Criteria for the prioritization of hypotheses in root cause analysis

Abstract

Explanatory hypotheses are formed and evaluated in root cause analysis. However, prior to investigation, the hypotheses must be prioritized. Often, methods such as nominal group technique, multi‐voting, and simple voting are used to decide which to investigate first. This research seeks to provide concrete criteria for the prioritization of hypotheses using three levels of prioritization based on the strength of the available evidence. A quality leadership email distribution list was used to distribute a survey to quality departments. Respondents were asked to rate various scenarios as confirmed, strong, moderate, and weak evidence towards supporting a hypothesis. Only 2 of 13 scenarios did not have statistically significant results and these results can be used by quality departments to prioritize hypotheses to investigate during root cause analysis.