ISEE Integrated System for Editing and Estimation

Transcription

1 EFFICIENT STATISTICAL PRODUCTION SESSION F: CASE STUDIES PRICE STATISTICS AND A COMMON TOOL FOR EDITING ISEE Integrated System for Editing and Estimation Per Ola Haugen Statistics Norway

2 ISEE Integrated System for Editing and Estimation Per Ola Haugen 1 Abstract. The editing and estimation application, ISEE, is used by just under 200 different statistics and has become an important common solution in processing data in Statistics Norway. The application was developed in 2005 and over the years new functionality has been added. The ISEE-system is built on the principles of creating general functionality, metadata-controlled processes, self-service and reuse. Today the ISEE-system is used mostly for micro editing, aggregation of data and examination of data. The estimating module is seldom used. With this background, a project was started to modernize the ISEE-system to achieve more efficiency and better quality in processing data. The project includes building functionality in ISEE so that the best statistical methods are used to ensure efficiency and quality. All statistical methods will be placed in a common Methods library. Relevant methods to put into the library are estimation/imputation, price indices, macro editing methods and evaluation of editing. A modernized ISEE-system will also involve opportunities for more focus on the final product. By prioritizing units in the editing process which have great impact on the final product, one would do an iterative process, with good integration between the editing and the estimation modules. The project will also imply a technological refinement of the ISEE-system in order to ensure a robust and stable system that can interact effectively both internally and with other systems. Benefits of the project are less resources used in processing data and tailored IT- procedures could be phased out. - Integrated editing and estimation - Methods Library - Macro editing 1 Statistics Norway, Senior Advisor, Kongsvinger, Norway, per.ola.haugen@ssb.no

3 Key words: editing, estimation, common solution, metadata, statistical methods 1. Introduction ISEE is a generalized system for statistical data processing, and the main system for data-editing in Statistics Norway. The system was originally developed for service production price indices back in 2005, where the goal was to build a generalized and metadatadriven solution for a set of approximately 20 new production price indices. Since 2005 the system is developed further with new functionality, improved performance, support for large volumes of data, and now consists of 4 core applications: - Dynarev, for microdataediting and non-statistical edits and assignments. The most used application. - Pris for estimation of price indices and statistical and aggregated edits. - Struktur for estimation of population aggregates and statistical and aggregated edits. - Driller for drill-down, microdataediting and non-statistical edits and assignments. Supports large volumes of data. The applications are fully integrated, and can be user together or separately.

4 Major principles for ISEE: - Metadata -driven and self-service-solution. Most of the functionality is metadata -driven. End-users can derive new variables, link to other data sources, and configure edits and assignments in building -applications. - Reuse metadata from data collection-systems. Metadata defined in the data collection system are imported to ISEE, which results in less manual configuration and larger efficiency. - -Think Big start small. New functionality added when needed when new statistics are implemented in ISEE. All new functionality added as generalized functionality. ISEE supports all kinds of structured data in a generalized data model, and ISEE fits for data editing of almost all kinds of statistics: Sample-survey Register Person Business Today just under 200 statistics use ISEE for data processing and editing, and many old tailor-made editing systems are phased out. The scope of statistics which use ISEE is large, from production price indices with a small number of respondents and variables, to the biggest registers with hundreds of variables and millions of records processed monthly. In 2015 the EDAG-project (electronic dialog between authorities and employers) was deployed with use of ISEE as a major component. EDAG collects monthly information about jobs, remuneration and tax, and processes all data in ISEE with automated assignments and edits. Approximately more than 50% of the published statistics use ISEE for data processing and editing. Especially among sample surveys from businesses the share of ISEE-use is large with over 90%. Even more register based data use ISEE, and among these kinds of statistics there is a considerable potential for further implementation based on existing functionality in ISEE. For statistics based on interviews and data collection from persons ISEE is seldom used. Even though ISEE has been a huge success, and has contributed to significant efficiency and standardization there are still some challenges: - One initial goal with ISEE was to improve and make the editing process more efficient and standardized. This goal has not been fulfilled as much as wanted. Some statistics still have too much focus micro data editing, and have not used the opportunity to improve the editing process when moving to ISEE. - Technology platforms are partly outdated and not standardized. - ISEE is only partly used tailor-made SAS-systems in addition because of a lack of needed functionality, or the functionality exists, but it is not known. - Existing functionality for statistical- and aggregated edits is limited to users of the Pris- and Struktur-modules. - ISEE is used, but not in an optimal way.

