Chapter 2 Getting the Governance Right

Getting the Governance Right icon

“Good governance of the data revolution for sustainable development will require the creation of open, equal platforms for collaboration.” (TReNDS 2017)

To govern the new ecosystem of data providers – and ensure they are providing high-quality data in a responsible manner and over a sustainable time period – we need new more inclusive and agile institutions. Traditionally, official statistics have been produced by National Statistical Offices (NSOs), with the standards and methods being overseen by the UN Statistical Commission (UNSC). These institutions continue to play vital leadership roles. But consensus is growing around the idea that we need to bring non-governmental actors into the tent, recognizing that they have a valuable role to play in data production, technical assistance, technological support and more (TReNDS 2017; UNSD 2017; IEAG 2014). Bringing academic partners, private companies, NGOs and others into formal processes also provides the opportunity to establish common standards, agree upon key principles, and create mechanisms to support public-private partnerships. In this chapter we reflect upon the reforms required both within NSOs and at the international level through the UN Statistical Commission. We also look at the crucial role of local governments in monitoring sub-national activity around the SDGs.

A. National Institutions: The Evolving Role of the National Statistical Office

Over the past few years, there has been a widespread call for NSOs to evolve from producers of data to coordinators of the broad data ecosystem, responsible for identifying a wide range of data sources and assessing their quality and rigor before using these data to compile national statistics. The Organisation for Economic Co-operation and Development (OECD) goes so far as to suggest NSOs become “clearing houses” of data, responsible for certifying new data sets and methods (Prydz 2014). However, as NSOs reform themselves, it is essential that they receive strong support from the executive (Head of State) and other, senior-level ministerial positions to coordinate the broad range of national data actors and ensure they are sufficiently resourced[1].

New Functions

Recognizing the need for higher-profile data leadership in government, the 2017 edition of Counting on the World called on countries to consider adopting chief data officers (CDOs) to support the NSO and chief statistician with additional data coordination and advocacy in government. Originating in 2003 with big tech and financial businesses per Wiseman (2018), the position of CDO – a high-profile coordinator of data partnerships, production, and use – has increased in popularity and prominence in government over recent years across different geographies and levels of authority – for example, at the country level in France and Estonia, and sub-nationally across the United States (see Box 1). Our initial recommendations emphasized the potential benefits of appointing a CDO within NSOs where this position could mobilize political capital, encourage third-party partnerships, help to coordinate data sharing across government departments, encourage novel applications of existing government data, and attract resources. For example, in France the CDO and the associated agency, Etalab, are not involved with the production of new statistics (which is firmly the remit of the NSO); however, they support the use and governance of existing, raw data (Banzet and Chignard 2019). Anyone can submit a request to the CDO for assistance with a particular data set (Banzet and Chignard 2019). Etalab’s general interest entrepreneurs program works with ministerial officials to promote data applications, such as using administrative data to help job seekers or develop tools to improve road safety (Etalab 2018). A key value add here is the focus on turning data into insights, useful for different government departments. This encourages evidence-based policy- and decision-making and improves the perceived value of the NSO.

Recent experiences show that there are a variety of ways to establish these functions in government, including by empowering the national statistician and the existing NSO to fulfill these duties. In New Zealand and the Philippines, for example, the National Statisticians are mandated to coordinate data across all of government, bring in new methods and partnerships, and encourage innovation with great success (Dahmm 2018b; Espey 2018b; Government of New Zealand 2019). Table 1 provides an overview of the traditional and new responsibilities that are increasingly falling to the national statistical system and should be managed either by the National Statistician or CDO. Further discussion on CDOs and their utility at ministerial and local levels is provided in Box 1.

Box 1: The Emergence of Chief Data Officers at Local and National Levels

The CDO role has evolved from the sub-national level to the federal level worldwide (Wiseman 2018). Examples abound from France, to Estonia, to New Zealand, to the US.

