Event and Causal Factor Charting is a structured investigation method used to reconstruct what happened before, during, and after an unwanted event.

The chart creates a time-based sequence of:

  • events;
  • conditions;
  • actions;
  • decisions;
  • relevant changes.

The objective is to replace vague narratives with an evidence-based chronology.

Define the event boundary

Start by defining the event being investigated.

Examples include:

  • equipment failure;
  • quality escape;
  • production interruption;
  • safety incident;
  • missed customer shipment.

5W1H Problem Definition can help establish what happened, where, when, who was involved, and the known impact.

Build the timeline from evidence

Useful sources may include:

  • control-system logs;
  • work orders;
  • operator records;
  • inspection data;
  • alarms;
  • emails;
  • timestamps;
  • interviews;
  • photographs.

The chart should distinguish confirmed fact from assumption.

If exact timing is unknown, record the uncertainty rather than inventing precision.

Separate events from conditions

An event is something that happened.

Examples:

  • pump stopped;
  • operator reset the drive;
  • material lot changed.

A condition is a state that existed.

Examples:

  • alarm had been disabled;
  • spare pump was unavailable;
  • work instruction was obsolete.

Separating events and conditions helps the team see how the operating environment influenced the sequence.

Identify causal factors

A causal factor is an event or condition that shaped the outcome and deserves deeper investigation.

Examples may include:

  • missing alarm response;
  • delayed escalation;
  • incorrect setting;
  • failed inspection;
  • unavailable backup equipment.

A causal factor is not automatically the final root cause.

Root Cause Analysis should continue into why the factor existed.

Look for decision points

Important questions include:

  • When could the sequence have been interrupted?
  • Which barrier should have stopped progression?
  • What information was available at that moment?
  • What decision was made?

Barrier Analysis can examine why preventive or protective controls failed to stop the event.

Avoid hindsight bias

After an event, the correct decision may appear obvious.

The chart should show what people knew at the time.

This prevents the investigation from judging past decisions using information that became available only later.

Update the chart as evidence improves

The first timeline may be incomplete.

New evidence can:

  • add events;
  • change timing;
  • disprove assumptions;
  • reveal missing conditions.

The chart should remain a working investigation tool until the sequence is stable enough for causal analysis.

Use the chart to guide interviews

A timeline can improve interviews.

Instead of asking:

What happened?

Ask:

The alarm log shows the first trip at 14:08 and the restart at 14:11. What information did you have during those three minutes?

Specific questions improve evidence quality.

Connect to corrective action

Once causal factors are verified, countermeasures should address the underlying mechanisms.

Countermeasure Management can help assign ownership, due dates, and effectiveness checks.

The chart itself does not solve the problem.

It creates a stronger factual basis for solving it.

Common mistakes

Building the timeline from memory only, mixing facts and assumptions, jumping from the final event directly to a favored cause, judging decisions with hindsight, ignoring conditions that existed before the event, and stopping the investigation at the first causal factor are common mistakes.

Practical sequence

  1. define the event boundary.
  2. collect time-based evidence.
  3. identify confirmed events.
  4. identify relevant conditions.
  5. place events in sequence.
  6. mark uncertainty explicitly.
  7. identify causal factors.
  8. examine failed barriers and decisions.
  9. investigate deeper causes.
  10. connect verified causes to corrective action.

The practical lesson

Event and Causal Factor Charting turns a complicated incident into a disciplined chronology.

A reliable timeline makes causal reasoning stronger because the team can see how the event actually developed.