1. Current and Future Applications of the Generic Statistical Business Process Model at Statistics Canada Laurie Reedman and Claude Julien May 5, 2010

2. 2 Overview  The Generic Statistical Business Process Model (GSBPM)  Quality Assurance Reviews  Quality in Publications  Quality Guidelines 5 th Edition  Corporate Business Architecture Integrated Business Statistics Program

3. 2 Design 3 Build 4 Collect 5 Process 6 Analyse 7 Disseminate 1 Specify Needs 3.5 Test statistical business process 3.4 Test production system 3.3 Configure workflows 3.2 Build or enhance process components 3.1 Build data collection instrument 1.6 Prepare business case 1.5 Check data availability 1.3 Establish output objectives 1.2 Consult and confirm needs 1.1 Determine needs for information 2.6 Design production systems and workflow 2.5 Design statistical processing methodology 2.4 Design frame and sample methodology 2.3 Design data collection methodology 2.2 Design variable descriptions 2.1 Design outputs 4.4 Finalize collection 4.3 Run collection 4.2 Set up collection 4.1 Select sample 5.1 Integrate data 5.2 Classify and code 5.3 Review, validate and edit 5.4 Impute 5.5 Derive new variables and statistical units 5.6 Calculate weights 5.7 Calculate aggregates 6.1 Prepare draft outputs 6.2 Validate outputs 6.3 Scrutinize and explain 6.4 Apply disclosure control 6.5 Finalize outputs 7.5 Manage user support 7.4 Promote dissemination products 7.3 Manage release of dissemination products 7.2 Produce dissemination products 7.1 Update output systems 8 Archive 9 Evaluate 8.2 Manage archive repository 8.1 Define archive rules 8.3 Preserve data and associate metadata 8.4 Dispose of data and associated metadata 9.1 Gather evaluation inputs 9.2 Conduct evaluation 9.3 Agree action plan Levels 1 and 2 Generic Statistical Business Process Model, version 4.0 (Joint UNECE/Eurostat/OECD Work Session, April 2009) 1.4 Identify concepts 3.6 Finalize production system 5.8 Finalize data files

4. 4 Quality Assurance Reviews  Independent review of the execution (not design) of statistical program  Focus is on quality assurance practices  Objective is to identify “best practices” as well as areas for improvement  Several programs reviewed each year  Summary presented to upper management

5. 5 Quality Assurance Reviews  Reviewer is a mid level manager with no experience in the program being reviewed  Tools to perform the review: Program documentation Meetings with program area managers and staff Templates for the written report and presentation GSBPM

6. 6 2 Design 3 Build 4 Collect 5 Process 6 Analyse 7 Disseminate 1 Specify Needs 3.5 Test statistical business process 3.4 Test production system 3.3 Configure workflows 3.2 Build or enhance process components 3.1 Build data collection instrument 1.6 Prepare business case 1.5 Check data availability 1.3 Establish output objectives 1.2 Consult and confirm needs 1.1 Determine needs for information 2.6 Design production systems and workflow 2.5 Design statistical processing methodology 2.4 Design frame and sample methodology 2.3 Design data collection methodology 2.2 Design variable descriptions 2.1 Design outputs 4.4 Finalize collection 4.3 Run collection 4.2 Set up collection 4.1 Select sample 5.1 Integrate data 5.2 Classify and code 5.3 Review, validate and edit 5.4 Impute 5.5 Derive new variables and statistical units 5.6 Calculate weights 5.7 Calculate aggregates 6.1 Prepare draft outputs 6.2 Validate outputs 6.3 Scrutinize and explain 6.4 Apply disclosure control 6.5 Finalize outputs 7.5 Manage user support 7.4 Promote dissemination products 7.3 Manage release of dissemination products 7.2 Produce dissemination products 7.1 Update output systems 8 Archive 9 Evaluate 8.2 Manage archive repository 8.1 Define archive rules 8.3 Preserve data and associate metadata 8.4 Dispose of data and associated metadata 9.1 Gather evaluation inputs 9.2 Conduct evaluation 9.3 Agree action plan 1.4 Identify concepts 3.6 Finalize production system 5.8 Finalize data files Factors to look for in particular: Staffing Renewal Training Workload Project Management Schedule Checklists Documentation Sign-off Risk planning Change Systems Specs Maintenance Renewal Validation Resources Tools Engagement

