How far can IT standards and tools help to reduce response burden?

Transcription

1 How far can IT standards and tools help to reduce response burden? John ALLEN and Claudia JUNKER Eurostat Abstract. NSIs use a rich set of IT standards and tools for raw data collection from businesses. XBRL is particularly interesting because of the potential for reducing response burden by unifying the different kinds of reporting required of businesses. The paper presents the conclusions of the Eurostat XBRL Pilot Project. It is argued that, for XBRL as for other IT standards and tools, real reductions in response burden require advanced technologies to be accompanied by rationalisation of reporting requirements and concepts. 1. Introduction Many of the instruments for reduction of response burden come from IT: there is a whole collection of standards and tools which have been developed and in some cases adopted. This document considers how far these standards and tools can be effective in the light of recent developments and experience. It is based particularly on a selection of the projects presented in two Task Forces, the Eurostat Task Force on Collection of Raw Data (CORD)[1], which has met regularly since 1999, and the UNECE/Eurostat Task Force on Electronic Raw Data Reporting (ERDR)[2], which worked on this subject in ; the results of the XBRL Pilot Project which was conducted by Eurostat together with a group of Member States in [3]. This document deals only with the impact of the standards and tools on raw data collection from businesses other than financial institutions by NSIs (together with other national authorities collecting statistical data, such as customs authorities). It does not consider data exchange between NSIs and Eurostat, nor does it consider their impact on the workload of NSIs. It should be noted that the collection of statistical data from banks and other financial institutions raises issues which are not addressed here, concerning the choice of standards. 2. Standards 2.1. XBRL Background XBRL[4] is the extensible Business Reporting Language, a technical standard for electronic communication of business and financial data. It is developed and maintained by an international non-profit consortium of more than 300 companies, organisations and government agencies. It is based on the XML and XLink technical standards.

2 It occupies a prominent place in this document because it has achieved high public visibility as a technology for company reporting, with its protagonists claiming that a wide range of benefits would be achieved by its wider adoption. For example, in March 2008 the European Parliament adopted the Lehne report[5] which mentions XBRL as an important element of a simplified business environment for companies in the areas of company law, accounting and auditing; the Parliament s resolution on this report, adopted on , urges the Commission to present a roadmap for introducing XBRL reporting in the EU [6]. Furthermore, the Security and Exchange Commission (SEC) in the US announced earlier this year that for the 500 largest companies the compulsory filing of returns (first financial data but later also narrative information) will be required in XBRL format from 2009 onwards and other companies will have to follow. A very similar development can be found also in Japan. Thus XBRL gains importance beyond the EU and may get even stronger emphasis Pilot Project For the ESS, the interest of XBRL lies in the possibility of exploiting for statistical purposes the use of XBRL in company reporting (for example, the company accounts which are delivered to national regulators and central banks), in order to lower the statistical reporting burden on businesses. In , Eurostat coordinated an XBRL Pilot Project to test the feasibility of exploiting XBRL company reports for statistical purposes. This project was carried out under the umbrella of the Accounting and Statistics Task Force, which is a joint Eurostat-ECB group comprising representatives of NSIs and Central Banks. The Pilot Project was financed by the EU IDABC programme[7], as part of the Eurostat X-DIS (XML for Data Interoperability in Statistics) project. The objective of the Pilot Project was to come to clear conclusions whether or not XBRL can be used efficiently in the statistical reporting chain and whether or not reporting with XBRL can gain widespread acceptance among European enterprises and NSIs. The pilot focused on the reporting by enterprises to NSIs and not on the reporting from NSIs to Eurostat. These objectives were to be reached by accomplishing the following tasks: mapping of existing taxonomies and the requirements in the relevant statistical legislation; monitoring of XBRL developments in existing XBRL projects in the statistical and accounting domains; creation of a statistical taxonomy; testing taxonomies in a live environment with the cooperation of four NSIs; assessing conditions for XBRL acceptance by NSIs; investigating whether it is feasible that enterprises would no longer send their information to the NSI, but that enterprises post data on their websites from where they would be retrieved by the NSI. The XBRL Pilot Project started in March 2006 and ended in December The taxonomy mapping task has been accomplished and a statistical XBRL taxonomy was developed for the Structural Business Statistics framework in 2006 and for the Short-Term Statistics framework in Eurostat formed a small Task Force to contribute actively to the above tasks and to monitor project progress. As of November 2007, the Pilot Project Task Force members were: Active members Observers NSIs: BE, ES, IE, NL, SE NSIs: LU, PL CBs: DE, ES 2

