From its extensive databases of projects, IPA has developed a set of statistical models that can evaluate project outcomes in a number of key areas, including cost, schedule, and operability. Collectively, the group of models and databases are known as the Project Evaluation System (PES®).
The PES is a reliable method for:
The underlying premise behind the PES is that the outcomes of projects can be predicted by understanding the historical relationship between project drivers (characteristics, technology, and project management practices) and the project's final outcomes.
Detailed data are the starting point for IPA's methodology. The PES is quantitative, empirical, and objective in its approach, and provides an industry-wide benchmark for assessing and comparing project elements and results. Empiricism is necessary because project systems are so complex that it is impossible to understand every facet of a system on first principles. However, project histories that are contained in the databases act as clear guides to understanding and quantifying the relationship between project drivers and project outcomes.
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 major advantage of IPA's statistical method is that it allows normative comparisons of project outcomes.
IPA collects project information in interviews with project team members. The project team members interviewed usually include, as relevant, the project manager; the process and lead design engineers; the cost estimator; the cost and scheduling engineer; and research and development, operations, maintenance, and business representatives. Data are gathered by the use of a standard IPA workbook involving the following major components:
The PES provides project-specific measures of cost, schedule, and operational performance outcomes. This project-specific comparison is important for understanding and quantifying the cost, schedule, and operational performance trade-offs necessary to produce a project that is optimal to the particular business circumstances.
The PES databases contain data for more than 2,000 individual data elements pertaining to more than 14,500 process plants projects,1,548 upstream projects, as well as more than 340 information technology projects. The data can be manipulated in many ways to determine central tendencies and variation within the designated samples.
The projects in the database represent a wide cross-section of process industry projects. Approximately 60 percent of the projects in the database have been constructed in North America, 19 percent in Europe, and the remaining percentage in Asia, South America, Mexico, Africa, and Australia.
All project types are covered, from greenfield to revamp. Projects range from small (less than $20,000) to very large (greater than $25 billion). The level of technological innovation varies from off-the-shelf (no new technology) to evolutionary (incremental improvement) to revolutionary (entirely new process).