Multiple Systemic Contributors versus Root Cause: Learning from a NASA Near Miss. (September 2016) - Walker, Katherine E.; Woods, David D.; Rayo, Michael F.
In 2013 NASA nearly drowned an astronaut during an Extravehicular Activity (EVA 23) on the International Space Station due to spacesuit water leakage. Indicators of trouble on the preceding EVA (22) were discounted. NASA carried out an investigation of the near miss event that is a sample of how root cause analysis is carried out in actual organizations (National Aeronautics and Space Administration, 2013). This paper contrasts the root cause analysis with a new analysis the authors carried out that captures how multiple systemic contributors combined to create the conditions that led up to the near miss. The new analysis illustrates the original finding from the late 1980s that accidents arise from multiple factors each necessary but only jointly sufficient (Reason, 1990; Woods, 1990; Cook, 2000; Woods, Dekker, Cook, Johannesen, & Sarter, 2010). Many of these contributors are system factors that have been present (latent) in the organization for some time prior to the specific sequence of events. In other words, the accidents arose from organizational or systemic factors (Reason, 1997). In contrast, the traditional root cause analysis focuses on the human roles closest to the adverse event and only raises systemic issues in terms of vague generalities that are difficult to address in systemic improvements (Dekker, 2014; Woods et al., 2010). The paper provides this contrast for two purposes. The first goal of this paper is to provide a concrete technique and diagram for identifying systemic contributors to adverse events (Systemic Contributors Analysis and Diagram or SCAD). The second goal is to highlight how the current practice of root cause analysis is unable to come to grips with systemic issues, misses the interactions between contributors, and misses emergent system properties. Using this systemic technique reveals that adverse events are very often due to production pressure at the blunt end, not human error at the sharp end of systems.