Neste artigo que mereceu o destaque da revista electrónica internacional PM World Today do PM Forum, Alexandre Rodrigues analisa a tendência actual para o crescimento da adopção do método de Earned Value Management (EVM) para o controlo de projectos e programas, em todo o mundo e nas mais váriadas industrias e áreas de aplicação. São apresentados vários casos de implementação do EVM no mundo real tanto em Portugal como no mercado internacional.
Alexandre Rodrigues, Maio 2008
by Alexandre Rodrigues, International Correspondent, PM Forum
The Earned Value Management (EVM) method has been introduced to the Project Management community for a number of decades. Initially developed in 1962 as a result of a joint effort between NASA and the US Department of Defense, the practical application of this project controlling technique was for a long period of time confined to specific industries and types of projects, particularly to the defense sector and to large projects. This phenomenon has mistakenly created the perception that EVM is only applicable (or worth applying), to these scenarios. Our practical experience over the last ten years of using and applying EVM in the field, has demonstrated exactly the contrary: Earned Value can be used effectively in any type of project and industry sector, very often requiring little effort in small projects. Ranging from small consulting projects with durations from 1 to 2 months and teams of 1 to 3 consultants, to large multi-year complex projects in the defense or telecommunications industries, we have been using Earned Value successfully. This is not only because Earned Value is, per se, a very complete and effective method for project performance measurement and controlling, but also because we developed a set of unique extensions to the basic method along with additional supporting tools and procedures. In this paper, we briefly present this extended version of Earned Value Management along with the critical factors for successful implementation, in particular communication and data quality issues.
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