Turns workflows, data, causes, and improvements into a tangible result by collecting event data, reconstructing the timeline, and deriving root causes and measures.
Which event factors and conditions actually shaped the incident, and which ones are root causes versus contributors?
The method helps clarify workflows, data, causes, and improvements in a concrete way. It looks for patterns, causes, weak points, or bottlenecks and derives measures from them. The result is captured as an event timeline, causal factor chart, and cause list.
The team follows the steps: collect event data, reconstruct the timeline, mark causal factors, check factors against evidence, and derive root causes and measures. Each step is captured visibly. At the end, an event timeline, causal factor chart, and cause list are available so decisions, tests, or actions can follow directly.
Method sketch for a quick mental model.
The runsheet guides execution with 5 phases, timeboxes, 5 pitfalls, and clear stop criteria.
Open runsheetCausal Factor Analysis combines timeline work with cause evaluation. First it makes clear what happened, then it marks conditions, decisions, gaps, and system factors that influenced the course of events. The method distinguishes between trigger event, contributing factor, and deeper cause. That creates a solid bridge from reconstruction to improvement measures.
Collect logs, statements, metrics, and decisions beforehand. Draw the chronology first before judging causes, otherwise memory errors and hindsight bias will dominate. Ask participants to label facts and interpretations separately.
Compact working template for Causal Factor Analysis with context, input, output artifacts, and next step.
Reconstructs events and contributing factors to understand the main causes of a problem.
When and for what do we use this method?
Which data, observations, decisions, or materials are available?
Short notes along the runsheet.
Owner, date, and success signal.
Short decision aid for existing alternatives.
Statt Causal Factor Analysis, wenn du einen Ausfall top-down über logische Verknüpfungen und Fehlerpfade zerlegen willst.
Statt Causal Factor Analysis, wenn du Ursachen als verzweigten Baum mit klaren Root Causes nachverfolgen willst.
Turns workflows, data, causes, and improvements into a tangible result by describing the deviation, choosing a comparison case, and deriving causes and actions.
A structured accident tree separates management controls, barriers, and events so serious incidents become auditable.
Hazards, targets, and failed barriers are mapped so controls can be strengthened at the point of exposure.
A recurring incident pattern links related cases across time so systemic causes become visible beyond one event.
Turns workflows, data, causes, and improvements into a tangible result by forming the team, describing the problem, and verifying correction and prevention.
Turns workflows, data, causes, and improvements into a tangible result by defining the top event, collecting direct causes, and deriving critical paths and measures.
Statt Causal Factor Analysis, wenn du einen Ausfall top-down über logische Verknüpfungen und Fehlerpfade zerlegen willst.