The National Statistical Committee of the Kyrgyz Republic (NSC KR) GSBPM implementation (Kyrgyz Republic example) Omurbek Ibraev SN local project coordinator at NSC KR 1
Institutional Cooperation between Statistics Norway (SN) and National Statistical Committee of the Kyrgyz Republic (NSC KR) Organizational Development Component Project on quality assurance 2
Project on Quality Assurance Overall project goals: - Introduction to Quality Assurance and staff capacity building in Quality Assurance - Use of the Generic Statistical Business Process Model (GSBPM) in the statistical practice of NSC KR; - Focus on mapping the existing production processes and moving towards implementing changes; - Ensure continuous quality in the statistics production and pursue a quality conscious culture in the institution; - QA project as one of the key projects providing the basis for transformation of the entire statistical system of NSC KR. 3
Quality assurance project phases - Mapping the existing production processes in selected subject matter areas using the “traffic light” approach - Detailed documentation of existing production processes/workflows and process analyses in key subject matter areas using a template suggested by SN; - Documentation of the entire production process of NSC KR (still ongoing) – AS-IS model. - The next step: documentation of the entire production process – TO-BE model. 4
The “traffic light” approach Getting familiar with GSBPM and its phases - and relevant sub-processes; A first attempt to have an overall mapping of - existing production processes of few pilot statistical products; Focus on guidelines and instructions and - checking if NSC KR follows them 5
Definition of colours for level of standardization • Green: Guidelines and standard tools exist and are used • Yellow: Guidelines and standard tools are under development or developed but not widely used • Red: Guidelines and standard tools neither exist nor are they under development
Implementation of GSBPM using the Norwegian experience No. of Phase/Process Instructions, rules: Data/metadata/documents which describe what, when, and how the No. of sub-process process should be performed. They are not changed during the process. Yellow Green Activity Output Red Activity runs until quality is satisfactory according to Data/metadata/documents produced in guidelines or until it is decided to go back to an earlier the process. They arise, change and/or process are approved during the processing. Input Data/metadata/documents needed to start the process. They might be changed during the processing Resources Link back to earlier Resources: people/roles and tools processes 7
A pilot statistical product “ Dordoy Market Survey” 1. Specify needs 1.1. Determine need Instructions, rules for information Colour Colour Colour Activity Output Contribution of Dordoy market in GDP Determine: Input Analyze users’ needs in specific statistical data: specific statistical data Statement of the Turnover; on economic entities Government Infrastructure of the market (café, containers, hair-dressing need for conducting Task set by NSC top saloons, banks etc.); Dordoy market survey Single survey; management the World Bank publication Searching stakeholder (public authorities) that could be engaged “Skeins of Silk: Borderless in data collection Coverage Bazaars and Border Trade in Central Asia Resources Human resources: economists statisticians Link back to earlier processes 8
Documentation of the existing production processes/workflows and process analyses • Understanding the process of data production in each statistical area. • Describing each existing statistical sub-process in line with GSBPM phases and having a detailed documentation of it. • Finding a technique to describe/document sub- processes (a template for description/documentation) • Finding ways to have a more efficient/streamlined statistical process and come up with concrete proposals. 9
Process analyses • фото 10
A template for documentation of f processes 1. Overall information about the subject matter area - statistical product name being documented, data collection mode, number and type of respondents, NSC KR units involved in data production etc.). 2. List of all data production sub-processes (as they are) in a sequential way broken down by GSBPM phases; - sub-processes numbered and listed in a flow-chart 3. A detailed description/documentation of each sub-process in the following frame: - Requirements: (Describe the current sub-processes in detail) - Problems and difficulties of each sub-process - Recommended actions: (how to solve the problems/difficulties) :
Outcomes of f process analyses and documentation of f curr rrent production processes 1. Production processes for nearly 20 different statistics had been analyzed and properly documented for the first time (30-40 pages for each statistics) 2. All levels of NSC KR system (local statistical offices, Main Computing Center and central office of NSC KR) involved in process analyses and documentation 3. Staff members coming from different levels of NSC KR system understand overall processes taking place in different levels of data production much better now 4. Staff members identified existing problems/difficulties in sub-processes from different angles and came up with solutions together 5. Communication and understanding between staff members coming from different levels of NSC KR system improved 6. Everyone is better aware of the end-product at each level 7. Documentation of production processes available for the entire team of NSC KR system, and in particular for new-comers 8. Staff members of NSC KR system have better understanding of GSBPM and became more quality conscious 9. And finally, it had been a great brain-storming exercise!
Documentation of the entir ire production process of NSC KR (s (still ll ongoing) – AS AS-IS model • Incorporate documentation of production processes for 20 different statistics in one document • Better to have one documentation of the entire production processes rather than 20+ various documentaion; • A basis for review, standardization and streamlining of production processes and defining way forward • The aim is to get to the next step: description of the entire production process – TO-BE model
Documentation of f the entire production process of f NSC KR KR 1. General information about GSBPM and why NSC KR should follow it 2. Overall information on each phase of GSBPM and its sub-processes 3. Sub-process description (as specified by UNECE) 4. Description of each GSBPM sub-process implementation in NSC KR system, if relevant 5. Description of NSC’s possible inconsistencies with and deviations from each GSBPM sub-process.
Key issues and problems identified in the course of GSBPM implementation Specify needs Design Build Collect Process Analyses Disseminate Evaluate NSC KR focused on No methodology Integrated collection, Paper-based data Data processing Quality of analytical Lack of single No QM System in government users’ department with processing and collection system overlaps at different materials should be metadata and place needs competence for the dissemination tools (district, region, MCC, levels of NSC KR enhanced. statistical output whole NSC are built in isolation NSC) should be (district, region, systems ready for No QM Department Weak interaction with for each replaced. MCC) Use new tools for dissemination in charge for other key users Poor interaction questionnaire production of new evaluation of among subject (stove-pipe Build a new system Lack of single statistics and making Lack of competence statistical business Existing tools to specify matter units and with approach) for data collection – metadata system good analyses in disseminating processes and setting needs are not effective – owners of NSC to collect data integrated with data statistics through up specific action needs are not properly administrative Lack of single directly from production system Lack of single new channels (social plans consulted and confirmed sources to reuse metadata system respondents through metadata system media) services, systems and integrated with data a new e-forms integrated with data NSC KR should review databases in design production system system. production system No dissemination relevance of current phase (stove-pipe policy with focus on statistical outputs with approach) Use more users’ needs. key users and specify administrative data emerging needs. Lack of single and reduce number Poor performance in metadata system of questionnaires terms of Some statistics produced integrated with data communicating with for many years and no production system Lack of single and promoting use of one is certain if they are metadata system statistical outputs by still relevant and integrated with data users and advocating demanded. production system evidence based decision-making Outcome: Very high burden on respondents and failure to meet existing and emerging needs of users adequately!
Thank you 17
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