ANALYSIS TOOL BOX

Chronologies & Timelines

Impose order on raw reporting by arranging events along a time axis — then interrogate the result. The tool flags unexplained gaps and density clusters for you to explain, color-codes the timeline by person, place, organization, or activity to test whether a pattern holds, and keeps every source citation intact through merges, edits, and the hand-off to ACH.

How this technique works
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About this technique

What are chronologies and timelines?

A chronology lists events in the order they happened. A timeline shows the same events along a time axis, so their order, spacing and clustering are visible at a glance. Heuer and Pherson group the technique with other ways of breaking down and visualizing raw information. It's simple to build. Its value comes from questioning the finished result: what connects these events, what explains a burst of activity, and what was happening during the gaps?

When to use it

Build a chronology early in a project, once the question is framed and reporting starts to accumulate, and before you move into evaluation techniques like ACH. It's essential for incident reconstruction, investigations, and any question where sequence suggests cause. Events captured here often become the evidence rows in a later ACH matrix.

How to use this tool

  1. State the analytic question the chronology supports.
  2. Add events one by one, or bulk-import them one per line. Mark partial dates as partial rather than inventing a precise date, and add an end date for events that span time.
  3. Cite sources, add tags and write analytic notes. Color the timeline by tag category (person, place, organization or activity) to spot patterns.
  4. Merge duplicate reports into one event without losing any citations, and link related events, such as a cause and its effect.
  5. Review gaps and clusters. The tool highlights periods longer than your gap threshold. Ask what absence of reporting means there.
  6. Send selected events to ACH as evidence, with citations included.

Common pitfalls

  • False precision. "Mid-March" entered as "March 15" invents certainty.
  • Counting one report several times. Merge duplicates so a single source isn't inflated.
  • Skipping the review. The analysis happens when you look at the gaps and clusters, not when you enter the data.

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