Transcript United Nations Economic Commission for Europe Statistical Division The Global Context International developments in the organisation of statistical production Steven Vale, UNECE.

United Nations Economic Commission for Europe
Statistical Division
The Global Context
International developments
in the organisation of
statistical production
Steven Vale, UNECE
Contents





Streamlining and Industrialisation
Introducing the HLG-BAS
The HLG-BAS vision
Other international initiatives
What does it mean in practice?
Streamlining is:





Improving efficiency
Reducing costs
More timely data
Increased flexibility to produce new outputs
A challenge faced by all statistical
organisations
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
Many international groups
and projects are talking
about streamlining and
industrialising statistics
Coordination – HLG-BAS



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









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)
Inventory of Groups
HLG-BAS Strategic Vision

Endorsed by the Conference of
European Statisticians on 14 June
•
Perspective
• Challenges
• Vision

The following slides are based on that
presentation
Some perspective:
The internet
has 1800
exabytes of
data in 2011
exa = 10^18
50,000 exabytes by 2020
27 fold
growth in
the next
9 years
We live in
exponential
times
Are these data interesting?

Probably 99.9% are videos, photos,
audio files, text messages and other
nonsense

But that still leaves
1,800,000,000,000,000,000
bytes of potentially relevant data
Private sector competitors?

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?
High Level Group Vision:
We have to re-invent our
products and processes
and adapt to a changed
world
The Challenges are too big
for statistical organisations
to tackle on their own.
We need to work together
Other international initiatives

“Industry” standards
•
Generic Statistical Business Process Model
• Generic Statistical Information Model
• Statistical Data and Metadata eXchange
• Data Documentation Initiative
Other international initiatives

New collaborative networks
“Statistical Network”
• Sharing Advisory Board
• ESSNet projects
• SDMX / DDI Dialogue
•
What does this mean in practice?




Collaboration
Coordination
Communication
We need to review our systems and
processes – are they right for the 21st
century?
Changing the focus

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?






Data integration
Quality assurance
More focus on analysis and interpretation
Partnerships for dissemination
Changing staff and cost profiles
Changing organisational culture
Next steps


From vision to strategy
Autumn 2011: workshop for
representatives of the groups in the
inventory to improve coordination and
determine how they can contribute to
implementing the vision
Questions?
[email protected]
www1.unece.org/stat/platform/display/hlgbas