Cost contingency

When estimating the cost for a project, product or other item or investment, there is always uncertainty as to the precise content of all items in the estimate, how work will be performed, what work conditions will be like when the project is executed and so on. These uncertainties are risks to the project. Some refer to these risks as "known-unknowns" because the estimator is aware of them, and based on past experience, can even estimate their probable costs. The estimated costs of the known-unknowns is referred to by cost estimators as cost contingency.

AACE International, the Association for the Advancement of Cost engineering, has defined contingency as "An amount added to an estimate to allow for items, conditions, or events for which the state, occurrence, or effect is uncertain and that experience shows will likely result, in aggregate, in additional costs. Typically estimated using statistical analysis or judgment based on past asset or project experience. Contingency usually excludes:

1. Major scope changes such as changes in end product specification, capacities, building sizes, and location of the asset or project;
2. Extraordinary events such as major strikes and natural disasters;
3. Management reserves; and
4. Escalation and currency effects.

Some of the items, conditions, or events for which the state, occurrence, and/or effect is uncertain include, but are not limited to, planning and estimating errors and omissions, minor price fluctuations other than general escalation), design developments and changes within the scope, and variations in market and environmental conditions. Contingency is generally included in most estimates, and is expected to be expended".^[1]

A key phrase above is that it is "expected to be expended". In other words, it is an item in an estimate like any other, and should be estimated and included in every estimate and every budget. Because management often thinks contingency money is "fat" that is not needed if a project team does its job well, it is a controversial topic.

In general, there are four classes of methods used to estimate contingency. ."^[2] These include the following:

1. Expert judgment
2. Predetermined guidelines (with varying degrees of judgment and empiricism used)
3. Simulation analysis (primarily risk analysis judgment incorporated in a simulation such as Monte-Carlo)
4. Parametric Modeling (empirically-based algorithm, usually derived through regression analysis, with varying degrees of judgment used).

A fifth method, called Reference Class Forecasting, was recently developed, based on prospect theory and theories of the planning fallacy, that won the Nobel Prize in economics 2002.^[3]

While all are valid methods, the method chosen should be consistent with the first principles of risk management in that the method must start with risk identification, and only then are the probable cost of those risks quantified. In best practice, the quantification will be probabilistic in nature (Monte-Carlo is a common method used for quantification).

Typically, the method results in a distribution of possible cost outcomes for the project, product, or other investment. From this distribution, a cost value can be selected that has the desired probability of having a cost underrun or cost overrun. Usually a value is selected with equal chance of over or underrunning. The difference between the cost estimate without contingency, and the selected cost from the distribution is contingency. For more information, AACE International has catalogued many professional papers on this complex topic.^[4]

Contingency is included in budgets as a control account. As risks occur on a project, and money is needed to pay for them, the contingency can be transferred to the appropriate accounts that need it. The transfer and its reason is recorded. In risk management, risks are continually reassessed during the course of a project, as are the needs for cost contingency.

References

1. ^ "Cost Engineering Terminology", Recommended Practice 10S-90, AACE International, WV, rev. 2007
2. ^ Hollmann, John K., "The Monte-Carlo Challenge: A Better Approach", 2007 AACE International Transactions, AACE International, Morgantown, WV, 2007.
3. ^ Flyvbjerg, Bent, "From Nobel Prize to Project Management: Getting Risks Right." Project Management Journal, vol. 37, no. 3, August 2006, pp. 5-15.
4. ^ Uppal, Kul (editor), Professional Practice Guide (PPG)#8, "Contingency", 2nd Edition, AACE International, Morgantown WV, 2007.