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AFRICAN UNION UNION AFRICAINE
UNIÃO AFRICANA
Meeting of Regional Economic Communities on the
Pan-African Statistics (PAS) programme :
Addis Ababa, 12-13 November 2015
Vision of AUC on management of
quality Statistics
African Union Commission - Email: crepinn@africa-union.org / gnzingoula@yahoo.fr - Tel: +251 11 5 18 26 70 - www.au.int
Mr. NZINGOULA Gildas Crépin
Economist Statistician Engineer
Presented by :
Vision of AUC on management of
quality Statistics

Outline of presentation
I. Quality management in statistics
II. African Charter on Statistics and SHaSA
III. Peer reviews
IV. Quality assurance Framework
V. Organisational Structure
Introduction
II. African Charter on Statistics and SHaSA
III. Peer reviews
IV. Quality assurance Framework
Next steps

Introduction
Meaning of statistical quality :
For ISO 9000 : the extent or degree to which materials, products, processes and
services meet PRE-SPECIFIED standards (requirements, specifications, guidelines or
characteristics) defined to serve a pre-defined purpose
For official statistics statistical quality refers to four interrelated perspectives
 Organisational context - provides an enabling environment for the production
and use of official statistics
 Key concepts: statistics system; standards; coordination
 Characteristics of the statistical product – must be for intended use
 Key concepts: pre-defined quality criteria, components or dimensions;
quality assessment
 User perception of the statistical product – users are the principal reason
statistics are produced
 Key concepts: credibility; trust; legitimacy; reputation of producer;
comparability and coherence; timeliness
• Statistical production process – fundamental determinant of statistical quality
 Key concepts: process design; statistical value chain (or GSBPM); resources
(inclusive of time); response rates; error rates; etc.
For official statistics statistical quality refers to four interrelated perspectives
 Organisational context - provides an enabling environment for the production
and use of official statistics
 Key concepts: statistics system; standards; coordination
 Characteristics of the statistical product – must be for intended use
 Key concepts: pre-defined quality criteria, components or dimensions;
quality assessment
 User perception of the statistical product – users are the principal reason
statistics are produced
 Key concepts: credibility; trust; legitimacy; reputation of producer;
comparability and coherence; timeliness
• Statistical production process – fundamental determinant of statistical quality
 Key concepts: process design; statistical value chain (or GSBPM); resources
(inclusive of time); response rates; error rates; etc.

Why Data Quality matters
“Data quality played a significant role in the mispricing and business
intelligence errors that caused the crisis” (Casualty Actuarial Society E-
forum, Spring 2010)
“Without strong data, policymakers cannot manage effectively and
business leaders may be left in the dark, unable to spot emerging trends
and danger signals” (IMF’s F&D, Vol. 46, No. 1, March 2009)
– “… economic policymaking is hindered by low frequency and long
publication lags associated with key … finance and spending data”
(Alan Krueger, US Treasury Dept, Feb. 2010)
– Poor Numbers: How We Are Misled by African Development
Statistics and What to Do about It ?
Morten Jerven
Introduction (cont’d)
“Data quality played a significant role in the mispricing and business
intelligence errors that caused the crisis” (Casualty Actuarial Society E-
forum, Spring 2010)
“Without strong data, policymakers cannot manage effectively and
business leaders may be left in the dark, unable to spot emerging trends
and danger signals” (IMF’s F&D, Vol. 46, No. 1, March 2009)
– “… economic policymaking is hindered by low frequency and long
publication lags associated with key … finance and spending data”
(Alan Krueger, US Treasury Dept, Feb. 2010)
– Poor Numbers: How We Are Misled by African Development
Statistics and What to Do about It ?
Morten Jerven

To manage quality of data or statistics produced by National
Statistical Offices, Regional Economic Communities, Pan-African and
other national and international institutions various methodes, tools,
reference documents or procedures may be used by producers to
improve or to ensure quality of statistical information. Among these
methodes, procedures or tools we have, namely:
African Charter on Statistics;
Strategy for the Harmonization of Statistics in Africa (SHASA);
Peer review;
National Strategy for the Development of Statistics (NSDS);
Organisational Structure;
Quality Assurance Framework; and
Certification or Visa on quality statistics.
To manage quality of data or statistics produced by National
Statistical Offices, Regional Economic Communities, Pan-African and
other national and international institutions various methodes, tools,
reference documents or procedures may be used by producers to
improve or to ensure quality of statistical information. Among these
methodes, procedures or tools we have, namely:
African Charter on Statistics;
Strategy for the Harmonization of Statistics in Africa (SHASA);
Peer review;
National Strategy for the Development of Statistics (NSDS);
Organisational Structure;
Quality Assurance Framework; and
Certification or Visa on quality statistics.

