IAOS-OECD 2018 conference, 19-21 September 2018, Paris. More information at: http://www.oecd.org/iaos2018/

1. Regional Statistics Agency as a Change
Agent – experiences of GCC-Stat in
assisting the transformation of NSIs in the
Gulf region
16th conference of IAOS, Paris September 2018,
Session 5A Regional and International Comparisons,
21 September 2018
Dr Salah Al Muzahmi
GCC-Stat
10/3/2018 1

2. Overview
10/3/2018 2
Introduction to GCC Statistical System
GCC, Statistics in GCC, GCC-Stat
Global Drivers of Change
Fourth Industrial Revolution
Data Revolution
Transforming and Modernising GCC Statistical System
Experiences
Challenges
Fourth Industrial Era in Official Statistics
Observations
Implications for Regional Statistics Agencies

3. Introduction to GCC Statistical
System
United Arab Emirates
Bahrain
Saudi Arabia
Oman
Qatar
Kuwait
10/3/2018 3
Gulf Cooperation Council
Key Indicators (2016)
Total Population (million) - 53.5
Total GDP (USD million) – 1,354,809
GDP per capita (USD) – 25,346

4. GCC Organisations
10/3/2018 4
Gulf Cooperation Council – formed 1981
GCC
Organisations
GCC-STAT
GCC
Secretariat
GCC
Committees
 Cooperation
 Coordination
 Strategic planning
 Monitoring
progress
 Sectoral Roles
 Implementation
 Reporting
 Developing plans
 Developing GCC
Stat System
 GCC statistics
 Collaboration
 Capacity building
 Leaders decisions
 SDGs
 Monitory
 Competitiveness
GCC
partners

5. 10/3/2018 5
GCC Statistical System
GCC-Stat
GCC
Secretariat
GCC
Organisations
Country
Statistical
Systems
International
Reporting
(e.g. UN, IMF)

6. 10/3/2018 6
GCC Statistical Strategy
Objectives
• Assembly and Production of Statistics
• Harmonisation of statistics across GCC consistent
with contemporary international standards
• Increase Statistical Capacity in GCC countries
Building a sustainable GCC statistical system and
partnership between GCC-Stat and the National Statistical
Centres

7. Global Drivers of Change
10/3/2018 7
1st
• Mechanisation
2nd
• Mass Production
3rd
• Digital
4th
• Integration of digital, physical and biology
Industrial Revolutions

8. 10/3/2018 8
4th Industrial Revolution – Exponential Increases in Data
• Statistics – exponential increase in
• Variety of Data sources
• Data availability
• Data Volumes
Example 1 - Hajj Statistics 2017 – 23 Aug – 4 Sept 2017
• 2.3 million pilgrims
• Over 700 million phone calls
• More than 23,000 terabytes of data
consumed
• 80% increase in data consumption
compared with 2016 – Snapchat and
YouTube driving volume increases
2018 – allowed for 15% increase in data
volume compared with 2017

9. 10/3/2018 9
Changing Demands and Data Sources
• New generation of decision makers , active social media
users, always connected, expect information NOW
• Official Statistics work programmes - heavy reliance on
trusted methodology but not same focus on future issues
• Methodologies seen as very routine and not relevant to
users (or public)

10. 10/3/2018 10
Example 2 – Oman Health Decision Makers
• Real time
Data
• Real time
Monitoring
• Real time
Decisions
Dashboards
Call Centre Monitoring

11. 10/3/2018 11
Oman MOH Dashboard –Visits to Hospitals

12. Implications for Statistical Offices
Organization
components
Organization
structure
I T
infrastructure
Tools
Users
Media
Resources
and
Process
Statistics
Data
Skills
Revolution
is changing
/ shaping all
components
Challenge;
Integration of
components
to utilize data
revolution
In data revolution:
Its not big fish eating small fish! Its fast ones eating slow ones!!
10/3/2018 12

13. 10/3/2018 13
Transforming GCC Statistical Systems
• Regional activities include:
• 2016 Doha Declaration on a Data Revolution in the Arab
World
• First GCC Statistical Forum, Riyadh 2017
• Gulf Statistical Day – 24 December
• Enhanced statistical availability (Regional, National level)
• GCC Harmonised Projects (e.g. 2020 Census)

