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Workshop on New Approaches to Capacity Development11-12 December

Input for Operationalisation Subgroup:Mapping of current practices in capacity development

ContentsI. Introduction................................................................................................................................................2II. Overview of examples................................................................................................................................4III. Summary of examples and mapping.........................................................................................................4

1. Data Communication: Journalist-Statistician Dialogue........................................................................52. EU-Twinning Kosovo – Improving Statistics.........................................................................................63. EU-Twinning Armenia – Strengthening of the National Statistical System of Armenia – Phase II

74. Leadership Training..............................................................................................................................85. Accelerated Data Program...................................................................................................................96. Building a Strong Community of Innovative and Forward Looking Leaders in Official Statistics........107. Good statistical practices in INDEC....................................................................................................118. Management Information System for the monitoring of statistical operations (SIG-OPERATIVE)

129. Statistical operations: Producer Price Index - PPI and Wholesale Price Index – WPI.........................1310. Socialization Process of the National Statistical System.....................................................................1411. Process of Innovation, Learning and Knowledge Management.........................................................1512. System of Certification of the Quality of the Statistical Operations...................................................1613. Capacity building activities in Mongolia.............................................................................................1714. Institutional cooperation for strengthening the capacity for macroeconomic analysis and strategic fiscal policy in MoFEP..................................................................................................................1815. Institutional cooperation between Statistics Norway and the Central Bureau of Statistics of the Republic of Sudan......................................................................................................................................1916. Institutional cooperation between Statistics Norway and the National Statistical Committee of the Kyrgyz Republic (NSC)..........................................................................................................................2017. Mongolian practices of implementing global action plan for sustainable development data............2118. UIS’ Support in National Statistical Capacity Development................................................................2219. Mexico's cooperation with the Central American Integration System...............................................23Annex: Summary of successful and unsuccessful practices.......................................................................24

Workshop on New Approaches to Capacity Development – December 2017________________________________________________________________________________

I. Introduction

The Operationalisation Subgroup of the CD4.0 Task Team started working in May 2017, focusing on the implementation of capacity development programmes. Its main task is to identify practices that can be scaled up or replicated, and to reflect areas that need further adjustment for implementation, given the transformation of data ecosystems.

Since its inception, Task Team members have shared examples of capacity development implementation with the aim of stimulating a group discussion. This document provides an insight into a systematic approach for identifying good practices and areas of improvement in capacity development. The PARIS21 Secretariat has proposed a conceptual framework for Capacity Development 4.0, which aims to synthetize the elements that compose ‘statistical capacity’. For the purposes of the Workshop on ‘New Approaches to Capacity Development’, the Secretariat will provide a preliminary mapping of examples shared by the Task Team members. A summary of “lessons learned” from the documents shared by Task Team members is provided in the annex.

The current version of the framework builds on the discussions and inputs from Task Team members as well as an extensive literature review conducted by PARIS21 Secretariat. It was proposed that the framework used by Denney and Mallet (2017)1 provided the necessary basis for conceptualising the definition of ‘capacity’ for National Statistical Systems. This framework takes the form of a matrix with 3 levels, 5 targets, 15 categories and 51 dimensions (see Table 1). It is based on the gaps and overlooked aspects of Capacity Development identified by the Task Team. It also takes into account the new challenges within the new data ecosystem and the 2030 Agenda, and considers the capacity needs at individual, organisational, and enabling environment levels. This conceptual framework incorporates several discussions within the Task Team and is still open for improvement.

1 Denney, L. and Mallett, R. (2017) Service delivery and state capacity: findings from the Secure Livelihoods Research Consortium. London: Secure Livelihoods Research Consortium.


TTable 1: Capacity Development 4.0 matrix

Target/Level Individual Organisational System

Resources

Education Human Resources Laws, regulations and reference frameworks

Work experience Budget and funds Funds infrastructure

Infrastucture (physical assets, IT, etc.)

