Back to Your “Roots”: 5 Best Practices for Performing Root Cause Analysis

Anastasia Diamond, Maya Gonczi, Lizzie Einarson, B. Baldwin
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Abstract

Root cause analysis (RCA) is not always a straightforward process, and many human factors researchers struggle with executing RCA effectively and efficiently. For example, when conducting large, multi-site studies, the data points from participants quickly add up and begin to blur together. Then, during data analysis, notes that once made sense or are left unfinished now require additional time and effort to decode. This can require further video review or internal discussion to corroborate what happened and why, creating delays in analysis and reporting. This may lead to more questions which are now too late to answer. To combat this unfortunate reality, we discuss 5 best practices that can help researchers conduct more efficient RCAs.
回到你的“根”:执行根本原因分析的5个最佳实践
根本原因分析(RCA)并不总是一个简单的过程,许多人为因素研究人员都在努力有效地执行RCA。例如,在进行大型多站点研究时,参与者的数据点会迅速相加,并开始模糊在一起。然后,在数据分析过程中,曾经有意义或未完成的注释现在需要额外的时间和精力来解码。这可能需要进一步的视频审查或内部讨论来证实发生了什么以及原因,从而导致分析和报告延迟。这可能会导致更多的问题,而这些问题现在已经来不及回答了。为了应对这一不幸的现实,我们讨论了5种可以帮助研究人员进行更有效的随机对照分析的最佳实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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