Analysis

The series

One Management Truth

• Part 1 of 5One Management Truth: From AI Know-How to Project Control Do-HowWhat must be in place for AI to improve project decisions?
• Part 2 of 5The AI Adoption Dilemma: Start Small Enough to VerifyHow do we choose an AI pilot worth expanding?
• Part 3 of 5The Early Intelligence Dilemma: Investigate Early, Commit ResponsiblyWhen should an early signal trigger investigation—and when should it support commitment?
• Part 4 of 5The Maturity Dilemma: Capability Needs the Conditions to WorkIs our organization ready to use the AI capability it is building?
• Part 5 of 5Integrated Project Controls: From Principles to WorkflowsHow do we carry one project issue from evidence to an accountable decision?

The series

This series

This article is the foundation of a thirteen-part series. Each article takes one section and works it through in depth — the detailed questions, the method, and what it looks like on a live project. New articles publish twice a month and are linked here as they go live.

• Intelligence Is Becoming Abundant. Judgment Is Not.Why raw analytical horsepower is now cheap while sound judgment stays scarce — and what that inversion changes.
• AI Changed the Economics of Production — Not the Responsibility of DecisionAI collapsed the cost of producing analysis, but accountability for the decision still sits with people.
• In Capital Projects, Cheap Analysis Does Not Equal Good DecisionsA low price per analysis says nothing about whether the resulting capital decision is any good.
• The New Executive Advantage Is Not More Answers. It Is Better Framing.Leaders win less by having more answers and more by framing the right question in the first place.
• Q1–Q5: The Five Management Questions That Turn Analysis into Decision SupportThe five management questions that convert raw analysis into genuine decision support.
• D1–D5: Not All Evidence Has the Same JobThe five evidence roles, and why each piece of evidence has a distinct job to do.
• From Questions to Evidence to Decision: How the SD Engine ThinksHow the structured-decision engine moves from questions to evidence to an accountable decision.
• Why Technique Depth MattersWhy the depth of the underlying technique — not surface output — determines whether analysis can be trusted.
• What AI Should Actually Do in This SystemDefining the specific, bounded role AI should play inside a structured decision system.
• Lessons from the New AI Economy for Project Controls LeadersWhat project controls leaders should take from the economics of the new AI landscape.
• The Decision Standard for Consequential ProjectsThe standard a decision must meet before it is used to commit consequential capital.
• The Final Shift: From More Intelligence to Accountable DecisionMoving the goal from producing more intelligence to owning an accountable decision.
• xPM Point of View: Structure First. Integration Second. Intelligence Third. Accountability Always.The xPM position: structure first, integration second, intelligence third, accountability always.