Plans (NSDS, sectoral…)Existing data

Institutional infrastructure

Skills & Knowledge

Technical skills Methods, practices and QC Data literacy

Work ‘Know-how’ Standards and regulations

Autonomy & problem solving Innovation

Creative thinking

Management

Talent management Strategic planning NSS co-ordinationTime management and

prioritisation Organisational design Data Ecosystem co-ordination

Leadership HR Management Advocacy strategy

Strategic thinking Transparency

Politics & Power

Teamwork & collaboration Change managementRelationship between producers

Relationship bet. producers and users

Communication & negotiation skills Workplace politicsInstitutional autonomy

AccountabilityStrategic networking Fundraising strategies Policy preferences

Incentives

Career expectations Career development Stakeholders' interests and strategiesIncome Compensation and benefits Public support/endorsement

Work ethic & self-motivation Organisational culture Legitimacy

Status Reputation/Visibility

This document will provide input to the breakout session for Day 1, with 2 main objectives in mind:

To identify success criteria for capacity development programmes To assess where the current provision of capacity development programmes stand in

satisfying those criteria.

The discussion will be guided by the following questions:

Where do we stand today in the implementation of capacity development? What criteria should success in capacity development be defined against? What characteristics do successful capacity development programs share?

II. Overview of examples

In total, 19 examples of Capacity Development implementation were shared in the Task Team platform.2 Some programmes and practices aimed to develop statistical capacity at the regional level, involving partnerships with statistical organisations and/or other stakeholders. It is possible to distinguish between programmes involving bilateral cooperation, multilateral cooperation and programmes that are created and implemented by the country.

The examples can be classified as follows:

• Formal programmes (e.g. Data Communication: PARIS21 Journalist-Statistician Dialogue) and projects (e.g. EU-Twinning Kosovo project)

• Workshops (e.g. PARIS21 Leadership Training)• Processes and systems (e.g. DANE Process of Innovation, Learning and Knowledge

Management)• National statistical capacity development (such as the examples shared by Mongolia and

Ecuador)

III. Summary of examples and mapping

This section provides a brief summary of the practices shared by Task Team members in the OECD Community Site dedicated to Capacity Development 4.0 and an initial attempt at mapping them to the Conceptual Framework. For a detailed description, please visit our community site.

2 Examples were provided from different task team members: 3 of those have been led by PARIS21 (one of them jointly with the World Bank); 2 by Statistics Denmark; 2 by DANE, 3 by Statistics Norway; 2 by the National Statistical Office of Mongolia (NSO); 1 by UNESCO Institute for Statistics; 1 by INEGI; 1 by INDEC; 1 by INEC; 1 by INE, 1 by National Statistics Institute; 1 by the International Statistical Institute.

https://community.oecd.org/community/capdev40/


1. Data Communication: Journalist-Statistician Dialogue

Lead Organisation: PARIS21.

Partners: AFRISTAT, GIZ, STATEC

Beneficiary countries/region: Benin, Burundi, Cameroon, Cote d’Ivoire, Mali, Sao Tome & Principe, Senegal

Audience: Journalists (Print and TV); Statisticians; NSO communication officers

Period of Implementation: Since 2015

Summary:

This training began in 2015 by selecting and instructing 12 participants from six countries to become trainers (including journalists, statisticians and NSO communication officers). It consists of three phases:

1. Distance learning using GC21 e-learning modules developed by GIZ

2. One week face-to-face training, including audio and video recording

3. In-country training, supervised by a senior or certified trainer

Capacity Development Dimensions:

1. Individual: Technical skills; Communication and negotiation skills

2. Organisation: Organisational design; Reputation/visibility

3. System: Data literacy; Relationship between producers and users; Legitimacy


2. EU-Twinning Kosovo – Improving Statistics

Lead Organisation: Statistics Denmark

Partners: Statistics Lithuania, Statistics Finland, Ni-Co Northern Ireland, Istat

Beneficiary country/region: Kosovo Agency of Statistics (KAS)

Period of Implementation: 2013-2016

Summary:

This EU twinning project “Support to Statistics” Kosovo, is a cooperation scheme that consisted of a partnership between the Kosovo Agency of Statistics (KAS) and Statistics Denmark to implement a twinning of their statistical institutions for 24 months. The overall objective of this project was to strengthen the statistical system of Kosovo, focusing on improving National Accounts and structural business statistics according to EU standards and modernising the KAS IT system and the internet dissemination of statistics. The two sub-goals of this twinning project were:

To strengthen the capacities of KAS and enable KAS to carry out its core activities in a standardized manner,

To improve the quality of annual National Accounts and start the compilation of quarterly accounts.

