ORIGINAL COMPANY-CONTEXT PRACTICE
Estimate demand when products sell out
Original practice scenario inspired by Hermès International Société en commandite par actions's public business context; this is not a reported interview question or a description of its internal systems. A synthetic retail dataset records sales and inventory. Some products sell out early, so their observed sales stop. Explain why ranking demand by sales alone is biased and propose a defensible analysis.
Written for independent practice using company context; this is not a verified question from a company interview.
A REASONED APPROACH
Model answer.
Observed sales are limited by both customer interest and available supply. A sold-out product has censored demand; a low total does not establish low interest when it was unavailable for much of the period.
Work through it
- Construct availability intervals at product-location level and distinguish stocked exposure from calendar time. Check inventory accuracy and replenishment delays.
- Compare sales rates during comparable available periods, with uncertainty for short exposures. Add waitlist or unavailable-page signals only after examining how they are collected.
- Report measured sales separately from inferred lost demand. Validate assumptions through controlled stock allocations or replenishment changes where practical.
Tradeoffs to discuss
- Additional signals can improve estimates but introduce selection effects. No method recovers exact unmet demand without assumptions about customer behavior.
Common pitfalls
- Treating stockout hours as zero-demand observations biases estimates.
- Extrapolating one unusually busy hour across a whole week can overcorrect just as severely.