United Nations Economic Commission for Africa African Centre for Statistics Reference Regional Framework for Statistical Capacity Building in Africa (RRSF) Ben Kiregyera Director African Centre for.
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Transcript United Nations Economic Commission for Africa African Centre for Statistics Reference Regional Framework for Statistical Capacity Building in Africa (RRSF) Ben Kiregyera Director African Centre for.
United Nations Economic Commission for Africa
African Centre for Statistics
Reference Regional Framework for Statistical
Capacity Building in Africa (RRSF)
Ben Kiregyera
Director
African Centre for Statistics
19 October, 2007
Motivation
Issues which have come up during this workshop:
organizational issues (including legal framework,
mandates, coordination, etc)
institutional issues (including infrastructure, funding,
HR, capacity building, etc)
data-related issues (data sources, data collection
methodologies, data management including
dissemination)
Many of these issues are best handled as part of broader
Frameworks and initiatives
Slide 2
Scope
Introduction
What is RRSF?
National Strategy for the Development of
Statistics (NSDS)
Capacity Building strategies
Critical success factors
Slide 3
Introduction
Addis Ababa Plan of Action for Statistical Development
in Africa in the 1990s (AAPA)
• Precipitous decline in statistical production in 70s & 80s
• Factors constraining statistical production identified as:
poor management
inadequate funding
lack of timeliness in delivery of statistics
unsatisfactory quality of produced data
inability to respond quickly to new data needs
•
AAPA adopted by the African Ministers for Planning and
Development in 1990 to:
reverse decline in statistical production
lay a basis for development of statistics in Africa
Slide 4
Evaluation of AAPA in 2000
Assessment
Results
Slide 5
Twin problem of data demand
and supply
High
Demand
II
“Data
Supply-constrained
countries”
Poor
Quality
IV
“Virtuous
Circle
countries”
III
I
“Vicious
Circle
countries”
Good
Quality
“Data
Demandconstrained
countries”
Low
Demand
Slide 6
Characteristics of statistical under-development
Inadequate statistical awareness/literacy
inadequate links of statistical systems to policy
inadequate coordination (next slide)
weaknesses in statistical capacity
limited capacity in management and strategic leadership
data gaps on some key demographic,
socio-economic and environmental indicators
unreliability of some existing data
inadequate use of existing data – challenge of
data use
unsustainability of statistical systems
Slide 7
Uncoordinated National Statistical System
Agriculture
etc
Health
NSO
Transport
Labour
Education
Slide 8
Partially coordinated National Statistical System
Agriculture
etc
Health
NSO
Transport
Labour
Education
Slide 9
Fully coordinated National Statistical System
Agriculture
etc
Health
NSO
Transport
Labour
Education
Slide 10
demand for good statistics increased exponentially since
countries signed up to managing for results
Managing for results has evolved as a global effort
among both national governments and development
agencies to:
reduce poverty
support sustainable and equitable economic
growth
better define and measure development
outcomes
Challenges
Opportunities
Slide 11
Opportunities
Increasing demand – results agenda is “data intensive”
Raising the public profile of statistics
Building statistical capacity in medium to longer term
International cooperation and partnerships for statistics
PARIS21
WB Trust Fund for Statistical Capacity Building
Multi – and bilateral donors
New emphasis on statistics by the African Development
Bank
Renaissance of statistics function at UN ECA with
establishment of the African Centre for Statistics
Slide 12
Management for results given impetus by a number of
roundtables among them, the Marrakech Roundtable
meeting on managing for result, Morocco (2004)
Better statistics identified as a priority of the results
agenda and Marrakech roundtable came up with a
global plan for statistics, commonly called the
Marrakech Action Plan for Statistics (MAPS) to
improve national & international statistics
Reference Regional Strategic Framework for Statistical
Capacity Building in Africa (RRSF) is a regional variant
of the MAPS
Slide 13
What is RRSF?
Overall objective
The overall objective of the RRSF is to contribute to policymaking, development outcomes and good governance in
Africa by guiding and accelerating sustainable statistical
capacity building activities.
Specific objectives
Raise societal awareness about role and importance of
data to national development (statistical advocacy)
Enhance data quality and usability
Promote greater use of data
Build sustainable statistical capacity
Slide 14
The process
assessment missions to more than 20 countries & 40 subregional, regional and international & bilateral development
partners
leveraged previous assessments, existing frameworks &
initiatives
lessons learnt from the Addis Ababa Plan of Action for
Statistical development in Africa in the 1990s
Assessment identified:
strengths to build on,
weaknesses to resolve
opportunities to exploit
threats to avoid
Slide 15
RRSF endorsed by:
the meeting of Directors of NSOs,
2nd Forum on African Statistical Development
Conference of African Ministers for Finance,
Planning and Economic Development
Slide 16
RRSF Capacity Building
Strategies
Overarching strategy: design of the National Strategy for
the development of Statistics (NSDS)
Establishing In-service Training Centres at NSOs
meet huge demand for minimum competencies
among technicians who collect/manage data in
government
In S. Africa, this number is estimated to be
between 50,000 and 200,000
Centres should also organize periodic short
courses, seminars and workshops to meet specific
needs of NSOs & other data producers
Slide 17
Strengthen Regional Statistical Training Centres
Building statistical capacity in sub-regional organizations
(ECOWAS, SADC, COMESA, etc)
Slide 18
National Strategy for the
Development of Statistics
(NSDS)
What is NSDS?
National
strategy
and plan of
action
A catalyst
for change
to build
confidence
to strengthen statistical capacity across the
entire National Statistical System
A medium to long-term vision for SCB
responding to key user needs
A robust, comprehensive and coherent
framework to:
address data limitations
Mobilize & prioritise the use of
resources
integrate statistics within national
policy processes
Slide 19
Importance of the process
as important as the strategy
facilitate statistical advocacy
mainstream key stakeholders i.e should:
be participatory
be inclusive
use a concensus-building approach
• Plans that are country-specific and countryowned
• Ownership leads to more commitment,
creativity, imagination, innovation and
productivity.
participation and ownership are essential for
successful strategic management and the key to
the success of strategy
Slide 20
process presupposes that we are aiming to build
a truly integrated National Statistical System
process should be based on NSDS principles
developed by PARIS21 and partners
Guide developed by PARIS21 (2004)
Guide on Integrating Sectoral Statistics into the
Design of NSDS (AfDB, PARIS21 and Intersect)
Slide 21
Bottom-up approach
NSDS
SSPS
(Agric)
SSPS
(Health)
SSPS
(Edn. )
SSPS – Sector Strategic Plan for Statistics
Slide 22
Critical success factors
Strategic leadership and management (strategic insight)
NSDS not just one of the statistical activities
Statistical reform (not cosmetics)
Managing change
“It’s not the strongest species that survive, nor the
most intelligent, but the most responsive to change”,
Charles Darwin – father of evolution theory
Process (participatory, continuity, empowering, involve
development partners)
Cultivate “Champions” and “Missionaries”
Partnerships
Slide 23
building partnerships in Africa and beyond
Statistical Commission for Africa (Statcom-Africa)
African Statistical Coordination Committee
•
•
•
•
ECA
African Development Bank (ADB)
African Union (AU)
African Capacity Building Foundation (ACBF)
UN agencies, PARIS21, multilateral and bilateral
agencies and other partners
Scaling up Support for Statistics – High Level Meeting
of Donors in Paris 15 November
Thank you!
African Centre for Statistics
Visit us at
http:www.uneca.org/statistics/
Slide 25