This project involved a wide audience, including statisticians, NSO communication officers, NSO management, ministries, students and users of statistics. The four project components (a quality system for statistics, national accounts, business statistics, IT and dissemination) were selected by KAS. A long term adviser from Statistics Denmark was sent to Kosovo for the length of the project and component leaders were appointed to ensure project success. There was continued communication between the long-term adviser and the project leaders in order to effectively tackle different aspects of capacity development.


1. Individual: Technical skills

2. Organisational: Infrastructure; Methods, practices and quality control; Standards and regulations; Organisational design

3. System: Data ecosystem co-ordination; Relationship between producers and users; Advocacy strategy


3. EU-Twinning Armenia – Strengthening of the National Statistical System of Armenia – Phase II

Lead Organisation: Statistics Denmark

Partners: NSOs of Finland, Italy and Lithuania

Beneficiary country/region: Armenia

Period of implementation: July 2015 - August 2017

Summary:

This project consisted of supporting the National Statistical Service of the Republic of Armenia through the implementation of an institutional twinning with the Danish Statistics Service for a period of 24 months. The beneficiary institution defined four components: dissemination, demographic statistics, labour market statistics, poverty statistics, innovation statistics and water accounts.

A long-term adviser was seconded to Armenia for the length of the project, who maintained continuous communication with the project leaders appointed by the twinned institutions. In addition, both institutions designated component leaders to ensure project progress. A wide audience was addressed in this project, including statisticians NSO communication officers, NSO management, ministries and users of statistics.

Each component included a number of short term-missions, in which specific tasks to be completed between missions by the beneficiary country were agreed upon. Each mission built on the accomplishments of the previous ones. There were also clearly defined benchmarks and end results, with enough flexibility to adjust to beneficiary needs for each quarter.



2. Organisational: Human resources; Methods, practices and quality control; Standards and regulations; Organisational culture

3. System: Data ecosystem co-ordination; Advocacy strategy; Accountability


4. Leadership Training

Lead Organisation: PARIS21

Partners: Centre for Creative Learning (CCL) + SIAP in Asia

Beneficiary country/region: Africa; Asia

Period of implementation: Since 2015

Summary:

The main aim of the programme is to improve and strengthen the leadership, management, governance and coordination capabilities of leaders of statistical offices. For this purpose, PARIS21 organised several regional workshops: the NSS Coordination Skills Training in Anglophone Africa3 in 2015, the Leadership Training in Francophone Africa4 and in Anglophone Africa5 in 2016 and the Asia Statistical Leadership Training for NSO DGs6 in 2017.

The workshops are a forum to discuss operational matters, to share experiences, to network and to elaborate on personal-development action plans. They seek to equip heads of statistics with the required skills to become successful leaders of a national statistical system. Some of the specific objectives include: to anticipate change by analysing and building capacities needed in the short term and engaging multiple players in the statistical system, strengthening leaders’ ability to develop and maintain a winning organisation culture and guiding them in strategic thinking and innovation.

Capacity development Dimensions:

1. Individual: Creative thinking; Communications and negotiation skills; Strategic networking

2. Organisational: Organisational design

3. System: NSS co-ordination

3 Eritrea; Djibouti; Ethiopia; Somalia; South Sudan; Sudan; Egypt; Kenya; Libya; Uganda.4 Benin, Burkina Faso, Cabo Verde, Cote d'Ivoire, Guinea, Guinea-Bissau, Mali, Mauritania, Niger, Senegal, Togo, Equatorial Guinea.5 Angola; Botswana; DR Congo; Lesotho; Malawi; Mauritius; Mozambique; Namibia; Seychelles; South Africa; Swaziland; Tanzania; Zambia; Zimbabwe.6 in Bhutan, Cambodia, Myanmar, Nepal, Thailand, Timor Leste, Sri Lanka, Kazakhstan, Tajikistan, Indonesia, Mongolia.