7. 7 Quality Assurance Reviews  Benefits of using the GSBPM: Common language for describing process steps Assurance that no steps would be overlooked Locate where in the process greater risks lie Compare risks in one process to another Identify global issues

8. 8 Quality in Publications  Over 400 statistical programs  Numerous tables, time series, publications and papers  The Daily - First line of communication  Over 1,250 texts published every year

9. 9 Quality in Publications  Some corrections after release  Corrections are recorded, analyzed, summarized and reported  Corrections on accuracy are further investigated to determine where, how and why error occurred  First level of GSPBM is used to summarize and report

10. 10 YearTexts Correction Rate Location of error and relative magnitude of correction DesignBuildCollectProcessDisseminate HigherLowerHigherLowerHigherLowerHigherLowerHigherLower 20066232.1%11413 200712343.1%3614210 200812602.2%112210111 200911710.8%2121 20103150.3%1 Quality in Publications

11. 11 Quality Guidelines 5 th Edition  Describe a set of best practices for all steps of a statistical program  Target audience is those developing and implementing the statistical program  Guiding principles: Quality must be built in at each phase of the process Quality is multidimensional  Guidelines for many boxes in the GSBPM

12. 2 Design 3 Build 4 Collect 5 Process 6 Analyse 7 Disseminate 1 Specify Needs 3.5 Test statistical business process 3.4 Test production system 3.3 Configure workflows 3.2 Build or enhance process components 3.1 Build data collection instrument 1.6 Prepare business case 1.5 Check data availability 1.3 Establish output objectives 1.2 Consult and confirm needs 1.1 Determine needs for information 2.6 Design production systems and workflow 2.5 Design statistical processing methodology 2.4 Design frame and sample methodology 2.3 Design data collection methodology 2.2 Design variable descriptions 2.1 Design outputs 4.4 Finalize collection 4.3 Run collection 4.2 Set up collection 4.1 Select sample 5.1 Integrate data 5.2 Classify and code 5.3 Review, validate and edit 5.4 Impute 5.5 Derive new variables and statistical units 5.6 Calculate weights 5.7 Calculate aggregates 6.1 Prepare draft outputs 6.2 Validate outputs 6.3 Scrutinize and explain 6.4 Apply disclosure control 6.5 Finalize outputs 7.5 Manage user support 7.4 Promote dissemination products 7.3 Manage release of dissemination products 7.2 Produce dissemination products 7.1 Update output systems 8 Archive 9 Evaluate 8.2 Manage archive repository 8.1 Define archive rules 8.3 Preserve data and associate metadata 8.4 Dispose of data and associated metadata 9.1 Gather evaluation inputs 9.2 Conduct evaluation 9.3 Agree action plan Levels 1 and 2 Generic Statistical Business Process Model, version 4.0 (Joint UNECE/Eurostat/OECD Work Session, April 2009) 1.4 Identify concepts 3.6 Finalize production system 5.8 Finalize data files

13. 13 Quality Guidelines 5 th Edition  Future plans to make greater use of the GSBPM: Provide guidelines for more (all?) Level 2 steps Base the structure of the Quality Guidelines document on the model itself Locate specific guidelines by navigating through the model

14. 14 Corporate Business Architecture  Challenge: maintain quality of products, use fewer resources  Corporate Business Architecture (CBA) is an initiative to address this challenge  CBA task force used the GSBPM to structure its analysis and organize its report  Embedded the GSBPM in their own Core Business Process

15. Core Business Process

16. 16 Integrated Business Statistics Program  Redesign of the business statistics program  Align with Corporate Business Architecture  Task force recommendations Align services with GSBPM Develop and maintain a business process model Use corporate services, statistical processing standards, industry best practices and the Corporate Business Architecture principles wherever possible

17. 17 Conclusions -Pre-occupation with quality assurance -GSBPM is relatively new to us -GSBPM is a good fit for us -GSBPM provides a common framework and tool for communication -Snowball effect – we are finding more and more ways to use it

18. 18 Contact information For more information, please contact: Pour plus d’information, veuillez contacter : Laurie.Reedman@statcan.gc.ca