Data Quality Assurance Plan

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Many things can go wrong during Primary Data Collection. The purpose of a data quality assurance plan is to think about everything that could go wrong ahead of time, and make a plan to preempt it. The plan should be shared with all impact evaluation stakeholders, including the Impact Evaluation Team and the Survey Firm before data collection starts. It is essential to delineate how data quality will be assessed and what actions will be taken when problems arise.

Guidelines

Your data quality assurance plan should include

• Back Checks
• Monitoring Data Quality
• For follow-up surveys, special consideration should be paid to Tracking and Attrition

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This article is part of the topic Field Management

Additional Resources

• Guidance on survey quality assurance from the UN World Health Surveys
• DIME's Planning for, Preparing & Monitoring Household Surveys
• DIME Analytics’ Real Time Data Quality Checks