3 Results of the Pilot Project The results of the Pilot Project can be summarised as follows: On the positive side: It was feasible to create a European statistical XBRL taxonomy incorporating the SBS and STS variables, as such a taxonomy was developed within the Pilot Project. A successful test of the use of a reference XBRL software architecture for primary data collection, developed by Eurostat, was conducted with Belgium (Statbel), who are now considering to use and extend this software for their XBRL-based data collections. On the feasibility of exploiting XBRL for statistics: Although there are a number of statistical surveys of enterprises (for example, labour cost, structure of earnings, vocational training, ICT, tourism statistics) the Pilot Project was not able to identify any areas of statistics other than SBS or STS where the use of XBRL could be investigated in the short term, as these other areas involve data which are quite separate from financial reporting There was little evidence of existing or spontaneous use of XBRL for reporting by companies. This was true for all the countries participating in the Pilot Project, even though the group included countries where XBRL had been promoted as a tool for reporting. The reasons for the lack of real instances of XBRL reports from companies is not clear. Several factors may be relevant, for example: accounting software and management information systems at companies are not capable of producing XBRL output; accounting software and management information systems at companies are capable of producing XBRL output but the rather complex state of national XBRL taxonomies has made it difficult for companies to exploit this capability; companies see no added value (for example, no substantial potential in reducing reporting burden) in producing reports in XBRL; there is as yet no European initiative corresponding to the US SEC programme for XBRL reporting and encouraging the use of XBRL. The Task Force saw this as a particularly important factor explaining the limited XBRL usage. There were big differences between countries in the degree of reusability of financial and balance sheet data/information for statistical purposes and the level of successful mapping between the SBS and STS variables and the test instances provided by countries was quite low: 3

4 Case/Taxonomy Framework Successful Matching Percentage NL case SBS 33% NTP version 1.1 STS 52% BE case SBS 5% CBSO_NBB version 1.1 STS 9% IE case SBS 9% Irish GAAP version 2.1 STS 13% ES case SBS 9% ES-BE-CB version 1.1 STS 17% As seen here, only in the NL case could the level of mapping be said to be encouraging: the NTP taxonomy version 1.1 is a reasonably good candidate for obtaining IFRS-based statistical information. The GAAP-based taxonomies used for the mapping exercise in BE, ES and IE seemed not to offer a satisfactory basis for generating useful data for SBS or STS. Even the low level of mapping needs to be further checked in what concerns the exact definitions and concepts behind accounting data and statistical variables to identify whether the definitions behind the variables are identical or whether an identical content can be derived by calculations. It was noted that it is not possible to extrapolate the findings of a mapping exercise to different versions of the taxonomies involved (as in the case of NTP 1.0 and 1.1). Even where taxonomies are fundamentally similar, the mapping process is affected by the differences between versions; in any future exploitation of XBRL for statistical purposes, it will be necessary to avoid versioning issues resulting from linguistic or terminological changes. The diversity of national XBRL taxonomies reflects the complexity of existing financial reporting arrangements, where different companies are required to follow GAAP and/or IFRS and where local GAAPs may substantially differ from IFRS and among each other. The latter would impose difficulties to create European wide taxonomies for given statistical areas with a high matching of concepts. The Task Force concluded that the Pilot Project had demonstrated that, currently, it is not realistic to propose the reuse, for statistical purposes, of XBRL reports sent by companies to regulators. In fact, the results of the Pilot Project demonstrate what could be considered self-evident, which is that a technology such as XBRL cannot impose uniformity and efficiency on a rather heterogeneous set of reporting requirements. On the other hand it can potentially trigger a development in such a direction. 4

