Workshop on Strategic Planning for Agricultural and · PDF fileWorkshop on Strategic Planning...
Transcript of Workshop on Strategic Planning for Agricultural and · PDF fileWorkshop on Strategic Planning...
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Workshop on Strategic Planning for
Agricultural and Rural Statistics
17-19 March 2015, Bangkok, Thailand
Strategic Planning for Improvement of
Agricultural and Rural Statistics: Issues,
Approaches and Best practices
By
Prof. Ben Kiregyera
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Scope
1.Challenges of statistical development
2.Strategic planning for statistics
3.National Strategy for the Development of
Statistics (NSDS)
3.Sectoral approach and best practice
4.Non-ideal situation: When there is already an
NSDS or no NSDS at all
5.Weaknesses of sectoral statistics – African
Experience
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1. Some statistical challenges
Institutional - environment in which statistics are
produced and used
low levels of numeracy
legislation (NSO versus sectors e.g. agriculture)
weak statistical coordination (within agriculture sector
and between agriculture and rest of the National
Statistical System and the NSDS – Pillar II of Global
Strategy) – Next slide
Pillar I - Minimum set of core data
Pillar III – Sustainability through governance
and capacity building
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Labour
Education
Transport
etc
Agriculture
Health
NSO
Partially coordinated National Statistical System
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Fully coordinated National Statistical System
Labour
Education
Transport
etc
Agriculture
Health
NSO
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Benefits of coordination
Mutual reinforcement
Achieve synergy (synergy is 2+2=5 effect)
Less duplication of effort & disruptive rivalries
More efficient use of resources
Cross-fertilization between sectors
More consistent data
Higher quality data
Greater availability of data
Wider use of data
More sophisticated analysis
More informed policies & decisions
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Organizational – relate to organizations – NSO,
Ministries
infrastructure – office, equipment, etc.
statistical capacity across statistical value chain – next
slide
systems and processes – surveys, censuses, etc.
resources (staffing, finances, policies, leadership and
governance)
Methodological challenges in agriculture –
[Scientific Advisory Committee]
• Improving administrative data
• Methods for estimating crop area, yield and production
(mixed crops, continuous cropping & harvesting)
• Cost of production
• Crop forecasting, etc.
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Statistical value chain
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Low demand
Inadequate resources
Poor output
Stronger demand
Increased resources
Better output
Stronger demand
•PRS, MDGs, results-based management Better resources •Budgets, skilled and motivated staff, financial and technical assistance
Better outputs •Improved data quantity, quality and dissemination
Statistical under-performance
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2. Strategic planning for statistics
Strategic planning is essential for statistical agencies and
systems whether or not they are doing well; ongoing in
both developing & developed countries.
Where they are weak and under-performing as is the
case in many developing countries, strategic planning will
help to reengineer them to perform better and to set long-
term objectives for improved performance and prioritised
use of limited resources among different activities –
business process reengineering (BPR)
Where they are doing well especially in industrialised
countries, strategic planning needed to achieve improved
performance in specific areas such as quality
enhancement, innovation, and enhanced IT applications.