France became the first country to appoint a national CDO in 2014 (Banzet and Chignard 2019). The role is appointed by and reports to the Prime Minister from Etalab, a group within the French government that promotes open data and data modernization. It does not have formal links with the NSO, but its position provides the ability to work across all ministries (Banzet and Chignard 2019). In Estonia, the CDO is a non-political appointee in the Ministry of Economic Affairs and Communications, reporting to the Chief Information Officer (Velsberg 2019). The position is separate from Statistics Estonia (which is under the Ministry of Finance) but relies on Statistics Estonia for data and statistics, and there is some overlap on governance and other issues (Velsberg 2019). In contrast, the role of Government Chief Data Steward in New Zealand is held by the executive director of Statistics New Zealand, providing them with a platform to advocate for the value of data across government (Government of New Zealand 2019). Yet another model is seen in the United States, where CDOs have been operating in individual federal agencies, often reporting to Chief Information Officers (Wiseman 2018).

Critical to the success of the CDO, regardless of location or exact remit, is executive-level support (Shah 2019; Wiseman 2019). Moreover, the CDO can be an advocate for data. In the example of Estonia, CDO Ott Velsberg advocates for data use and education, saying, “It is really a spokesperson role in that sense. Creating a data driven drive that isn’t necessarily present in the public sector” (Velsberg 2019).

CDOs to date have also served convening roles, exemplifying collaboration and new ways of working (Shah 2019). For example, in France, a number of ministries have data officers who deal with information or statistical systems, and the national CDO meets every other month with these officials to facilitate knowledge sharing (Banzet and Chignard 2019). Under new legislation, Estonia will introduce Data Stewards throughout the entire government, and the CDO is working with Statistics Estonia to describe data governance core principles on how to reeducate these data stewards (Velsberg 2019).

CDOs can also play a very helpful role promoting open data standards by addressing both technical and administrative issues (Shah and Eggers 2018). For instance, nine different data sets from the French government have been identified as key for social and economic development, and Etalab ensures these data sets are published openly and with regularity (Banzet and Chignard 2019).

On a practical level, CDOs have also performed useful functions expediting data applications and brokering dispersed data source; ministerial-level CDOs in particular allow sector-specific engagement and capitalization on unique knowledge and connections to maximize the impact of data use. For example, to tackle the opioid epidemic in the United States, sub-national and agency-level CDOs are brokering data from different agencies and levels of government to inform policymakers – e.g. at the state level, the CDO of the State of Connecticut coordinates data sharing from various state agencies and publishes accidental overdose death data sets on the state’s Open Data Portal (Shah 2019; Martinez 2018). At the federal ministerial level, the CDO for the US Department of Transportation has led the gathering of troves of data from state and local governments on road conditions, transit usage, accidents, and more; one application has been a geospatial database of transit routes and schedules for travelers and researchers alike, the National Transit Map (Wiseman 2018).

With these successes serving as models, countries should consider creating ministerial and local CDOs to complement the national statistical system, strengthen the wider data ecosystem, and originate data solutions from within responsible agencies.

Table 1: Changing Functions of the NSO and a Potential Division of Labor Between the Chief Statistician and Chief Data Officer

Core Functions New Functions
Primary Role Manage the impartial production of official statistics. Broker new partnerships to produce, clean, compile, and analyze data and produce official statistics
  • Produce official statistics including data on social, economic, and environmental conditions, as well as national accounts
  • Coordinate and oversee agreed data partners
  • Conduct data quality assurance, testing and evaluation
  • Connect and coordinate data activities across government
  • Identify new data partners and new data sources for the government (ministries and departments) in partnership with the NSO
  • Broker the partnerships, including overseeing legal partnership agreements
  • Conduct internal advocacy to ensure the government maintains a spotlight on data for sustainable development, makes its data openly available, and uses an evidence-based approach to policy- and decision-making
  • Build data science capacity across government
Expertise Statistical methods to tertiary degree level Coordinating multi-stakeholder partnership agreements, familiarity with both official and non-official data sources, understanding of data science methods
Reports to N/A – produces data for government, but is administratively independent Either the head of government, the Chief Statistician, or another ministerial-level position, but with a dotted line to the NSO to ensure adherence to the same data quality standards

