Decomposition: Drivers & Indicators

Decomposition is the process of breaking a complex problem into manageable parts that can be examined independently and in relation to each other. Visualizing these components helps individuals and teams understand how each element contributes to the larger issue, making thorny questions manageable and even forecastable.

Background

The concept of analytic decomposition was popularized by CIA analyst Richards J. Heuer in Psychology of Intelligence Analysis as a way to counter human biases and make the analytic process more transparent and collaborative. Intelligence analysts are trained on decomposition to clarify priorities, assign monitoring responsibility, and provide decision-makers with actionable intelligence.

Decomposition is especially critical in warning intelligence. For example, analysts assessing the risk of a terrorist attack might break the problem into key indicators including intent (public statements or propaganda), capability (training activities or acquisition of materials), and opportunity (surveillance of potential targets or movement of operatives). Each indicator is tracked and assessed for changes, with results synthesized to inform judgments and warnings.

Why Decomposition Matters

While developed by intelligence professionals, decomposition extends to any organization operating under uncertainty. It helps overcome a "wait and see" mentality or over-reliance on expert assumptions. Breaking down a complex problem into its components surfaces priorities and clearer insights that enable better decisions.

For decision-makers and leaders, decomposition helps to:

  • Assign ownership by allocating staff or teams to monitor specific drivers or indicators
  • Communicate priorities clearly across the organization through a common framework
  • Identify hidden risks or opportunities that might otherwise be missed

For analysts, decomposition helps to:

  • Routinely monitor, update, and refine how an issue is assessed with new information
  • Facilitate more accurate risk assessments and prioritization through detailed evaluation
  • Clarify boundaries and scope, ensuring analysis remains focused and actionable

The Decomposition Process

A typical decomposition workflow involves these steps:

  1. Scope the strategic question — Frame a clear, future-facing research question to set the stage for focused analysis.
  2. Explore scenarios — Map out plausible futures and likelihoods to inform which drivers and indicators matter most. (You can also run decomposition first to shape your scenarios.)
  3. Develop the initial decomposition — Break the question into major drivers and their observable indicators, incorporating source materials and search results.
  4. Monitor and forecast — Track drivers and indicators via ongoing search results and source materials. Crowdsource probabilistic forecasts from colleagues on key indicators.
  5. Iterate and refine — As new developments occur, revisit the decomposition. Add new drivers if conditions shift, merge indicators as issues converge, or remove outdated ones.
  6. Report — Provide regular updates to stakeholders using visualizations and draft output templates to communicate changes and emerging risks.

Decomposition in Hinsley

Step 1: Define Your Research Question

Start by entering a research question and receiving an AI-generated Research Brief from global news sources. For example, you might analyze how evolving European security dynamics impact your global technology company's operations.

Step 2: Generate the Decomposition

  • Access the Decomposition section and select source materials
  • Hinsley produces a breakdown with key drivers and indicators
  • Customize elements through the Builder tab
  • Visualize connections using Icicle, Tree, or Nested views
  • Export for stakeholder sharing

Step 3: Iterate with Hinsley

Use Hinsley to combine drivers, suggest additional indicators, provide research context, and refine your decomposition through AI-assisted iteration.

Step 4: Enable Collaboration

Invite colleagues to refine the analysis and ensure it reflects diverse perspectives.

Step 5: Monitor and Report

  • Track updates via the Search Results section
  • Regenerate research briefs as information evolves
  • Create draft reports using templates
  • Export visualizations to Word or PDF

The process emphasizes ongoing iteration and stakeholder engagement throughout the analytical lifecycle.

References

  1. Richards J. Heuer Jr., "Taxonomy of Structured Analytic Techniques" (paper presented at the International Studies Association Annual Convention, San Francisco, CA, March 26–29, 2008).
  2. Richards J. Heuer Jr., Psychology of Intelligence Analysis (Washington, D.C.: Center for the Study of Intelligence, Central Intelligence Agency, 1999).
  3. Sarah Miller Beebe and Randolph H. Pherson, Cases in Intelligence Analysis: Structured Analytic Techniques in Action, 2nd ed. (Thousand Oaks, CA: SAGE Publications, 2014).
  4. Penn State, "The Structured Analytic Techniques 'Toolbox'," The Learner's Guide to Geospatial Analysis.
  5. U.S. Government, Tradecraft Primer: Structured Analytic Techniques for Improving Intelligence Analysis (March 2009).