ASSESSMENT OF CURRENT STATUS OF NATIONAL STATISTICAL SYSTEM

1. ASSESSMENT OF CURRENT STATUS OF NATIONAL STATISTICAL SYSTEM Prof. Ben Kiregyera NSDS Workshop, Addis Ababa, Ethiopia 10 August 2005

2. What is strategic planning about? 2. WHERE DO WE WANT TO BE? Mission/vision • WHERE ARE WE NOW? • Current situation Statistical capacity 4. HOW DO WE KNOW WE HAVE ARRIVED & HOW DO WE STAY THERE? Monitoring/evaluation/ Sustainability 3. HOW DO WE GET THERE? Strategies/Actions

3. ASSESSMENT OF CURRENT STATUS OF NATIONAL STATISTICAL SYSTEMS DIAGNOSIS

4. I. WHAT IS A NATIONAL STATISTICAL SYSTEM (NSS)? Arrangements for production , n management a d statistics u s e of NSS

5. II. WHY ASSESS THE NSS? • a strong strategy is based on assessment of current situation (context map) • in most cases not developing NSDS from scratch • most countries, will exist NSS • existing initiatives for improving national statistics (e.g. GDDS) • been various assessments of NSSs using DQAF, etc. Purpose of NSDS will be to build on & extend (leverage from) existing approaches & initiatives to improve existing NSS

6. III. BENCHMARK ASSESSMENT OF NSS • 1st step in development of NSDS • Assessment should : • be in-depth and not cursory; realistic, objective, detached and critical • be benchmarked against international standards, frameworks &best practices • lead to understanding of: • adequacy of outputs & services • organization, management & infrastructure of NSS

7. Characteristics of an effective NSS • UN Fundamental Principles of Official Statistics • NSS should comply with these for public to have trust in official statistics • 10 Principles • professional independence • relevance • credibility • respondent relations • Legal framework • fundamental pre-requisite for effective NSS • comprehensive checklist (UN, World Bank, IMF, • others)

8. Shared direction • strategic goals and objectives • Stakeholder-driven and user-focused • national data needs • sub-regional data needs (SADC, ECOWAS, COMESA) • International data needs e.g. for MDG monitoring • Versatile (able to quickly respond to changing demand for • data) • Effectively led and coordinated • well-resourced & well-structured NSO with technical • expertise, organizational systems and capacity to lead • and coordinate NSS

9. Assessment of NSS should lead to understanding of: • user requirements for statistical data • users’ current and perceived future needs • adequacy of existing statistics • gaps in existing and planned data • priorities for data • capacity to use data • availability of statistics • sources • availability and access - publication and dissemination policies • linkages and coordination arrangements – user-producer, producer-producer, producer-researcher/analyst, etc.

10. Coordination and collaboration • Why coordinate, collaborate and network? • mutual reinforcement • achieve synergy • avoid working at cross-purpose and destructive rivalries • avoid production of conflicting data • Types of coordination • inter-institutional or horizontal coordination (break the “silo mentality”) • technical coordination (standardization of concepts, definitions, classifications, etc) • donor coordination Generally Weak

11. ON-GOING DATA USER-PRODUCER DIALOGUE USERS PRODUCERS • available data • how data are • collected • data quality • constraints • future plans • required data • when required • how required • - frequency • - timing • - form

12. legal and institutional framework in which data are produced • organizational aspects including • management of NSS • human resource policies • strengths, weaknesses, opportunities and threats • quality of statistics in terms of: • Integrity • independence of statistical operations (provided in Act) • professional and ethical standards (confidentiality, scientific • objectivity, professional competencies) • transparency about statistical processes DQAF

13. Methodological soundness: sub-regional, regional and international standards - broad standards followed e.g. Fundamental Principles of Official Statistics, GDDS, International Standard Industrial Classification - subject-specific standards and methodologies followed e.g. System of National Accounts, FAO guidelines, ILO guidelines, UNESCO guidelines, etc. Accuracy and reliability - incompleteness data/many data gaps - validation of administrative data - response rates - spatial coherence in reporting - sampling error rates

14. Serviceability: user consultation, periodicity of statistical outputs,timeliness of statistical outputs • User consultations • - regular and continuing or insufficient, ad hoc, far • between? - are user needs sufficiently analyzed, collated and prioritized? - are there serious data gaps? • periodicity of outputs - monthly, quarterly, annually - Income and Expenditure Survey (3-5 years)

15. Accessibility: effectiveness of dissemination, updated metadata • dissemination and access • statistics haveextrinsic valuewhich lies in their power to inform processes e.g. planning, monitoring • therefore,statistics have no value unless they: • reach those who need them • are easily understood • are actually used • well-defined and forward-looking dissemination policy based on GDDS principles: • advance publication of release calendar • simultaneous release of data– principle of equal access to data • providing metadata- information about the data • specific statistical products to well-targeted users • use different dissemination media (reports, electronic e.g. CDs, web site) – e-dissemination • Help-Desk (CBS)

