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Learn through experiments

Count stock that has not arrived yet

Why can empty shelves trigger too many replacement orders?

Entering midway? Revisit Put capacity where the demand arrives for the preceding worked example, or start here and use the explanation below.

1 · Try

Start with a concrete question

Original synthetic scenario. A ten-day store starts with 12 items. Orders arrive after a fixed delay, unmet demand is lost, and day five has twice the normal demand.

Try the initial inputs, then write a prediction before changing one setting. All calculations run locally on your CPU.

Go directly to the experiment · Review basic mathematics

2 · Predict

What do you expect?

Will ordering up to a target from shelf stock alone avoid excess inventory?

3 · Experiment

Change one thing. Inspect what happens.

  1. Trace the first three days and identify which orders are still in transit.
  2. Compare shelf-only and pipeline-aware ordering at the same target.
  3. Increase delivery delay and test whether the old target still avoids stockouts.
  4. Choose a target that trades holding stock against shortages, and document the demand surge assumption.
Experiment inputs
Inputs
Your settingsMechanism
Calculation belowEvidence
Compare outcomes
Unfilled demand0 items
Ending stock6 items
Ordered total72 items
Still in transit12 items

Compare the current results

Every bar starts at zero and uses the same numeric scale in this chart. The upper bound automatically adjusts to the largest current value (at least 1), so compare the numbers when changing inputs. Units and quantities come from each label; different kinds of quantity are not interchangeable. Displayed values are rounded to at most six significant digits.
06
  • Day 1 end stock (items)6
    Day 1 end stock (items): 6Horizontal bar from zero to 6, on the shared zero to 6 numeric axis.
  • Day 2 end stock (items)0
    Day 2 end stock (items): 0Horizontal bar from zero to 0, on the shared zero to 6 numeric axis.
  • Day 3 end stock (items)6
    Day 3 end stock (items): 6Horizontal bar from zero to 6, on the shared zero to 6 numeric axis.
  • Day 4 end stock (items)6
    Day 4 end stock (items): 6Horizontal bar from zero to 6, on the shared zero to 6 numeric axis.
  • Day 5 end stock (items)0
    Day 5 end stock (items): 0Horizontal bar from zero to 0, on the shared zero to 6 numeric axis.
  • Day 6 end stock (items)0
    Day 6 end stock (items): 0Horizontal bar from zero to 0, on the shared zero to 6 numeric axis.
  • Day 7 end stock (items)6
    Day 7 end stock (items): 6Horizontal bar from zero to 6, on the shared zero to 6 numeric axis.
  • Day 8 end stock (items)6
    Day 8 end stock (items): 6Horizontal bar from zero to 6, on the shared zero to 6 numeric axis.
  • Day 9 end stock (items)6
    Day 9 end stock (items): 6Horizontal bar from zero to 6, on the shared zero to 6 numeric axis.
  • Day 10 end stock (items)6
    Day 10 end stock (items): 6Horizontal bar from zero to 6, on the shared zero to 6 numeric axis.

Follow the calculation

  1. Day 1: arrive 0; demand 6, supply 6, end stock 6; pending 0; order max(0, 18 − 6 − 0) = 12, due day 3.
  2. Day 2: arrive 0; demand 6, supply 6, end stock 0; pending 12; order max(0, 18 − 0 − 12) = 6, due day 4.
  3. Day 3: arrive 12; demand 6, supply 6, end stock 6; pending 6; order max(0, 18 − 6 − 6) = 6, due day 5.
  4. Day 4: arrive 6; demand 6, supply 6, end stock 6; pending 6; order max(0, 18 − 6 − 6) = 6, due day 6.
  5. Day 5: arrive 6; demand 12, supply 12, end stock 0; pending 6; order max(0, 18 − 0 − 6) = 12, due day 7.
  6. Day 6: arrive 6; demand 6, supply 6, end stock 0; pending 12; order max(0, 18 − 0 − 12) = 6, due day 8.
  7. Day 7: arrive 12; demand 6, supply 6, end stock 6; pending 6; order max(0, 18 − 6 − 6) = 6, due day 9.
  8. Day 8: arrive 6; demand 6, supply 6, end stock 6; pending 6; order max(0, 18 − 6 − 6) = 6, due day 10.
  9. Day 9: arrive 6; demand 6, supply 6, end stock 6; pending 6; order max(0, 18 − 6 − 6) = 6, due day 11.
  10. Day 10: arrive 6; demand 6, supply 6, end stock 6; pending 6; order max(0, 18 − 6 − 6) = 6, due day 12.

Reordering from shelf stock alone can duplicate orders already in transit. Delivery delays and the one-day demand surge still require a reserve even with pipeline awareness.

Captures keep your inputs, prediction and observation. Results are recalculated from those inputs. Resetting inputs keeps your captures and challenge history.

4 · Understand

Explain the mechanism

What the experiment explains

Original synthetic scenario. A ten-day store starts with 12 items. Orders arrive after a fixed delay, unmet demand is lost, and day five has twice the normal demand.

Inventory position includes stock on hand plus incoming orders. Ignoring incoming orders can request the same replacement multiple times during a delay.

At defaults, day one ends with 6 items and orders 12 for day three. Day two ends with zero; including those 12 pending items orders only 6 more, while shelf-only ordering requests 18.

A correct reorder calculation cannot create instant supply. Targets must account for demand during delivery delay and uncertainty; this scenario has one visible surge.

Read the relationship

Order = max(0, target − shelf stock − pending orders), when pipeline-aware. Next arrival day = current day + lead time. Unmet demand is not backlogged.

Inspect the evidence

The numerical trace is recalculated from your current settings. Compare a controlled pair of trials before changing several inputs together. Inspect intermediate quantities as well as final metrics; state which assumptions make the comparison meaningful.

Boundaries of the model

  • Deterministic demand except one programmed surge; unlimited supplier capacity, no ordering or holding prices.
  • Ten-day horizon; final pending orders are reported separately from stock.

Return to the systems thinking and operations course and project to connect this mechanism to the broader investigation.

5 · Apply

Try a fresh case

After demand, shelf stock is 3 and incoming orders total 7. An order-up-to target is 18. How many items should a pipeline-aware policy order?

This is a public practice check. Retries support learning; matching a number does not certify independent proficiency.

Take the investigation further

Choose any extension. These are project prompts for you to carry out; they are not automatically assessed.

School investigation

Track paper order cards by delivery date for a five-day example.

College investigation

Add backorders and stochastic demand, comparing service level and average stock over repeated seeds.

Workplace investigation

Draft a replenishment policy with lead-time evidence, service targets and a review for outstanding orders.

6 · Continue

Keep the evidence, choose your next step

Completion records your own decision that you have worked through this investigation. Practice checks and independent project evidence are separate.