Performance Measurement (an integral part of Earned Value Management (EVM)) has, over at least the last two decades, become a gold standard process (i. e., best practice) for monitoring and controlling the progress of software development projects. It employs the fundamental measurement-based command/feedback principals of control theory to increase the probability that a project’s actual performance matches its expected (planned) performance; i. e., that a project is delivered on time and within budget or, at least, that there is an early warning of looming disaster. This process is generally well-understood by project managers and reasonably well supported by commercially-available tools. Experience with this process suggests an opportunity for significant process improvement by including established estimation methodology and algorithms as part of the forecasting and re-baselining activities performed during the project monitoring and control process. This paper first reviews the fundamentals of software project management and of Performance Measurement (including some proposed extensions to the notion of earning value) and then proposes a process called Parametric Project Monitoring and Control (PPMC) whereby accepted algorithms currently used for software cost and schedule estimation during the project planning process are incorporated into the forecasting and re baselining processes to yield a more-realistic time-range prediction of the project’s cost and duration.
Integrating Three Level 2 CMMI™ Process Areas: Closing the Loop on Software Project Management
2006-01-01
578142 byte
Conference paper
Electronic Resource
English
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