Modernization of statistical production and services

Transcription

1 ADVANCING STATISTICS FOR DEVELOPMENT Modernization of statistical production and services Marko Javorsek ESCAP Statistics Division

2 Why modernization of statistical production and services? 2

3 In 1990 data were scarce, interpretation was readily available Paradigm shift In 2014 data are everywhere, interpretation is scarce 3

4 So what is modernization? What modernization IS? Transforming the way NSOs work through: Common generic processes Common tools Common methodologies Recognizing all statistics are produced in a similar way Increased flexibility to adapt What modernization is NOT? No special domains Use of IT 4

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6 What are the main drivers of modernization? Creation of a more adaptive and cost-effective information management environment through stronger collaboration Processes that are more agile and quality assured, while requiring less resources to operate and maintain Modernize information systems to address the evolving field of statistics and maintain relevance across developed and developing countries Regional collaboration and influence global directions Collaborative efforts are likely to be more cost-effective and of higher quality 6

7 Specificities of Asia-Pacific region in the field of modernisation Cost-effectiveness benefit was assessed to be of less immediate priority Improved quality could be taken up as a key objective Concepts, standards and tools are relatively new to a large number of countries in the region NSOs in the region are most often structured by statistical areas or domains and are decentralized No transnational legislation on statistics The least developed countries lack the full range of methodological and information technology expertise 7

8 Committee on Statistics (2010) Strategic direction of the Committee Ensuring that all countries in the region by 2020 have the capability to provide an agreed basic range of population, economic, social and environmental statistics. Creating a more adaptive and cost-effective information management environment for national statistical offices through stronger collaboration. 8

9 governance structure & strategic direction 9

10 Global initiatives & collaboration mechanisms High-Level Group for the Modernization of Statistical Production and Services (HLG) Objectives: To promote common standards, models, tools and methods to support the modernization of official statistics. To drive new developments in the production, organization and products of official statistics, ensuring effective coordination and information sharing within official statistics, and with relevant external bodies. To advise the Bureau of the CES on the direction of strategic developments in the modernization of official statistics, and ensure that there is a maximum of convergence and coordination within the statistical "industry". 10

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12 Regional perspective on modernization CST 3 (2012) proposes the establishment of High-level strategic body Network of Experts Strategic Advisory Body for the Modernization of Statistical Production and Services in Asia and the Pacific (SAB-AP) The mission is To raise awareness and build capacity, particularly related to concepts, methods and standards, to support national modernization efforts The Body has 7 members (Australia, India, Malaysia, Pakistan, Republic of Korea, Samoa, Viet Nam) and is chaired by Australia First meeting of the body in November 2013 in Japan 12

13 Schematic depiction of the HLG, SAB-AP and working groups as suggested by MSIS 2013 participants 13

14 standards & tools driving modernization 14

15 Key standards The following are the key standards that have been developed on the global level: GSBPM GSIM CSPA SDMX DDI 15

16 Generic Statistical Business Process Model (GSBPM) Why do we need the GSBPM? To define and describe statistical processes in a coherent way To standardize process terminology To compare and benchmark processes within and between organisations To identify synergies between processes To inform decisions on systems architectures and organisation of resources 16

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18 GSBPM Not a linear model Sub-processes do not have to be followed in a strict order It is a matrix, through which there are many possible paths, including iterative loops within and between phases Some iterations of a regular process may skip certain sub-processes 18

19 GSIM and CSPA Generic Statistical Information Model (GSIM) describes the information objects and flows within the statistical business process Examples include data and metadata (such as classifications) as well as the rules and parameters needed for production processes to run (for example, data editing rules). GSIM is not a software tool: It is a new way of thinking! Common Statistical Production Architecture: An statistical industry architecture will make it easier for each organization to standardize and combine the components of statistical production, regardless of where the statistical services are built 19

20 SDMX and DDI Standard Data and Metadata exchange (SDMX) Common data transmission format for statistical data and metadata Data Documentation Initiatives (DDI) Standard dedicated to microdata documentation; enables documentation of complex microdatafiles 20

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22 Business Architecture Information Architecture Application Architecture Technology Architecture 22

