Risk Analysis of Project Scheduling Using Microsoft Excel

doi:10.31940/logic.v18i3.1135

Abstract

Scheduling plays a very important role for the successful implementation of construction projects. One of the biggest risks in scheduling is in terms of project costs and duration uncertainty. To anticipate these uncertainties, scheduling methods have been developed using probabilistic duration, including PERT and Monte Carlo Simulation methods. In this research the simulation process was carried out using Microsoft Excel which was integrated with @Risk's add-ins. From the results of the analysis, the project duration obtained from the scheduling model with the CPM method, conventional PERT and Monte Carlo simulation produces an average value that is close to the same. The difference occurs in the standard deviation value, the conventional PERT method produces the smallest standard deviation, followed by a Monte Carlo simulation using the PERT distribution and the last is Monte Carlo simulation using the TRIANGULAR distribution. From the results of the sensitivity analysis, it was found that the dominant input variables that affect the duration of the project are the duration of activities that most often enter the critical path or those that have a great critical index. Meanwhile, project costs are influenced by a combination of the duration of activities on the critical path and activities that have a great direct cost.

Highlights

Projects, especially construction projects, are always full of uncertainty, for example in terms of uncertainty over costs and completion times, which can cause a risk of losses for both contractors and project owners
The simulation process is carried out using Microsoft Excel which has been integrated with @Risk, an auxiliary application in Microsoft Excel to run Monte Carlo simulations
Input data in the form of: duration of each activity, direct costs of each activity and indirect costs of the project per day with their respective probability distributions. It is simulated by the Monte Carlo method using the @Risk program that has been integrated with Microsoft Excel

Summary

Introduction

Especially construction projects, are always full of uncertainty, for example in terms of uncertainty over costs and completion times, which can cause a risk of losses for both contractors and project owners. To minimize the impact of these risks, you need tools to analyze them. Some scheduling methods such as CPM and PDM have not included risk factors explicitly in determining the duration of each project activity, in which they still uses deterministic duration (exact number) which is considered most likely to occur. One alternative is to overcome the above problems by using Monte Carlo simulation method [1,2]. This method uses stochastic input like PERT, but with a choice of various probability distribution curves. The simulation process is carried out using Microsoft Excel which has been integrated with @Risk, an auxiliary application (add-ins) in Microsoft Excel to run Monte Carlo simulations

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Conclusion