16. Timeliness of statistical outputs in Namibia

17. Main sources of data • Administrative records (line Ministries) • Are there Management Information Systems (MISs) • Are Statistical Bulletins produced and in time? • Are there databases • Constraints to data development • human capacity (understaffing, and/or limited technical skills, competences) • material resources • financial resources

18. Surveys (current data) • household-based surveys • Household Income & Expenditure Survey • (periodicity) • Annual Agricultural Survey • Labour Force Survey (periodicity) • Demographic and Health Survey (between • censuses) • are these surveys coordinated/integrated? • establishment-based surveys • frequency of establishment surveys • business registers • are these surveys coordinated/integrated? • other surveys • Consumer Price Survey • major constraint: data disaggregation, sampling errors

19. Censuses • main sources of benchmark data • held after 10 years • Population and Housing Census • Agricultural Census • Economic Census • Major constraints: cost, enormity of exercise • Assessments Qualitative assessments (poverty related issues) (focus group discussions) Supplement quantitative information Challenges: a) coordinate systems to produce complementary data/information b) combine quantitative and qualitative data (triangulation)

20. how data are produced • methods and procedures • use of regional & international standards • constraints and problems • how data are managed i.e. processed, analyzed and archived • IT policies & strategies • databases and data warehouses

21. Five Levels of IT-induced business transformation - High Business Scope Redefinition Business Network Redesign Re volutionary Degree of Business Transformation Business Process Redesign Levels Evolutionary Internal Integration Levels Localized Exploitation n Low Low High Degree of potential benefits Business transformation using IT

22. ICT Infrastructure • do most institutions have adequate computers (numbers, right power, how old are they, etc)? • are there Local Area Networks (LANs) in place in many institutions? • are ICT resources optimally utilized? • has ICT improved communication & information sharing? • status of Internet access & web sites • are there IT policies and standards in NSS? • is GIS capability developed? • are there databases? • levels of IT application

23. Data cycle Planning Stage 1 Stage 2 Implementation Dissemination Feedback Stage 3 Reporting Processing Analysis/Interpretation

24. Assessment of user needs Data Producers • End users: • Policy makers • Decision makers Packaging/Communication • Intermediate users: • Researchers • Subject-matter • Specialists Data Suppliers Detailed/ Policy-related analysis Information Data Processing & Primary Analysis data(raw materials from which inform. obtained) Add value to data Data versus Information

25. Knowledge Information Data Data, Information, Knowledge Informed decisions

26. Main issues in data analysis and reporting • data producers do basic analysis • (generally poorly, water-is-wet types of analysis) • detailed data analysis is usually not done • no customized/targeted, value-added statistical products and services (e.g. special reports on gender, nutrition, etc) • shortage of analytical skills at NSOs • reporting usually poorly done • lack of analytical skills • lack of soft skills (communication, etc) • inadequate partnerships with subject-matter specialists and analysts

27. how statistics are disseminated and used • dissemination policies • metadata • data use • current capacity of the NSS • Demand side • capacity to articulate requirements • capacity to effectively use data for policy and decision-making • Supply side • infrastructure (physical, statistical & ICT) • human and financial resources • dissemination policies and strategies

28. IV. METHODOLOGY • Do document review to appreciate: • government policy environment (PRS, etc) • sub-regional & international development agenda (MDGs, etc) • Review international standards and frameworks • Other country experiences • Interview key data users • Government ministries, politicians, • Public sector (e.g. Central Bank, parastatals) • Private sector (Chamber of Commerce and/or Industry), • Civil society (NGOs, news media) • Research & Training institutions (Research Centres, Universities) • Donors and international organizations

29. Information from key data users • What they do • How they use statistics in their operations • Availability of statistics and how they may have been constrained by lack of data • Their ability to effectively use data • Their assessment of existing data – criteria • Their relationship with main data producers & their role in contributing to the development of the NSS • Their current & future statistical needs & priorities • How they think their needs can best be met within the context of the NSDS

30. how do you identify key users and collect data from them? • starting point should be NSO mailing list • divide users into main user groups • select some manageable users from each group • visit users, organize small group discussions, etc. • having identified users and their needs, proceed to assess capacity to meet their needs using PARIS21 Statistical Capacity Building Indicators (SCBIs)

31. interview key data producers mainly in NSO, Central Bank • line ministries and the private sector to establish: • inventory of their capacities to meet user needs • what data they produce • how they produce data (legal and institutional framework, human resources, office infrastructure, equipment, communications and transport, methods and procedures, systems) • main constraints and problems they face • how they co-ordinate with data users and other data producers • how they process, analyse, store data and disseminate statistical information • existence of databases.

32. Interviews at NSO • management • professional staff • administrative staff • junior staff • Focus/small group discussions (NSO staff and • key stakeholders) to: • articulate an ideal profile for the NSO, • carry out SWOT analysis • determine resource requirements in terms of personnel, office infrastructure, equipment, communications and transport, and budgets • develop a prioritized and costed work and capacity building programme • identify technical assistance that may be required

33. END • INSTRUMENTS FOR COLLECTING INFORMATION • Examples

34. Thank You