5. Accelerated Data Program

Lead Organisation: PARIS21 and the World Bank

Partners: Various, country-based

Beneficiary country/region: 60 countries, global

Period of implementation: 2007-2014

Summary:

This long-term programme consisted of providing tools and technical assistance for improving the preservation, documentation and access to/of microdata in NSOs and line ministries (including survey practitioners) in 60 countries. The programme focused on relevant issues for data producers and users, by engaging the latter to promote change together with the former. The programme was supported by strong and sustained financial commitment from the World Bank for seven years.

Capacity Development dimensions:


2. Organisational: Methods, practices and quality control; Standards and regulations

3. System: Laws, regulations and reference frameworks; Accountability


6. Building a Strong Community of Innovative and Forward Looking Leaders in Official Statistics

Lead Organisation: International Statistical Institute

Partners: World Bank, African Development Bank, Expertise – France, NSO Cameroon

Beneficiary country/region: Africa

Period of implementation: 06/04/2016 – 08/04/2016

Summary:

The workshop in Yaoundé (Cameroon) aimed to build a strong community of innovative and visionary leaders in official statistics, who would profit from the data revolution and respond to the demands of the Post-2015 Sustainable Development Agenda. It focused on building leadership and management skills of NSO heads and other senior managers and offered a suitable platform for exchanging best practices and innovative ideas between colleagues.

The workshop was an opportunity to discuss recent statistical developments, with the aim of improving the quality of NSS. Innovative strategies for improving the structure of NSO and NSS were also addressed. There were seven working groups that discussed practices and topics related to capacity development.


1. Individual: Technical skills; Leadership; Strategic thinking

2. Organisational: Change management

3. System: Laws, regulations and reference frameworks; Institutional infrastructure


7. Good statistical practices in INDEC

Lead Organisation: National Institute of Statistics and Censuses (INDEC)

Partners: Statistical Offices of other countries

Beneficiary country/region: Argentina

Period of implementation: Annual

Summary:

The ‘Good Statistical Practices’ (recommended by international organisations) are a set of actions to be implemented by public entities of the National Statistical System and users in general. The 17 Practices7 cover the institutional environment, the design of the statistical process and the statistical production. The current management of INDEC has decided to implement them with the objectives of:

• Collaborating with the technical, methodological and administrative standardisation of the organisation, since in previous years it had been discredited by national and international users

• Adapting the production and dissemination of INDEC’s statistics to the current national regulations and to international standards

• Clarifying how statistical indicators are produced, to make users aware of their main methodological characteristics and allow them to evaluate their quality

These practices tackle specific aspects of capacity development: an open dissemination policy (based on the notions of accessibility and clarity), an advanced publication schedule, press conferences to introduce new indicators or present the divergences with the data collected by the previous administration, meetings between qualified specialists and users and cooperation with international organisations, including the UN, ECLAC, OECD and IMF, in order to comply with the requirements of consistency and comparability.


1. Individual:

2. Organisational: Methods, practices and quality control; Standards and regulations; Transparency

3. System: Data ecosystem co-ordination

7 Those 17 good statistical practices are the following: Professional independence, Coordination of the National Statistical System; Legal mandate for data collection; statistical confidentiality; adequate resources; commitment to quality; impartiality and objectivity; International cooperation and participation; Solid methodology; adequate statistical processes; request for information not excessive; relationship between cost and effectiveness: resources must be used efficiently and effectively; relevance; accuracy and reliability; opportunity and punctuality; consistency and comparability; accessibility and clarity.


8. Management Information System for the monitoring of statistical operations (SIG-OPERATIVE)

Lead Organisation: Statistics National Institute


Beneficiary countries/region: Bolivia

Period of Implementation: Annual

Summary:

The Management Information System for the monitoring of statistical operations is addressed to public entities of the National Statistical System. It relays current information on the performance, quality and coverage of operations. The system evaluates statistical quality, through the following actions: (I) data quality control; (II) sending and correcting errors; (III) producing optimized reports. This system includes specific practices related to capacity development: reducing processing time and increasing the reliability of data, real-time online monitoring of synchronized data and of the geo-location of brigades and interviewers, producing reports on lapse of questionnaire completion and interviewer ranking and progress. The system allows capturing geo-positions even without signal or data access.


