Difference between revisions of "Field Management"

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Field management is the process of planning, monitoring and overseeing  primary data collection. Correct and careful management of fieldwork activities and field staff is essential to completing data collection on time, on budget, without missing observations, and at high quality. Without direct (and usually intensive) supervision of these critical aspects, unknown errors can enter the dataset. If these errors are made systematically by the data collection team, they can induce biases of unknown size and direction into the estimates of program effects for even the best-executed interventions.
 
Field management is the process of planning, monitoring and overseeing  primary data collection. Correct and careful management of fieldwork activities and field staff is essential to completing data collection on time, on budget, without missing observations, and at high quality. Without direct (and usually intensive) supervision of these critical aspects, unknown errors can enter the dataset. If these errors are made systematically by the data collection team, they can induce biases of unknown size and direction into the estimates of program effects for even the best-executed interventions.
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== Read First ==
 
== Read First ==
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* Field management is a key piece of any evaluation; it ensures timely, consistent and accurate data collection.
 
* Field management is a key piece of any evaluation; it ensures timely, consistent and accurate data collection.
 
* Insufficient supervision of field management aspects can result into systematic errors in the dataset and biased estimators.
 
* Insufficient supervision of field management aspects can result into systematic errors in the dataset and biased estimators.
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== Guidelines ==
 
== Guidelines ==

Revision as of 09:44, 11 February 2020

Field management is the process of planning, monitoring and overseeing primary data collection. Correct and careful management of fieldwork activities and field staff is essential to completing data collection on time, on budget, without missing observations, and at high quality. Without direct (and usually intensive) supervision of these critical aspects, unknown errors can enter the dataset. If these errors are made systematically by the data collection team, they can induce biases of unknown size and direction into the estimates of program effects for even the best-executed interventions.


Read First

  • Field management is a key piece of any evaluation; it ensures timely, consistent and accurate data collection.
  • Insufficient supervision of field management aspects can result into systematic errors in the dataset and biased estimators.

Guidelines

Field management activities can be divided into three broad areas:

  • Fieldwork organization - Planning all details of fieldwork, defining how the survey will be implemented, and piloting questionnaires and field protocols.
  • Field staff - Selection, training and supervision of field staff, including enumerators, contractors and Survey Firm.
  • Data Quality Assurance - Designing protocols and quality control methods to monitor ongoing data collection and ensure data consistency and quality.

The following steps are essential to ensure good field management:

Additional Resources