Data quality standards

This paper from USAID provides guidance for ensuring good data quality as a central part of establishing effective management systems.

The paper argues that without good quality data, decisions makers will lack confidence in the data and may make decisions based on misleading data.

The guide describes the following five standards as essential to ensuring the data you collect is of high quality.

  1. Validity
  2. Reliability
  3. Precision
  4. Integrity
  5. Timeliness 

Contents

  • Why is data quality important
  • Data quality plays a central role in developing effective performance management systems
  • Data quality standards
  • Validity
  • Reliability
  • Precision
  • Integrity
  • Timelines

Sources

Britan, G., & Mehdi, S. USAID, Office of Management Policy, Budget and Performance (MPBP). (2009).Performance monitoring & evaluation tips data quality standards (NUMBER 12, 2ND EDITION). Retrieved from website: http://transition.usaid.gov/policy/evalweb/documents/TIPS-DataQualityStandards.pdf