Utility Analysis for Multiple Selection Devices and Multiple Outcomes

Traditional utility analysis only calculates the value of a given selection procedure over random selection. This assumption is not only an inaccurate representation of staffing policy but also leads to overestimates of a device’s value. This paper presents a more accurate method for computing the validity of a selection battery for when there are multiple selection devices and multiple criteria. Application of the method is illustrated using previous utility analysis work and an actual case of administrative assistants with eight predictors and nine criteria. A final example also is provided that includes these advancements as well as other researchers’ advances in a combined utility model. Results reveal that accounting for multiple criteria and outcomes dramatically reduces the utility estimates of implementing new selection devices.

An Empirical Analysis of Manufacturing Overhead Cost Drivers

Empirical validity of the claim that overhead costs are driven not by production volume but by transactions resulting from production complexity is examined using data from 32 manufacturing plants from the electronics, machinery, and automobile components industries. Transactions are measured using number of engineering change orders, number of purchasing and production planning personnel, shop- floor area per part, and number of quality control and improvement personnel. Results indicate a strong positive relation between manufacturing overhead costs and both manufacturing transactions and production volume. Most of the variation in overhead costs, however, is explained by measures of manufacturing transactions, not volume.