II. African Charter on Statistics as a quality tool
The African Charter on Statistics was
prepared following a participatory process
in which all members of the African
statistical system, African political
authorities and development partners took
part. The African Charter on Statistics was
adopted by the Heads of State and
Government of the African Union on 4
February 2009 in Addis Ababa.
the African Charter on Statistics came into
force on 8 February 2015, thirty (30) days
after the deposit of the instruments of
ratification by the fifteen (15) Member
States.
I-1. African Charter on Statistics
The African Charter on Statistics was
prepared following a participatory process
in which all members of the African
statistical system, African political
authorities and development partners took
part. The African Charter on Statistics was
adopted by the Heads of State and
Government of the African Union on 4
February 2009 in Addis Ababa.
the African Charter on Statistics came into
force on 8 February 2015, thirty (30) days
after the deposit of the instruments of
ratification by the fifteen (15) Member
States.
.

II. African Charter on Statistics (cont’d)
I-2. Status of the signing and ratification
Number of
countries
Situation as regards the African Charter on
Statistics
15
Countries that have already signed,
ratified and deposited the instruments of
ratification of the Charter with the
African Union Commission
2
Countries that have signed and whose
Parliaments have adopted the African
Charter on Statistics and they have not
yet deposited the instruments of
ratification
2
Countries that have signed and whose
Parliaments have adopted the African
Charter on Statistics and they have not
yet deposited the instruments of
ratification
16
Countries that have only signed the
African Charter on Statistics
21 Countries that have not yet signed
54 Member States of the African Union
Source: AUC

I-2. Status of the signing and ratification
Source: AUC

I-3. Principles of the Charter
 African Charter on Statistics has 6 principles which
constitute quality dimensions:
1. Professional independence
2. Quality
3. Mandate for data collection and resources
4. Dissemination
5. Protection of individual data, information
sources and respondents
6. Coordination and Cooperation
 African Charter on Statistics has 6 principles which
constitute quality dimensions:
1. Professional independence
2. Quality
3. Mandate for data collection and resources
4. Dissemination
5. Protection of individual data, information
sources and respondents
6. Coordination and Cooperation
LEVEL ITEM QUANTITY
1 Principles 6
2 Subprinciples 29
3 Elements 133
4 Indicators 181

I-3. Principles of the Charter
LEVEL 1: Principles LEVEL 2:
Subprinciples
LEVEL 3: Elements
LEVEL 4:
Indicators
1. Professional independence 4 8 5
2. Quality 11 54 78
3. Mandate 3 17 18
4. Accessibility 5 24 37
5. Protection of individual data,
information sources and respondents
4 11 16
5. Protection of individual data,
information sources and respondents
6. Coordination and cooperation 2 19 27
TOTAL 6 29 133 181
 SHaSA legitimises as Strategic Theme 1: to produce
quality statistics for Africa
Source: AUC

III. Peer Reviews
The focus of the peer reviews is on
governance of the national statistical
system (NSS), its organisation,
strategic planning, service to users,
funding, and sustainability. Peer review
teams typically include both senior
statisticians (normally the head or
deputy head of the NSS) and senior
policy makers from two other countries.
n° Countries Year
1 Mauritania 2014
2 Benin 2010
3 Burkina Faso 2009
4 Malawi 2009
5 Mozambique 2009
6 Niger 2009
The focus of the peer reviews is on
governance of the national statistical
system (NSS), its organisation,
strategic planning, service to users,
funding, and sustainability. Peer review
teams typically include both senior
statisticians (normally the head or
deputy head of the NSS) and senior
policy makers from two other countries.
6 Niger 2009
7 Congo 2010
8 Ghana 2007
9 Tanzania 2007
10 Zambia 2007
11 Senegal 2011
12 Kenya 2015
13 Egypt 2015
Status of Peer Reviews conducted
so far on the continent Africa
Source: Paris21

III. Peer Reviews (cont’d)
The African peer review process of NSSs was launched by the
Economic Commission for Africa's Committee on Development
Information (CODI) meeting in 2003. CODI recommended that African
countries, supported by PARIS21, carry out peer reviews to ensure that
good practice passes from country to country, based on the first hand
experience of peers, to help accelerate the change processes in
reforming statistical systems.
In 2010, it was decided during CoDGs meeting held in Yaounde,
Cameroon, that the African Union Commission should take over of the
Peer review exercise. Unfortunately, due to lack of funding, the Peer
reviews exercises are still being conducted by Paris21.
The African peer review process of NSSs was launched by the
Economic Commission for Africa's Committee on Development
Information (CODI) meeting in 2003. CODI recommended that African
countries, supported by PARIS21, carry out peer reviews to ensure that
good practice passes from country to country, based on the first hand
experience of peers, to help accelerate the change processes in
reforming statistical systems.
In 2010, it was decided during CoDGs meeting held in Yaounde,
Cameroon, that the African Union Commission should take over of the
Peer review exercise. Unfortunately, due to lack of funding, the Peer
reviews exercises are still being conducted by Paris21.
Better quality
statistics
Better policies and
decision making
BETTER
DEVELOPMENT

