GSBPM implementation (Kyrgyz Republic example) Omurbek Ibraev SN - - PowerPoint PPT Presentation

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GSBPM implementation (Kyrgyz Republic example)

The National Statistical Committee of the Kyrgyz Republic (NSC KR)

Omurbek Ibraev

SN local project coordinator at NSC KR

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Institutional Cooperation between Statistics Norway (SN) and National Statistical Committee of the Kyrgyz Republic (NSC KR)

Organizational Development Component Project on quality assurance

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• 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.

Project on Quality Assurance

Overall project goals:

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• 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.

Quality assurance project phases

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• 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

The “traffic light” approach

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

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Implementation of GSBPM using the Norwegian experience

Activity

Activity runs until quality is satisfactory according to guidelines or until it is decided to go back to an earlier process

Output

Data/metadata/documents produced in the process. They arise, change and/or are approved during the processing.

Instructions, rules:

Data/metadata/documents which describe what, when, and how the process should be performed. They are not changed during the process.

Resources

Resources: people/roles and tools

Link back to earlier processes

• No. of sub-process

Input

Data/metadata/documents needed to start the process. They might be changed during the processing Green Yellow Red

• No. of Phase/Process

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A pilot statistical product “Dordoy Market Survey”

Activity

Contribution of Dordoy market in GDP Analyze users’ needs in specific statistical data:  Turnover;  Infrastructure of the market (café, containers, hair-dressing saloons, banks etc.);  Single survey;  Searching stakeholder (public authorities) that could be engaged in data collection Coverage

Instructions, rules Resources Human resources: economists statisticians Link back to earlier processes 1.1. Determine need for information Input  Statement of the Government  Task set by NSC top management  the World Bank publication “Skeins of Silk: Borderless Bazaars and Border Trade in Central Asia Colour Colour Colour

• 1. Specify needs

Output Determine: specific statistical data

• n economic entities

 need for conducting Dordoy market survey

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• 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.

Documentation of the existing production processes/workflows and process analyses

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• фото

Process analyses

A template for documentation

• f

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

• verall 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

• f 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 government users’ needs Weak interaction with

• ther key users

Existing tools to specify needs are not effective – needs are not properly consulted and confirmed NSC KR should review relevance of current statistical outputs with key users and specify emerging needs. Some statistics produced for many years and no

• ne is certain if they are

still relevant and demanded. Outcome: Very high burden on respondents and failure to meet existing and emerging needs of users adequately! No methodology department with competence for the whole NSC Poor interaction among subject matter units and with

• wners of

administrative sources to reuse services, systems and databases in design phase (stove-pipe approach) Lack of single metadata system integrated with data production system Integrated collection, processing and dissemination tools are built in isolation for each questionnaire (stove-pipe approach) Lack of single metadata system integrated with data production system Paper-based data collection system (district, region, MCC, NSC) should be replaced. Build a new system for data collection – NSC to collect data directly from respondents through a new e-forms system. Use more administrative data and reduce number

• f questionnaires

Lack of single metadata system integrated with data production system Data processing

• verlaps at different

levels of NSC KR (district, region, MCC) Lack of single metadata system integrated with data production system Quality of analytical materials should be enhanced. Use new tools for production of new statistics and making good analyses Lack of single metadata system integrated with data production system Lack of single metadata and statistical output systems ready for dissemination Lack of competence in disseminating statistics through new channels (social media) No dissemination policy with focus on users’ needs. Poor performance in terms of communicating with and promoting use of statistical outputs by users and advocating evidence based decision-making No QM System in place No QM Department in charge for evaluation of statistical business processes and setting up specific action plans

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Thank you