Adherence to standard operating procedures for improving data quality: An empirical analysis in the postal service industry

Complete and accurate data is an important enabler of effective supply chain decision making. Despite the increasing efforts to fully automate data collection processes using advanced sensors and scanners, human operators are still in charge of data entry tasks in most industries. Unfortunately, operators do not often comply with the standard operating procedures (SOPs) and do not always exhibit the consistency and commitment required to collect high-quality data. In fact, data collection is often perceived as a non-value-adding activity that increases workloads and lowers productivity. We aim to empirically study the extent to which compliance with SOPs for data collection is affected by some of the key factors. Using a large dataset obtained from a leading postal service provider in Australia, we find that an operator's workload, fatigue, and related work experience directly impact the compliance levels. We also find that a company's compliance reinforcement intervention to improve compliance behavior can moderate these impacts.

Automated summary

Complete and accurate data is crucial for effective supply chain decision making. However, human operators in charge of data entry tasks often do not comply with standard operating procedures (SOPs), leading to low-quality data. This study finds that an operator's workload, fatigue, and work experience directly impact compliance levels, and a company's intervention to reinforce compliance behavior can moderate these impacts.