This Guest paper was submitted for publication and is copyright to Gary J. Summers © 2009
Published October 2009

Introduction | The Bayes' Law PPM Model | Proposals and Selection
New PPM Metrics | Management | Improving Your PPM Situation | Conclusion

Gary J. Summers received a BA in physics from Washington University, in St. Louis, and a Ph.D. in Industrial Engineering from Northwestern University. He was a professor at the Oregon Graduate Institute and a visiting professor at Portland State University. Dr. Summers is the founder and CEO of Star Decision Science, from which he conducts research and consults on decision-making in project portfolio management. He can be reached by Email at or through his web site at

Editor's Note

The author of this paper is attempting to develop a new model of Project Portfolio Management (PPM) with a view to analyzing PPM results and providing feedback. The idea is that this feedback, like any feedback, will provide real value to the organization by enabling it to make better decisions, use resources more effectively and hence become more successful. The author is currently seeking to test this model and is looking for companies willing to participate in his research.


If you fund a portfolio of projects, you will have a portfolio of results.
You should analyze these results to evaluate and improve your PPM.

This paper presents a new project portfolio management (PPM) model and corresponding metrics with which you can analyze your PPM. However, this paper is a condensed version that introduces numerous ideas in short order, so it may be find difficult to digest. If this is the case, you can find a more detailed explanation in my paper "Improving PPM with Feedback." You can download the paper from my website.[1]

Most companies perform PPM with a process involving evaluation, prioritization and selection, preferably linked to the organization's strategic goals. There is little if any attempt at gathering feedback from actual benefits achieved. So why do so many companies fail to analyze and learn from PPM results? There are two basic reasons:

  1. The models that help executives create portfolios are poorly suited to analyzing results.
  2. PPM results only include the outcomes of funded projects.

Presumably, the projects you fund are your best prospects. In statistical terms, the funded projects comprise a non-random sample of your proposals, and this fact complicates the analysis of PPM results. An analysis must address this complication or it will be biased and misleading.

In evaluating your project portfolio, your analysis must be more than just evaluating each project individually, such as comparing a project's expectations to its results. If you consider the entire portfolio of results, you can evaluate and improve each step of PPM. Figure 1 illustrates the feedback you can generate.

Figure 1: Flowchart of PPM process feedback
Figure 1: Flowchart of PPM process feedback

Most companies perform PPM with a variation of the process shown on the left side of Figure 1, but they omit the feedback steps on the right side of the Figure. Therefore, I am developing and testing a new PPM model that overcomes these limitations. The model produces new metrics, but unlike current PPM metrics, the new ones do not come from evaluations of current proposals. The new metrics reveal your company's actual proven performance.

In the course of introducing the new model to you, you will learn how Bayes' law models PPM. You will then learn metrics that reveal key qualities of your proposal processes, corporate strategy, project evaluation, project prioritization, project selection, Phase-Gate systems and resource allocation (the green feedback steps in Figure 1). These metrics are the outcomes I am currently developing and testing.


1. Go to, click on the title "A New Model of PPM" and select Improving PPM with Feedback. Site accessed 6/30/09.
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