1. Individual:

2. Organisational: infrastructure; Methods, practices and quality control; Innovation.

3. System:


9. Statistical operations: Producer Price Index - PPI and Wholesale Price Index – WPI

Lead Organisation: Statistics National Institute (INE)

Beneficiary countries/region: Bolivia

Period of Implementation: Monthly

Summary

This programme consists of using mobile devices for the collection of data for the Producer Price Index and the Wholesale Price Index. It allows to register, monitor and geo-reference of the establishment using GPS. Interviewers are automatically assigned a list of communities, markets and establishments to visit that they can view on their device.

The computer technology uses different software (PostgreSql, PHP and Android). This system is highly scalable and contains the following modules: field personnel registration, assignment and workload module, consolidation surveyed data in the INE Central Database, coverage and performance and information dissemination.

The statistical operations include practices related to capacity development. In regards to the indicators, the keying stage is deleted, the processing time is reduced and the monitoring is done through the system, which allows verification and correction at the point of price capture. The system allows geo-locating price captures, ranking of interviewers and progress reports.


1. Individual:

2. Organisational: Infrastructure; Methods, practices and quality control; Innovation.

3. System:


10. Socialization Process of the National Statistical System

Lead Organisation: National Administrative Department of Statistics (DANE)


Beneficiary countries/region: Colombia


Summary:

The National Statistical System (NSS) Socialisation Process aims to share the instruments defined by DANE, the agency responsible for coordinating and regulating the NSS in compliance with Decree 1743 of 2016. It has been implemented to contribute to the strengthening of the quality of statistical processes, as well promoting a statistical culture in society. DANE responsibilities include advising NSS members on the implementation of guidelines and technical standards for the production and dissemination of official statistics and the use of administrative records for statistical purposed.

The socialisation process covers the following topics:

(I) Planning, e.g. the elaboration of a Statistical Plan; designing, building and interpreting indicators

(II) Quality, e.g. promotion of statistical quality

(III) Regulation, e.g. implementation of guidelines for methodological documentation, implementation of SDMX, DDI and Dublin Core standards.



2. Organisational: Methods, practices and quality control; Standards and regulations, HR management

3. System: Plans, NSS co-ordination


11. Process of Innovation, Learning and Knowledge Management

Lead Organisation: National Administrative Department of Statistics (DANE)


Beneficiary countries/region: Colombia

Period of Implementation: Annual, created in 2014

Summary:

This process aims to generate and promote a culture of innovation, learning and knowledge management, by enabling collaborators to be innovative, to unlearn, learn and share knowledge and profit from it, as part of their daily activity. It targets members of DANE, members of the National Statistical System and outsiders interested in the production and dissemination of statistics.

The main characteristics of the process are: 1) teamwork and articulation with other DANE processes; and 2) the interdependence between sub-processes of innovation, learning and knowledge management. The underlying concept is that knowledge management provides an opportunity to learn, which can generate innovations at the same time. Innovation projects can generate learning processes or the other way around.

In 2015 the Working Group was given official status in order to "promote an innovation culture, lifelong learning and knowledge management in DANE, contributing to the fulfilment of its mission, vision and superior purpose". The Group seeks to generate skills through the transformation of learning and knowledge management procedures.


1. Individual: Technical Skills; Teamwork and collaboration

2. Organisational: Innovation; HR management; Organisational culture

3. System: NSS co-ordination


12. System of Certification of the Quality of the Statistical Operations

Lead Organisation: National Institute of Statistics and Censuses (INEC)


Beneficiary countries/region: Ecuador


Summary:

The Certification System in Ecuador for NSS institutions aims to strengthen the quality of the process of statistical production for those used in the formulation, monitoring and evaluation of public policies. In addition, it seeks to increase the use of official statistics and foster a statistical culture in the society. The System performs all these actions in compliance with the technical regulations issued by the National Institute of Statistics and Censuses (INEC), based on the quality requirements of the Statistical Production Model and the Code of Good Statistical Practices.

