Execution Failures in Retail Supply Chains - A Virtual Reality Experiment

Problem definition: Increasingly, retail store employees find themselves being asked to pick orders from inventory. These tasks are performed under intense conditions and, in many cases, are made more difficult because of high product variety and high degrees of product similarity.

Academic/Practical relevance: It is important to provide quantifiable information about the impact of task complexity and task intensity on worker performance and understand how actions can boost productivity and reduce errors.

Methodology: We conduct a real-effort task in a virtual environment where subjects are to sort cubes into bins. We study task complexity by varying the degree of similarity between the cubes and task intensity by varying the arrival pace of the cube. Beyond traditional descriptive performance analysis we also analyze subjects' movements.

Results: Reducing task complexity by making the cubes more distinct increases productivity by as much as 38.2% and reduces the error rate by as much as 93.6%. It also induces subjects to move more efficiently. Increasing task intensity improves throughput but decrease accuracy slightly; also, varying task intensity appears to improve performance via faster learning. The highest performing subjects appear to be those who move the least and the most fluidly. Subjects have a higher tendency to cut corners when the task is more complex and/or more intense.

Managerial implications: Managers should trade off throughput vs accuracy based on the cost of errors in their business. By designing products in a way that takes retail execution into account, and specifically, reduces product similarity, substantial improvements in performance can be obtained. Managers should consider varying task intensity for their workers and training them to make fluid motions.