Asee peer logo

Use Of Static And Predictive Metrics In R, D & E Management

Download Paper |

Conference

1996 Annual Conference

Location

Washington, District of Columbia

Publication Date

June 23, 1996

Start Date

June 23, 1996

End Date

June 26, 1996

ISSN

2153-5965

Page Count

5

Page Numbers

1.500.1 - 1.500.5

Permanent URL

https://peer.asee.org/6368

Download Count

26

Request a correction

Paper Authors

author page

Donald N. Merino

Download Paper |

Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

~ Session 2542

Use of Static and Predictive Metrics in R, D & E Management

Donald N. Merino, Ph. D., P. E. Professor of Management and Engineering Management, Stevens Institute of Technology, Hoboken, NJ

Introduction

Metrics are a fundamental part of managing the R, D and E function. Every major R, D and E organization collects and analyzes metrics. Continuous process improvement (CPI) requires metrics. However, as the results of a symposium attended by R, D and E Research Directors of hi-tech companies indicates that no one is satisfied with the metrics they used.

A methodology is presented that shows the relationship between static and predictive metrics and continuous process improvement. A comparison of the pros and cons of static and predictive metrics and experiences are presented.

Findings from SATM and Symposium on metrics in R, D and E

A symposium attended by research directors of leading hi-tech companies in the NJ area on the subject of the use of metrics in Research, Development and Engineering (R, D and E) was held. The symposium was sponsored by the Stevens Alliance for Technology Management (SATM)* .

Some of the observation and lessons learned from this symposium are (Merino, 1993) : - Everyone had an extensive set of metrics and had a TQM process for R, D and E. - No one was satisfied with the metrics they used in R, D &E. - There was a heavy reliance on Static metrics. - There was great interest in Predictive metrics.

In addition, all the companies agreed that for metrics to be effective they must be directly related to the improvement process in which they are embedded. All the companies had Quality Management (QM / TQM) programs for their organizations and in the R, D and E areas they presented. To understand the value of metrics, one must understand how they fit into the QM/TQM, continuous process improvement (CPI) process.

Continuous Process Improvement (CPI) and Metrics

Continuous Process Improvement (CPI) is one of the absolutes of quality (Juran 1988). CPI requires measurements and measurements require metrics. Figure 1 represents a typical approach to CPI and the role that metrics play.

In 1993, the Stevens Alliance for Technology Management consists of AT & T, Bell Labs, Allied Signal R &T, Exxon R & E, Picatinny Arsenal (ARDEC), Engelhardt (R & D). @!iii’1996 ASEE Annual Conference Proceedings } ‘.,+,~ll~’: .

Merino, D. N. (1996, June), Use Of Static And Predictive Metrics In R, D & E Management Paper presented at 1996 Annual Conference, Washington, District of Columbia. https://peer.asee.org/6368

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 1996 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015