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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

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