Task Performance in Knowledge-Intensive Environments: An Empirical Analysis of the Interplay between Worker and Supervisory Experience


Speaker


Abstract

Knowledge-intensive firms heavily rely on front-line worker experience as a source of value creation. In these firms, workers’ experience gained through task repetition has been shown to improve task execution performance. However, recent models of task execution performance have begun to account for the fact that workers seldom execute tasks in isolation and often augment their experiences by interacting with other personnel within the organization. In this study, we contribute to understand these interactions by hypothesizing that worker’s task execution performance depends on the interplay between worker’s task experience and manager’s supervisory experience. We test our hypotheses using data from 1500 software maintenance tasks 215 workers executed under the supervision of 75 managers in the software maintenance unit of a Fortune 100 multinational company. Results indicate worker’s task experience and manager’s supervisory experience have a strong interactive effect on worker execution times. Specifically, under the guidance of a manager with high supervisory experience, we find that the relationship between worker’s task experience and execution time monotonically decreases, consistent with the learning curve argument. However, under the guidance of a manager with low supervisory experience, the same relationship follows a U-shaped pattern such that task execution times decreases with increase in worker experience up to a threshold beyond which further accumulation of experience increases execution times. Furthermore, our econometric model indicates that worker and manager supervisory experience drive worker selection decisions, and that ignoring non-randomness in worker selection may lead to wrong statistical conclusions about the effect of experience on task execution performance. Overall our findings indicate the importance of pairing workers with managers based on role experience (i.e., supervisory or execution) for effective performance.