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Making Decisions When The Data Is Incomplete

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About

About

About the Book

Most consequential decisions are made without sufficient data, clear signals, or stable conditions. This reference manual provides a structured approach to decision-making under uncertainty, grounded in professional practice rather than theory.

It distinguishes between information gaps that matter and those that do not, introduces robust decision heuristics, and shows how experienced practitioners manage risk, reversibility, and regret.

The emphasis is on making defensible decisions and moving forward with clarity when certainty is unavailable.

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Author

About the Author

Kim Parker

Kim Parker is a teacher, technologist, and lifelong student of how human beings learn. He began as a secondary mathematics and computer science teacher, spending twelve years in state and independent schools. As Head of Computers in a large K–12 setting, he saw how often traditional systems overlook neurodivergent, gifted, and introverted minds—an insight that shaped his enduring interest in knowledge and human potential.

He later moved into information technology, working for 27 years as a programmer, database administrator, project manager, systems engineer, enterprise architect, and ultimately Manager of Data Analytics and Knowledge. Across these roles, he observed that learning is rarely linear; it flourishes in curiosity, collaboration, and thoughtful design.

Now semi-retired, Kim writes and teaches, exploring knowledge acquisition, decision-making, neurodivergence, and mentoring through his publication, The Knowledge Economy. At 71, he continues to question assumptions and advocate for a more humane approach to education and work.

Contents

Table of Contents

Making Decisions When the Data Is Incomplete

  1. Purpose of This Manual
  2. Who This Manual Is For
  3. What This Manual Is Not
  4. How to Use This Manual
  5. Why This Matters

Part I — The Nature of Decisions Under Uncertainty

  1. 1. Decisions Are Not Problems to Be Solved
  2. 2. The Myth of Sufficient Information
  3. 3. Types of Uncertainty

Part II — What Actually Makes a Decision Defensible

  1. 4. Defensibility vs Correctness
  2. 5. The Decision Context
  3. 6. Stakes, Reversibility, and Consequence

Part III — A Practical Decision Framework

  1. 7. Step 1: Clarify the Decision Being Made
  2. 8. Step 2: Identify What Must Be True
  3. 9. Step 3: Bound the Information Search
  4. 10. Step 4: Generate Viable Options
  5. 11. Step 5: Evaluate Through Consequences, Not Scores

Part IV — Heuristics Used by Experienced Practitioners

  1. 12. Robustness Over Optimality
  2. 13. Regret Minimisation
  3. 14. Reversibility Thinking
  4. 15. Time as a Decision Variable

Part V — Common Failure Modes

  1. 16. Analysis as Self-Protection
  2. 17. Consensus and Committee Drift
  3. 18. Tool and Framework Overreach

Part VI — Applying the Framework in Practice

  1. 19. Decisions in Professional Contexts
  2. 20. Decisions in Personal Contexts
  3. 21. Documenting Decisions

Part VII — Developing Decision Maturity

  1. 22. Learning From Past Decisions

Closing Material

  1. A Final Word on Uncertainty
  2. Using This Manual Going Forward

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