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Estimate monthly demand for an AI repair-quote assistant. How would you check your answer?

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Build a monthly task estimate from a fictional shop market. Cross-check it through technicians, then explain which assumption you would investigate first.

Updated Nov 2026 · Original practice questions with worked answers and teaching rubrics. Our editorial policy explains the sources, review process and limits.

Case briefRead the inputs, then make your call

Fictional market-sizing exercise. Estimate monthly submitted requests, with one request per repair job requiring a quote. All inputs are assumptions. Eligibility refers to the supported workflow; submission is conditional on eligibility.

Scenario inputs
Active shops24000
Quote requests per shop per working day8
Working days per month22
Eligible request share, percent50
Submitted share of eligible requests, percent25
Lower submitted share, percent10
Upper submitted share, percent40
Technicians in cross-check96000
Requests per technician per working day2
Review minutes per submitted request4

Your task. Estimate base monthly demand and a submission scenario range. Cross-check through technicians, identify possible double counting and choose the first assumption to investigate. Calculate required review-hours.

Build a monthly task estimate from a fictional shop market. Cross-check it through technicians, then explain which assumption you would investigate first.

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