Start with something familiar
Imagine ten bus trips. Two buses are late, but one is late by a minute and the other by an hour. Saying eight trips were on time tells you frequency, not the size of the disruption. A second measure might track total minutes lost. Inventory service also has multiple views. A cycle with one missing bottle and a cycle with fifty missing bottles both count as a failed cycle, but their effect on customers is very different.
Words to know: Cycle service level, Fill rate, Backlog.
Count cycles and units separately
A cycle-service measure asks how many replenishment cycles had no stockout. If eight of ten cycles are clean, cycle service is eighty percent. Immediate unit fill asks what share of demanded units was supplied at the required event. If demand totals two hundred and five units were initially unfilled, immediate fill is 195 divided by 200, or 97.5 percent.
Both results can describe the same operation. Neither replaces the other. Define a cycle boundary, the required event, and whether partial shipment counts. A later backlog shipment improves eventual completion but does not retroactively become immediate fill. Keep the original due date when measuring performance so moving promises cannot erase a failure.
Connect policy to evidence
A safety-stock normal factor is typically linked here to cycle-service probability under stated assumptions. It is not directly a unit fill-rate formula. A target of 95 percent cycle service therefore does not promise a 95 percent immediate fill rate. Different order sizes and shortage magnitudes can create very different unit outcomes at the same cycle frequency.
Small samples can be noisy. If a new policy has only ten observed cycles, an observed eighty percent clean-cycle rate is evidence, not a precise long-run truth. Show numerator and denominator beside every percentage. Compare similar demand mixes and lead-time conditions, and investigate missed cycles rather than automatically raising every item’s buffer.
Run an honest policy trial
Use a holdout period or a transparent scenario set when comparing policies. Retrospectively choosing parameters that best fit the same observations can flatter the result. In a teaching exercise, keep the rules fixed and apply all supplied cycles, including the awkward ones. Record both service gains and extra inventory needed.
Root causes guide action. A late usable receipt may call for supplier work, while an overlooked order may call for data repair. Increasing stock can hide either issue without fixing it. The lab builds a cycle ledger and a daily backlog view so that service, recovery, and inventory can be discussed together with clear definitions.
- 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 |
|---|---|
| Cycles observed | 10 |
| Clean cycles | 8 |
| Demand units | 200 |
| Immediately unfilled units | 5 |
- 1. Cycle service = 8 / 10 = 80%.
- 2. Immediate fill = (200 - 5) / 200 = 97.5%.
- 3. Later supply of five clears backlog but leaves immediate fill at 97.5%.
80 percent clean-cycle service and 97.5 percent immediate fill are both correct.
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
Use ten independent replenishment cycles. Each has demand twenty. Immediately unfilled units by cycle are 0, 0, 2, 0, 0, 0, 3, 0, 0, 0. Each backlog is fully cleared one day later before the next cycle. For a simple alternative policy, assume an added reserve of two units is replenished before each cycle; revised shortage is max(0, original shortage minus two). 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. Use ten independent replenishment cycles. Each has demand twenty. Immediately unfilled units by cycle are 0, 0, 2, 0, 0, 0, 3, 0, 0, 0. Each backlog is fully cleared one day later before the next cycle. For a simple alternative policy, assume an added reserve of two units is replenished before each cycle; revised shortage is max(0, original shortage minus two). 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. Compare reserves zero, one, two, and three. Assume reserve carrying cost is $3 per unit per year and report annual incremental holding cost; the service scenario is ten cycles, not a full-year economic experiment. 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
- 80 percent clean-cycle service and 97.5 percent immediate fill are both correct.
- Increasing shortage to twenty units across the same two failed cycles gives 90 percent fill, still 80 percent cycle service.
- No claim about long-run achieved service follows exactly from ten observations.
- Reserves zero, one, two, three give total shortages 5,3,1,0; immediate fill 97.5%,98.5%,99.5%,100%.
- Clean-cycle service is 80%,80%,90%,100%; incremental annual reserve cost is$0,$3,$6,$9. These scenario outcomes are not calibrated long-run probabilities.
Keep these three ideas
- Distinguish clean cycles, immediate unit fill, and backlog recovery.
- 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
Distinguish clean cycles, immediate unit fill, and backlog recovery.
- Count cycles and units separately
- Connect policy to evidence
- Run an honest policy trial
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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