The General Policy for Data Quality Management in Agriculture provides for the development of a Code of Good Practice in Surveys for Harmonization of Approaches. during the design and production phases. Here, the term "survey" refers to any activity aimed at collecting or acquiring data for statistical purposes. This includes censuses, sample surveys, and the production of statistics from data from administrative records produced by agents. The creation and maintenance of an administrative file for statistical purposes does not fall into this category, only the exploitation of such a file for statistical purposes belongs to the field of surveys.
The collection of good data collection and analysis practices is one of the internal mechanisms contributing to the quality of processes, a prerequisite for the quality of products and services. Distributed to the staff of the practical guides while directing the responsibility since 2016 the GIZ initiated an institutional mechanism of collection of the data and on the other hand a measure of Audit (against verification) of the quality of the data collected by the team of responsible for the production of the data. However, GIZ's desire to reach out to a broader audience of customers, users and partners led to the development of the Policy Statement on Quality in Surveys. It consists of sections of the Code of Good Practice in Surveys whose content is less specialized.
The definition of quality
Like many statistical organizations, the Institute defines the quality of a product by all the characteristics that influence its capacity to satisfy a given need, to allow a planned use. GIZ uses six dimensions as criteria of quality: relevance, reliability and objectivity, comparability, timeliness, intelligibility and accessibility. Table 1 summarizes the definition and general guidelines for quality assurance for each of these dimensions. During the realization of a survey project, the dimensions are targets to be met to ensure the quality of the statistical information resulting from this survey. After its realization, they represent the criteria that make it possible to evaluate the quality of the statistical information produced. In the process of being implemented, the decisions made regarding the procedures and their implementation must take into account all the dimensions of quality. The quality assurance of a survey product therefore depends on the work done by the implementation team and all the staff involved, at all stages of the survey.
RE: What can we do to improve food security data?
Data Quality Management and Surveys
The General Policy for Data Quality Management in Agriculture provides for the development of a Code of Good Practice in Surveys for Harmonization of Approaches. during the design and production phases. Here, the term "survey" refers to any activity aimed at collecting or acquiring data for statistical purposes. This includes censuses, sample surveys, and the production of statistics from data from administrative records produced by agents. The creation and maintenance of an administrative file for statistical purposes does not fall into this category, only the exploitation of such a file for statistical purposes belongs to the field of surveys.
The collection of good data collection and analysis practices is one of the internal mechanisms contributing to the quality of processes, a prerequisite for the quality of products and services. Distributed to the staff of the practical guides while directing the responsibility since 2016 the GIZ initiated an institutional mechanism of collection of the data and on the other hand a measure of Audit (against verification) of the quality of the data collected by the team of responsible for the production of the data. However, GIZ's desire to reach out to a broader audience of customers, users and partners led to the development of the Policy Statement on Quality in Surveys. It consists of sections of the Code of Good Practice in Surveys whose content is less specialized.
The definition of quality
Like many statistical organizations, the Institute defines the quality of a product by all the characteristics that influence its capacity to satisfy a given need, to allow a planned use. GIZ uses six dimensions as criteria of quality: relevance, reliability and objectivity, comparability, timeliness, intelligibility and accessibility. Table 1 summarizes the definition and general guidelines for quality assurance for each of these dimensions. During the realization of a survey project, the dimensions are targets to be met to ensure the quality of the statistical information resulting from this survey. After its realization, they represent the criteria that make it possible to evaluate the quality of the statistical information produced. In the process of being implemented, the decisions made regarding the procedures and their implementation must take into account all the dimensions of quality. The quality assurance of a survey product therefore depends on the work done by the implementation team and all the staff involved, at all stages of the survey.