The%20Adoption%20of%20METIS%20GSBPM%20in%20Statistics%20Denmark

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The Adoption of METIS GSBPMin Statistics Denmark
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Agenda

• Background and context
• Working with business processes
• An example of documentation
• Results of process analysis
• Metadata coverage
• Lessons learned

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Agenda

• Background and context
• Working with business processes
• An example of documentation
• Results of process analysis
• Metadata coverage
• Lessons learned

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Working group on standardisation

• Multi-annual corporate strategy as basis
  (Strategy 2015)
• Working group, that refers to Board of Directors
• METIS GSBPM adopted as common frame
• Dual focus
• Process analysis and documentation
• Coverage of metadata systems

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Quality management / Metadata Management
2 Design
1 Specify Needs
3 Build
4 Collect
5 Process
6 Analyse
7 Disseminate
8 Archive
9 Evaluate
6.1 Prepare draft outputs
7.1 Update output systems
8.1 Define archive rules
3.1 Build data collection instrument
9.1 Gather evaluation inputs
5.1 Integrate data
1.1 Determine need for information
2.1 Design outputs
4.1 Select sample
6.2 Validate outputs
3.2 Build or enhance process comp.
7.2 Produce dissemination products
8.2 Manage archive repository
5.2 Classify code
1.2 Consult confirm need
4.2 Set up collection
9.2 Conduct evaluation
2.2 Design variable descriptions
5.3 Validate edit
2.3 Design data collection methodology
4.3 Run collection
8.3 Preserve data associated metadata
7.3 Manage release of dissem. prod.
9.3 Agree action plan
1.3 Establish output objectives
3.3 Configure workflows
6.3 Scrutinize explain
5.4 Impute
6.4 Apply disclosure control
7.4 Promote dissemination products
2.4 Design Frame sample methodology
1.4 Identify concepts variables
3.4 Test production systems
8.4 Dispose of data assoc. metadata
4.4 Finalize collection
7.5 Manage user support
5.5 Derive new variables stat. units
2.5 Design stat. processing methodology
3.5 Test statistical business process
1.5 Check data availability
6.5 Finalize outputs
2.6 Design prod. systems / workflows
1.6 Prepare business case
3.6 Finalize production system
5.6 Calculate weights
5.7 Calculate aggregates
5.8 Finalize data files
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Reference document SDs METIS

• METIS confirmed standard for official
  statistical production
• Adopted by some of our peers
• Translation of document
• Approach for SD version
• Testing the extent to which the model apply to SD
• An SD METIS would be a milestone for business
  process- and architectural maturity
• Necessary to move ahead according to our
  corporate objective of increasing standardisation
• Initial focus on phases 4-7

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Agenda

• Background and context
• Working with business processes
• An example of documentation
• Results of process analysis
• Metadata coverage
• Lessons learned

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Model/template for statistical business processes

• METIS level (which phases do we open?)
• Control-flow level (phases, input, output, time)
• Functional level (who does what, and in what
  order?)
• AS-IS and/or TO-BE
• BPMN Standardized notation
• Collect ideas and convert them into action
  (standardisation, efficiency and quality)
• Form
• Workshop
• Facilitated by working group
• Ownership of results to the statistical team
• Needs a mandate!

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Selection of pilot cases

• Social Statistics
• Population register
• Student register (register updates)
• Business Statistics
• General account statistics (SBS)
• Employment in construction industries
• Retail Trade Index
• Industrial commodity statistic
• Farm Structure Survey
• Car register and associated statistics
• Use of ICT in enterprises
• Economic Statistics
• Consumer price index
• Foreign trade in services
• Sales and Marketing
• Interview task Yearly survey on safety
• Key figures in housing (standardized product from
  SDs Customer Services Centre)
• User Services
• Data collection-processes/-systems (XIS, CEMOS)

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Selection of cases in Business Statistics
Dimension Values Cases
Frequency - Short term vs. - Structural statistics - ECS SBS
Standardised system (if any) - Statistics in standardised systems vs. - Statistics in stand-alone systems - ECS SBS
Complexity - Simple vs. Complex - RTI SBS
Type of Statistical Unit - Statistics based on SBR vs. - Statistics with other units - SBS - C-Reg
Method for error detection Micro-based error detection vs. Macro-based error detection - SBS - ECS
Coverage - Sample vs. - Cut-off vs. Population - ECS - ICS FSS
Confidentiality scheme - Positive confidentiality vs. - Negative confidentiality - SBS ICS
Cost Statistics with high cost vs. Statistics with low cost SBS RTI
Stability - Few changes by each iteration vs. - Many changes by each iteration ECS UIE
Maturity - Well established statistic in SD - New statistic in SD - SBS - (RII)
Type - Primary statistic vs. - Derived statistic - ICS - C-Reg

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Agenda

• Background and context
• Working with business processes
• An example of documentation
• Results of process analysis
• Metadata coverage
• Lessons learned

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Example METIS level
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Example Control flow level

• Trigger
• Phases
• Input
• Regulations
• Data
• etc.
• Output
• Intermediate
• Final
• Time

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Example Functional level

• Who does what
• Start condition
• End condition
• Note that

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Agenda

• Background and context
• Working with business processes
• An example of documentation
• Results of process analysis
• Metadata coverage
• Lessons learned

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Results of process analysis (an overview)

• Focus on processes is useful and has immediate
  effect in some cases
• Improvements for statistical teams
• Quality (documentation, new quality measures,
  etc.)
• Standardisation (Use of standardised systems)
• Efficiency (Eliminate manual processes)
• Improvements in communication
• Many project managers regarding digitalisation
• Coordinator function
• Improvements in efficiency for data collection
• Focus on areas of responsibility
• Huge difference in degree of standardisation
• Dissemination
• Data collection
• Data processing

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Agenda

• Background and context
• Working with business processes
• An example of documentation
• Results of process analysis
• Metadata coverage
• Lessons learned

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Metadata coverage
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Metadata coverage

• Dissemination phase is very well covered
• Although dissemination phase is covered by four
  different applications the overlap is very
  limited
• The vision for the future is to create a single
  metadata system
• The data model should be based on three data
  stages (raw data, micro data, macro data)

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Metadata coverage
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Agenda

• Background and context
• Working with business processes
• An example of documentation
• Results of process analysis
• Metadata coverage
• Lessons learned

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Lessons learned

• Planning a strategy for further development is
  better using GSBPM
• Identify areas of interest for improvement
  initiatives.
• Major challenges regarding steps where data is
  processed
• Further standardization of methods is necessary
• A clearer view of the different need for metadata
  and documentation
• A better overview of the strong and the weak
  areas of our metadata applications