Predictive Planning: How AI Made Strategy Continuous.
The book that defines predictive planning as a leadership discipline — not a software feature, not a forecasting upgrade, not a futurist narrative. A practitioner-grade framework for the executive layer of an AI-native operating environment.
Planning
Your competitors are buying predictive planning software. Nobody has written the strategy that goes with it.
Scenario planning was invented for a pre-AI world — slow-moving, expert-dependent, episodic. The tools have changed radically. The methodology has not caught up. Meanwhile, enterprise software vendors are seeding "predictive planning" as a vocabulary into every CFO and COO in the Fortune 500, with no strategic framework behind the term. This book defines predictive planning as a leadership discipline — a practitioner-grade framework executives can actually use in the operating environment they actually have.
Sources & Ingestion
External and internal sources flow through adapters, a governance gate, and an extraction layer before they reach the math contract on the facing page.
Lattice, Modules & Decisions
The math contract composes signals into interpretive surfaces and drives the four decision types that close the Loop.
Raw Signals & Composites
The upstream half of the composition surface — raw signals fan into named composites and into the steward's own.
Steward-Built → Generated Scenario
The synthesis half — the same scoring engine that powers ranking, probability, and personalization writes the scenario.
Fifteen passes through the discipline.
An introduction, thirteen chapters, and a conclusion. Readable straight through for the framework, or referenced by chapter as the discipline is installed.
- 00Introduction — The planning crisis
Why the cadence of the world has outpaced the cadence of strategy.
- 01The end of the planning calendar
Why the quarterly cycle no longer matches the cadence of the operating environment.
- 02What predictive planning is — and isn't
The discipline as distinct from forecasting, scenario planning alone, and software.
- 03The prediction-market era
What public probability infrastructure tells us about the new shape of foresight.
- 04Scan — the live signal layer
Building the operating intake of system data, paid feeds, and human signal.
- 05Story — scenarios as decisions
Three scenarios, named distinctly, with indicator sets that make them accountable.
- 06Stake — sizing the commitment
Probe, Hedge, Build, Bet. Reversibility and conviction as the only two axes that matter.
- 07Steer — adjustment without restart
Continuous correction as the alternative to periodic relitigation.
- 08AI as planning partner
Where the model adds leverage, where it actively misleads, and how to keep both straight.
- 09Tacit knowledge and the operator
Why the senior operator's chair is the most underweighted in the modern executive suite.
- 10Installing the discipline
Ninety days from cold start to first stake decision in a single operating unit.
- 11The prepared organization
What it looks like when the discipline becomes the operating system.
- 12The category and the categorist
Naming the discipline as a precondition for teaching it — and a hazard if mistaken for the work itself.
- 13The next ten years
What an AI-native operating environment asks of executive judgment between now and the late 2030s.
- 14Conclusion — A working discipline
What the prepared organization actually feels like from the inside on a Tuesday morning.
The book also names a new vocation — the Predictionist — formalized in Appendix B. The Predictive Planning Institute is building the certification at /certification.
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