Business model Transformation Strategy (BmTS)

1. Statistics NZ’s Business model Transformation Strategy (BmTS) John Pearson and Tracey Savage

2. Overview • Introduction to the BmTS • 3 key themes: • People, process, methods…then software • Advances in Stats NZ methodology • Evolutionary change - business, cultural & programme • Questions

3. BmTS Objectives • Better service • Operational excellence • Attractive workplace

4. BmTS Deliverables • Standard processes • 80/20 • Disciplined approach • Data and metadata • Enterprise-wide technical architecture

5. BmTS Approach People Process Methods Software

6. BmTS Approach People People Process Methods Software Process Methods Software Time

7. Build Collect Process Analyse Disseminate Need Design Business Process Model (BPM)

8. Identify sample Establish population Generate sample Validate And Q.A. Maintain sample Manage providers Setup collection Run Collection Load data Business Process Model Build Collect Process Analyse Disseminate Need Design

9. Build Build Collect Collect Process Process Analyse Analyse Disseminate Disseminate Need Need Design Design Identify sample Identify sample Establish population Establish population Generate sample Generate sample Validate And Q.A. Validate And Q.A. Maintain sample Maintain sample Manage providers Manage providers Setup collection Setup collection Run Collection Run Collection Load data Load data Business Process Model

10. Identify sample Establish population Generate sample Validate And Q.A. Maintain sample Manage providers Setup collection Run Collection Load data Business Process Model Build Collect Process Analyse Disseminate Need Design

11. CORPORATE STATISTICAL MANAGE Business Process Model Current generic BPM (gBPM) Design Build Collect Process Need Analyse Disseminate Methodology

12. CORPORATE STATISTICAL MANAGE Business Process Model Future gBPM Analyse Disseminate Need Design Build Collect Process Methodology

13. Process - Progress & successes • gBPM - for all collections - developed, agreed and used • Detailed business processes - documented for • Collect, Analyse, Disseminate • Administrative data, data integration, & feasibility projects

14. Methods – Establishment surveys Advances in: • longitudinal Business Frame • size measures on our Business Frame • modelled tax data for the "small" strata • regular reselection • record linkage methodology • research into sample rotation • p% rule for confidentialisation of tables

15. Methods – Case study

16. Methods - Progress & successes • Standard methods – being developed and/or documented • Standard tools – examples: • BANFF (Statistics Canada) for editing and imputation • INTERP (in-house) for benchmarking and interpolation • QualityStage (IBM) for data integration • GREGWT (ABS) for integrated weighting • X12-ARIMA (US Census Bureau) / SADJ (in-house)

17. Software Our current system… SurveyProcessingTemplate

18. Software evolution BmTS builds on SProceT foundations • metadata driven systems • common look and feel • re-use of 'best practice' • availability of management information • dynamic nature of views • interactive processing • fully integrated desktop processing

19. Software evolution BmTS: The next generation • not a template that is iteratively improved; not in Lotus Notes • wider scope - end-to-end; used by all Statistics NZ collections • generic & standard business processes, methods, tools • workflows, centralised data & metadata; service oriented architecture (SOA)

20. 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 Future Software - BmTS Components Disseminate Need Collect Process Analyse Design CURFS CURFS Imaging Imaging Build 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

21. 10. Dashboard / Workflow 4. Analytical Environment 5. Information Portal 6. Transformations 9. Reference Data Stores Aggregate ‘UR’Data Summary Clean Raw 7. Respondent Management 8. Customer Management Data Data Data Data BmTS Components - Progress Link to Analytics Link to Portal SAS BI D/board workflow MS Excel TS Analysis Graphical Analysis IDC Imaging Datalab CURFS CURFS Imaging Imaging Multi Multi BANFF - - T’form library UR T’form Logi+ Category EI Confid T’form Data Data INFOS INFOS Admin. Admin. Output Channels Output Channels Output cubes 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 Call Mgmt Web Web CAI CAI Aggregate Area Clean Area Table builder Summary ‘ UR’ Aggregate Clean Raw Statis phere E E - - Q stage Data Data Data RADL Data Data RADL Admin Data T’form Form Form CRM Customer CRM RM portal 3. Metadata Store 3. Metadata Environment System Metadata Statistical Statistical Process Process Knowledge Base Knowledge Base BF

22. Software – Progress & successes • Strategy & Broad Logical Design for 7/10 BmTS components • Proof of concept / prototype solutions for: • National Accounts / time series data • dissemination products • unit record data: collect to clean • Standardised collection phase in production • Fact table approach utilised for all data • Reuse of components is happening • User Interface guide developed and utilised • Service oriented architecture in place

23. Changes and challenges Cultural change required • business processes as the driver (not ICT) • focus on commonalities between business areas • support for and use of standards • culture of analysis

24. Changes and challenges • Ownership - of processes, methods, and tools / software • Monitoring progress • Clarifying future statistical architecture • Impact on data quality • Determining the impact on specific outputs

25. Lessons learned • People > process > method >… systems • Collection areas focus on their differences • Compromise: development vs BAU • Long-term gain has short-term cost • Evolutionary transformation: • many minor successes and failures Do not expect to get it 100% right the first time

26. Contacts • John.Pearson@stats.govt.nzmethodology • Tracey.Savage@stats.govt.nzBmTS general • Craig.Mitchell@stats.govt.nz Metadata • Elizabeth.Rayner@stats.govt.nz BPM