Run a controlled business experiment, calculate customer-level economics, diagnose the operating constraint, and make a recommendation that protects quality as well as profit.
Name:
Date:
Team role:
Learning goal: explain how demand, practical capacity, service quality, variable cost, and fixed cost connect to profit. A strong answer cites evidence and does not assume that the busiest or highest-revenue strategy is automatically best.
1. Frame one useful investigation
Choose one decision question. Keep the car wash format and location stable so the comparison remains interpretable.
My investigation question:
Why this question matters to customers, workers, cash, or long-term trust:
2. Plan a controlled comparison
Record a baseline before changing an important decision. For the test, change only one main variable. Observe equal periods and repeat the test when a random demand, weather, supplier, review, or equipment event makes the first comparison unusually different.
Independent variable—the one decision I will change:
Controlled variables—the decisions I will keep stable:
Baseline setting:
Test setting:
Prediction: If I change __________ from __________ to __________, then __________ will change because:
Guardrail: I will reject the change even if profit rises when it causes this unacceptable queue, quality, safety, staffing, waste, cash, or customer outcome:
3. Calculate the economics before judging the strategy
Use the simulator’s Finance and profit-breakdown panels. Keep dollars, percentages, customers, and minutes labeled. These formulas organize the evidence; they do not replace checking wash quality, satisfaction, reviews, inventory, and lost customers.
Capacity reasonableness check: Can the current bays and staff complete the break-even customer count without unacceptable queues or quality loss? ☐ Yes ☐ No ☐ Unsure
Show one calculation with units:
4. Record baseline, test, and repeat evidence
Use the same observation length for every row. Record an event note so a rainy period, equipment issue, supplier delay, or positive review is not mistaken for the effect of your decision.
Run
Decision tested
Cars served
Average ticket
Queue time
Lost customers
Wash quality
Satisfaction / review
Chemical inventory
Waste
Revenue
Profit
Event note
Baseline
Test
Repeat
Profit difference, test − baseline:
Queue-time difference:
Quality difference:
Strongest repeated pattern:
Confounding event or uncertainty:
5. Diagnose the constraint before recommending a change
Check every pattern supported by your evidence. Then explain the most important relationship with at least two measures.
My diagnosis:
Evidence against a competing explanation:
Expansion stop rule: Do not recommend another bay merely because one busy period produced a queue. Require repeated staffed-capacity pressure, lost customers, durable demand, acceptable quality, and enough cash or expected contribution to support added equipment and labor.
6. Write an evidence-bounded recommendation
Claim: Which decision should the car wash keep, reverse, or test next?
Evidence: Cite at least three numbers, including profit or contribution and one customer or operating measure.
Reasoning: Connect the decision to demand, capacity, quality, cost, and the observed result.
Tradeoff: What improved less, became worse, or still needs monitoring?
Limit: What does this simulation omit that would matter in a real car wash?
Next controlled test:
Teacher guide: a 50-minute car wash decision lab
0–7 minutes — orient: distinguish traffic from completed washes, revenue from profit, and theoretical bay capacity from practical capacity after staffing, queues, quality, and downtime.
7–14 minutes — plan: pairs select one decision, state a mechanism, record controls and a guardrail, and predict two measures that should change.
14–29 minutes — test: run a baseline and test for equal periods. Students record the evidence table rather than relying on the final score.
29–36 minutes — verify: repeat when possible, calculate contribution or margin, and flag any event that weakens the comparison.
36–45 minutes — recommend: write a claim using financial and non-financial evidence, one tradeoff, one model limit, and a next test.
45–50 minutes — debrief: compare teams that increased demand with teams that improved flow, quality, or margin. Ask why the highest-revenue strategy may not be the strongest business.
Suggested teacher answers and look-fors
Good fair test: same format, location, observation length, service mix, supplier, and staffing; only price changes. A broad redesign with price, promotion, staffing, and supplier all changed is not a controlled test.
Good contribution reasoning: a higher average ticket helps only when the customer-level variable cost and demand response leave enough contribution to cover payroll, rent, marketing, and profit.
Good capacity diagnosis: long queues plus repeated lost customers can support a staffing or bay test. High traffic alone cannot, especially when many customers are still served quickly.
Good quality diagnosis: cheaper chemicals or lean staffing may reduce cost but become a weak strategy when wash quality, satisfaction, or reviews fall enough to threaten repeat demand.
Good uncertainty statement: a random rain, review, supplier, festival, or equipment event means the result should be repeated before claiming the changed decision caused the difference.
15-minute option: give every team the same saved or teacher-described baseline. Students choose one change, predict its mechanism, observe one short test, and submit a two-number diagnosis.
30-minute option: complete the question, plan, baseline, test, calculation, and short recommendation. Assign the repeat as a follow-up or use another team’s matched run as supporting evidence.
No-device option: provide three completed result rows from a prior run. Students calculate contribution and margin, identify the constraint, challenge one unsupported claim, and write the next-test recommendation.
Quick 12-point assessment rubric
Investigation design (0–3): asks a useful question, changes one main decision, identifies controls, and states a measurable prediction and guardrail.
Evidence and calculations (0–3): records comparable runs, labels units, calculates accurately, and acknowledges a relevant event or uncertainty.
Diagnosis and reasoning (0–3): connects at least one financial and one operating or customer measure through a plausible business mechanism.
Recommendation and boundaries (0–3): gives a bounded action, tradeoff, stop rule or next test, and a meaningful real-world limitation.
The simulator is a simplified learning model, not operating, legal, environmental, financial, or safety advice. A real car wash may need permits, wastewater capture and discharge controls, chemical storage and labeling, worker training and protective equipment, accessibility, equipment maintenance, insurance, tax compliance, truthful offer terms, and local labor and consumer-law review.
Do not treat customers, workers, reviews, or environmental impacts as numbers to manipulate. Promotions should be truthful, material conditions should be clear, and a rain guarantee or membership offer should not hide exclusions. Do not collect personal data for a classroom exercise. Students should name at least one stakeholder who could bear a cost that the simulated profit result does not show.
Decision boundary: use the activity to practice evidence and tradeoff reasoning. Verify real requirements with qualified local authorities or professionals before applying any idea outside the simulation.
Car wash worksheet FAQ
What should students change in a car wash experiment?
Students should change one major decision, such as price, service mix, staffing style, quality investment, promotion, supplier, or marketing budget. Keep the car wash format and other important settings stable.
How do students calculate contribution per customer?
Subtract the chemical, waste, and other customer-level variable costs from the average ticket. The result estimates how much one completed wash contributes toward payroll, rent, marketing, and profit.
Does serving more cars always improve profit?
No. More traffic can increase payroll, chemical use, waste, queues, lost customers, and service strain. Compare profit with quality, satisfaction, reviews, and capacity measures.
When should students recommend another wash bay?
Recommend capacity expansion only after repeated evidence shows a staffed operation has long queues and lost customers, demand is durable, and expected contribution can support the extra bay and staffing costs.
Can this worksheet be used without grading profit alone?
Yes. The rubric rewards a fair test, accurate evidence, connected reasoning, uncertainty, and responsible boundaries. A well-supported diagnosis can earn full credit even when the simulated business loses money.