Here is an excellent causation model that maps a causal factor (cause) down to the management system level (root cause level):
(This chart includes references to the original work in the legend.) It differs substantially from Dan Peterson’s approach and many others (including ILCI / SCAT) in that it is all focused on the company responsibility for implementing and enforcing systems to control human error rates. More than a million accidents and near misses have been investigated with this model or with ones very similar to it (based on it). This originated in the US DOE work in 1985-86, which in turn was a simplification of MORT by US DOE decades earlier. It became popular in the private industry around 1990. (Note that at least one proprietary method was developed from the same basis.) This also matches nicely the US NRC description of human error originating from human factors; see SPAR-H from US NRC for more details on that aspect; SPAR-H also has many scaling factors for the importance of good and poor human factors on error probability; these factors originating from Swain and others in the 1970s and 1980s have been amended to account for newer data derived from control room data and cockpit data. So, both methods (the root cause chart and SPAR-H and derivatives) are in turn derived from tons of hands-on data (data collected to quantify the likelihood of human error and since supported by site/company data in many independent studies). These approaches are used extensively in the process industry for quality, reliability, and process safety incidents. Those in the occupational safety field seem to want a different model; possibly because many of the incidents related to occupational safety have only one layer of protection, which is up to the worker who may also be the initiator of an accident sequence. There are lower limits to the human error rate; once that reality sinks in you must look to re-engineer the task (different fixtures, different tools, and different processes) to lower the risk further.