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Initiatives for the industrialisation of statistics and their impact on business registers. Steven Vale UNECE [email protected] Contents. Streamlining and Industrialisation International initiatives Implications for business registers Opportunities and threats Conclusions.

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Initiatives for the industrialisation of statistics and their impact on business registers l.jpg

Initiatives for the industrialisationof statistics and their impact on business registers

Steven Vale

UNECE

[email protected]


Contents l.jpg
Contents

  • Streamlining and Industrialisation

  • International initiatives

  • Implications for business registers

    • Opportunities and threats

  • Conclusions


Streamlining is l.jpg
Streamlining is:

  • Improving efficiency

  • Reducing costs

  • More timely data

  • Increased flexibility to produce new outputs

  • A challenge faced by all statistical organisations


Industrialisation is l.jpg
Industrialisation is:

  • Common processes

  • Common tools

  • Common methodologies

  • Recognising that all statistics are produced in a similar way, rather than each domain being “special”

  • A consequence of streamlining


Slide5 l.jpg
Many international groups and projects are talking about streamlining and industrialising statistics


Why this great interest l.jpg

The internet streamlining and industrialising statistics

has 1800

exabytes of

data in 2011

exa = 10^18

Why this great interest?


50 000 exabytes by 2020 l.jpg

We live in streamlining and industrialising statistics

exponential

times!

50,000 exabytes by 2020

27 fold

growth in

the next

9 years


Are these data interesting l.jpg
Are these data interesting? streamlining and industrialising statistics

  • Probably 99.9% are videos, photos, audio files, text messages and other nonsense

  • But that still leaves1,800,000,000,000,000,000bytes of potentially relevant data


Private sector competitors l.jpg
Private sector competitors? streamlining and industrialising statistics

  • Google:

    • Data labs

    • Public Data Explorer

    • Real-time price indices

    • First point of reference for the “data generation”

  • Facebook, store cards, credit agencies, ...

    • What if they link their data?


Coordination hlg bas l.jpg
Coordination – HLG-BAS streamlining and industrialising statistics

  • High-Level Group for Strategic Directions in Business Architecture in Statistics

  • UNECE group, created by the Conference of European Statisticians in 2010

  • Mission:

    • To oversee and guide discussions on developments in the business architecture of the statistical production process, including methodological and information technology aspects


Hlg bas members l.jpg
HLG-BAS Members streamlining and industrialising statistics

  • Netherlands - Gosse van der Veen (Chairman)

  • Australia - Brian Pink

  • Italy - Enrico Giovannini

  • Slovenia - Irena Krizman

  • United States - Katherine Wallman

  • Eurostat - Walter Radermacher

  • OECD – Martine Durand

  • UNECE - Lidia Bratanova

  • Observers METIS – Alice Born (Canada) MSIS – Rune Gløersen (Norway) SAB – Marton Vucsan (Netherlands)


Hlg bas strategic vision l.jpg
HLG-BAS Strategic Vision streamlining and industrialising statistics

  • Endorsed by the Conference of European Statisticians on 14 June

    We have to re-invent our products and processes and adapt to a changed world


Slide14 l.jpg
The Challenges are too big for statistical organisations to tackle on their own.We need to work together


Other international initiatives l.jpg
Other international initiatives tackle on their own.

  • “Industry” standards

    • Generic Statistical Business Process Model

    • Generic Statistical Information Model

    • Statistical Data and Metadata eXchange

    • Data Documentation Initiative


Other international initiatives16 l.jpg
Other international initiatives tackle on their own.

  • New collaborative networks

    • “Statistical Network”

    • Sharing Advisory Board

    • ESSNet projects

    • SDMX / DDI Dialogue


What does this mean in practice l.jpg
What does this mean in practice? tackle on their own.

  • Collaboration

  • Coordination

  • Communication


Changing the focus l.jpg
Changing the focus tackle on their own.

  • From local to corporate optimum

    • Standard processes within an organisation

    • Not always the best choice for individual statistical domains, but more efficient at the level of the organisation

    • Requires strategic decisions and clear management commitment

  • From corporate to global optimum?


Changing roles for nsos l.jpg
Changing roles for NSOs? tackle on their own.

  • Data integration

  • Quality assurance

  • More focus on analysis and interpretation

  • Partnerships for dissemination

  • Changing staff and cost profiles

  • Changing organisational culture


Opportunities and threats for statistical business registers l.jpg
Opportunities and threats for statistical business registers tackle on their own.

  • Reduced role of surveys and sampling frames

  • Greater use of external and mixed data sources

    • BR becomes “gateway” for business data

      • More satellite registers?

    • More sophisticated matching techniques needed

  • More integration between statistical registers

  • Register or business statistics database?

  • Source of new statistics


Questions steven vale@unece org www1 unece org stat platform display hlgbas l.jpg
Questions? tackle on their [email protected]/stat/platform/display/hlgbas


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