Difference between revisions of "Data Quality Assurance Plan"

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== Read First ==
 
== Read First ==
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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.  
 
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.  
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== Guidelines ==
 
== Guidelines ==

Revision as of 11:31, 5 April 2018

Read First

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

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This article is part of the topic Field Management

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