Standards based modernization: experience of Kazakhstan

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Committee on statistics of the Ministry of National Economy of the Republic of Kazakhstan Standards based modernization: experience of Kazakhstan Jarkinbayev Zhasser Vice

1 Committee on statistics of the Ministry of National Economy of the Republic of Kazakhstan Standards based modernization: experience of Kazakhstan Jarkinbayev Zhasser Vice Chairman Bangkok, 25 August 2016 Modernization of the Quality Management System Modernization of Information Systems Work on implementation of GSBPM,GSIM Main conclusions 1 1

production and processes Modernization of public governance improvement of quality of public services 2 Quality Management

2 2007 start of works to implement the Quality Management System (QMS), that corresponds with the requirements of the international standard ISO 9001 Main purpose of implementation creation of conditions for constant quality improvements of production and processes Modernization of public governance improvement of quality of public services 2 Quality Management System In 2011 Committee on Statistics and it s regional offices received international Certificate ISO 9001:2008 Committee Regional offices 3 2

3 Declared and expected user requirements Planning of statistical activities Collection of primary statistical data Processing of primary statistical data Dissemination of statistical Users Quality policy and goals were developed and approved; 2. QMS documentation was developed and annually updated; 3. Main processes of statistical activities and their interactions were identified; 4. Users and staff are interviewed annually about their satisfaction; 5. Paperwork management was improved; 6. Responsibilities and authorities of departments and staff were clearly defined. 4 Quality Management System Registry maintenance Formation of statistical Classification maintenance Development of statistical toolkit Price statistics Production and environmental statistics Service statistics Establishment of sample frame Social and demographic statistics Coordination of activities to collect administrative data Statistics of labor and standard of living Structural statistics and leading indicators Establishment of SNA indicators Staff management Information infrastructure management 5 3

Problems of business processes Processes Data collection Disadvantages Significant financial, labor, transport and time costs of respondents to deliver paper reports Processing Low efficiency, low

4 Problems of business processes Processes Data collection Disadvantages Significant financial, labor, transport and time costs of respondents to deliver paper reports Processing Low efficiency, low productivity and risk of dubbing Regions/cities 16 Regions Data formation Large waste of time from data collection till issue of publications Processing centers Dissemination Lack of visualization instruments (cartograms, diagrams, time series), for users of statistical 6 Information Systems Architecture of the CS in 2010 Information Systems of other state bodies District Offices Regional Departments Central Office Employee Reference data CLASS Paper Based Forms (around 150) REGISTERS Population Census DB Agricultural Census DB... Electronic Publications Base Publications Electronic forms (around 50) Processing module Processing module Electronic Forms warehouse Processing module WEB 7 4

Goal and tasks of the Integrated Information System «е-statistics» for 2011-2014 Goal Enabling respondents to deliver statistical

development of registers Modernization of processing and storage of primary statistical data Establishment of the Single Statistical

and integration with systems of government bodies 8 Architecture of IIS «е-statistics» e-government infrastructure IS of other state

Single System of Data Output Publications Respondents Reporting forms (around 200) REGISTERS Collection of primary data Data

5 Goal and tasks of the Integrated Information System «е-statistics» for Goal Enabling respondents to deliver statistical reports on-line Automation of processes of collection, processing and dissemination of statistical t a s k s Establishment and development of registers Modernization of processing and storage of primary statistical data Establishment of the Single Statistical database of the Agency Dissemination of in electronic format using modern IT-technologies Establishment of mechanisms of interaction and integration with systems of government bodies 8 Architecture of IIS «е-statistics» e-government infrastructure IS of other state bodies e-service for Respondents Digital Signature Integration component Single Environment of IIS «е-statistics» Uniform Transportation Network of State Bodies Data Warehouse Single System of Data Output Publications Respondents Reporting forms (around 200) REGISTERS Collection of primary data Data collection module On-line Data Collection Reference data METADATA Classifiers Primary Statistical Data Warehouse Administrative Information DB Population Census DB Agricultural Census DB Primary and Administrative Data Processing IS Aggregated indicators DB Internal portal External portal Analytical Information System Interactive Services WEB Diagrams 9 5

6 QMS compliance with requirements of ISO 9001 does not provide compliance with all specific requirements for statistical products and processes Lack of descriptions of some important statistical processes and procedures QMS based on ISO was not fully integrated with general management system When creating architecture of IIS e-statistics, no international practices of GSBPM and GSIM models were considered. In general, not all business processes in the IIS e-statistics were described in accordance with these models 10 Start of work on GSBPM, GSIM under the KAZSTAT project in 2014 Working Group for further development of the application of the GSBPM and the GSIM under QMS improvement was established Visits of experts from Slovakia, Iceland, Germany, study visits to Sweden, Germany, Italy, Korea Training of the staff of CS (GSBPM,GSIM, Microsoft Visio) First version of CS organization specific adaption of the GSBPM in the local language. Mapped four different processes for three different statistical products 11 6

7 Управление качеством/управление метаданными Определение потребностей Разработка Построен ие Сбор Обработк а Анализ Распространение Оценка Определить потребность в информации Обсуждение и подтверждение Установление цели формирования материалов Определить концепции Проверка наличия Подготовка экономического обоснования Проектирова ние выходного стат продукта Проектиров ание описания показателей Дизайн методологи и сбора Проектиров ание ген совокупност и и выборки Проектиров ание бработки и анализа Проектирова ние производстве нных систем и процеса Построени е механизма сбора Компонент ы процесса Компановк а производст венных процессов Тестирован ие систем Тестирован ие бизнес - процесса Ввод в строй производст в. системы Определен ие выборки Подготовк а сбора Организац ия сбора Финализац ия сбора Интеграци я Кодирован ие Редактиров ание Импутация Разработка новых показателе й Расчет весов Расчет сводных Финализац ия файлов Проект готовых Проверка Критически й взгляд и объяснение Контроль раскрытия Финализац ия выпуска Обновление систем выпуска Производство продукции для распространения Управление распространением Продвижение продукции Поддержка пользователей Сбор для оценки Проведен ие оценки План действий по улучшению Official approval of the first version of GSBPM by CS management Possible creation of the separate Quality management department Educating and training other employees, including employees in the regional offices Better vision for the quality management system is needed 13 7

8 From the view of quality management there is no necessity to implement GSIM at the present state. It should be noted, that the design of new ITsystems with the use of GSIM has as a precondition that the processes of statistical production are in line with international product and process quality assessments. The theoretical overview of the use of GSIM model in the design of new IT-Systems in the statistical production process and the demonstration of practical experience of GSIM implementation have led to the conclusion, that it could be considered by the CS IT department to join the Common Statistical Production Architecture (CSPA) project. A deeper contact to members of the CSPA like Sweden is advisable. 14 Under KAZSTAT project CS staff received basic knowledge of the SDMX standard Experience of NSO s of Germany, Czech Republic, Korea was studied Plan on SDMX implementation in was approved Pilot exchange of data using SDMX with the Eurasian Economic Commission was made 15 8

9 Standard-based modernization should be a priority Implementation of GSBPM requires resources, change of philosophy and organizational structure, commitment of all employees, etc. Development of new IT and QM systems should take into account GSBPM, GSIM, CSPA For countries with insufficient resources it is very difficult to implement GSIM, CSPA 16 Thank you for your attention! 17 9

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