Project Management, Performance Measures, and Statistical Decision Making

Herding Cats

There is a current rash of suggestions on how to improve the performance of software projects. I work in the Software Intensive System of Systems domains in Aerospace, Defense, Enterprise IT (both commercial and government) applying Agile, Earned Value Management, Productive Statistical Estimating (both parametric and Monte Carlo), Risk Management, and Root Cause Analysis with a variety of capabilities. Figure 1 - Planned Estimates versus Actual Performance from [1].

Increasing the Probability of Program Success

Herding Cats

The origins of this paper came about at a recent JSCC meeting here in Boulder, with local Aerospace contractors, the DCMA (Defense Contract Management Agency) and several government agencies (NRO and NASA). Top Four Sources of Unfavorable Program Performance. Unrealistic Performance Expectations. Impacts of Risk on Program Performance. Be Clear About What the System is to Do in Units of Measure Meaningful to the Decision Makers.

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Complete Collection of Project Management Statistics 2015

Wrike

Agile Project Management. 80% of “high-performing” projects are led by a certified project manager. [4]. 89% of high-performing organizations value project management, 81% actively engage sponsors, 57% align projects with business strategy. [6]. More than 90% of organizations perform some type of project postmortem or closeout retrospective. [9]. How Project Success is Measured: 20% — Satisfied stakeholders. 19% say Agile techniques. Aerospace/.

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