Apresentação realizada por convite na Conferência Anual do Risk Specific Interest Group do PMI (Risk SIG), Long Beach - CA, 2002. Este artigo apresenta uma análise exaustiva da forma como diferentes políticas de controlo baseadas no método de EVM podem afectar o desempenho final do projecto. É utilizado um modelo de simulação dinâmica (System Dynamics) como suporte de teste e análise what-if
Earned Value Management (EVM) provides a number of benefits to project control, like the measurement of current progress, relative productivity (CPI) and relative work rate (SPI), as well as the estimation of likely completion dates and cost. It also provides the diagnosis of project performance down the WBS. EVM provides the project manager with reliable data to make good risk management decisions. EVM indices detect deviations while work is underway, and therefore provide an excellent means to define risk management triggers. However, effective decisions depend not only on data availability, but primarily on data utilization to formulate reactive and mitigating actions: given the specific values of the EVM indices, what are the best risk control decisions? If the project is saving on budget but is behind schedule, should we hire more staff, re-schedule interim milestones, or have more stringent QA procedures; or should we go for a combination of these? The effectiveness of risk decisions depends on their log-term impact on the overall project dynamics. Decisions affect the way in which the technical work is accomplished in the filed, as well as the way in which people behave; in turn these affect actual results, which lead to the EVM performance indices, thereby closing the loop. In order to formulate the best EVM-based risk control decisions, the project manager needs a laboratory to experiment the effectiveness of different policies. System Dynamics is a proven modeling technique, which delivers simulation models that capture effectively the complex web of cause and effect wherein project dynamics take place. “What-if” scenarios combining risks and mitigating decisions can be defined, simulated and analyzed. The use of System Dynamics to identify best EVM-based risk management policies is discussed in this paper. A simple SD project model is presented as practical example of application.
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