5 Eurostat envisages further work on XBRL within the MEETS programme, but on the precondition that XBRL is linked to broader actions on improving reporting frameworks. As a step in this direction, Eurostat plans to start, in 2009, a project to develop a taxonomy linking accounting and statistical concepts for business reporting, with a focus on SBS and STS first and extending it to other statistical areas is feasible. The project should be based in a first phase on the already adopted IFRS for traded companies and later encompass also the not yet adopted IFRS for small and medium-sized enterprises (SME). Obviously, this taxonomy project will make use of the work done in this area by the XBRL Pilot Project. This project will thus address the challenge to first develop common taxonomies for accounting data and statistical variables and check in detail the definitions and concepts behind these data and variables to identify whether they are similar or not. The intention of this taxonomy project is to produce a kind of list of statistical variables that can be retrieved from accounting information available in the companies either directly or on the basis of calculations but also a list of variables for which no corresponding information exists in the companies' accounting system. Its results are thus a sort of pre-condition to embark on any future technology-oriented XBRL project SDMX SDMX[8] consists of technical and statistical standards and guidelines, together with an IT architecture and IT tools, to be used for the efficient exchange and sharing of statistical data and metadata. Seven European and international organisations (the Bank of International Settlements, the European Central Bank, Eurostat, the International Monetary Fund, the Organisation for Economic Co-operation and Development, the United Nations Statistical Division and the World Bank) act as sponsors of SDMX. In February 2008, at the 39 th Session of the UN Statistical Commission, SDMX was recognized as the preferred standard for exchange and sharing of data and metadata in the global statistical community[9]. SDMX is built around the SDMX Information Model, which was designed to described aggregated statistics of the kind typically transmitted from national statistical authorities to Eurostat, to ECB and to international organisations which collect statistics; the SDMX Information Model also fits the kinds of statistics which are disseminated at national or international level. The SDMX Information Model is essentially the same as the GESMES/TS Information Model, and GESMES/TS - now renamed SDMX-EDI - is now part of the SDMX standard. However, GESMES uses the EDIFACT syntax, whereas full exploitation of the possibilities of SDMX requires the XML syntax (SDMX-ML), which is supported by a much richer set of tools. Although SDMX is being applied for some microdata (for example in the exchange of PPP data), it is not recommended for raw data reporting by businesses. However, the SDMX initiative can contribute to reducing the response burden for businesses, since it includes actions aimed at harmonising the statistical concepts and code lists used for data collection for different purposes, via the SDMX content-oriented guidelines which include cross-domain concepts and code lists[10]. SDMX can also benefit businesses because the SDMX standards and architecture facilitate regular retrieval of statistical data through automated systems. SDMX and XBRL therefore have clearly different functions, with XBRL being useful, or potentially useful, for raw data reporting by businesses, and SDMX supporting the subsequent stages of statistical production and dissemination. Nonetheless, the SDMX and XBRL sponsors are aware of the need for interoperability between the two frameworks, which would make it easier to move data and metadata between the business reporting and statistical communities, and an expert group is working on this topic[11]. 5