5 These challenges show the need for modernization of ISEE, both technologically and methodologically. 1.1 Pre-project for modernization of ISEE A pre-project for modernization of ISEE took place last year. The pre-project was divided into two parts, with one part focusing on statistical methods and demands from users, and the other part focusing on the need for technological refinement. A user study, with interviews and a web-survey among users in the production departments, collected valuable information on benefits, drawbacks and suggestions for new functionality in ISEE. All production divisions that use ISEE have been involved in the process. Modernization of ISEE must also be viewed in conjunction with adaption to development of other internal systems interfaced with ISEE, like metadata- and data collection systems, and adaption to national and international guidelines and standards, e.g. GSIM. 1.2 Methods library A key in modernizing ISEE will be to establish a methods library. The methods library will be a collection of statistical methods for estimation, price indices, macro editing and evaluation of editing. The methods will be well documented, e.g. contain information on which statistics the methods are suitable for and for which statistics they are actually used. A goal is also to implement the methods as general metadata driven programs in the library. The statisticians then could pick finished methods from the library, and set up proper configurations for the methods. A key to making efficient use of the methods library will be to save configurations for reuse on later periods. More use of graphics is another vital point in modernization of ISEE. All results from the functions in the methods library could be represented as graphics. We think more use of graphics will be a valuable addition to ISEE, and will contribute to more efficiency. By investigating results from statistical methods on macro level by viewing graphics you can find irregularities in microdata which not had been discovered by more traditional investigation.

6 1.3 Technological refinement The 4 core ISEE-applications are developed during different periods and on different technology-platforms. The underlying information model is however common for all 4 applications. Some parts of the solutions are technologically old-fashioned and outdated. The tools these applications are built on are still supported by the vendors, but not further developed for more than 10 years. This causes challenges related to skills, integration and problems to meet the demands for a modern and future-oriented IT-solution. The newest part of ISEE is however built in a more modern and future-oriented way. 2. Plan for Modernization of ISEE Initially the plan was to run the Modernization of ISEE project separately. Modernization of ISEE is now however included in a big modernization programme in Statistics Norway. It is important to view the modernization of ISEE in conjunction with modernization of the whole production process. Several factors are foreseen that taken together reinforce the need to streamline operations and improve productivity: Anticipation of reduced budget in future Generation shift in SSB, 277 staff in 2015 are over 58 years of which 195 of these work in statistics departments, data collection and dissemination. Necessity to increase leverage of new data sources Expectation of faster changes in user requirements Rationalization and improvement of the business is also in line with the steering signals that SSB is receiving from the Norwegian government: The main objectives in the budget assignment for SSB in 2016 point to rationalization, restructuring and improvement, as well as new data sources and improved data management The digitalization circular of 2015 points to increased value creation, innovation and contribution to better and more efficient public services. In addition there are requirements for information security, architectural principles, reuse of data, common components and use of cloud services. White Paper 27 ( ) - Digital Agenda for Norway - ICT for an easier life and increased productivity National strategy for the use of cloud services. The objectives of the modernization programme are illustrated in the figure below:

7 Figure: Modernisation objectives The preliminary efficiency gains foreseen are: The modernization programme will contribute to that a significant proportion of those who will retire need not be replaced and that new recruitments will be based on needs for future skills An increased level of automation will reduce the amount of repetitive tasks and routine work An efficient production system will make it easier to exploit new data sources, increase research work and accommodate new user requirements faster. A preliminary investigation of target pictures, requirements related to functionality and data flow, including a rationale for the modernization was made, limited to the four main processes Plan, Collect, Process and Analyze in the business process model. This resulted in the identification of the following action areas: Improved information management Increased reuse Increased automation and self-service Modern IT platform for development, drift and administration of infrastructure and solutions Improved control of the production of statistics A prerequisite to deliver on future expectations is to restructure and organize the management of SSB's main asset "information". The quality must be improved, precise states should be defined, the data flow must be made more efficient and data and information must be standardized and consolidated. This is a prerequisite for increased reuse of data, services, methods and solutions. When a sufficient choice of "reusable services" is available, these can be utilized to increase automation and digitalization with the associated efficiency gains and benefits realization. This service-oriented solution concept is radically different from the solution portfolio that SSB has today. This will require a modern IT platform where the solutions can be developed, operated and managed in an efficient manner.

8 Improved control has two different aspects: control of statistical production and control of common and individual circumstances in processes, activities, information and solutions. The first will be handled through the modernization as requirements associated with parts of the target picture. The second revolves around culture and behavior, and relates to how common and individual circumstances in the business are addressed, prioritized and managed. Our target pictures and ambitions of substantially more standardization, consolidation, automation, self-service and reuse will require change and an adjusted control model that dissolves our distinctly divisional and departmental ownership and control. This must be addressed early in the programme, necessary changes must be made, and form the basis for management of the modernization program. Modernization of ISEE, now seen as an important part of the modernization of the Process part of the business process model, will contribute to all 5 action areas mentioned above. For example the methods library will contribute to self-service and reuse of the statistical methods. The technological refinement needed will be important input to the new modern IT-platform that will support all common solutions. 3. Conclusion Establishment and development of ISEE has been a key factor for standardization and efficiency in Statistics Norway over the last 10 years. However, the full potentials for efficiency and standardization have not been fulfilled. To achieve further standardization and efficiency there is a need for a modernized ISEE by implementing more functionality for a macro-oriented view on the editing process, and a technological refinement. The implementation of ISEE modernizing will take place as a part of the Modernization programme in Statistics Norway. 4. References Zhang, L.-C. (2009). Ideas on editing of statistical registers, paper presented on Work Session on Statistical Data Editing in Neuchatel, Switzerland, 5-7 October 2009.