The Benefits from Better Testing and Training: A Comprehensive Framework
Abstract
This paper puts forward a new paradigm for thinking about better ways for assessing candidates and for training employees increased efficiency. It transcends the limitations of the two currently most popular paradigms for doing so: the psychologists' "utility" models and economists' decentralized matching models. In contrast to these models, this new paradigm identifies and includes three distinct ways by which improved assessment methods increase efficiency. It also points the way towards a method for quantifying all the benefits of using improved methods of assessment candidates. Moreover, this new paradigm can deal with the benefits of improved training methods as well as those of improved assessment methods. So, it provides a contest in which an analyst can trade-off expenditures for improving assessment methods against expenditures for improving training methods. This paradigm builds on a fifty-year old tradition in applying mathematical programming techniques to improve job assignment processes in the military services. It incorporates advances both in representing quantitatively on-the-job performance and in stochastic programming and integer techniques. The paper starts with the concept of an applicant's expected first-term productivity and lays out the structure of the mathematical programming model. Next, the paper explains how improvements in assessment methods and training programs can be linked to the model. Finally, it shows how the duel of the programming model and its shadow prices can be used to estimate the benefits of the improvement.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1999
- Accession Number
- ADA370507
Entities
People
- Burke Burright
Organizations
- Air Force Research Laboratory