Stochastic budget simulation

doi:10.1016/S0263-7863(98)00078-7

International Journal of Project Management

Volume 18, Issue 2, April 2000, Pages 139-147

https://doi.org/10.1016/S0263-7863(98)00078-7 Get rights and content

Abstract

The purpose of this article is to present a new method for cost estimation. The innovative idea is to combine the conventional calculation method stochastic simulation with basic facets of the successive principle. The purpose of this is to avoid the assessment of dependencies between cost items in the budget. The method is Stochastic Budget Simulation (SBS), and it is made operational with a software application. The method can be applied to most projects with a simple cost structure in the early stages where uncertainty plays a significant role in estimating the overall cost. The most likely users are planners, project managers or consultants. It is not necessary to understand the calculations, the statistical theory, or the simulation technique in order to use the method. However, users should be able to arrange items and overall influences in accordance with the urgent requirement of statistical independence. SBS is a new and radically different way to analyse and evaluate the economic consequences of large-scale projects by quantifying intervals for cost items and using simulation as a tool to represent distributions of the possible costs.

Section snippets

Context

Many projects are undertaken in a complex environment. Earlier definitions are annulled or at least changed and new situations continually arise. Often there are no reliable data when estimating cost items. In the proposal stage where a feasibility study is usually initiated, the design and demands are still relatively unclear. At this stage it is sensible to consider uncertainties and to use probabilistic range estimation rather than single point estimation, because a probabilistic range

Risk and uncertainty

Before describing the approach of Stochastic Budget Simulation it is necessary to explain the difference between risk and uncertainty. There seems to be some disagreement in the literature regarding the distinction between risk and uncertainty.[4] However, the writer finds it suitable to differ between the two words, and be careful not to use the words as synonyms. Confusion arises when one regards a subjective risk assessment as an uncertainty analysis.

A risk is a normally unwanted event. It

The approach

This section outlines the approach of Stochastic Budget Simulation. The approach is illustrated below in Fig. 1. It is urgent at this point to emphasise the conditions required for a realistic and reliable economic result. Prior to conducting SBS, the following five steps are recommended.

1.
An identification and grouping of all relevant matters with an overall influence upon the project. This requires use of the Work Breakdown Structure (WBS) as well as a consideration of stochastic dependencies.

Features of the software application

The method Stochastic Budget Simulation is made operational by a software program application based on Excel spreadsheets and Visual Basic. The main feature of the software program is to handle the stochastic simulation. The software program makes it possible to perform a sensitivity analysis, as it is possible to change the parameters (the minimum estimate, the most likely estimate and the maximum estimate) for specific cost items. This might be done if the calculator assesses that for

An example

Although the primary objective of this paper is to present a new approach to calculating the overall cost of any project in the conception phases, the following example will be used to illustrate the operational use and features of SBS. The example is based on a fictive developing software project. The budget is therefore not complete and the estimates do not reflect realistic values. Due to a better comprehension of the application of Stochastic Budget Simulation the spreadsheets are

The results

By using Stochastic Budget Simulation planners, decision-makers are able to make decisions based on a mathematically exact distribution instead of approximate algorithms. If the preconditions are well performed the total distribution might show the actual costs. The distribution of the total costs presents the expected mean and standard deviation, and subsequently establishes a confidence interval. The distribution further indicates the probability that costs will not exceed a particular value.

Conclusions

Most projects are conducted in a changing environment, which makes the analysis of the project economy in the early stages quite difficult. It is necessary to study the uncertainties involved in the project and to let the economic result reflect the possible total costs. By using a probabilistic approach by including distributions for each item in the budget, the decision-makers will have an analytical tool with which to evaluate the most likely total cost. This is done with the use of

Martin Elkjaer graduated in April 1998 from the Technical University of Denmark. He now works as a management consultant for Price-Waterhouse Coopers in Copenhagen, Denmark. This article is based on Mr. Elkjaer's report “Project management of cost and risk”[7] which concluded his Master of Science in Engineering (Planning and Technology Management). Requests or questions can be forwarded to [email protected]

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View full text

Stochastic budget simulation

Abstract

Section snippets

Context

Risk and uncertainty

The approach

Features of the software application

An example

The results

Conclusions

Risk analysis of a construction cost estimate

Journal of Project Management

Life cycle costing and risk management

E. & F.N. Spon

New project management principles for the conception stage

Proceedings, INTERNET 88 and Journal of Project Management