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Statistics New Zealand's Move to Process-oriented Statistics Production

Statistics New Zealand's Move to Process-oriented Statistics Production. Julia Gretton and Tracey Savage IAOS Conference Shanghai, China, October 2008. Objectives. Increase confidence in outputs Improve communication Support business and IT planning Improve staff orientation and training

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Statistics New Zealand's Move to Process-oriented Statistics Production

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  1. Statistics New Zealand's Move to Process-oriented Statistics Production Julia Gretton and Tracey Savage IAOS Conference Shanghai, China, October 2008

  2. Objectives • Increase confidence in outputs • Improve communication • Support business and IT planning • Improve staff orientation and training • Improve quality and risk management Business process modelling

  3. Generic model • Recognise common processes • Understand similarities and differences • See where our role fits • Identify opportunities to standardise

  4. Need Design/ Develop Build Collect Process Analyse Disseminate Prioritise efforts • Actual state

  5. Need Design/ Develop Build Collect Process Analyse Disseminate Need Design/ Develop Build Collect Process Analyse Disseminate Prioritise efforts • Actual state • Desired state

  6. Expected benefits of transformation • Decrease time processing data • Increase time building capabilities • Improve responsiveness to users • Improve access • Increase use of administrative data • Allow complex data integration • Facilitate business and IT planning

  7. 10. Dashboard / Workflow 4. Analytical Environment 5. Information Portal 6.Transformations 3. Metadata Store 3. Metadata Environment Statistical Statistical Process Process Knowledge Base Knowledge Base 9. Reference Data Stores Aggregate ‘UR’Data Summary Clean Raw 7. RespondentManagement 8. Customer Management Data Data Data Data Disseminate Collect Process Analyse 10 Conceptual components CURFS CURFS Imaging Imaging Multi Multi - - Data Data INFOS INFOS Admin. Admin. Output Channels Output Channels Official Statistics System & Official Statistics System & Data Archive Data Archive Modal Collection Modal Collection 1. Input Data Environment 1. Input Data Store 2. Output Data Envt. 2. Output Data Store Web Web CAI CAI Summary ‘ UR’ Clean Raw E E - - Data Data Data RADL Data Data RADL Form Form

  8. Personal experiences • Develop new processing system • Obligation to meet survey release dates • Constrained resources and time • Compromises made • Resulting system meets all our needs and aligns with many of the principles

  9. Lessons learnt to date • Statistical outputs compete with strategic outputs • Complex governance, no one single programme owner Focus is on separate components, rather than end-to-end solution Driven by software solutions Assumed ease of integrating these

  10. People Process Methods Software Future plans • Shift focus to people, processes, methods • Promote wider use of existing tools • Resource development projects separately • Continue to improve governance and ownership of key deliverables

  11. Conclusion • Seeing benefits from becoming more process-oriented • Challenges around implementation • The principles are sound and are still strongly supported • Change is gradual and at many levels • Culture, behaviour, processes, standards and technology

  12. Thank you For further information please contact: tracey.savage@stats.govt.nz or julia.gretton@stats.govt.nz

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