A Capability Maturity Model for the SDGs

This research aims to develop a Capability Maturirty Model (CMM) towards strengthening the institutional capabilities of the National Statistics Offices (NSOs), as the national custodians of indicators data and the entities within the national data ecosystem responsible for monitoring progress on the Sustainable Development Goals (SDGs).

The SDGs present an ambitious set of objectives that must balance the three pillars of sustainable development: social inclusion, economic development, and environmental sustainability. Monitoring progress of these developmental objectives is supported by the SDG indicators, which are a means for countries to monitor and report on their achievements towards the SDG goals and targets. The data for the SDG indicators need to be primarily based on data produced by national statistical systems – usually under the ambit of the NSOs – and needs to maximize international comparability and time trends consistency with the data produced at international level. The monitoring of the indicators for the SDGs requires an unprecedented amount of data to be generated and analyzed, which poses a significant challenge for national statistical systems both in developing and developed countries. Achieving the SDGs also demands dealing with the data revolution for sustainable development – the integration of new and traditional data to produce high-quality information that is detailed, timely, and relevant for multiple purposes and to a variety of users.

Measuring sustainable development enables data-driven decision making, which is critical for the development of implementation strategies and the proper allocation of resources. While numerous efforts have been made to improve the quality of social indicators, two main aspects remain overlooked. First, most of the efforts focus on the quality of the data produced, disregarding how (i.e. the institutional processes) such data was produced; second, there is still a general lack of solutions explicitly designed to deal with the requirements for the monitoring of the SDGs.

This research posits that the more mature the organizations within the ecosystems are, the higher the quality of data that they produce, and it subsequently aims to enhance the quality of the SDG indicators data through the development of a tool for assessing the maturity of processes towards the production of indicators data, and also for prescribing a pathway towards increased process maturity.

To understand how the capability of the entities responsible for monitoring and reporting the progress on the SDGs can be improved, this research aims to answer the following questions:

  1. What are the current processes and mechanisms for quality assurance of social indicators?
  2. What are the elements (i.e. actants, stakeholders, processes) of the social indicators ecosystem and the dynamics of value production within these ecosystems?
  3. What is the effectiveness of CMMs towards ensuring the quality of indicators data / How can CMM support the assurance of quality of indicators data?

To strengthen the NSOs to safeguard the quality of the data they produced for the SDG indicators, the following are the specific objectives:

  1. Survey and compare current practices for the production of statistics to feed the SDGs’ indicator framework, including the existing MDG monitoring architectures and other reporting mechanisms.
  2. Design a multidimensional prescriptive Capability Maturity Model suitable to assess and enhance the maturity of the organizations responsible for producing data for the SDGs at the national level.
  3. Validate the proposed model utilizing different validation techniques.
  4. Promote and support the model implementation and utilization.

This research embraces a pragmatic philosophical perspective and takes on the Design Science (DS) approach over a longitudinal time horizon. A three-cycle view of DS research is adopted, where DS is understood as three closely related cycles of activities: relevance – where the contextual environment is bridged with the DS activities, design – where the artifacts are built and evaluated, and rigor – where the DS activities are connected with the knowledge base of scientific foundations, experience, and expertise that informs the project.


Sustainable Development Goals, Indicators Monitoring, Capability Maturity Model, Institutional Capacity

Ignacio Marcovechio

This research activity is addressing all of the UN Sustainable Development Goals (SDGs)


This project is part of the Small Data Lab.
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