Document Detail

Title: RS156-1 - Engineering Productivity Measurement
Publication Date: 12/1/2001
Product Type: Research Summary
Status: Archived Supporting Product
Pages: 22
This publication has been archived, but is available for download for informational purposes only.

Describes a new model to measure engineering productivity, an elusive metric until now. Focuses on readily measurable, installed quantities at the discipline level in the detailed design phase. The model developed uses influencing factors appropriate to project characteristics and industry sector, and puts engineering and construction resources on an equivalent basis -- a significant advancement in integrated project controls.
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Abstract

Engineering costs on major capital construction projects continue to rise to levels approaching 20 percent of total project cost on Industrial projects. Increased facility complexity, OSHA documentation requirements, and the increasing need for more definitive and complete design are only a few of the factors driving this trend. In addition, the shortage of skilled craftsmen intensifies.

Reliable engineering productivity measurement is a critical element of predictable project performance and improvement. Unlike construction labor productivity, however, little research has been conducted in the area of engineering productivity measurement. Standard engineering productivity measurements must be established and applied to present day work processes before significant improvement and predictability of performance can be made.

CII established the Engineering Productivity Measurement Research Team (RT 156) to determine a valid measurement approach that will drive the improvement that present day design tools only promise. The research team concludes that a new model is required for measurement of engineering productivity. This model should focus on readily measurable, installed quantities. To be useful to the industry in driving continuous improvement, it should be applied at the discipline level in the detail design phase of projects using influencing factors appropriate to project characteristics and industry sector.

The research team has developed a model that meets these requirements. This publication presents the model as well as a summary of the research activities leading up it.