Conducting a M&E Data Quality Audit
Conducting a data quality audit is essentially a very important aspect in implementation of Monitoring and Evaluation activities. In this article we are going to explain what the Audit is, why it is important and how it is conducted.
What is the Data Quality Audit?
This activity is conducted in order to determine the state in the quality of the data. When data collection takes place in the field, it is important that it adheres to the standards. The standard for data quality is as follows:
- ACCURACY: The data must reflect what is truly on the ground
- COMPLETENESS: The data must have no gaps
- CONSISTENCY: The methodology used to collect the data must be the same regardless of who collects, when it is collected and how it is collected.
- CREDIBILITY: The data must be trustworthy without attracting any form of doubt
- CURRENTNESS: The data must be up to date or recent for effective decision making to be achieved
Why is it Important?
Maintaining high data quality standards allows organization’s to lower the expense of finding and resolving incorrect data in their systems. Implementing agencies can also minimize operational mistakes and breakdowns in business processes, which can raise operating expenditures and diminish revenues.
Furthermore, strong data quality enhances the accuracy of analytics, which may lead to improved corporate decision-making, which increases sales, improves internal processes, and provides firms with a competitive advantage over competitors. Effective data quality management also allows data management teams to concentrate on more productive duties rather than cleaning up data sets. They can, for example, spend more time assisting business users and data analysts in making the most of available data in systems and promoting data quality best practices in business operations to reduce data mistakes.
How it is conducted?
To learn more on the step by step process of conducting this Audit, refer to the Audit HANDBOOK.
