Challenge and validate assumptions

Quick Overview

This question evaluates a data scientist's competency in identifying fragile business assumptions, conducting sensitivity analysis, and designing experiments and observational studies to validate parameters related to demand, price elasticity, cannibalization, supply constraints, labor learning curves, regional heterogeneity, and promotional decay.

Vegan-Burger Launch: Assumptions at Risk, Validation, Sensitivity, and Experiment Plan

Background

You are evaluating the launch of a vegan burger across a quick-service restaurant network. Your goal is to stress-test the business case by identifying fragile assumptions, proposing validation methods, and outlining a sensitivity and experimentation plan to estimate true incremental impact.

Tasks

Identify which assumptions are most likely to be wrong or unstable, and how you would validate them. Discuss:
- Demand forecast uncertainty
- Price elasticity of demand
- Cannibalization of the classic burger
- Substitution/halo effects on other menu items
- Supplier reliability and minimum order quantities (MOQs)
- Learning-curve effects on labor time
- Kitchen capacity constraints
- Regional heterogeneity
- Promotional lift and novelty/decay
Propose a sensitivity analysis plan:
- Key variables and their plausible ranges
- How you would generate and read a tornado chart
Propose an experiment and/or observational design to de-bias estimates and validate model parameters.

Challenge and validate assumptions

Quick Overview