Amended Laws and National Development Plans

For an NSO to launch a program of modernization – including potentially appointing a CDO – a strong and open statistical law and/or policy framework is required. This must empower the national statistician to engage with third parties and use their data, as well as perform other essential functions like coordinating data compilation across government entities. The CTGAP identified this as a central and urgent action for all countries, to “enhance the status, independence and coordination role of national statistics offices” as well as encourage the development of “a mechanism for the use of data from alternative and innovative sources within official statistics” (UNSD 2017). Sadly, many countries in the world still have laws and policies that actively limit these activities. For example, Nigeria’s Statistics Act, 2007 explicitly says that official statistics are those produced by the national bureau of statistics, line ministries, public authorities, state statistical agencies, and local government statistical units, making no provision for the national bureau to vet, sanction, and use data generated by third parties, even if it is of exceptionally high quality and directly measures the outcomes they wish to track (Government of Nigeria 2007). In Tanzania a similarly stringent act is in place that makes it illegal for independent groups to publish what the government deems “false official statistics” or to disseminate information that would result in the “distortion of facts” (Mwema 2017). The result of this was the arrest of opposition politician Zitto Kabwe in 2017 for violating the law for remarks he made about Tanzania’s economic growth. But in June 2019, thanks to pressure from citizens and donors, the Parliament passed an amendment lifting some of the restrictions and also giving every person the right to collect and disseminate statistical information, removing criminal liability for publishing independent statistics (Nyeko 2018).

In addition to the appropriate laws, equally important are national strategies for the development of statistics and national development plans stressing the significance of data. For example, Ghana has made statistics a clear focus in its national development plans and SDG planning (Republic of Ghana 2017). The Coordinated Programme of Economic and Social Development Policies (2017-2024) highlights the establishment of a national database as a flagship initiative and emphasizes the need to strengthen civil registration and vital statistics (CRVS) systems (Ibid). And the country’s 2019 Voluntary National Review places significant focus on the need for statistics for the SDGs – particularly for reliable and timely sex-disaggregated data (Republic of Ghana 2019). Furthermore, the Ghana Statistical Service has launched an SDG data reporting platform as a step to make data easily accessible and ensure the integrity of official statistics[2]. Such efforts highlight the importance of national government, particularly the national statistical office, in supporting the use of data for the SDGs.

Increased Human Resources and Capacity

The expanding remit of NSOs – to include cross-government data coordination, analysis, and external partnerships – places a heavy burden on many agencies that are already underfunded and resource-constrained. As such, skill development and recruitment should be a major priority for every country in the world.

For national statisticians taking on responsibilities for brokering partnerships with external actors and across government, having skills in political negotiation will be critical, while at the junior- and mid-level, analytic capacities will need to be increased to translate raw data into useful insights for policymakers. Familiarity and training in geospatial data is particularly pressing, given the plethora of free imagery now available that can be usefully overlaid with most survey-based methods to enable geographic disaggregation. Familiarity with big data, artificial intelligence, and writing algorithms will also be useful as technologies evolve and become more accessible to the public sector.

But it is not just new technologies and innovations brought on by the data revolution that require more capacity and resources; more traditional data such as basic economic, social, and geographic statistics need ongoing investment and well-trained staff. Capacity to monitor inequalities, such as gender-based inequalities, needs focus as well. Increasing awareness and understanding of persistent biases and gaps in gender data collection have placed pressure on national and international statistical systems to respond. To address these issues, the African Centre for Statistics of the UN Economic Commission for Africa (UNECA), in partnership with Data2X, has initiated a project aimed at improving the production and use of gender data within African national statistics systems through the creation of a strong and vibrant network: The Gender Data Network. The main goal of the project is to raise the standard of gender data production to better link with demand for these data, improve the effectiveness of communication of and about gender data, encourage their use, and build capacity across participating countries. The knowledge gleaned from this network will also aid development partners to design effective interventions to move the field of gender data and statistics forward. In this regard, the network fosters gender data expertise, facilitates cross-country learning, enables capacity building and training, enhances coordination mechanisms, and provides a platform for members to raise and solve issues they face. The Gender Data Network may serve as an example for other data sectors.

