Choosing between Unit Formulation and Cumulative Average

The difference between unit and cumulative average theory is that unit theory calculates each unit or lot individually, while cumulative average theory calculates the cumulative average cost of all units collectively to date. The difference between unit formulation and cumulative average theory is in where the curve affects the overall cost. Using a cumulative average for the first few units will yield higher cost savings than using unit theory with the same slope. As the number of units increases, the difference between the results decreases.

There are no firm rules that would cause a cost estimator to select one approach over the other, but some factors can help decide which might best model the actual production environment. Some factors to consider when determining which approach to use are:

1. analogous systems

2. industry standards

3. historical experience

4. expected production environment

Analogous Systems

Systems that are similar in form, function, development, or production process may help justify choosing one method over the other. For example, if an agency is looking to buy a modified version of a commercial aircraft and unit theory was used to model the production cost for a previous version of a modified commercial jet, the estimator should choose unit theory.

Industry Standards

Certain industries sometimes tend to prefer one method over the other. For example, some space systems are better modeled using cumulative average theory. If an analyst were estimating one of these space systems, cumulative average theory should be used, since it is an industry standard.

Historical Experience

Some contractors have a history of using one method over another because it models their production process better. The cost estimator should use the same method as the contractor if the contractor’s method is known.

Expected Production Environment

Certain production environments favor one method over another. For example, cumulative average theory best models production environments in which the contractor is starting production with prototype tooling, has an inadequate supplier base, expects early design changes, or is subject to short lead times. In such situations, there is a risk of concurrency between the development and production phases. Cumulative averaging helps smooth out the initial cost variations and provides overall a better fit to the data. In contrast, unit theory is a better fit for production environments where the contractor is well prepared to begin production in terms of tooling, suppliers, lead times, and so on. As a result, there is less need for the data to be smoothed out by averaging the results.