The System evaluates statistical quality, considering the following aspects:

(I) Environment, including the regulatory framework and commitment to quality;

(II) Statistical production process, including the processes comprised in the Statistical Production Model of Ecuador and the required resources (human, financial, infrastructure and technological resources);

(III) Statistical production: includes analysing the consistency of statistics and of the database produced by the statistical process.


1. Individual: Technical Skills

2. Organisational: Methods, practices and quality control; Standards and regulations

3. System: NSS Co-ordination; Data Literacy


13. Capacity building activities in Mongolia

Lead Organisation: National Statistical office of Mongolia (NSO)

Partners:

Beneficiary countries/region: Mongolia

Period of Implementation: 2017

Summary:

The National Statistical Office of Mongolia is implementing several capacity building activities in order to strengthen its statistical capacity. It has sanctioned a new National Strategy for the Development of Statistics for the period 2017-2020. In addition, it has conducted a feasibility study on the integration of databases from ministries and other public organisations (around 40 databases at 25 Organisations). Several databases are being integrated as a result of this study.

To improve the coordination of work between the NSO and relevant authorities such as the Bank of Mongolia (BoM) and the Ministry of Finance, an Inter-agency Working Group on BoP, GFS and SNA and a Memorandum of Cooperation with the BoM have been set up.

In terms of technological upgrade, it has incorporated IT into data collection (using tablets or online questionnaires) and transfer of data. Other aspects such as training and dissemination (e.g. using mobile apps, distributing statistics through social media) have also been informatised. For improving statistical methodology, it has utilised administrative records as the frame for the 2015 Population and Housing By Census and for the 2016 Establishment Census.

Consultants have been hired for implementing the GBSPM under the World Bank “Smart Government” Project. Further organisational design changes have been implemented by setting up an “Inspection and monitoring division” and a “Public Relations division” (to develop the marketing of statistics and advocacy activities).

In order to support education of users of statistical information, regular and sequential training is targeted at target groups included governmental organisations, non-governmental organisations, enterprises, media organisations, high school and university students.

Under an ADB Technical Assistance Project, the NSO is aiming to compile new accounts such as material flow, energy, and environmental tax within the Framework SEEA, which would serve as data sources for SDGs.


1. Individual: Technical Skills,

2. Organisational: Infrastructure; Methods, practices and quality control; Standards and regulations; Organisational design,

3. System: Plans, NSS Co-ordination, Data Ecosystem Co-ordination


14. Institutional cooperation for strengthening the capacity for macroeconomic analysis and strategic fiscal policy in MoFEP

Lead Organisation: Statistics Norway

Partners: Ministry of Finance and Economic Planning (MoFEP)

Beneficiary countries/region: South Sudan

Period of Implementation: April 2012 – June 2017

Summary:

This institutional cooperation between Statistics Norway and the Ministry of Finance and Economic Planning in South Sudan aimed at improving macroeconomic analysis and fiscal policy in South Sudan. It was mainly addressed to Economists and to the management of MoFEP.

The project components defined together with MoFEP included general capacity development of staff, macroeconomic framework, macroeconomic model, data library, analysis, debt management, poverty reduction, budget process and execution. A long-term adviser, a Norway based project coordinator and a local project manager were designated for ensuring project progress. This cooperation was supported by frequent communication between the long-term adviser and MoFEP’s project manager and frequent short-term missions from Norwegian experts to train and assist on specific topics.