To support the recruitment and retention of skilled people, an effective back office is required with strong human resource capacity, as well as efficient administrative and financial management services. This requires investing in these essential support functions: allocating sufficient overhead on grants, gifts, and investments to support these professions.

B. Local Institutions: Building Data Leadership and Capacities

Strong, inclusive national institutions are vital for effective coordination of the broad range of data producers now in operation. However, with 84% of the world's current population living in urban and peri-urban areas, the engagement of local governments is critical to success (Scruggs 2018). Among other things, local governments can collect disaggregated data, validate data with local residents, and add nuance to aggregate national statistics. Fortunately, municipalities, metropolitan regions, and provinces the world over are starting to engage with the SDGs, setting cutting-edge examples for local initiatives that successfully promote sustainability.

Since 2016, TReNDS and SDSN Cities (SDSN’s urban program) have supported more than nine cities and local regions to develop and document local data solutions in support of sub-national SDG monitoring[3]. The Local Data Action Solutions Initiative (LDA-SI) explores themes related to indicator localization (“How can we tailor the global indicators to the subnational context and identify additional local indicators to promote SDG action and achievement?”), data platforms (identifying data dashboard models to provide easy-to-use granular data on SDG dimensions), the use of third-party data (filling sub-national data system gaps with citizen-generated data, telecommunications data, and similar) and national-to-local data integration (specifically, focusing on methods for aligning and integrating national and subnational SDG reporting systems)[4].

A range of common lessons and practices have emerged from these case studies, including the vital importance of local government leadership and engagement. In all of the regions, the active engagement of the mayor and other city officials has been crucial to shore up broad support across local residents and ringfence dedicated time and resources for data collection, as well as data uptake in policy design. Grantees noted, however, that political support was more easily built when an SDG effort was formulated around existing policies, initiatives, and monitoring frameworks. In Patiala, India, for example, the SDG strategy was developed around the stated priorities of the city’s leadership, as aligned with SDGs related to health, clean water and sanitation, infrastructure, sustainable cities, climate change, and governance (SDGs 3, 6, 9, 11, 13, and 16) (see Box 2). This simple, connect-the-dots approach was found to reduce any skepticism and improve buy-in from local officials (Varma 2019). In the case of Los Angeles, where the mayor has played a leadership role in promoting the SDGs, the grantee team (including representatives from the city government and local universities) developed a list of proposed local SDG indicators that aligned with LA’s Sustainable City pLAn (Bromaghim 2019). The team aimed to propose a set of targets and associated indicators that would enable a more coordinated government effort to achieve the SDGs.

Box 2: Local Data Action in Patiala, India

In 2018, Community Systems Foundation’s OpenCities Institute was selected as a grantee of the LDA-SI, aiming to craft a localized SDG indicator framework for Patiala, India. Critical to identifying priorities in Patiala was a multi-stakeholder approach. The project team identified stakeholders from the city who could support the SDG localization process, including municipal entities and leaders (such as the Commissioner and Joint Commissioner and the Municipal Corporation); local academics from the Thapar Institute of Engineering and Technology and The Transportation Research and Injury Prevention Programme (TRIPP) at the Indian Institute of Technology (ITT) Delhi; and non-governmental organizations. The project team convened these groups throughout the project, starting in June 2018 with a priority-setting meeting to share the most pressing issues in the city of Patiala: solid waste management, air pollution, parking management, stray animals, and road safety. An August 2018 session brought together urban experts and practitioners across sectors, from UN-Habitat India to TRIPP, ITT Delhi to ICLEI South Asia. This session served not only to gather information from the stakeholders, but to proactively seek their feedback on the localization methodology. The participants of this session also emphasized the value of further multi-stakeholder workshops in the city to determine if the priorities defined by the municipal corporation matched with the needs of the citizens. Through these participatory approaches, the project team ensured its prioritization and methodology aligned the global to the local. For more information, see Varma (2019).

