Gsbpm

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Gsbpm

  1. 1. United Nations Economic Commission for Europe Statistical Division United Nations Economic Commission for Europe Statistical Division Towards a Generic Statistical Business Process Model Steven Vale, UNECE
  2. 2. Steven Vale - UNECE Statistical Division Slide 2 Contents  Background  Modelling statistical business processes  Applicability  Structure and key features  Relevance to SDMX  Next steps
  3. 3. Steven Vale - UNECE Statistical Division Slide 3 Background  Defining and mapping business processes in statistical organisations started at least 10 years ago • “Statistical value chain” • “Survey life-cycle” • “Statistical process cycle” • “Business process model”
  4. 4. Steven Vale - UNECE Statistical Division Slide 4 Background  Defining and mapping business processes in statistical organisations started at least 10 years ago • “Statistical value chain” X • “Survey life-cycle” X • “Statistical process cycle” X • “Business process model” X Generic Statistical Business Process Model
  5. 5. Steven Vale - UNECE Statistical Division Slide 5 Modelling Statistical Business Processes  Reached a stage of maturity where a generic international standard is the logical next step  Many drivers for a generic model: • “End-to-end” metadata systems development • Harmonization of terminology • Software sharing • Process-based organization structures • Process quality management requirements • ...
  6. 6. Steven Vale - UNECE Statistical Division Slide 6 Why do we need a model?  To define, describe and map statistical processes in a coherent way  To standardize process terminology  To compare / benchmark processes within and between organisations  To identify synergies between processes  To inform decisions on systems architectures and organisation of resources
  7. 7. Steven Vale - UNECE Statistical Division Slide 7 History of the Current Model  Based on the business process model developed by Statistics New Zealand  Added phases for: • Archive (inspired by Statistics Canada) • Evaluate (Australia and others)  Three rounds of comments  Terminology and descriptions made more generic  Wider applicability?
  8. 8. Steven Vale - UNECE Statistical Division Slide 8 Applicability (1)  All activities undertaken by producers of official statistics which result in data outputs  National and international statistical organisations  Independent of data source, can be used for: • Surveys / censuses • Administrative sources / register-based statistics • Mixed sources
  9. 9. Steven Vale - UNECE Statistical Division Slide 9 Applicability (2)  Producing statistics from raw data (micro or macro-data)  Revision of existing data / re-calculation of time-series  Development and maintenance of statistical registers
  10. 10. Steven Vale - UNECE Statistical Division Slide 10 Structure of the Model (1) Process Phases Sub- processes (Descriptions)
  11. 11. Steven Vale - UNECE Statistical Division Slide 11 Structure of the Model (2)  National implementations may need additional levels  Over-arching processes • Quality management • Metadata management • Statistical framework management • Statistical programme management • ........ (8 more – see paper)
  12. 12. Steven Vale - UNECE Statistical Division Slide 12 Key features (1)  Not a linear model  Sub-processes do not have to be followed in a strict order  It is a matrix, through which there are many possible paths, including iterative loops within and between phases  Some iterations of a regular process may skip certain sub-processes
  13. 13. Steven Vale - UNECE Statistical Division Slide 14 Key Features (2)  In theory the model is circular: • Evaluation can lead to modified needs and design  In practice it is more like a multiple helix: • There may be several iterations of a process underway at any point in time
  14. 14. Steven Vale - UNECE Statistical Division Slide 15 Mapping to Other Models
  15. 15. Steven Vale - UNECE Statistical Division Slide 16 Relevance to SDMX  Process modelling already mentioned in: • SDMX User Guide • V2 Technical Standards • Euro SDMX Metadata Structure  Common terminology  If inputs and outputs use SDMX formats, why not the intermediate processes?
  16. 16. Steven Vale - UNECE Statistical Division Slide 17 Standardized process descriptions Harmonised processes Rationalization of software Use of open source and shared components SDMX between components Convergence of business architectures
  17. 17. Steven Vale - UNECE Statistical Division Slide 18 Next steps  Several organisations are implementing this model or similar ones  Gather implementation experiences and other comments as input for Part C of the “Common Metadata Framework”  Present to the Bureau of the Conference of European Statisticians  Role in SDMX?
  18. 18. Steven Vale - UNECE Statistical Division Slide 19 Questions and Comments? steven.vale@unece.org For more information see the METIS wiki: www1.unece.org/stat/platform/display/metis

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