2. Organisational: Methods, practices and quality control; Strategic Planning; Organisational Design

3. System:


15. Institutional cooperation between Statistics Norway and the Central Bureau of Statistics of the Republic of Sudan

Lead Organisation: Statistics Norway (SN), funded by the Norwegian Embassy to Sudan

Partners: Central Bureau of Statistics (CBS)

Beneficiary countries/region: Sudan

Period of Implementation: January 2014 – February 2017

Summary:

The institutional cooperation between Statistics Norway and the Central Bureau of Statistics aimed to develop statistical capacity in Sudan. This programme was addressed to statisticians in CBS and other National data owners, providers and Sudanese institutions. The activities for each module were agreed by the partner institutions and reviewed annually to reflect changes in priorities and needs. There were three modules: further development of economic statistics and business registers; support to the National Household Budget Survey; and cross sector capacity building. The project involved technical assistance and training missions/workshops from Statistics Norway to CBS. Sudanese institutions sent staff on training missions to Norway and provided direct support to project activity by providing relevant technical equipment.



2. Organisational: Infrastructure, Methods, practices and quality control; Standards and Regulations; Organisational Design

3. System: Data ecosystem Co-ordination; Relationship between producers


16. Institutional cooperation between Statistics Norway and the National Statistical Committee of the Kyrgyz Republic (NSC)

Lead Organisation: Statistics Norway (SN), funded by the Norwegian Ministry of Foreign Affairs

Partners: National Statistical Committee of the Kyrgyz Republic (NSC)

Beneficiary countries/region: Kyrgyzstan

Period of Implementation: January 2014 – December 2017

Summary:

The institutional cooperation between Statistics Norway and the National Statistical Committee of the Kyrgyz Republic (NSC) aimed to strengthen statistical capacity in Kyrgyzstan by focusing on activities related to the modules agreed by the partners. These were revised in annual meetings to reflect changes in priorities and needs. This programme was addressed to statisticians in NSC and other National data owners, providers and institutions. The project modules were the following:

Organisational Development (including a quality assurance framework; a project management methodology and framework; human resource management; metadata management; an overall plan for IT development; setting an intranet up; physical security/new library) .

IT (including capacity building on statistical tools, programming and database design and upgrading IT systems)

Agricultural register (including setting the register up; upgrading the current household book system to ensure maintenance of the register)

The cooperation consisted of SN technical assistance and training missions/workshops to the NSC; Kyrgyz institutions sent staff on training missions to SN and provided direct support to project activity by providing relevant technical equipment.



2. Organisational: Infrastructure; Methods, practices and quality control; Standards and regulations; Innovation; Strategic Planning; HR Management

3. System: Data ecosystem Co-ordination


17. Mongolian practices of implementing global action plan for sustainable development data

Lead Organisation: National Statistical Office of Mongolia (NSO)Beneficiary countries/region: Mongolia

Period of Implementation: Ongoing

Summary:

The National Statistical Office of Mongolia (NSO) has carried out specific activities in order to implement the Global Action Plan for Sustainable Development Data, including:

• Organising the “Sustainable Development-Statistics” National Forum held on 13-14 November, 2017 for defining approaches to measure and monitor the implementation of SDGs

• Cooperating with international organisations to evaluate the implementation of SDGs and data development

• Improving its web page for reinforcing the coordination between government agencies, and for providing more user-friendly information

• Creating a “PR division” within the NSO to develop the marketing of statistics and advocacy activities

• Developing a portal and android/IOS applications

• Using QR codes for statistical products such as monthly bulletin and statistical yearbook

• Launching a “Data Lab” for enabling users to access the micro database and developing a “media centre” to provide videos and multimedia to enhance statistical knowledge and literacy of users

• Setting up cooperation agreements between the NSO and the Ministry of Education, Culture, Science Sports to develop handbooks and to organise trainings, to improve data literacy of high-school school teachers and students

•Organising regular trainings for statistical system officers on a regular basis.



