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Probability Management extends traditional information management into the domain of probability distributions. The goal is to mitigate the Flaw of Averages, a class of systematic errors which occur when single numbers are substituted for uncertainties.

Two foundational articles on Probability Management were published by OR/MS Today in 2006. You can download the original articles in PDF form (Part I, Part II) or view them in HTML (Part I, Part II).


Probability Management is based on three core principles designed to improve the analysis and communication of uncertainty and risk:

  • Probability distributions should be organizationally certified to ensure consistency and accuracy.
  • Distributions should be modular, to allow cross-functional consolidation of risk models. The DIST (DIstribution STring) data type is a field-tested, compact and additive representation for distributions.
  • Graphical analysis of probability distributions and simulations is essential to understand, validate and communicate model inputs and outputs.

More about Probability Management >>

 News
DIST 1.0 specification released
The DIST™ (Distribution String) data type encapsulates thousands of Monte Carlo trials in a single cell, enabling modular risk models that can be consolidated across divisional boundaries. The DIST 1.0 standard was developed in cooperation with AnalyCorp Inc, Frontline Systems, Oracle Corp, SAS Institute and Vanguard Software Corp. More about DIST >>

Risk visualization seminars scheduled for Q1, 2009
Dr. Sam Savage will deliver a series of half-day seminars on Risk Visualization in cooperation with SAS. The seminar will include a discussion of the tools and practices of Probability Management, in particular, interactive simulation, the validation of stochastic data, and the presentation of probabilistic results to managers who are still suffering post traumatic stress syndrome from their college statistics course.
San Francisco, April 23, 2009 >>
Dallas, May 27, 2009 >>
Cary, June 19, 2009 >>


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