یک روش جدید برای کنترل پروژه تحت عدم قطعیت.بازگشت به اصول اولیه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|23181||2014||12 صفحه PDF||سفارش دهید||5780 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Project Management, Volume 32, Issue 3, April 2014, Pages 423–434
In this paper we propose a new methodology for project control under uncertainty. In particular, we integrate Earned Value Methodology (EVM) with project risk analysis. The methodology helps project managers to know whether the project deviations from planned values are within the “expected” deviations derived from activity planned variability. Although the methodology is new and innovative, we only go back to the fundamentals of project simulation to generate the “universe” of possible projects, according to the assumed variability of project activities. Then we organize and gather the information in order to make the data coherent with EVM. We explain the steps to implement the methodology and we show three case studies. The methodology makes explicit that the schedule and budget resulting from traditional methods like PERT are statistically very optimistic.
Project control consists in the comparison of a plan or baseline with the actual results of the project to identify deviations and activate early corrective actions if needed. Earned Value Management (EVM) is a widely used project management methodology for project control, as it integrates scope, time and cost control under the same framework (Abba and Niel, 2010, Anbari, 2003, Blanco, 2013, Burke, 2003, Cioffi, 2006, Fleming and Koppelman, 2005, Henderson, 2003, Henderson, 2004, Jacob, 2003, Jacob and Kane, 2004, Kim et al., 2003, Lipke, 1999, Lipke, 2003, Lipke, 2004b and McKim et al., 2000).
نتیجه گیری انگلیسی
In this paper, we suggest a new methodology for controlling projects under uncertainty. We integrate EVM methodology with all the literature concerning activity and project variability. EVM was developed under certainty assumptions, therefore project managers know whether the project is delayed or ahead of schedule, has over or under costs, depending on comparisons with planned values. But when we introduce variability within the analysis, we are more interested in knowing how far the deviations from planned value are (from the statistical point of view). This way, project managers will know whether the deviations from planned values are or not in agreement with the deviations assumed from activities variability and, therefore, take early corrective actions.