Competence retention analysis: a technique for predicting and managing retention within organizational training design and delivery

Abstract

Those responsible in organisations for the design and delivery of training require a practical method for the analysis and prediction of skills retention. To address this, a taxonomy of nine psychological domains was developed specifically to provide a finer-grained approach to analysis of the skills required in the performance of trained tasks. An extant predictive model relevant to five of the domains was applied to produce a set of domain retention curves for physical/lower-order cognitive skills. These curves informed the development of a novel Competence Retention Analysis Technique (CRA-T) that incorporates a simple ‘traffic light’ approach indicating workforce proficiency, following a period without practice. CRA-T simplifies the process of understanding skill retention for practitioners by providing an alternative to separate empirical studies. By identifying the psychological domains involved in task performance insights can be gained into the acquisition and retention of these components, allowing the determination of those most at risk of decay. CRA-T is suitable for the analysis of a range of physical/cognitive tasks across sectors, where systematic approaches to training analysis/design for skill retention optimisation are required. CRA-T considers complex cognitive skills, but as no predictive models currently exist, longitudinal research is required to define their retention levels.