Governing Enterprise Estimation. Dieser Artikel ist nicht verfügbar.Governing Enterprise Estimation

Why do enterprise estimates fail even when the calculations appear precise?

Because organizations often approve a number before its scope, assumptions, evidence, uncertainty, and decision rights are ready to support it.

Governing Enterprise Estimation establishes the governance foundation of the Enterprise AI-Enabled Estimation Framework (EAEF). It shows how to turn incomplete enterprise intent into estimates that can withstand executive, financial, commercial, delivery, and assurance scrutiny.

Rather than treating an estimate as spreadsheet output, the book presents it as a controlled decision artifact connecting purpose, scope, technical baseline, evidence, assumptions, methods, uncertainty, review, approval, and permitted use.

Readers will learn to establish estimation policy and decision rights; classify initiatives and determine proportionate evidence and review; govern scope, complexity, uncertainty, and readiness; build a defensible Basis of Estimate with end-to-end traceability; conduct independent challenge and baseline approval; maintain estimates through forecasting, change, closure, and calibration; and govern AI-supported estimation while preserving source lineage and human accountability.

Written for executives, PMO and portfolio leaders, estimators, enterprise architects, delivery and commercial leaders, finance teams, and assurance professionals, this volume provides a practical foundation for estimates that are transparent, auditable, decision-ready, and defensible.