
- 3. Periodic target = 10 × (3 + 4) + 10 = 80; order 80 - 45 = 35.
Inventory position is 45 bottles.
Assumptions
- Use only the quantities and timing stated; no hidden receipts, losses, or substitutions.
- Fractional mathematical results are rounded only where whole-unit or pack rules are explicitly stated.
Where this can fail: This is a transparent teaching model. Confirm calendars, data definitions, and operating constraints before using an analogous policy in practice.
Build, test and explain a plan
Simulate twelve days with daily demand ten, opening on-hand fifty, no backlog or open supply, and receipts before demand. Continuous policy: check after daily demand, reorder point forty, fixed lot forty, receipt before demand three days after release. Periodic policy: review after demand on days 1, 5, 9, target eighty, same three-day lead time. Use no rounding. The eight-hour allocation is a self-paced estimate, not experimentally validated; it includes model building, scenario testing, a memo, and teach-back.
Use paper or a spreadsheet. The estimates below include the study and worked example already on this page.
| Estimated hours | Activity |
|---|---|
| 0.5 | Study the reading and make a one-page definition sheet. Mark every unit, date convention, and inclusion rule. Explain the difference between the policy input and the outcome being measured. |
| 0.5 | Recalculate the worked example independently, without copying the displayed result. Show intermediate arithmetic and reconcile the answer to the physical story. Note one assumption that could change the decision. |
| 3 | Build a reusable multi-period spreadsheet from the supplied lab data. Simulate twelve days with daily demand ten, opening on-hand fifty, no backlog or open supply, and receipts before demand. Continuous policy: check after daily demand, reorder point forty, fixed lot forty, receipt before demand three days after release. Periodic policy: review after demand on days 1, 5, 9, target eighty, same three-day lead time. Use no rounding. Keep inputs separate from formulas, add a clear output table, and include a check column that flags any quantity or timing inconsistency. Walk through the first and last rows manually. |
| 2 | Create separate named scenario tabs. For each policy separately, replace day-6 demand ten with twenty; then change lead time to four days while leaving the original settings unchanged. Count shortage events and explain exposure. Preserve the baseline and record both changed inputs and changed outputs. Explain any outcome that stays the same, since a binding constraint or a measurement rule can make an intervention ineffective. |
| 1 | Write a 400-word decision memo naming your recommended action, evidence, assumptions, responsible role, and next check. Compare at least two alternatives using your table. State one limitation that could reverse the recommendation and what additional evidence would resolve it. |
| 1 | Teach the result aloud in five minutes using an original diagram. Then review every formula, answer the module questions relevant to this lesson, and write a short correction log. Use the remaining time to reproduce the key calculation from a blank sheet. |
Your deliverables
- An auditable multi-period workbook with baseline and named stress cases.
- A decision memo with numerical evidence and explicit limitations.
- An original explanatory diagram and a correction log.
Check your practice work
- Inventory position is 45 bottles.
- At position 40 the stated continuous rule triggers a fixed lot.
- If pack size is twelve, periodic order 35 rounds to 36 and position becomes 81.
- Continuous baseline releases forty after demand on days 1,5,9; receipts occur before demand on days 4,8,12. No shortage occurs.
- Periodic baseline orders forty on day 1, forty on day 5, forty on day 9, also with no shortage.
- With four-day lead and unchanged rules, base opening fifty still prevents a shortage; receipts occur days 5,9,13. The demand-spike case must be simulated separately as instructed, rather than silently combined with longer lead time.
- Both baseline policies have daily ending stock 40,30,20,50,40,30,20,50,40,30,20,50.
- With only the day 6 demand spike, continuous releases forty on days 1,5,8,12; periodic releases 40 on day 1,40 on day 5,50 on day 9. Neither has a shortage.
- With only four-day lead, daily ending stock 40,30,20,10,40,30,20,10,40,30,20,10 for both rules. No shortage appears; the test should report that honestly.
Keep these three ideas
- Calculate order triggers and order-up-to quantities using a consistent inventory position.
- Keep the unit, timing, and denominator visible.
- Treat model outputs as conditional on their stated assumptions.
Common mistakes
- Changing an input definition without changing all affected formulas.
- Presenting an expected or proposed quantity as confirmed usable supply.
Optional video study
Calculate order triggers and order-up-to quantities using a consistent inventory position.
- Use position for the order decision
- Protect the review interval
- Test boundary cases
Second half: application, contrasting scenario, and handoff.
Open the module media & quizPut this idea to use
Carry your assumptions into a practical tool, then compare your result with a short guide.
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