14. 10/3/2018 14
Regional Challenges
• Changing Strategic Directions increasing
demand for statistics
• Post Oil-economy – increased diversification
• Competitiveness Indicators – ranking information
increasingly important
• Reporting against international standard reporting
frameworks, e.g. SDGs, GDDS
• Different Demographic situations requiring different
data disaggregations
• Highly connected populations – citizens and non-citizens

15. 10/3/2018 15
Regional Challenges - continued
Changing Operating Environment for Statistical Systems
• Lower Oil and Gas prices Government Efficiency
programmes
• E-government and Digitalization strategies
• Balancing local capacity development and addressing
technical gaps
• Building skills to work with administrative and big data
(technical and expanded relationship skills)
• Greater availability of information in region, but not
always ‘official statistics’
• Balancing regional and national priorities
• New Statistical Issues
• Measuring impact of digital and digital based economy
• Utilising new data sources (e.g. Big Data)

16. 10/3/2018 16
Fourth Industrial Era for Official Statistics
• Fourth Industrial Revolution arrived in our region
The Fourth Industrial Revolution – a Trillion Riyal Opportunity for Saudi Arabia –
Saudi Arabia Dec 2017
Fourth Industrial Revolution will result
in loss of traditional jobs: Al-Kharafi –
‘Enabling a culture of innovation is a
necessity for corporate growth and
skills development’ – Bahrain, Jan 2018
Fourth Industrial Revolution, cloud
transforming media industry – Qatar,
March 2018
Are-We-Ready-for-the-4th-Industrial-
Revolution? Oman, May 2018
UAE Fourth Industrial Revolution Strategy,
2017(https://www.mocaf.gov.ae/docs/default-source/default-document-
library/uae-4ir_strategy-booklet_en.pdf?sfvrsn=0)
• Recent Media Headlines

17. 10/3/2018 17
Impact on Official Statistics
• Future uncertain –but statistics systems need to be ready
• Example 3 – Possible scenarios1 for future of work
• Speed of implementation of 3 factors will shape the future of work
• Technological Change
• Learning Evolution (acquiring skills)
• Talent Mobility
1World Economic Forum White Paper “Eight Futures of Work Scenarios and their Implications”
Technology
Change Learning
Talent
Mobility

18. Data revolution: Facing the shift!
Data Life Cycle is iterating: Bye Bye business as usual
 No fieldwork as before; virtually (Free online data)
 No processing as before; Machine learning, AI
 No dissemination as before; tweeting …
10/3/2018 18
We need to Compete to Stay Fit
Will Traditional official statistics and their Techniques be fit for
the future?

19. 10/3/2018 19
Response necessary for survival
• Statistics systems need to be innovative and responsive to
prepare for many scenarios
• Traditional measures and domains (Economy, Society and
Environment) still important
• New methods to use new and emerging data sources
• Measuring new phenomena – digital economy, interaction of virtual
and physical worlds
• Measuring impact of Fourth Industrial Revolution on
• Economy
• Society (e.g. Health, Labour, Societal outcomes)
• Environment (e.g. Environment impact of Cloud computing)
• Systems need to be flexible and nimble, yet remain trusted
by all stakeholders – new and old

20. 10/3/2018 20
Implications for Regional Statistics Offices
• Regional Statistics Offices MUST
Be aware of broader issues and patterns, and place regional situation in
international context
Form partnerships, linking regional, international and local partners to
utilize methodologies and techniques
Prototype new solutions
• As Change Agents, Regional Statistics Offices need to:
Be advocates for change, while still championing good statistical practice
Encourage NSIs to work in different ways with users and providers
Develop new partnerships (e.g. Gateway to regional data providers)
Take active role in prototyping
Model good practices

21. 10/3/2018 21
Conclusion
• Regional Statistics Centres can be change agent
• New challenges from 4th Industrial Era in Official Statistics,
mean
• More efforts needed to support transformation and modernization
• Requires Innovative approach
• Important to measure the status quo – but ALSO measure the new
world and provide information in new ways, relevant to users
• Partnerships will be critical
Acknowledgements
Co-authors (Sabir Al Harbi, Nancy McBeth)
Colleagues at GCC-Stat and across GCC Statistical System
Thank you