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Better Statistics
Require better
planning of the
National Statistical
System
1st Generation
Statistical Plans • NSO-Centric
• Inadequate
attention to
Process
2nd Generation
Statistical Plans - NSDS •Covers whole NSS
(including sectors)
•Great attention to
Process
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• Framework to strengthen statistical capacity
across the entire National Statistical System
• A robust, comprehensive and coherent
framework to:
• address statistical devlp. challenges
• integrate statistics within national
policy and decision-making processes
• mobilize resources & prioritize their
use
• introduce & manage change
National
strategy and
action plan
A catalyst
for change &
building
confidence
through
ownership
3. National Strategy for the
Development of Statistics (NSDS)
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4. Sectoral approach and best
practice
Process is as important as the strategy
Process should:
• enhance statistical advocacy
• broaden and deepen statistical reforms
• participatory & inclusive (management, staff &
external stakeholders)
•empower data users and producers (build capacity)
• use best practices & draw on experiences of other
countries (peer learning & benchmarking)
• enhance coordination by building a truly integrated
National Statistical System – see next slide
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Labour
Education
Transport
etc
Agriculture
Health
NSO
Partially coordinated National Statistical System
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Fully coordinated National Statistical System
Labour
Education
Transport
etc
Agriculture
Health
NSO
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a lot of development data are collected/ compiled by sectors:
Agriculture Health Education Labour **********
sectoral issues and concerns usually not given sufficient attention in national statistics statisticians from line ministries largely isolated & inadequately involved in discussion on national statistical development issues sectoral component of NSS has tended to be under- resourced & is in need of more voice in sectors and in NSS
The Case for Integration of Sectors into the
NSDS
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How to mainstream sectors into the NSDS
Guidelines by AfDB, PARIS21 and Intersect, “Mainstreaming
sectoral statistical system: a guide to planning a coordinated
national statistical system” (2007) – best practice
& my book on “Emerging data revolution in Africa” (see next
slide)
For selected sectors:
1. Undertake statistical advocacy especially at high level
2. Undertake assessment of the state of statistics in the
sector (use different frameworks/guides) (next slide)
3. Write/discuss Assessment Report following common
template
4. Design Sector Statistics Plans following common template
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Using Health Matrix Network Framework
Components Scope
Resources
Policies; Financial resources; Human
resources; Communication; Coordination
and Leadership
Indicators Minimum set of indicators & targets
Data sources Types of data sources and standards
Data
management
Data definition; flow; quality; storage;
linkage
Information
products Users requirements; analysis; presentation
Dissemination
and use
Infrastructure; synthesis; packaging;
communication
Assessment of state of sectoral data
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Bottom-up (sectoral) approach to NSDS
NSDS
SPS
(Health)
SPS
(NSO)
SPS
(Edn. )
SPS
(Agric)
SPS - Sector Plan for Statistics
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Component Opportunities to coordinate
Agriculture Education Labour Health Etc.
Resources
Harmonize policies and budgets
Coordinate training/allocation of human resources
Build communities of practice
Rationalize the use of information technology
Indicators Identify and standardize common indicators
Data sources Synchronize surveys and routine data collection
Data
management
Link data dictionaries and warehouses
Build consistent data quality
Coordinate data transmission
Information
products
Analyze and present data across sectors
Synchronize reports for the same users
Dissemination
and use
Advocate with one voice
Coordinate evaluation across sectors
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In some countries, there is already an NSDS BUT
was designed not using the sectoral approach
or
There is no NSDS BUT we have to design a
Strategic Plan for Agricultural and Rural
Statistics (SPARS)
Follow Guidelines for Designing SPARS by FAO
(to be presented in workshop). In Africa, SPARS
Guide launched in November 2014, Mozambique
5. Non-ideal situation: When there is already an NSDS or No NSDS
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Africa’s Action Plan for Implementing the
Global Strategy – 1st region to design plan Assessment of statistical capacity and needs (two stage
process))
First stage assessment covering all countries – self
assessment:
2013 collected data from 52 countries to establish
baselines on countries’ capacities and needs -
questionnaire
Data used to compile Agricultural Statistics Capacity
Indicator (ASCI) for each country & build country profiles
ASCI has four dimensions: Institutional infrastructure (Pre-
requisites dimension), Resources (Input dimension),
Statistical Methods and Practices (Throughput dimension),
Availability of Statistical Information (Output dimension).
Categorization of countries by capacity and needs
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Africa’s Action Plan for Implementing the
Global Strategy (ctd)
In-depth assessment for selected countries (on demand):
Why in-depth assessment?
Information from 1st stage may not be most reliable
because of self-assessment (even after training)
Need detailed information for designing the SPARS
(Strategic Plan for Agricultural and Rural Statistics)
Need information to prepare funding proposals
Power of sectoral approach (SPARS) – Uganda
NSDS 2013 – Ministry of Agriculture has Senior Statistician &
2 Statisticians
- after – 18 Statisticians headed by Ass.
Commission (member of management)
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6. Weaknesses of sectoral
statistics– African experience
poor statistical governance and function in the Sectors,
questionable administrative data sources and poorly defined
indicators,
lack of a statistical law and supporting regulation, and
guidelines governing statistical operations in sectors.
low profile of statistics and unpredictable funding in the
sector ministries.
limited capacity and statistical infrastructure, gaps in data
coverage and quality,
alienation of statisticians in line ministries
absence of systematic monitoring and evaluation
frameworks for statistics across the NSS.
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Thank You