National Strategy for the Development of
Statistics (NSDS): A Framework for Building
Statistical Capacity
Presented by Pali Lehohla, Statistician General,
South Africa
Prof. Ben Kiregyera
I.



Monitoring
SCOPE Progress
About tracking progress towards MDGs & realization of
national development agenda (PRSP)
“If you can’t measure it, you can’t manage it”
Monitoring requires:
•
that we set:
Base or benchmark year: For MDGs, it is 1990
Target date: For MDGs, it is 2015
•
A stream of quality & transparent data: in between
the two dates, to measure and report on progress
or lack of it
Reporting
• national reports
• regional reports
• world report
These reports require
good statistics
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“Statistics is not just a technical issue,
it is also a development issue”
therefore
Data producers should strive to understand better
national and international development agenda and
related issues
and
Data users should appreciate and talk more about
statistics and use them for policy and decisionmaking
in pursuit of development outcomes
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II. Main data challenges for monitoring progress

Data challenges become apparent when we try to
answer these questions:
•
Are data available?
•
If Yes, how often are they made available (frequency)
•
How many years are data available? (trend)
•
What disaggregations/classifications are being
used?
•
Which agencies and what activities produce the
data?
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Many countries are trapped in a vicious circle of statistical
under-development / under-performance: statistics are of
poor quality, and both the supply of and demand for statistics
are low
• Limited:
Domestic
under-funding
Conflicting
donor agendas
institutional development
infrastructural development
• Lower demand
• Fewer resources
under-performance
i.e. limited outputs & services
(quality and quantity)
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 data availability (in many countries data not available on
some indicators; for some indicators, lack of baseline data
(1990 benchmark year for MDGs); in some countries, data
collected intermittently; no data series to assist determine
trends or measure progress over time; in some countries,
basic data incomplete
 data comparability (value of data enhanced if data can be
compared between sources, over time & between locations;
problems of comparing data over time and space especially
on poverty in countries due to – changes in definitions
across time and sources; lack of data for 1990, benchmark
year or where available, difficult to compare with current
data due to difference in concepts and methods in data
collection
 inconsistencies between national and international
estimates, particularly on population statistics.
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
Data disaggregation (needed to target interventions
and resources; need for population, sex, sectorspecific & geographic disaggregation of poverty data
(problems with survey data)

Data periodicity and timeliness (large variation in
frequency with which poverty data collected; need for
annual calendar indicating when data for each indicator;
need to align time lag and frequency; need to release
data in timely manner

data quality (many indicators come from administrative
sources; data quality from these sources often poor due
to - lack of resources, limited human capacity, high staff
turnover; in some countries, parallel reporting systems
in same ministries
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III. National Strategy for the Development of
Statistics (NSDS)
Better Statistics
Require better planning of
National Statistical System
(NSS)
National Strategy for the Development of Statistics
(NSDS)
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What is the National Strategy for the Development of
Statistics (NSDS)?
National
strategy and
plan of
actions
Framework 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:
 integrate statistics within national
A catalyst
for change
& building
confidence




policy processes
address data limitations
introduce modern management
principles
prioritise the use of resources
manage change
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Importance of the NSDS process


process as important as the Strategy itself
process should provide opportunity for:
 statistical advocacy
 mainstreaming statistics in national
development policies
 mainstreaming key stakeholders in process
(political leadership, decision-makers & development
partners)
“People support what they help to create”
 empowerment of personnel (international
standards, frameworks, other country experiences)
 broadening and deepening communication
(between policy/decision-makers & data producers,
among institutions & within institutions)

process should be participatory, inclusive & consensusbuilding
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New approach to NSDS design - Bottom-up approach
Successfully used in Uganda 2005/06
NSDS
SSP1
SSP2
SSP3
NSO
Sector Statistical Plans
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Mainstreaming sectoral statistics in the NSDS
Agriculture
etc
Health
NSO
Transport
Labour
Education
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Steps in the design of the NSDS
2. WHERE DO WE
WANT TO BE?
1. WHERE ARE WE
NOW?
Current situation
Mission/vision
Statistical
capacity
4. HOW DO WE
STAY THERE?
Sustainability
3. HOW DO WE
GET THERE?
Strategies/Actions
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IV. Conclusions



Better statistics needed to monitor progress
There are many data challenges in developing
countries
Need to design & implement NSDS to address
challenges

Process of designing NSDS important

Issues in the design process includes:

familiarization with policy processes

statistical advocacy

mainstreaming sectoral statistics

methodology
 Assessing current situation
 Visioning and strategizing
 Action planning
 Monitoring and evaluation
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Thank You
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