6 2.3. Other standards During the past twenty years Eurostat and Member States have developed a number of standard formats and tools to support raw data reporting. Much of this work was financed through the EU IDA-I and IDA-II programmes[12] as well as various EU research and development framework programmes, and was linked to standardisation activities under CEN[13]. The following paragraphs do not attempt a complete review of this work, but list a few examples of the standards that were developed. We also give examples of national and sectoral standards which are relevant to the theme of this document. RDRMES[14] is an EDIFACT standard for raw data reporting, which was developed in parallel with GESMES. Like GESMES, it is a generic framework message covering as much as possible of its field of application. In practice, applications only use a part of the elements and options offered by the generic message. This leads to subsets of generic messages being defined for specific purposes. Because standards such as RDRMES are designed to be embedded within national data collection systems, it is difficult to judge the extent of the current usage of RDRMES. One example of its use is in the Belgian EDIVAT system[15]. XML4DR[16] was developed as the XML version of RDRMES, within the IQML project (see below). In addition to providing a data exchange format, XML4DR allows the specification of forms for Web-based surveys, including many useful features like validations, calculations, dynamic guidance and support to automated database access. The use of XML makes it more interesting for current IT systems developement and XML4DR has been used or proposed to be used in a number of national data collection systems, for example in Norway and in the Netherlands[17]. Trade data standards: there is a whole family of standards developed for raw data reporting for intra-eu (Intrastat) and extra-eu (Extrastat) trade statistics. These are subsets of customs message standards (as opposed to statistical message standards). The EDIFACT messages are CUSDEC/INSTAT (for Intrastat declarations), CUSDEC/EXSTAT (for Extrastat declarations) and CUSRES/INSRES (response message relating to both CUSDEC/INSTAT and CUSDEC/EXSTAT). XML equivalents have also been developed. IQML (Intelligent Questionnaire Markup Language) was an EU research project (5FP)[ 18]. IQML aimed at developing a software suite and extended mark-up language for intelligent questionnaires intended to automate and integrate the data collection process by producing software to support and implement emerging metadata standards based on XML. The ultimate goal was to improve the accuracy and timeliness of statistical data collection from enterprises and individuals, and also to reduce response burden for enterprises. In the IQML project, modules have been produced for metadata maintenance, questionnaire design, questionnaire presentation, database interrogation and survey administration. The QDT (Questionnaire Design Tool) module enables the user to design and manage questionnaires through the question bank concept, which enables reuse of questionnaire components. The Metadata Repository module supports the storage and retrieval of metadata objects. The QPT (Questionnaire Presentation Tool) module renders the questionnaire for use with web browsers, supports the presentation of questionnaires defined in the QDT and implements validation, navigation and calculation rules. The DIT (Database Interrogation Tool) module supports the extraction of data from popular databases and maps this data to the questionnaire XML. The SAT (Survey Administration Tool) module allows the questionnaires to be integrated with registers and sample frames. 6

7 Various data models have been developed in the IQML project. The QPT XML model for on-line questionnaires is the basis for XML4DR (see above). Certain national standards are also relevant in this context of this document. As examples, we mention here two XML-based data standards: (i) DatML, used in the estatistik.core system in Germany (see below) and (ii) the data file specification which the CSO in Ireland offers for respondents in some major business surveys[19]: CSO has been successful in getting payroll software providers in Ireland to implement the generation of reports from their software packages using this data file specification. A company can use such reports to meet the majority of the data requirements of the Earnings, Hours and Employment Costs Survey (EHECS) and the National Employment Survey (NES). There are many other sectoral XML standards for data exchange which might be considered as candidates for raw data collection for statistics, on the principle that if a standard is already used by a businesses of a particular type, then those businesses might already be generating reports containing data needed by NSIs. Within the X-DIS project, Eurostat has conducted a study[20] to identify other sectoral XML standards which could potentially be exploited for statistical purposes. Thirty-six XML-based standards were reviewed in the study. Three XML standards were selected as identified as candidates for more in-depth investigation in a second study: HL7[21] standard for data exchange in the health domain; HR-XML[22] standard for human resources data OTA[23] standard for travel industry data This second study is still ongoing, but the indications are that in all three cases the kinds of data exchanged by businesses using these standards, as well as the level of usage of the standards, means that as of now they have little interest for NSIs, which was also the case for the other thirty-three standards covered by the first study. 3. Tools 3.1. General remarks Most of the standards mentioned in section 2, if applied to raw data collection from businesses, are typically embedded within IT applications where the respondent business is not necessarily aware of the underlying standards. Member States have developed and use a large number of IT tools for raw data collection and it would be impracticable to try and list them. Once again, we give some representative examples Electronic questionnaires and data entry systems There are two basic EDR technologies: Computerised Self-Administered Questionnaires (CSAQ) and Web forms[24]. CSAQ systems existed already before the World Wide Web. A CSAQ is a stand-alone software package that is installed on the data provider s workstation. It allows statistical data to be captured and packed in a format accepted by the data collector. Later CSAQ systems made more use of the Internet: data are sent over the Internet; program updates can be downloaded from the data collector s website; long code lists may be consulted on the collector s web server; and so on. 7

