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Increasing Relevance of Official Business Statistics Using Proven Business Approaches

Increasing Relevance of Official Business Statistics Using Proven Business Approaches. Mojca Bavdaž & Jaka Lindič. Situation. more information less money more competition burden vs . value. Problem. Product Positioning. Business approaches in public sector. TQM 6 σ L ean

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Increasing Relevance of Official Business Statistics Using Proven Business Approaches

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  1. Increasing Relevance of Official Business Statistics Using Proven Business Approaches Mojca Bavdaž & Jaka Lindič

  2. Situation • more information • less money • more competition • burdenvs. value

  3. Problem • Product • Positioning

  4. Businessapproaches in publicsector • TQM • 6σ • Lean • Blue-ocean strategy • Customer development • Lean start-up HOW? WHAT & WHY?

  5. Generic Statistical Business Process Model (GSBPM)

  6. GSBPM • Waterfall (linear) model • non-linearpaths • iterations •  Inadequate for product development

  7. 1. Customer Discovery • GSBPM: phase Specify needs •  No search or definition of the target group

  8. What problems businesses solvewith offstats? •  Problem unknown • + • How offstats couldsolve the problems? •  Solution unknown

  9. Needs specification in GSBPM • Focus on NSIs’ perspective • “what is needed of statistics” • “consideration of practice amongst … statistical organizations” • Dissemination separately treated

  10. 2. Min Viable Product Development • GSBPM: statistical products released when finalized • Delayed market feedback • Min features allowing product deployment •  More features ONLY IF product accepted

  11. 3.Experimentation & Validated Learning • Experiments  Findings  Validated learning • GSBPM: • experimentation NO • evaluation YES • content/purpose? product characteristics? • “a report”

  12. 4. Fast Iterative Product Releases • GSBPM: not supporting so many iterations (tens, even hundreds)

  13. Recommendations • Layer on GSBPM • Add missing sub-processes • Shift in focus to obtain a better problem-solution fit: • job-to-be-done • business-related hypotheses

  14. Concluding thoughts • Layer on GSBPM: • usual statistical production • (re)use of data • less resistance, low cost, fast delivery • Change in way of thinking and working

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