US store detectives: the relationship between individual characteristics and job performance

US retailers lose over $30 billion in merchandise annually. Merchants also suffer billions more in losses of cash, supplies, time, equipment, and growing civil liability costs. In order to control these losses, retail companies use a combination of people, programs, and systems. A review of the literature indicates specialized loss prevention employees are an important part of many asset protection programs. A major interest of managers is improving the efficiency of their crime and loss control processes, including loss prevention store detective programs. Retail managers commonly use job performance reviews to gauge the individual efficacy of store detectives. In addition to job training, and job output supervision, research has indicated certain stable characteristics of individuals helps explain actual job performance, making pre-employment selection a critical part of process improvement. However, relatively little attention has been devoted to the selection of in-store detectives in the literature. Qualitative research was used to identify critical job tasks in order to develop and validate a specialised job performance instrument. The preliminary research with subject matter experts indicated four distinct job roles of store detectives. This job analysis also resulted in a new job performance rating instrument later tested in the quantitative phase of the project. Subsequently, a quantitative study of 201 US store detectives (using the performance instrument in a concurrent validity design) developed four distinct selection models designed to help explain role-specific job performance variance. Four hypotheses regarding the relationship between biographical data, personality traits, cognitive ability and the four measures of job performance were tested using multiple and logistic regression. The four resulting models explained between 13% and 23% of the variance in detective job performance measures. Implications of the project’s findings, and suggestions are also discussed in context to the current sample, as well as prior work in pre-employment selection research