Utility analysis for the one-cohort selection-retention decision with a probationary period.

Abstract

This article provides a method for estimating the utility of a choice between alternative predictors for selecting a single cohort of new employees when some of these employees are later judged to perform at an unacceptable level and are therefore dismissed at the end of the probationary period. The method is shown to apply to both the traditional selection utility situation, in which the objective is to obtain a fixed number of hires, and the situation in which the objective is to obtain a fixed number of employees who successfully survive the initial probationary period. The utility estimation method proposed applies J. W. Boudreau and C. J. Berger's (1985) conceptual model to a singlecohort probationary case and extends that model by providing an estimation method to predict the utility of alternative predictors before selection takes place. The limitations of the proposal as well as its relationship to recruitment and separation costs are also discussed. I thank William Whitely and two particularly helpful anonymous reviewers for their useful comments on a draft of the article.A computer program (written in FORTRAN 77) that performs the utility calculations described in this article is available on request. Because the program calls routines from the Numerical Algorithms Group library, interested readers should first check whether they have this library (or a similar one) at their disposal.

3 Staffing Twenty‐first‐century Organizations

“…In fact, there are at a number of considerations-some of which increase payoffs and some of which decrease them-that, when taken into account, help to make staffing payoffs more realistic, and better connected to traditional financial logic (Cascio, 1993). Five of these are: (1) economic factors such as variable costs, corporate taxes, and discounting (Boudreau, 1983a); (2) employee flows, or additive cohort effects (Boudreau, 1983b); (3) probationary periods (De Corte, 1994); (4) the use of multiple selection devices (which, in combination, should yield higher validity coefficients); and (5) departures from top-down hiring (Murphy, 1986). Sturman (2000) used computer simulation of 10,000 scenarios, each of which comprised various values of the five factors just noted.…”

Utility Analysis: Current Trends and Future Directions

“…There is a need for systematic investigation of the various models (including the BCG extensions proposed by Boudreau and Berger (1985a, 1985b) and De Corte (1994, 1996) with respect to implementation problems and the congruence of utility estimates. Such investigations are essential if we are to take full advantage of the various utility models and for generating greater acceptance of the utility models among managers and business executives.…”

“…Other methods have been proposed for estimating SD Y (Cascio and Ramos 1986;Hunter and Schmidt 1982), Brogden's original UA model has been modified and extended (Cronbach and Gleser 1965;Boudreau, 1983aBoudreau, , 1983bBerger, 1985a, 1985b;De Corte 1994, 1996 and new UA models have been developed (Raju, Burke and Normand 1990;Raju, Cabrera and Lezotte 1996).…”

Utility analysis for the probationary selection decision to obtain a fixed quota of successful selectees

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SummaryThis article presents the extension of the one-cohort probationary selection (OCPS) framework (De Corte, 1994) to a multiple cohort model and shows how the extension can be applied to estimate the utility of probationary selection with replacement (PSWR) when a ®xed quota of successfully performing selectees is required. Next, formulas to compute the net present value of the OCPS and the PSWR approach to the selection of a ®xed quota of successful employees are derived.

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