Screenshot of prototype of Patiala’s dashboard aligning the SDGs with local indicators
Figure 1: A prototype of Patiala’s dashboard aligning the SDGs with local indicators. Source: Community Systems Foundation / OpenCities Institute

Across SDSN’s sub-national work, partnerships with city-level actors, universities, and local civil society organizations (CSOs) have proven essential as local governments seldom have the internal capacity to develop SDG-aligned monitoring frameworks. They also do not have the bandwidth to identify new data sources, validate third-party data options, and ensure their indicators can be harmonized with regional or national SDG monitoring frameworks (to the greatest extent possible). For these purposes, partnerships with local universities (which can potentially benefit from student capacity) and local CSOs have been highly effective, where coordinated by a clear local government focal point and/or SDG working group that can help to ensure results are integrated into local government plans.

C. Global Institutions: Reforming the UN Statistical Commission

The international data community – comprised of national statistical offices, multilateral institutions, research institutes, and NGOs – has made great strides in its efforts to include more actors in the production of data and statistics for sustainable development. For example, in 2016 the Global Partnership for Sustainable Development Data (GPSDD) was established, a multi-stakeholder consortium in support of the data revolution for sustainable development, with strong support from the UN (including the Chair of the Board, the Deputy Secretary-General). There is also great potential to create a more inclusive environment for advances in data and statistics at the regional level (see Box 3). In 2017 and 2019 the UN Statistics Division worked in partnership with the GPSDD and other stakeholders to host a World Data Forum – a space for governments, CSOs, and private companies to share new and alternative approaches to data collection and monitoring, with particular emphasis on the monitoring of the new SDGs. These kinds of informal spaces are already helping to match supply and demand, enabling countries to articulate what they want to monitor and to invite non-governmental actors to help them fill gaps. But as important as these spaces and networking opportunities are, their informal nature renders them unable to establish accountability framework or key standards for all of the partners involved. To produce strong, reliable, multi-stakeholder partnerships that will endure for the duration of the SDGs and beyond, more formal mechanisms are required – mechanisms that can ensure the quality and security of the data being produced with the same rigor of those produced for official statistics.

Box 3: Taking a Regional Approach to Statistical Modernization

Regional cooperation is critical for transboundary issues. It is often only by using a regional approach that governments can address economic, social and environmental conditions. For example, water or forestry systems may span multiple countries and require effective regional cooperation for their sustainable management. Therefore, cooperation around data and statistics at the regional levels is also crucial. However, to date, regional economic and political groups have been largely ignored by the global multilateral system.

Moving forward, the regional level is an ideal platform to develop data and evidence (analytical), organize programmatic interventions (operational), and exchange knowledge and experiences among countries (convening). This can be achieved by increasing resources (financial, human and technological) to promote the use of official and non-traditional data sources within regional entities, such as regional economic commissions. With this in mind, a strategic framework for statistical capacity development to deliver the SDGs should be established. It should set out the roles and areas of work for different institutions at the global, regional, and national levels to help to align the funding, functions, governance, and organizational arrangements, and could share the burden of monitoring and achieving such a complex sustainable development agenda.

