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This paper seeks to develop a theory and a practical qualitative modeling tool that accurately predicts the probability that an industrial sales lead will convert to a booking based on observable lead characteristics and one that can be used by a typical sales manager.

Past lead characterization models were reviewed and gaps and weaknesses examined. A qualitative model of lead characterization and qualification was then developed based upon the determinants of customer purchase decisions.

In total, 16 commonly available lead characteristics that represent proxies for the eight determinants of industrial customer purchase decisions were identified. These were adapted to a scoring model that enables sales and marketing personnel to assess the probability that a lead will convert to a booking.

Different companies use different criteria and different weighting factors for making purchase decisions; therefore, no single quantitative lead characterization model will be accurate for all companies. The proposed model has not yet been formally field validated, but that is planned for future work.

The qualitative model proposed herein is more comprehensive than previous models and should thus prove more accurate. This should prove useful to sales and marketing managers, who need to forecast bookings and sales, optimally allocate resources, and structure marketing and promotion efforts for maximum return.

Several lead characterization models have been proposed in the past, but none are based upon sound theory and none have been field validated. Use of this work should significantly increase selling effectiveness as well as the accuracy of sales projections.

The purpose of this paper is to develop an improved management/performance model that yields superior business productivity by conjoining internal benchmarking, external benchmarking, and a strong employee performance/behavior paradigm.

Strengths and weaknesses of conventional benchmarking approaches to productivity maximization are examined through both literature surveys and experiments.

It is found that most benchmarking efforts are hampered by resistance of employees to change. It is therefore concluded that benchmarking efforts could be enhanced by integrating employee motivation/behavior programs with the benchmarking efforts.

The individual elements of the proposed model have been field‐validated; however the integrated model has not been field‐tested. This is planned as future research.

The conjoining of internal benchmarking, external benchmarking, and employee motivation/behavior programs should substantially enhance the results of productivity improvement programs based upon benchmarking.

This is the first effort that integrates internal benchmarking, external benchmarking, and employee motivation/behavior programs. This synergistic management model should be quite significant in enhancing corporate productivity.