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 OECD World Forum, Istanbul, 29 June 2007

2  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 SCOPE I.Monitoring Progress

3 “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 decision- making in pursuit of development outcomes

4  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? II. Main data challenges for monitoring progress

5 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 Domestic under-funding Conflicting donor agendas Domestic under-funding Conflicting donor agendas Lower demand Fewer resources Lower demand Fewer resources Limited: institutional development infrastructural development under-performance i.e. limited outputs & services (quality and quantity) Limited: institutional development infrastructural development under-performance i.e. limited outputs & services (quality and quantity)

6  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.

7  Data disaggregation (needed to target interventions and resources; need for population, sex, sector- specific & 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

8 Better Statistics Require better planning of National Statistical System (NSS) National Strategy for the Development of Statistics (NSDS) III. National Strategy for the Development of Statistics (NSDS)

9 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 integrate statistics within national policy processes policy processes address data limitations address data limitations introduce modern management introduce modern management principles principles prioritise the use of resources prioritise the use of resources manage change manage change National strategy and plan of actions A catalyst for change & building confidence What is the National Strategy for the Development of Statistics (NSDS)?

10 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 & consensus- building

11 New approach to NSDS design - Bottom-up approach Successfully used in Uganda 2005/06 NSDS SSP 1 SSP 2 NSO Sector Statistical Plans SSP 3

12 Labour Education Transport etc Agriculture Health NSO Mainstreaming sectoral statistics in the NSDS

13 1.WHERE ARE WE NOW? Current situation 1.WHERE ARE WE NOW? Current situation 2. WHERE DO WE WANT TO BE? Mission/vision 2. WHERE DO WE WANT TO BE? Mission/vision 3. HOW DO WE GET THERE? Strategies/Actions 3. HOW DO WE GET THERE? Strategies/Actions 4. HOW DO WE IMPROVE AND MAINTAIN Sustainability 4. HOW DO WE IMPROVE AND MAINTAIN Sustainability Statistical capacity Steps in the design of the NSDS

14  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 IV. Conclusions

15 Thank You