8 A successful example of a CSAQ is IDEP/CN8, an electronic questionnaire for Intrastat declaration; Intrastat is the statistical system relating to the trading of goods between EU member states. IDEP/CN8 was originally developed by Eurostat; it was later taken over by a group of Member States. The competent national administrations take care of distribution and user support. By 2001, IDEP/CN8 was thought to be used by over 50,000 enterprises. While traditional CSAQ systems like IDEP/CN8 cover only one statistical survey, multiquestionnaire CSAQ systems can be used for several surveys in parallel. New questionnaires can be added whenever needed, for example through download via the Internet. EDISENT, one of the first multiquestionnaire systems, was developed in the TELER research project[25]. A more recent development is the e-quest (later e-quest/web) system developed and used in Statistics Austria[26]. The Blaise system from Statistics Netherlands[27] might also be included here, although its uses are wider than raw data collection from businesses. Like e-quest, it has evolved to make use of web technologies Web forms and web-based services for data submission from businesses Web forms are electronic questionnaires that do not require software installation on the provider s computer. A web form is available on the data collector s web server and can be accessed and completed via a web browser. This kind of solution is now widely offered by statistical offices and other national authorities. Examples are the e-quest/web system in Austria (mentioned in the previous section) and the XCola system from Statistics Finland[28], which makes use of XML4DR. Some systems go further than the electronic questionnaire, providing a complete web-based data collection system. One example which may influence developments elesewhere in the EU is the German the estatistik.core[29], which has been developed to facilitate the data transmission from companies to the statistical offices of the Länder. The overall architecture is shown in the following schema[30]: The basic principle of estatistik.core is the following: The federal statistical institute (DESTATIS) offers the free CORE.connect module, which reads the survey definition, sends the data to DESTATIS, and receives an acknowledgement. The data are then redistributed to the statistical offices of the Länder. 8

9 Inside a company, the CORE.connect module can be used in two different ways: The ERP (Enterprise Resource Planning) system may include a Statistics Module for a given survey, which passes the statistical data to the CORE.connect module. About 20 different software companies (under them SAP and Oracle/Peoplesoft) are already offering such Statistics Modules, 8 surveys have been prepared for this way of electronic reporting. If the ERP system of a company does not have a Statistics Module for a given survey, the company may use instead the freely available CORE.reporter module. This module accepts CSV data prepared by the respondent and sends them via the CORE.connnect module to the statistical institute. In both cases, the respondent may look at the data before the sending, and will get an acknowledgement after the successful reception and validation of the data. 4. Overall conclusions The information and examples presented in sections 2 and 3 should be sufficient to demonstrate that NSIs have at their disposal a rich collection of standards and tools for raw data collection. NSIs have often indicated in meetings that they consider their raw data collection systems to be effective; certainly, they can reduce the costs of data collection from the NSI perspective, and they may also increase data quality, by avoiding manual data entry and by allowing data to be checked at the time of encoding or uploading. However, except for the cases where electronic data returns are automatically generated from standard business software packages, it is still generally true that businesses have to generate the statistical data for entry into the systems, which accounts for the majority of the response burden imposed by statistics. XBRL is a particularly interesting case because at first sight it appears to offer considerable promise for unifying the different kinds of reporting required of businesses and at the same time permitting an automated treatment of reporting data. However, while XBRL continues to offer prospects for lowering costs and response burden for business statistics, the results of the Pilot Project suggest that Member States have not yet made much progress in the exploitation of XBRL. It seems likely that these benefits would not be realised without strategic decisions and significant investments by Member States, aimed at more homogeneous reporting requirements within and between Member States, independent of the use of XBRL or any other technology; This conclusion can be generalised to other interesting technologies. Basically, for reducing response burden, it is never sufficient to introduce a technological solution on its own; it should always be combined with some rethinking of the nature of the information demanded from businesses, not only for statistics but also for other administrative and regulatory purposes. Consider the following cases: 9

