JD

Structured Analytic Techniques for Improving Intelligence Analysis

Introduction

  • Purpose: To highlight structured analytic techniques for challenging judgments, identifying mindsets, stimulating creativity, and managing uncertainty in intelligence analysis.
  • Scope: A toolkit, not a comprehensive workflow, to structure thinking for difficult analytic questions.
  • Core Idea: Techniques help surface assumptions and explore alternatives, as cognitive biases and mental models influence information acceptance.
  • Foundational Concepts:
    • Mental models bias interpretation toward expected patterns.
    • Mind-set risks include perceiving what's expected, resistance to change, and ignoring conflicting data.
    • Analysts should be aware of their reasoning.
  • Context: Increased uncertainty and unexpected shifts in complex global environments.

How To Use These Techniques

  • Grouping: Techniques are grouped by purpose: Diagnostic, Contrarian, and Imaginative thinking.
  • Application: Select tools based on the analytic objective.
  • Limitations: Techniques improve sophistication and credibility but not precision; they help avoid rigid thinking and foster new insights.
  • Reference: Based on Heuer’s concept that “analysis can be improved.”

Diagnostic Techniques

  • Focus: Making analytic arguments explicit and exposing hidden assumptions.
  • Core Techniques: Key Assumptions Check (KAC), Quality of Information Check (QoIC), and Indicators or Signposts of Change.

Key Assumptions Check (KAC)

  • Purpose: List and review key working assumptions underpinning judgments.
  • When to Use: Best at the start of a project; recheck before final judgments.
  • Definition: A hypothesis accepted as true, forming the assessment's basis (e.g., military, political, or economic stability).
  • Value Added:
    • Makes logic explicit and exposes flaws.
    • Identifies shaping factors