COUNTING ON THE WORLD
An annual report on building modern data systems for sustainable development
How can national statistics systems evolve to leverage the data revolution?
There is no one right way to go about harnessing the data revolution for sustainable development, and there is not one perfect statistical system. The process of bringing on board a wide range of actors, each using different methodologies and approaches to produce, analyze, curate and disseminate data, will be messy and challenging.
In this annual report, TReNDS highlights progress and interrogates emerging methods. It revolves around four key themes:
Data to help achieve sustainable development
2. The data we need
Understanding the past, present and future
3. Actors and incentives in the current data landscape
4. Achieving a modern data system
Breaking down institutional barriers and fostering new partnerships
5. Counting on the world
A roadmap for urgent action
Using academic inputs to model estimates and help to fill data gaps
The term “data revolution” is ubiquitous. Over the last five years, we have heard time and time again about the potential of new technologies and big data to transform the way we do business within both the private and public sectors. But the need for new approaches was brought into sharp relief during the negotiations on the new global sustainable development agenda.
Unfortunately, much of the data required to monitor this new agenda is unavailable. Issues relating to quality, timeliness, human and financial capacity, and lack of standardized methodologies all hamper our ability to comprehensively track this important agenda. Financial investment in statistical systems is urgently required to help rectify these problems, but we also need to harness the so-called “data revolution,” bringing in private companies and other data innovators from academia, civil society and multilateral institutions to develop new technologies and approaches to monitoring sustainable development.
In September 2015, 193 heads of state and government agreed to set the world on a path to a more sustainable future by adopting the Sustainable Development Goals (SDGs) via the 2030 Agenda for Sustainable Development.
These goals are extraordinary; they represent the greatest consensus of the global international community since the signing of the Universal Declaration of Human Rights.
But they are also ambitious.
Each goal will require considerable investment by each and every government. Each will require strong political will. And each will require new technologies, data, and innovation.
Monitoring the Past: Tracking our progress on sustainable development requires huge quantities of data. The indicators of the SDGs will come from a wide array range of data sources and tools including censuses, household surveys, civil registration and vital statistics systems, administrative data systems, and environmental data such as geospatial imagery.
Managing the Present: Fundamentally, data for sustainable development should help governments to effectively manage their resources, services and responsibilities so as to provide the best possible support and protection for their citizens and the natural habitat. Data should serve as an administrative tool supporting governments to make judicious decisions about where and how to direct attention and resources. But to be a helpful tool, data needs to be both timely and relevant.
Planning for the Future: A key imperative of sustainable development is to protect the Earth’s natural resources for future generations, ensuring that we do not deplete natural stocks at a rate that cannot be replenished. Managing these risks and the increased incidence of natural disasters arising from extreme weather requires that we use data to analyze past trends and predict future scenarios. Tools for forecasting or modeling future scenarios are needed to make this possible.
There is a wide range of expertise required for comprehensive SDG planning, management and monitoring. Classically trained statisticians may be experts at conducting surveys or censuses, but they are less likely to have expertise in administrative data collection and analysis within a given sector – such as interpreting satellite imagery or geographic information systems (GIS) – or forecasting. The range of expertise required can sometimes be gathered from across government, with the NSO undertaking the census and surveys, ministries of environment or agriculture interpreting satellite data and using GIS, and different sectoral ministries compiling administrative data. Still, more often than not (and particularly in countries with low government capacity), these kinds of national statistics need to be gathered in partnership with nongovernmental actors who can provide additional expertise or resources.
There are a number of challenges to establishing modern data systems and broad data partnerships for monitoring and attainment of the SDGs. Challenges include differing incentives; capacity issues; a lack of formalized spaces for multi-stakeholder engagement; differing standards and rules about data sharing; and varying levels of resources. This section highlights four pathways to overcoming institutional roadblocks, presenting practical suggestions that aim to challenge the status quo. It also includes illustrative case studies to show groundbreaking initiatives already underway.
A 21st-century data system that is fit for purpose to both monitor and achieve the SDGs will need to help us plan and prepare for the future, manage and govern more effectively, and track our progress to ensure we stay on course to meet our objectives. This requires a new approach to data and information systems that places data at the heart of government. An evidence-based approach to decision-making is vital if we are to meet the wide-ranging and ambitious SDGs within the remaining years available.