23 projects & activities 23

24 HLG Some global activities Generic Statistical Information Model (GSIM) Common Statistical Production Architecture Frameworks and Standards for Statistical Modernisation Implementing the Common Statistical Production Architecture The use of Big Data for official statistics UNSD Global working group on big data 24

25 Big Data (HLG) Priority: facilitating the use of Big Data for official statistics Key challenges (April 2014): The need for a quality framework for Big Data Managing privacy and data security Developing partnerships with data suppliers, processors and users Developing methodology for Big Data Developing the skills needed to use Big Data 25

26 Big Data (UNSD) UN Statistical Commission (2014): Big data and modernization of statistical systems The UN Statistical Commission has supported: The need to further investigate the sources, challenges and areas of use of big data for official statistics at the global level, especially with respect to the circumstances of developing countries and the link to the post-2015 development agenda and the data revolution initiative. The creation of a global working group on the use of big data for official statistics whose activities would complement the work carried out by the regional commissions and manage the globally relevant issues. 26

27 ESCAP past events on modernization Side event to the Committee on Statistics, Second session Modernizing statistical information systems, Bangkok 2010 Expert Group Meeting: Opportunities and advantages of enhanced collaboration on statistical information management in Asia and the Pacific, Bangkok 2011 SIAP Management Seminar 2011 Shifting from stovepipe data producer to information service provider Practical advisory workshop: Supporting effective use of information and communication technology in population census operations, Moscow 2012 GSBPM & SDMX Expert group meeting: MSIS 2013, Bangkok/Paris 27

28 ADB/ESCAP SDMX Capacity Building Initiative Direct outcome from MSIS 2013 The primary focus of the project is to promote the use of SDMX among national statistical systems in the region and build regional capacities in applying SDMX The project is focusing on Mapping of DSDs for data exchange (reuse global DSDs); Capacity building on using tools to support automated data exchange (e.g. Eurostat SDMX-RI, IMF Open Data Platfrom). 28

29 ADB/ESCAP SDMX Capacity Building Initiative (cont d) Focus on economic statistics indicators (ADB Key Indicators), limited to NA or BoP in the first stage (due to the recent adoption of the global DSDs) Take into account the specific needs of other international organizations collecting economic data (e.g. OECD, IMF, UNSD, WB, etc.) The pilot phase involves 4 countries: Australia, Malaysia, New Zealand, and Thailand. Timeline

30 Modernization wiki 30

31 objectives 31

32 MSIS 2013 In 2013 ESCAP joins the organization and MSIS; first time in Asia-Pacific in 2010 in the Republic of Korea April 2013 held in 2 venues joined by live web link Paris hosted by OECD Bangkok hosted by ESCAP Joint sessions were held Bangkok afternoon and Paris morning time 32

33 Outcomes of the MSIS 2013 (Bangkok) Participants recommended that the work of the expert community centre around key priority areas; and interested practitioners and experts to gather in smaller working groups. Key priority areas identified by the participants: Strengthening national statistical systems (coordination, information flow in decentralized systems, etc.) Generic Standard Business Process Model (GSBPM) Statistical Data and Metadata Exchange (SDMX) e-collection Data dissemination Big data 33

34 Objectives of MSIS 2014 Provide guidance on future modernization work in Asia-Pacific Energize the network of experts Provide a forum for exchange of experiences Collect, discuss and make available examples of good practice Facilitate implementation of relevant standards and recommendations 34

35 What do we need for future work? Commitment for collaboration on modernization efforts Establishment and participation in informal working groups in specific areas of work What kind of modalities for collaboration Future expert group meetings (e.g. MSIS 2015) Virtual collaboration / knowledge sharing How to work with limited financial means 35

36 Reflections What kind of activities does the region need: General awareness for modernization or collaborative work on specific topics? What are the best ways to work on modernization? What are the benefits of regional collaboration? How can we better share practices and experiences? How can an Asia-Pacific network of experts add value to modernization efforts in each country? What can we contribute to the network of experts? Are we willing co commit time and resources to regional collaboration? How can we better ensure the applicability and implementation of the standards developed at the global level to Asia-Pacific? 36