10 IT standards and tools for reporting Not used or very primitive Advanced Reporting requirements and concepts Multiple reporting requirements with inconsistent concepts Case A: This is the base situation (which still applies in some countries) Case B: Some small benefits for businesses, but low impact on overall response burden. Reduced number of separate reporting requirements, use of consistent concepts Case C: No major improvement over case A, although response burden might even be lower than Case B. Case D: Real reduction in response burden. This line of argument may appear over-simplified, but it is necessary to offset the enthusiasm of the protagonists of many IT standards and tools. At the same time, it does make the point that it is certainly worth investing in new technologies for collecting data from businesses, so long as this investment runs in parallel with decisions on the reporting requirements and concepts - which involve quite different issues and actors but one can also say that technological development can trigger other developments if those are taken up by the relevant authorities and decision makers. 5. References [1] (requires CIRCA userid for access) [2] [3] (requires CIRCA userid for access) [4] XBRL: XBRL Europe: [5] Report on a simplified business environment for companies in the areas of company law, accounting and auditing (2007/2254(INI)). See: [6] See : [7] IDABC: Decision 2004/387/EC of the European Parliament and of the Council of 21 April 2004 on interoperable delivery of pan-european egovernment services to public administrations, businesses and citizens (IDABC). For more information, see the IDA web-site at [8] SDMX: Statistical Data and Metadata exchange. See 10

11 [9] The report of the UNSC session is linked from this page : [10] SDMX Content-Oriented Guidelines were released for public comment in February 2008: see [11] See [12] IDA programmes: [13] Statistical standardisation work for raw data collection was funder the CEN (European Commitee for Standardisation) ebes (e-business Board for European Standardization) EEG6 (Expert Group 6) Working Group 4. Due to changes in CEN working arrangements, EEG6 decided on to terminate its existence. The EEG6 documents are online at: [14] RDRMES: Raw Data Reporting Message. Information in this and the following paragraphs is taken from the document XML standardisation for data collection and exchange, Uwe Kunzler (then at Eurostat) prepared for the Accounting and Statistics Task Force in September See: [15] See: [16] XML4DR: XML for Data Reporting. See: [17] See: [18] Ma,D., Lamb,J. and Taylor,A. (2003) Developing a Software Suite for Intelligent Questionnaires. Interoperability and Standards, Proceedings of the Association for Survey Computing International Conference. Abstract online: [19] See: [20] See: ailed&sb=title (requires CIRCA userid for access) [21] HL7: Health Level Seven: see [22] HR-XML: Human Resources XML: see [23] OTA: OpenTravel Allianec: see [24] Wolfgang Knüppel and Uwe Kunzler (2001), Influence of the Internet on data collection and dissemination in the European Statistical System IAOS Satellite Meeting on Statistics for the Information Society, August 30 and 31, 2001, Tokyo, Japan. Available online: [25] Gerrit W. de Bolster and Kees J. Metz (1997), The TELER-EDISENT project in Netherlands Official Statistics Volume 12, autumn 1997, special issue on EDI: The State of the Dutch Art. There are a number of other interesting articles in this issue, which is available online at: [26] cord_force_meetings/cord_meeting_2005/presentations/equestwebppt/_en_1.0_&a=d [27] 11

12 [28] cord_force_meetings/cord_meeting_2005/presentations/xcola_cordppt/_en_1.0_&a=d [29] estatistik.core stands for electronic Statistics Common Online Rawdata Entry; detailed specifications (in German) can be found on [30] Source: DESTATIS 12