Quantifying the Effects of Budget Management on Project Cost and Success

Today's typical probabilistic cost analysis assumes an "ideal" project in which whenever a cost element comes in low its savings are passed on where they are needed. Unfortunately in the real world “Money Allocated is Money Spent" (MAIMS principle), and cost underruns are rarely available to protect against cost overruns while task overruns are passed on to the total project cost. Realistic cost estimates require a modified probabilistic cost analysis because the project cost at a given confidence level cannot be estimated until the budget management practices including allocation is specified. We present a probabilistic cost analysis that integrates valid mathematical with sound management techniques to obtain realistic cost estimates and effectively achieve project success. The analysis is readily implemented using standard Monte Carlo simulation Excel add-ins. We illustrate the approach and its implications for a representative design and engineering project. The analysis substantiates that today's typical probabilistic cost analysis is likely to severely underestimate project cost for probability of success values of importance to contractors and procuring activities. Budget management practices have a substantial impact on the cost of the project and/or probability of success. Using this information we develop a viable strategy for effectively allocating budgets and managing contingencies.