1. A perspective from beyond the ESS Alistair Hamilton Director – Statistical Information Standards Australian Bureau of Statistics

2. Overview Frameworks for collaborations beyond the ESS Towards a top down view on what’s required for industrialisation – Possible “top down” pre-requisites

3. ESS Strategy & “GSS” Aspirations Legal framework – Different situation Very little binding governance across GSS (Global Statistical System) More diverse national contexts(?) Methodological Developments – Shared interest : Best practice & common tools – More heterogeneous, less well bound, context Modernisation of IT Infrastructure – Shared challenge, broadly shared directions Standardisation and industrialisation – Shared aspirations : eg HLG-BAS

4. HLG-BAS High Level Group for Strategic Directions in Business Architecture in Statistics – Created by Bureau of the Conference of European Statisticians (CES) in 2010 – Mission : Oversee and guide discussions on developments in the business architecture of the statistical production process, including methodology and information technology aspects – Strategic Vision endorsed by CES in June 2011 – Translating vision to strategy (and implementation) is theme for workshop next week

6. Some key points from the vision We have to re-invent our products and processes and adapt to a changed world We need to work together – The challenges are too big for statistical organisations to tackle on their own Emphasis on related themes of Industrialisation and Standardisation

9. Examples of other joint efforts : Statistical Network Idea discussed at CSTAT (OECD Committee on Statistics) in 2009 – Trial a collaboration approach in striving for improvement in Statistical Information Management Initial members : SE, NO, NZ, GB, CA, AU Critical goal : "Harmonising statistical methods, systems and capabilities across statistical agencies". Practical small steps to industrialise methods and processes to quickly and effectively benefit all participating NSIs Building with sharing and re-use across the whole community, in mind 5 specific collaborations in 1 st round

10. Example project Generic Statistical Information Model (GSIM) – developing & operationalising GSIM agreed as highest priority strategic enabler of efficient & effective collaboration in the development & sharing of statistical information management systems. – progress through to associating GSIM with, eg, commonly agreed representation in XML – harness existing standards based representations wherever fit for purpose SDMX & DDI-L agreed as key starting points – Co-ordinate & collaborate with other “networks” & groups Eg METIS, ESSnets – GSIM focuses on all information objects used and/or produced in the course of various sub processes within a statistical business process.

11. (additional level of formalisation & detail required to support consistent operationalization) GSIM

12. Other examples Statistical Open Standards (SOS) Group – Members : IS, NO, SE, FI, DK, NL OECD.Stat User Group – Members : OECD, IMF, IT, AU, NZ Paris Microdata Access Group Groups associated with PC-Axis & Blaise Many, many cases of individual NSIs undertaking R&D on topics covered by ESSnets!

13. Top Down Pre-requisites (1) Industry definition – Value propositions – Scope – Relationship with allied industries comparisons with other information industries that have industrialised – More detail on what industrialisation means Implications for future roles of NSIs, for staff

14. Top Down Pre-requisites (2) Ways and means – Effective industry bodies Role of international agencies – Additional industry frameworks/guides Includes collaboration frameworks covering legal/IP/whole of life considerations – Agility (financial resources, projects, staff) – Confidence in delivery – Cultural change – Easier matching of costs & benefits

15. Top Down Pre-requisites (3) Industry standards – Reference architecture – Service/component (particularly interface) – Information GSIM + operationalisation – Process GSBPM + operationalisation via CORE IM etc – Method Combine service/component and information in plug and play and connectivity

16. Statistical Business Process Conduit Statistical Information Conduit Connection Layer Process/Workflow Definitions Process Metrics (Paradata/BI) Statistical Metadata Data Connection Layer “Plugged in” applications “Plugged in” data & metadata stores Workflow Management Registry

17. Challenges What are the other pre-requisites? What is the critical path? – What are the first steps on it? – What is the role & path for connecting concept & practice? How quickly can we progress it? How best to organise to progress it? What is the best interim strategy for agencies already undertaking major developments? The local vs global “industrialisation” approach Product vs Process

18. External observations on ESSnets A lot of current interest beyond the ESS in regard to various ESSnets – Wider awareness (at a summary level) would generate even more interest ESSnet processes are commendably open, eg – external participants as observers – dissemination of results & sharing of experiences Admire resources and frameworks available to facilitate collaborative R&D within ESS and produced shared outputs Agreed common directions across member states potentially represents a critical mass of “aligned” NSIs in a global context – ESS decisions influence broader GSS ESSnet outputs, however, are not always put into practice consistently across member states? Can be difficult to determine actual focus of an ESSnet and relationships with other work

20. Possibilities Mapping is useful (of ESSnets & other work) – Network analysis of activities? May also help identify gaps and overlaps? Top down priorities may be clarified by – HLG-BAS Strategy for industrialisation & standardisation, and – Sponsorship on Standardisation – Architectural framework for ESS Continue to consider going beyond ESS in “state of the art” studies Seek to identify national & multi-national initiatives beyond ESS which strongly intersect with proposed ESSnets (or specific work packages within them) – via “community knowledge within the ESS” – via “advertising” to parties beyond the ESS self identify possible use of UNECE, OECD etc channels?