Written by Cepei

At the highest level of the global statistical system is the UN Statistical Commission (UNSC), established in 1947. The UNSC brings together the chief statisticians from Member States from around the world and a number of agencies engaged in statistical activities. The UN Statistical Commission is the highest decision-making body for international statistical activities, notably responsible for the setting of statistical standards, the development of concepts and methods, and their implementation at the national and international level. The UNSC has played an important role in the governance and quality assurance of official statistics and in building a united and professional community for official government statisticians from around the world. For example, it developed a set of Fundamental Principles of Official Statistics that has guided and guarded the work of NSOs and their independence (UNSD 2013). Given its successful track record convening NSOs and systematizing national statistical approaches, as well as its international mandate and eminence, the UNSC is a natural convening space for the wide range of data providers looking to support the SDGs. And for this reason, it should play a leadership role in advancing the uptake of new methods and approaches to improve the quality of data for sustainable development.

However, in spite of its achievements, the UNSC has not kept up with a number of emerging areas and the demand for more, better, and more timely official statistics. These include: filling crucial data gaps in many countries, such as in gender and poverty data; harmonization of surveys and tools used for collecting microdata; focusing on administrative data systems and improving their linkages to the official statistics in many countries; and insufficient focus on barriers to data dissemination and use. Many of these issues were acknowledged as areas needing improvements in the CTGAP, jointly developed by members of the UNSC, UNSD, and other international data actors represented in the GPSDD (UNSD 2017). However, the CTGAP falls short of considering the governance of official statistics and specifically how the UNSC Commission and its various bodies could be updated to accommodate these needs and evolutions, while maintaining the overall goals and strengths of the Commission.

To improve the inclusivity, responsiveness, and efficiency of the Commission and all of its processes within the context of the new global data ecosystem, it will be important to do the following:

1. Clarify the role of UN Statistical Commission in the new data ecosystem, defining the roles of new actors to improve coordination and increase representation of emerging data communities

Before taking on any coordination of external actors, the UN Statistical Commission would benefit from clarifying certain ambiguities in its scope of governance. For example, with recent changes to the global data ecosystem and the increasing prominence of geospatial data, the linkages between the UNSC and the UN Committee of Experts on Global Geospatial Information Management (UN-GGIM) are unclear. It is also unclear if the UNSC has any governance responsibilities for big data groups within the UN, such as the Global Pulse initiative.

In 2017, TReNDS called for the UNSC to “expand its annual meeting to include a dedicated session with non-governmental actors and experts (TReNDS 2017). As of 2019 there have been some advances in the inclusivity of the UN Statistical Commission, with more non-governmental actors invited to attend and observe the traditional special seminar held in advance of the annual UNSC meeting, and to observe the main proceedings; however, there is still no formal space for non-governmental actors to actively participate and provide inputs.

Lack of coordination with private providers, academics, NGOs, and others – and excluding these actors from technical decision-making processes – risks inefficiencies and lost for building partnerships, sharing knowledge, technical assistance, facilitating links between different data communities, and sharing modern tools. There are several ways to improve the UNSC’s inclusiveness; for example, it can provide opportunities for NGO groups to share materials, encourage Member State representatives to include civil society representatives in their formal delegations (as done by Colombia, among others), and invite into its meetings external experts on specific topics and agendas. The overall goal is to strike a balance between preserving the efficiency of the UNSC sessions and benefiting from the perspective and expertise of those outside the current system.

2. Improve coordination across the UN

The UN Statistics Division – the operational agency that supports the Commission, under the UN Department of Economic and Social Affairs (UNDESA) – could benefit from a broader mandate to coordinate statistical activities across UN agencies, particularly statistical units of regional commissions. With expanding data sources and the increasing role of big data and private sector data to complement official statistics, many areas could benefit from a “one UN solution” – e.g those needing legal and procurement solutions, developing memorandums of understanding (MOUs) with new data providers, procurement of special services, and acquisition of IT tools. Better collaboration across UN agencies will not only improve efficiency but also aid advances in the field through better sharing of data and information among agencies, countries, and regions.

