One of the more fascinating elements of history is the way in which individual humans can influence its course and change the future. For instance, where would the world be today if Winston Churchill had not stood so indomitably – and virtually alone against Hitler and Nazism? One person can impact the whole of humanity from one point in time forward. Another such contributor to the progress of humanity was Thomas Bayes. Bayes, the father of Bayesian analysis., lived in England in the 1700’s. It was his forward thinking that brought us probabilistic stochastic modeling.
In his “Essay towards solving a Problem in the Doctrine of Chances,” published posthumously, Bayes wrote:
“If there be two subsequent events, the probability of the second b/N and the probability of both together P/N, and it being first discovered that the second event has also happened, from hence I guess that the first event has also happened, the probability I am right is P/b.”
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Probabilistic modeling is the basis of the mathematical statistical algorithmic portion of today’s schedule risk analysis. The ability to forecast schedule and cost probability has profound implications for our industry. Bayesian theory and its application relies on the current state of information as the basis to assess risks, which are mapped with project uncertainties at various stages during feasibility study, design, and construction.
Future entries in this series will discuss the flaws in the CPM model as a tool for schedule risk analysis, new thinking about the role of risk analysis within project management, and new ways to simplify cost and schedule risk analysis.