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Chapter 9  Data quality: assurance, measurement and reporting

9.1.            Introduction. The present chapter is based on IMTS 2010, chapter IX (on data quality and metadata). It provides an overview of quality assurance at customs and the responsible agency. Major quality issues are identified and discussed, including issues related to the editing of data and the responsibilities of each agency. Further, the chapter describes the process of producing quality reports and the measurement of quality, and provides examples and best practices. A special section is dedicated to reconciliation studies, cross-country comparability and bilateral data exchanges. Data quality assurance and reporting are essential for producing and disseminating trade statistics that are of the highest possible quality. This chapter aims to provide relevant information and to describe good practices so as to guide countries in making quality assurance, measurement and reporting operational. Data quality is a cross-cutting task and is touched upon throughout the Manual. This chapter is linked, in particular, with chapter V on institutional arrangements.

9.2.            Quality management system. Data quality assurance, measurement and reporting must be viewed as parts of a quality management system, often called a quality management framework (QMF). A QMF often contains the following elements: (a) a quality policy which affirms the commitment to quality management, (b) a quality model which provides a definition of quality, often formulated in terms of the components of data quality, (c) quality objectives, standards and guidelines, (d) quality assurance procedures which are often part of the production process, (e) quality assessment procedures, (f) quality measurement procedures and (g) quality improvement procedures.[1]

[1]   See Eurostat, ESS Handbook for Quality Reports, 2009 edition, Eurostat Methodologies and Working Papers, (Luxembourg, Office for the Official Publications of the European Community, 2009), p.15.