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Working Paper
| HBS Working Paper Series
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2018
How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections
by
Maria Ibanez and Michael W. Toffel
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Abstract
Many production processes are subject to inspection to ensure they meet quality, safety, and environmental standards imposed by companies and regulators. Inspection accuracy is critical to inspections being a useful input to assessing risks, allocating quality improvement resources, and making sourcing decisions. This paper examines how the scheduling of inspections risks introducing bias that erodes inspection quality by altering inspector stringency. In particular, we theorize that inspection results are affected by (a) the inspection outcomes at the inspector’s prior inspected establishment and (b) when the inspection occurs within an inspector’s daily schedule. Analyzing thousands of food safety inspections of restaurants and other food-handling establishments, we find that inspectors cite more violations after inspecting establishments that exhibited worse compliance or greater deterioration in compliance and that inspectors cite fewer violations in successive inspections throughout their day and when inspections risk prolonging their typical workday. Our estimates suggest that, if the outcome effects were amplified by 100% and the daily schedule effects were fully mitigated (that is, reduced by 100%), the increase in inspectors’ detection rates would result in their citing an average of 9.9% more violations. Scaled nationwide, this would yield 19 million fewer foodborne illness cases per year, reducing annual foodborne illness costs by $14.2 billion to $30.9 billion. Understanding these biases can help managers develop alternative scheduling regimes that reduce bias in quality assessments in domains such as food safety, process quality, occupational safety, working conditions, and regulatory compliance.
Keywords: Assessment;
quality;
bias;
inspection;
scheduling;
Econometric Analysis;
Empirical Research;
regulation;
Health;
Food;
Safety;
Quality;
Performance Consistency;
Performance Evaluation;
Food and Beverage Industry;
Service Industry;
