Certified Supply Chain Professional (CSCP) Practice Exam

Why is passive/automatic data considered beneficial in data management?

1. It requires extensive manual oversight

2. It is often less accurate than manual methods

3. It reduces human error associated with manual processes

4. It limits the types of data collected

The correct answer is: It reduces human error associated with manual processes

Passive or automatic data collection methods are beneficial in data management primarily because they significantly reduce human error associated with manual processes. When data is gathered automatically, the reliance on human input is minimized, hence lowering the likelihood of mistakes that can occur during manual data entry or observation. Human error can arise from various sources, including fatigue, misinterpretation of data, or oversight. By automating data collection, organizations can achieve a higher level of accuracy and consistency. This accuracy is crucial for making informed decisions in supply chain management, where even minor inaccuracies can lead to larger operational issues. Additionally, automated systems can continuously collect data in real-time, allowing for timely insights and improving responsiveness to changes in the supply chain. While other options mention drawbacks of passive data collection, such as the need for manual oversight or limitations in the type of data collected, these aspects do not outweigh the significant advantage of reducing errors through automation. This improvement in data integrity and reliability makes automated data collection an invaluable practice in modern data management strategies.