Ensuring Quality Data

The previous video emphasised that effective, data-driven supervision relies on a strong foundation of high-quality data. You also learned how important it is to have a data strategy and robust data governance, and that you need to align data needs with policy goals and supervisory objectives. 

A key decision for the data strategy is to decide whether to increase the level of data granularity. This has significant implications for the data collection mechanisms you use, as well as the internal capacity needed to handle high volumes of data. 

In this interaction, we explore some of the data quality issues that supervisors experience, as well as measures that supervisors can take to ensure data quality.