Test plausible severe scenarios explicitly: Which testing distinction matters most?
Rare severe events require explicit scenario or stress testing, not merely more routine data or average performance reporting.
The question
A retailer’s demand planner performs well on ordinary weeks, but failures during pandemics and port closures could cause severe shortages. Assume data quality, provenance, privacy, and ordinary validation are already addressed. Which testing distinction matters most?
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- Report average forecast error quarterlyQuarterly averages summarize routine performance and may dilute failures occurring during unusual but consequential disruptions.
- Add more ordinary weekly examplesMore routine data may improve average fit but does not directly examine rare conditions with disproportionate operational consequences.
- Compare performance against another plannerBenchmarking another planner may provide context, but it does not demonstrate robustness under specified severe disruptions.
- Test plausible severe scenarios explicitly ✓Scenario testing directly evaluates rare, high-consequence conditions that ordinary aggregate performance can conceal in demand planning.
The trap
Look for the option that directly recreates or evaluates the exceptional condition named in the scenario. How to remember it
Rare severe events require explicit scenario or stress testing, not merely more routine data or average performance reporting.
How many of these would you get right?
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