Complexity: Moving Beyond Talk

Most of us have read about or heard talks on “complexity”; its nature, its impact on projects and ways to deal with it. Many have also worked on complex projects that are all too often failures, if not disasters.

What has been missing are practical ways to measure complexity and quantify its impacts; we know enough now to move beyond theory and “talk”. Empirical studies show that the distribution of actual/estimate cost for projects has a long tail on the high side. For complex projects, the tail is also fat; almost bimodal.

Traditional risk analyses fail to predict long, fat tails. Borrowing from chaos and complexity theory, the author has developed a practical complexity measurement and risk analysis method that warns management when a project’s risks threaten to push project behavior over the tipping point into chaos (i.e., a blowout).

Complexity theory is a mature project management topic; however, it has not found practical application in risk quantification which assumes orderly, linear behavior (and no, system dynamics modeling is not the answer).

The session reviews chaos and complexity theory (e.g., complex adaptive systems and the edge of chaos), how they relate to project cost performance, and finally presents a method that brings the understanding of chaos into a practical risk quantification toolset.

The session is based on Chapter 14 of the presenter’s book: “Project Risk Quantification: A Practitioner’s Guide to Realistic Cost and Schedule Risk Management”.

About The Speakers

John Hollmann

John Hollmann

Owner, Validation Estimating LLC

John Hollmann is author of the book “Project Risk Quantification” (hardcopy via or on Kindle via Amazon). John, owner of Validation Estimating, LLC (VE), works with capital program managers and project leaders to improve their cost engineering practices, including cost/schedule risk quantification in support of investment decision making. John regularly reviews major international estimates in many industries and conducts risk analyses in support of investment decision making and contingency setting.