Powerpoint quality statistics_nzingoula

AFRICAN UNION UNION AFRICAINE

UNIÃO AFRICANA

Meeting of Regional Economic Communities on thePan-African Statistics (PAS) programme :

Addis Ababa, 12-13 November 2015

Vision of AUC on management ofquality Statistics

African Union Commission - Email: [email protected] / [email protected] - Tel: +251 11 5 18 26 70 - www.au.int

Mr. NZINGOULA Gildas CrépinEconomist Statistician Engineer

Presented by :

Vision of AUC on management ofquality 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

IntroductionMeaning of statistical quality :For ISO 9000 : the extent or degree to which materials, products, processes andservices meet PRE-SPECIFIED standards (requirements, specifications, guidelines orcharacteristics) 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 businessintelligence errors that caused the crisis” (Casualty Actuarial Society E-forum, Spring 2010)“Without strong data, policymakers cannot manage effectively andbusiness leaders may be left in the dark, unable to spot emerging trendsand danger signals” (IMF’s F&D, Vol. 46, No. 1, March 2009)– “… economic policymaking is hindered by low frequency and longpublication lags associated with key … finance and spending data”(Alan Krueger, US Treasury Dept, Feb. 2010)– Poor Numbers: How We Are Misled by African DevelopmentStatistics and What to Do about It ?Morten Jerven

Introduction (cont’d)


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

To manage quality of data or statistics produced by NationalStatistical Offices, Regional Economic Communities, Pan-African andother national and international institutions various methodes, tools,reference documents or procedures may be used by producers toimprove or to ensure quality of statistical information. Among thesemethodes, 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; andCertification or Visa on quality statistics.



To manage quality of data or statistics produced by NationalStatistical Offices, Regional Economic Communities, Pan-African andother national and international institutions various methodes, tools,reference documents or procedures may be used by producers toimprove or to ensure quality of statistical information. Among thesemethodes, 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; andCertification or Visa on quality statistics.

II. African Charter on Statistics as a quality tool

The African Charter on Statistics wasprepared following a participatory processin which all members of the Africanstatistical system, African politicalauthorities and development partners tookpart. The African Charter on Statistics wasadopted by the Heads of State andGovernment of the African Union on 4February 2009 in Addis Ababa.

the African Charter on Statistics came intoforce on 8 February 2015, thirty (30) daysafter the deposit of the instruments ofratification by the fifteen (15) MemberStates.

I-1. African Charter on Statistics


The African Charter on Statistics wasprepared following a participatory processin which all members of the Africanstatistical system, African politicalauthorities and development partners tookpart. The African Charter on Statistics wasadopted by the Heads of State andGovernment of the African Union on 4February 2009 in Addis Ababa.

the African Charter on Statistics came intoforce on 8 February 2015, thirty (30) daysafter the deposit of the instruments ofratification by the fifteen (15) MemberStates.

.

II. African Charter on Statistics (cont’d)

I-2. Status of the signing and ratificationNumber ofcountries

Situation as regards the African Charter onStatistics

15

Countries that have already signed,ratified and deposited the instruments ofratification of the Charter with theAfrican Union Commission

2

Countries that have signed and whoseParliaments have adopted the AfricanCharter on Statistics and they have notyet deposited the instruments ofratification


2

Countries that have signed and whoseParliaments have adopted the AfricanCharter on Statistics and they have notyet deposited the instruments ofratification

16Countries that have only signed theAfrican 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 independence2. Quality3. Mandate for data collection and resources4. Dissemination5. Protection of individual data, information

sources and respondents6. Coordination and Cooperation


African Charter on Statistics has 6 principles whichconstitute quality dimensions:

1. Professional independence2. Quality3. Mandate for data collection and resources4. Dissemination5. Protection of individual data, information

sources and respondents6. Coordination and Cooperation

LEVEL ITEM QUANTITY1 Principles 62 Subprinciples 293 Elements 1334 Indicators 181

II. African Charter on Statistics (cont’d)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 producequality statistics for Africa

Source: AUC

III. Peer Reviews

The focus of the peer reviews is ongovernance of the national statisticalsystem (NSS), its organisation,strategic planning, service to users,funding, and sustainability. Peer reviewteams typically include both seniorstatisticians (normally the head ordeputy head of the NSS) and seniorpolicy makers from two other countries.

n° Countries Year1 Mauritania 20142 Benin 20103 Burkina Faso 20094 Malawi 20095 Mozambique 20096 Niger 2009


The focus of the peer reviews is ongovernance of the national statisticalsystem (NSS), its organisation,strategic planning, service to users,funding, and sustainability. Peer reviewteams typically include both seniorstatisticians (normally the head ordeputy head of the NSS) and seniorpolicy makers from two other countries.