Across the UN there have been some informal discussions about a UN-wide Chief Statistician. Although the establishment of this role may help break down the silos between different UN agencies and regional commissions, it would be very complicated to implement and likely need to be phased in over time. One way of encouraging better coordination across the UN would be to consider encouraging the appointment of CDO roles within different agencies and regional economic commissions, with clear mandates to coordinate with each other and the UNSD. These appointments could focus on building linkages and addressing new challenges and opportunities in the data ecosystem, such as links with the private sector and use of big data and disruptive technologies.

3. Focus the UN Statistical Commission meetings on strategic priorities

Focused attention on SDG monitoring has highlighted acute challenges in both global and national statistical systems, such as huge differentials in countries’ statistical production capacity. The UNSC should take on some of these challenges directly as part of its official agenda. Subjects such as national accounts, balance of payments, and price statistics have been on the agenda of the Commission for many years and are tabled annually. They take up the bulk of the annual meeting time and attention[5]. Time allocated to these recurrent issues should be shortened or brought to the Commission less frequently to make room in the agenda for emerging topics, including pressing SDG monitoring challenges. When an expert agency is invited to provide background information on thematic discussions at the Commission and emerging, cross-sectional topics do not fall into its areas of expertise, the UNSC could call in additional, related agencies or experts in the CSO and academic communities to collaborate.

4. Conduct periodic self- or external evaluation of the UN Statistical Commission, covering both operations and focus areas

From time to time, the UNSC has surveyed the members to measure the impact of its decisions through its working groups and Friends of Chair groups (mandated technical working groups traditionally focused on new forms of measurement). One example is the recent polling of countries to learn how far countries have adopted and implemented the Fundamental Principles of Official Statistics (UN Economic and Social Council 2019). Moving forward, the Commission should consider complementing such surveys with a semi-frequent, light-touch evaluation. Questions to consider might include the breadth of membership and inclusivity of the UNSC, the benefits countries derive from participation, and the quality and depth of substantive debates. Most importantly, the evaluation could track progress towards fulfillment of the goals in the CTGAP. Donors with significant investments in official statistics and a results-oriented focus would most likely be interested in supporting such periodic evaluation.


  1. Local governments should look to bolster their statistical capacity to monitor local sustainable development challenges and share data upwards with national government. They should work with local expert groups like universities and, where resources permit, appoint dedicated data officers with the support and backing of the mayor or another relevant executive.

  2. National governments should empower their national statistical offices with capacity, resources, and the right policy and legal frameworks to take on coordination of data curation and use across the whole of government. They should empower the NSOs to partner with third parties as appropriate to use high-quality, vetted data to supplement official statistics.

  3. National statisticians should be mandated to coordinate this change, working with a supportive Chief Data Officer who can focus on data use across government and partnerships (where necessary and practical).

  4. Internationally,

    • Member States should call for reform of the UN Statistical Commission to ensure more focus on and resources allocated to addressing data gaps and capacity issues, as well as establishing a more inclusive governance structure that invites in expertise from non-governmental groups.

    • Member States should push the UNSC to assume greater responsibility for the UN data ecosystem, encouraging coordination with newly-appointed agency and regional economic commission CDOs while also improving its inclusivity and inviting in external parties as active participants in formal proceedings.

    • With such a broad mandate, it will be important to encourage frequent self-evaluations and ensure UNSC meetings focus on the most pressing political and SDG-related challenges.

  1. As highlighted by the successful reforms enacted in the Philippines, further documented in Espey (2018b). ↩︎

  2. Available here: ↩︎

  3. Including Aruba (Kingdom of the Netherlands), Belo Horizonte (Brazil), a network of municipalities in Colombia, Patiala (India), Los Angeles (USA), Bristol (UK), all since 2018. In 2017 we worked with Baltimore (USA), the Northern California Bay Area (USA), and a network of municipalities in Brazil. For more information, visit: ↩︎

  4. For more information, visit: ↩︎

  5. See agendas from past UN Statistical Commission sessions, available at []. ↩︎

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