Document Detail

Title: IR192-2 - Engineering Productivity Measurement System
Publication Date: 4/1/2006
Product Type: Implementation Resource
Status: Archived Tool
Pages: 67
The tool offers an off-the-shelf method and a custom-tailored approach to measure engineering productivity. Helps in establishing an engineering productivity baseline, but the user organization must already have good records of design hours per discipline and physical quantities installed for capital projects. The analyses can be shared across organizations, and new methods to improve projects can be validated and compared.

Due to the large size of the files (58MB), download may take some time.

NOTE: This publication's accompanying beta software is a proof of concept that has been archived and is available for download for informational purposes only.

By downloading or purchasing this publication, you understand and accept that its accompanying software might not open or run properly on current platforms and is not supported or maintained by CII.

Both the publication and its software are protected by applicable copyright restrictions as set forth by CII.

Any party interested in adapting this software is invited to contact CII Associate Director for Deployment to discuss licensing.
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Abstract

The Engineering Productivity Measurement System consists of this manual and the associated software. This manual will provide detailed instructions on the use of the software. However, the user is cautioned that the software arises from a statistical analysis of a particular database, and that attempts to use the results for cases too dissimilar from that database may produce inaccurate or misleading results. Accordingly, this manual will begin with a brief summary of the database and its development.

The data for this study were collected during the months of January–December 2002 from a group of engineering design firms and owner-operators that are members of CII (see Chapter 5). The large number and different types of organizations in CII provide a good target population for empirical studies. Data quality is indicated by the experience level of the person completing the questionnaire, which averaged 22.7 years.

In total, historical data on 118 projects were collected from 12 different companies. The projects can be categorized on a number of different dimensions.