6 Niger 20097 Congo 20108 Ghana 20079 Tanzania 200710 Zambia 200711 Senegal 201112 Kenya 201513 Egypt 2015

Status of Peer Reviews conductedso far on the continent Africa

Source: Paris21

III. Peer Reviews (cont’d)The African peer review process of NSSs was launched by theEconomic Commission for Africa's Committee on DevelopmentInformation (CODI) meeting in 2003. CODI recommended that Africancountries, supported by PARIS21, carry out peer reviews to ensure thatgood practice passes from country to country, based on the first handexperience of peers, to help accelerate the change processes inreforming statistical systems.

In 2010, it was decided during CoDGs meeting held in Yaounde,Cameroon, that the African Union Commission should take over of thePeer review exercise. Unfortunately, due to lack of funding, the Peerreviews exercises are still being conducted by Paris21.


The African peer review process of NSSs was launched by theEconomic Commission for Africa's Committee on DevelopmentInformation (CODI) meeting in 2003. CODI recommended that Africancountries, supported by PARIS21, carry out peer reviews to ensure thatgood practice passes from country to country, based on the first handexperience of peers, to help accelerate the change processes inreforming statistical systems.

In 2010, it was decided during CoDGs meeting held in Yaounde,Cameroon, that the African Union Commission should take over of thePeer review exercise. Unfortunately, due to lack of funding, the Peerreviews exercises are still being conducted by Paris21.

Better qualitystatistics

Better policies anddecision making

BETTERDEVELOPMENT

ASS-QAF will define standards and identify indicators against which Africanstatistics are to be assessed for quality

The QAF is being developed within the framework of the African Charter onStatistics (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 Africanstatistics are to be assessed for quality

The QAF is being developed within the framework of the African Charter onStatistics (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)


NSOBOARD

StandardsT. C

AuditT.Cs

I.A.CS.Q.A.C

T.C of UBOSBOD

StatisticalCertification

Publicity andDocumentation

Organisational Structure to Manage the Quality of Statistics: at national levelExample: Case UBOS of Uganda


NSOQAT , M&E

NGOcontact

SSCSQAT

LGcontact

SSCSQAT

Agencycontact

SSCSQAT

NSOSSC

SQAT

ResearchersSSC

SQAT

S.Q.A.CT.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 andcontinental levels


RECs, NSO’s partnersNational Statistical Offices

Ministries National agencies Central Bank Etc.

STATAFRIC

AfDB, ECA,UN agencies,other partners



RECs, AFRISTAT, NSO’s partnersNational 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 possiblesub-regional organizations;

Encourage a better dialogue between the producers and users ofstatistics in order to identify possible gaps;

Promote establishment of a structure, team, unit or division in chargeof quality within NSOs;

Strengthen human resources capacity of the NSS by allocating staff toquality matters and organise training on quality;

Promote at national level a Statistical Quality Certification for dataproduce by other Institutions; and

Develop a National Quality Assurance Framework (guidelines andbest practices).


Establish an African working group on the quality of statisticsproduced by the countries. This group should include the AUC, ECA,AfDB, AFRISTAT and some countries and resource persons, if possiblesub-regional organizations;

Encourage a better dialogue between the producers and users ofstatistics in order to identify possible gaps;

Promote establishment of a structure, team, unit or division in chargeof quality within NSOs;

Strengthen human resources capacity of the NSS by allocating staff toquality matters and organise training on quality;

Promote at national level a Statistical Quality Certification for dataproduce by other Institutions; and

Develop a National Quality Assurance Framework (guidelines andbest practices).

THANK YOU FOR YOURKIND ATTENTION


MERCI DE VOTRE ATTENTION !

WELCOME TO STATAFRIC ?

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African Union Commission - Email: [email protected] / [email protected] - Tel: +251 11 5 18 26 70 - www.au.intE-mail: [email protected] / Website: www.austat.org

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