2. Organisational: Human Resources; Infrastructure; Methods, practices and quality control; Standards and regulations; Innovation; Strategic Planning; HR Management

3. System: NSS Co-ordination; Data ecosystem Co-ordination; Data Literacy


18. UIS’ Support in National Statistical Capacity Development

Lead Organisation: UNESCO Institute for Statistics (UIS)

Beneficiary countries/region: Around 200 countries

Period of Implementation:

Summary:

The UNESCO Institute for Statistics (UIS) plays a key role in strengthening country data systems, particularly in low- and middle-income countries. The objectives of capacity building are to:

Support countries in the establishment of national mechanisms to coordinate their education data production systems

Institute National Strategies for the Development of Education Statistics (NSDES) and to secure funding and resources for national education statistical capacity

Develop a variety of technical resources for supporting national capacity development efforts; to provide technical assistance including trainings to the Member States on diverse issues related to education statistics, including human and financial resource mobilization

Develop a knowledge-base and to provide for sharing experiences between regions/countries

Reinforce networks of countries, experts and institutions for sharing experiences and best practices and for mutual help in statistical capacity building.



2. Organisational: Methods, practices and quality control; Standards and regulations; Fundraising strategies

3. System: Plans; Funds infrastructure; NSS Co-ordination; Data Ecosystem co-ordination


19. Mexico's cooperation with the Central American Integration System

Lead Organisation: INEGI

Partners: Central American Integration System (SICA)

Beneficiary countries/region: Member States of the Central American Integration System (SICA)

Period of Implementation: From 2011

Summary:

In 2011, Mexico presented a national report on progress towards the Millennium Development Goals, together with a digital platform developed by INEGI to feed the databases and provide a better visualisation of indicators and statistics. Mexico proposed in that year to the Central American Integration System (SICA) a cooperation agreement to offer member states such a platform, as well as to establish a Mesoamerican Expert Network on MDGs. Eight countries participated.

Although not initially planned, several countries requested that mechanisms for coordinating the integration of statistics from different ministries be developed, with use of the website as a coordinating tool. In addition, countries asked for cooperation on specific issues, including statistics on poverty, health, environment, employment and project evaluation. Advice on legal and regulatory aspects to coordinate their national statistical systems was also requested.


2. Organisational: Resources, Methods, practices and quality control; Standards and regulations;

3. System: NSS Co-ordination; Data-Ecosystem Co-ordination; Laws, regulations and reference frameworks


Annex: Summary of successful and unsuccessful practices

People Organisations Enabling Environment/Systems

Successful practices

Employees: On-the-job training produces visible results Fora where they meet stakeholders (e.g. journalists)Managers: Teach change management Show a working culture based on trust, acceptance of failure, team work and shared responsibility Allow them to share their own point of viewDecision-makers: illustrate potential use of various data sources for statistics and their in policy makingUsers: Distribute statistics through social media Regular and sequential trainings from NSO

Partner: Assess own competence and capacity for cooperation. Adjust working methods to the local setting Learn how to transfer knowledge in new cultural settings. Be flexible to beneficiary needs Have a long term adviser working in the partner organisation for a period of one to two years, who can understand that specific institution, and contribute to establish a solid basis for cooperation Provide technical and technological innovations for the operation of official statistical agenciesNSO: Have a “PR division” to develop the marketing of statistics and advocacy activities. Supporting mechanisms to promote a real and sustained consultation with usersEstablish mechanisms for work planning and budget managementCooperation: Fluent communication between institutions. Clear definition of achievements and measurable targets. Provide basket funds

Partner: Partnerships to avoid duplication of the different partners’ support to the country Selecting lead donor with statistical expertise improves coordination among donors Know and understand the structures in force in the organisation that we are cooperating withProvide legal advisory on how to coordinate NSS and NSONSS: Focus not only in production but also in use of statistics (involve national users) Identify decision makers at a very high level and ensure their support for the projectCooperation: Monitor how the cooperation itself is working. Establish a mechanism for evaluating with partners Guide efforts by country priorities, needs and integrated into national policies and implementation’s programmes

Unsuccessfulpractices

Employees: Relying too much on individuals, they can leave the organisation and the knowledge is lost Letting low motivated employees self-select into training

Partner: Withdraw assistance once a new system is in place. Launching the project without proper analysis of competence, capacity, needs, commitment and ownership; baselines, and sustainability elements in the receiving institution Designing projects without assessing absorption capacity of target organisationCooperation: Working on regional programmes assuming that all countries dispose of the same capabilities Ambiguity on communication channels

Cooperation: Continue working when trust is missing Lacking accountability to coordinating structures at the international level

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