Cherry-picking and its Negative Effect on System Service Level: Evidence from a Radiology Workflow Platform

Abstract

Piece-rate compensation schemes, where workers are paid for each completed task regardless of the time spent on it, are common in practice. However, imbalances between pay and workload of different tasks could result in cherry-picking of tasks deemed to have high pay relative to workload. Using a large dataset from a radiology workflow platform that connects off-site radiologists with hospitals, we empirically investigate whether radiologists cherry-pick tasks with high pay-to-workload, and if cherry-picking has a negative impact on system service level. In the platform we study, radiologists have discretion to select tasks from a common pool, and the service level is characterized by meeting priority-specific turnaround time targets. We show that turnaround time is monotonically decreasing in pay-to-workload. More importantly, we also show a spillover effect. Namely, that cherry-picking of low priority tasks can lead to longer turnaround times for higher priority tasks, resulting in delays. Our results suggest that organizations where workers have task discretion from a common pool need to carefully align their piece-rate compensation scheme with the workload of each task. Imbalances may lead to a degradation in the system service level provided to time-sensitive customers.