Probabilistic Project Time Management: Integrating Risk Register and Project Schedule Network.
Budi Hartono · Gadjah Mada University Library (Gadjah Mada University) · 2006
This paper presents a spreadsheet-based simulation model for analyzing project time management using probabilistic approach. The new feature in the proposed model is that the model recognizes the existence of risks and uncertainty and includes those factors directly on determining the lower-level project task or work package duration estimate. In other words, it provides a means of integrating project time management and risk management. The model utilizes the project risk register to identify all possible work packagerelated risks, to develop appropriate response and to qualitatively foresee the possible residual risk Referring to the risk register, the activity duration for each work package is then quantitatively estimated. The estimate is on the form of a probability density function (PDF). To convert the qualitative data to quantitative values, the Delphi technique, Nominal group technique or expert opinion can be employed. The PDF is then used as inputs of the spreadsheet-based Monte Carlo simulation. The proposed model offers some positive points. It provides a truly direct integration mapping between project scheduling and project risk Secondly, the work packagelevel of integration provides a lower level visibility. It assists the analyst to manage the details which in turn may increase the accuracy of the estimate. Despites its positive aspects, some further improvements are required The model needs a more robust method on converting qualitative to quantitative value. Moreover, it also needs an instrument to incorporate non-work package related risk. The model also needs an extension to cover other project factors: project cost and project specification. To provide more insight, a hypothetical case study on a product development project is also presented. Keywords: project, integration, risk register, probabilistic scheduling, Monte Carlo