Comparing an input-cost shock with a baseline
A supplier raises its price for two quarters. See how much operating contribution changes under the cost shock alone and when demand falls at the same time.
Set the baseline and two alternatives
A fictional manufacturer sells 10,000, 10,200, 10,400 and 10,600 units over four quarters. The selling price is €100, variable cost is €60 per unit and fixed costs are €300,000 per quarter. These inputs are illustrative and do not describe a client.
- Baseline: keep these assumptions in all four quarters.
- Input-cost shock: increase variable cost from €60 to €68 in Q2 and Q3. Keep prices and volume fixed.
- Cost shock and lower demand: apply the same cost increase and sell 5% fewer units in Q2 and Q3. Keep prices and fixed costs unchanged.
Calculation: units × (selling price − variable cost per unit) − fixed costs. Calculate this for each quarter, then sum the four quarterly results.
Compare the four-quarter results
| Scenario | Total | Change from baseline |
|---|---|---|
| Baseline | €448,000 | €0 |
| Input-cost shock | €283,200 | −€164,800 |
| Cost shock and lower demand | €250,240 | −€197,760 |
In Q2, the combined shock reduces volume to 9,690 units and contribution per unit to €32. The result after fixed costs is €10,080. At baseline volumes, every extra €1 in unit cost in Q2 and Q3 reduces the four-quarter total by €20,600. You can reproduce both figures with the CSV inputs.
What the comparison can support
Use the comparison to see how exposed the baseline is to specified changes in costs and sales. It can inform a discussion about supplier contracts, pricing or contingency budgets. The example uses simple accounting arithmetic. It does not estimate demand, assign probabilities or predict cash flow. Tax, financing, inventory and price responses are outside the model.
For a real decision, test the assumptions most likely to change the choice. An econometric model may help estimate a demand response if there are enough relevant data and credible variation.