 ASS-QAF will define standards and identify indicators against which African
statistics are to be assessed for quality
 The QAF is being developed within the framework of the African Charter on
Statistics (ACS). QAF will act as an implementation arm of the ACS
 It is founded on the UN’s Fundamental Principles of Official Statistics, and
 It has reference to current international frameworks, e.g., among others
• IMF’s Data Quality Assessment Framework (DQAF)
• UN’s Guidelines for the Template for a Generic National Quality
Assurance Framework (NQAF)
• Quality Assurance Framework of the European Statistical System
• Statistics Canada’s Quality Assurance Framework
• Statistics Finland’s Quality Guidelines for Official Statistics
• Statistics South Africa’s South African Statistics Quality Assessment
Framework (SASQAF)
IV. Quality Assurance Framework
 ASS-QAF will define standards and identify indicators against which African
statistics are to be assessed for quality
 The QAF is being developed within the framework of the African Charter on
Statistics (ACS). QAF will act as an implementation arm of the ACS
 It is founded on the UN’s Fundamental Principles of Official Statistics, and
 It has reference to current international frameworks, e.g., among others
• IMF’s Data Quality Assessment Framework (DQAF)
• UN’s Guidelines for the Template for a Generic National Quality
Assurance Framework (NQAF)
• Quality Assurance Framework of the European Statistical System
• Statistics Canada’s Quality Assurance Framework
• Statistics Finland’s Quality Guidelines for Official Statistics
• Statistics South Africa’s South African Statistics Quality Assessment
Framework (SASQAF)

NSO
BOARD
Standards
T. C
Audit
T.Cs
I.A.C
S.Q.A.C
T.C of UBOS
BOD
Statistical
Certification
Publicity and
Documentation
Organisational Structure to Manage the Quality of Statistics: at national level
Example: Case UBOS of Uganda
NSO
QAT , M&E
NGO
contact
SSC
SQAT
LG
contact
SSC
SQAT
Agency
contact
SSC
SQAT
NSO
SSC
SQAT
Researchers
SSC
SQAT
S.Q.A.C
T.C of UBOS
BOD
Review
(after 3yrs)

V. Organisational Structure (Cont’d)
AUC’s Statistics Division AfDB, ECA, UN agencies, other partners
Organisational Structure to Manage the Quality of Statistics: at regional and
continental levels
RECs, NSO’s partners
National Statistical Offices
Ministries National agencies Central Bank Etc.

STATAFRIC
AfDB, ECA,
UN agencies,
other partners
RECs, AFRISTAT, NSO’s partners
National Statistical Offices
Ministries National agencies Central Bank Etc.
AfDB, ECA,
UN agencies,
other partners

Next steps
 Establish an African working group on the quality of statistics
produced by the countries. This group should include the AUC, ECA,
AfDB, AFRISTAT and some countries and resource persons, if possible
sub-regional organizations;
 Encourage a better dialogue between the producers and users of
statistics in order to identify possible gaps;
 Promote establishment of a structure, team, unit or division in charge
of quality within NSOs;
 Strengthen human resources capacity of the NSS by allocating staff to
quality matters and organise training on quality;
 Promote at national level a Statistical Quality Certification for data
produce by other Institutions; and
 Develop a National Quality Assurance Framework (guidelines and
best practices).
 Establish an African working group on the quality of statistics
produced by the countries. This group should include the AUC, ECA,
AfDB, AFRISTAT and some countries and resource persons, if possible
sub-regional organizations;
 Encourage a better dialogue between the producers and users of
statistics in order to identify possible gaps;
 Promote establishment of a structure, team, unit or division in charge
of quality within NSOs;
 Strengthen human resources capacity of the NSS by allocating staff to
quality matters and organise training on quality;
 Promote at national level a Statistical Quality Certification for data
produce by other Institutions; and
 Develop a National Quality Assurance Framework (guidelines and
best practices).

THANK YOU FOR YOUR
KIND ATTENTION
MERCI DE VOTRE ATTENTION !

WELCOME TO STATAFRIC ?
The new born
E-mail: austatdivision@africa-union.org / Website: www.austat.org

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