Causal-factor-tree-analysis.docx

Events and Causal Factors Analysis Events and Causal Factors Analysis (ECFA) is an important component in the accident investigation repertoire of methods. It is designed as a stand-technique but is most powerful when applied with other techniques found in the Management Oversight and Risk Tree (MORT) programme. ECFA serves three main purposes in investigations: (1) assists the verification of causal chains and event sequences; (2) provides a structure for integrating investigation findings; (3) assists communication both during and on completion of the investigation. This document discusses the benefits of EFCA and provides a primer in the application of the technique.

Causal Factor Tree Analysis Description Causal factor tree analysis is a Root Cause Analysis technique used to record and display, in a logical, tree-structured hierarchy, all the actions and conditions (or Causal Factors) that were Necessary and Sufficient for a given consequence to have occurred.

Pros and Cons Pros      

Provides structure for the recording of evidence and display of what is known. Through application of logic checks, gaps in knowledge are exposed. Tree structure is familiar and easy to follow. Can easily be extended to handle multiple (potential) scenarios. Can incorporate results from the use of other tools. Works well as a master investigation/analysis technique. Cons

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Cannot easily handle or display time dependence. Sequence dependencies can be treated, but difficulty increases significantly with added complexity. Shows where unknowns exist, but provides no means of resolving them. Stopping points can be somewhat arbitrary.

Definitions Branch: A cause-effect link from one item in the tree to another immediately above it. This assumes the tree is drawn from the top down, i.e. consequence on top and causes below it.

Chain: A continuous sequence of branches from one item that is lower in the tree, through one or more intervening items, to one item that is higher in the tree. Endpoint: An item in the tree that has no branches leading into it; the first (or lowest) item in a chain leading to the final consequence.

Example This is one short example that illustrates the basic structure and flow of a causal factor tree analysis. In this case, the problem/event is shown at the top and all the causal factors are below it. Causal flow is generally from the bottom to the top; branches, chains, and endpoints are clearly identifiable.

Discussion Tree structures are often used to display information in an organized, hierarchical fashion: organization charts, work breakdown structures, genealogical charts, disk directory

listings, etc. The ability of tree structures to incorporate large amounts of data, while clearly displaying parent-child or other dependency relationships, also makes the tree a very good vehicle for incident investigation and analysis. Combination of the tree structure with causeeffect linking rules and appropriate stopping criteria yields the causal factor tree, one of the more popular investigation and analysis tools in use today. Each new cause added to the tree should be evaluated as a potential endpoint. When can a cause be designated as an endpoint? This is an object of some debate. Several notable RCA practitioners use some version of the following criteria:   

The cause must be fundamental (i.e. not caused by something more important), AND The cause must be correctable by management (or does not require correction), AND If the cause is removed or corrected, the adverse consequence does not occur. In summary, the causal factor tree is an investigation/analysis tool that is used to display a logical hierarchy of all the causes leading to a given effect or consequence. When gaps in knowledge are encountered, the tree exposes the gap, but does not provide any means to resolve it; other tools are required. Once the required knowledge is available, it can be added to the tree. A completed causal factor tree provides a complete picture of all the actions and conditions that were required for the consequence to have occurred. Success in causal factor tree analysis depends on the rigour used in adding causes to the tree (i.e., ensuring necessity, sufficiency, and existence), and in stopping any given cause-effect chain at an appropriate endpoint.