A. Summary of good practices
13.2. Integrating data from different sources is advised as the principle way to ensure the production of more detailed and comprehensive statistics as well as to reduce the burden on survey respondents. Compilers are encouraged to determine which data sources are most appropriate on a case-by-case basis, carefully considering the strengths and weaknesses of each data source. More specifically, compilers should be aware of the statistical units used in each source, the entities covered, the services categories identified, the variables compiled (e.g., the value of services exports/imports by EBOPS categories for the compilation of trade in services between residents and non-residents or output or turnover/sales and employment for the compilation of FATS, etc.), the availability of geographic breakdown, the time period of reference, the presence of thresholds and the survey frequency. Ideally, compilers should identify the sources in which they have more confidence, to be used as a benchmark for the other data sources.
13.3. To optimally exploit the advantages of data integration, it is recommended that the potential of using linked data be considered from an early stage and that decisions on survey design and sampling frameworks, for example, be made while keeping in mind that the data will be linked later on. Such forward thinking requires positive coordination across surveys, that is, compilers should ensure that the entities covered by different surveys and registers have sufficient overlap to avoid large shares of non-matched records, which make data integration more difficult and may create statistical biases. It is recognized that such coordination may be seen as a long-term strategy by countries whose capacity to compile statistics on the international supply of services needs significant strengthening.
13.4. The present Guide encourages national statistical agencies to adopt an integrated business survey programme, as outlined in the Guidelines on Integrated Economic Statistics. Specifically, under those guidelines, it is recommended that the collection of statistical information move from a “stovepipe” approach, in which each statistical programme collects information for its own purposes, towards an integrated approach, which aims to integrate survey design and implementation across all statistical programme areas. That recommendation is particularly relevant in the context of statistics on the international supply of services, given that information needs cut across various statistical domains. Such integration of data collection procedures will reduce the burden on respondents. It will also create a common standardized statistical framework for presenting more coherent statistics for the entire economy, covering business statistics, short term statistics, national accounts and international statistics, for evidence-based policy making.
13.5. It is good practice to use the statistical business register (SBR) to identify the common statistical unit and to provide the sampling frameworks. In addition, it is advised that ITRS and the trade register, which includes merchandise trade statistics, be linked to the SBR, with the enterprise as common statistical unit. This is particularly relevant for services categories with a strong link between trade in goods and trade in services, such as manufacturing services.
13.6. Compilers should take note that for the purposes of the present chapter, the term “data integration” refers to bringing together information from two or more data sources, with the object of better understanding and presenting the nature of a transaction than would be possible on the basis of any one source alone. “Data consolidation” is understood as the summation of data from multiple sources, in which the sources generally provide information on non-overlapping parts of the total. “Merging data” refers to the process of combining data, especially data covering the same activities or entities, from different sources via common denominators, such as a unique identifier in the SBR, when individual sources provide incomplete information. Merging data is the final step in the process and creates a unified view of an entity or activity. Before merging data, compilers must be aware of the definitions and methodologies used across the various data sources to ensure internal consistency of the merged data and to prevent the duplication or overlap of records.
 See Guidelines on Integrated Economic Statistics.