Empirical and Statistical—these two characteristics describe the methodology that sets IPA apart from other consultancy firms.
Empiricism is necessary because project systems are so complex that it is impossible to understand every facet of a system on the basis of first principles. However, the project histories that are contained in the databases act as clear guides to understanding and quantifying performance.
Although it is true that every project is unique in some respect, it is possible—with sufficient information—to compare performances on an even basis. The principal advantage of IPA's statistical method is that it allows normative comparisons of project outcomes.
IPA has developed a series of statistical models that can predict results in a number of key areas including cost, schedule, and performance. Collectively, the group of models is known as the Project Evaluation System (PES®).
IPA has created more than 25 statistical models to benchmark cost and contingency use. Other models benchmark execution schedule and total cycle time and another series benchmark startup time and operational performance of newly completed assets. These models are tailored to the unique issues faced by each industry sector that IPA evaluates.
The premise of the models is that performance can be predicted based on historical relationships to project characteristics. The results are shown as probabilities rather than certainties. However, the predictions are not skewed to some preconceived weighing of inputs or execution philosophies. The analysis is empirically grounded and provides a fair, industry-wide benchmark for assessing and comparing project results with a known degree of accuracy.
IPA also tracks practices that greatly influence performance. Based on project data, analysts can evaluate the practices that historically have driven better results. The demonstrated link between the use of a particular practice and better results is referred to as a “Best Practice.”