Measuring and Managing Performance in Organizations (eBook)

This is the digital version of the printed book.

Based on an award-winning doctoral thesis at Carnegie Mellon University, Measuring and Managing Performance in Organizations presents a captivating analysis of the perils of performance measurement systems. In the book's foreword, Peopleware authors Tom DeMarco and Timothy Lister rave, 'We believe this is a book that needs to be on the desk of just about anyone who manages anything.'

Because people often react with unanticipated sophistication when they are being measured, measurement-based management systems can become dysfunctional, interfering with achievement of intended results. Fortunately, as the author shows, measurement dysfunction follows a pattern that can be identified and avoided.

The author's findings are bolstered by interviews with eight recognized experts in the use of measurement to manage computer software development: David N. Card, of Software Productivity Solutions, Tom DeMarco, of the Atlantic Systems Guild, Capers Jones, of Software Productivity Research, John Musa, of AT&T Bell Laboratories, Daniel J. Paulish, of Siemens Corporate Research, Lawrence H. Putnam, of Quantitative Software Management, E. O. Tilford, Sr., of Fissure, plus the anonymous Expert X.

A practical model for analyzing measurement projects solidifies the text—don't start without it!

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This is the digital version of the printed book (Copyright (c) 1996). Based on an award-winning doctoral thesis at Carnegie Mellon University, Measuring and Managing Performance in Organizations presents a captivating analysis of the perils of performance measurement systems. In the book's foreword, Peopleware authors Tom DeMarco and Timothy Lister rave, "e;We believe this is a book that needs to be on the desk of just about anyone who manages anything."e; Because people often react with unanticipated sophistication when they are being measured, measurement-based management systems can become dysfunctional, interfering with achievement of intended results. Fortunately, as the author shows, measurement dysfunction follows a pattern that can be identified and avoided. The author's findings are bolstered by interviews with eight recognized experts in the use of measurement to manage computer software development: David N. Card, of Software Productivity Solutions; Tom DeMarco, of the Atlantic Systems Guild; Capers Jones, of Software Productivity Research; John Musa, of AT&T Bell Laboratories; Daniel J. Paulish, of Siemens Corporate Research; Lawrence H. Putnam, of Quantitative Software Management; E. O. Tilford, Sr., of Fissure; plus the anonymous Expert X. A practical model for analyzing measurement projects solidifies the text-don't start without it!