We Need to Re-Boot the Education Sector with Demand-Side Data Innovation

For years, the UNESCO Institute for Statistics (UIS) and many other international agencies have been assisting countries in producing better education data, which are needed more than ever. The approach has typically been supply-side: capacity building, technical assistance, donation of hardware and software, etc. This has led to significant improvement. For example, today we have much better data on primary school completion rates than we did 20 years ago.

While this supply-side approach is critical, we must also take a sharper focus on demand from countries, central statistical offices, teachers: the side that should shape donor decisions around funding. Which means that it is time to make a collective and demand-driven investment case for the production of international data, backed by innovative and flexible approaches to meet specific donor demands.

First, let’s remind ourselves why this matters. Right now, some countries don’t know exactly how many schools they have or how many teachers are on their payroll, or whether all of those on the payroll are working at the schools they claim to work at! With such basic information lacking, it is no wonder that the world is collecting only half of the more complex data needed to monitor progress towards a quality education for every child.

Transforming the education sector through data         

The good news is that we have plenty of examples from other sectors that have been transformed by the effective and efficient use of data, particularly agriculture and health. Good data have improved the way these sectors are organized, their delivery models and their equity and efficiency. Now we need to create the same momentum for education.

What is holding us back? After all, donors have shored up education management information systems for decades, as well as supported learning assessments and statistical capacity building initiatives. While one could question whether enough resources were invested in these initiatives, the real problem may lie elsewhere: the demand side.

We need to re-boot

We believe that there is an urgent need for institutional innovations to bolster data systems for education. Creative approaches, from prize-giving to challenge-solving, could work in combination with more traditional approaches, adding some much-needed ‘spice’ to the mix. More of the same, as so often, is unlikely to yield results. The solution may be a re-boot for data collection, storage and sharing, as well as stronger analysis and better use of data analytics.

To help get us there, the UIS has developed a new 12-year Global Strategy for Education Data (GSED). It aims to improve evidence-based decisionmaking for education in line with SDG 4, enabling target countries to develop sustainable statistical systems for education, and the production and dissemination of accurate and timely education statistics that are comparable over time and across countries.

The Global Strategy for Education Data

The GSED proposes an alternative and complementary approach to the traditional supply-led model that has been used in the last decade. It utilises a concept of disaggregated and specific demand coming from individual countries or self-identified groupings of countries with a common interest to stimulate innovation. In the past, we have used aggregated or average demand and supplied similar services to most countries. We want to stress that any new approach would build – rather than dispense – with all the useful tools developed by a supply-side model. For example, a standardised framework for diagnosing why an education data system is underperforming, such as that discussed in the SDG 4 Data Digest, is still valid and useful – if supplemented by demand-side ideas.

The argument, however, is that we must focus on both sides of the equation – supply and demand – to avoid taking the same road as in the past without solving the basic problems. We would suggest that the standard work of the UIS, well-funded and managed, is the necessary complement to the innovation work outlined here.

A second key point of the proposal is the use of virtuality, and clever information systems to manage these innovative arrangements.

The GSED positions quality data as a global public good, promoting:

• tools and platforms to report data, calculate indicators and assess quality and procedures to improve the institutional, organizational and technical capacities of education statistical systems;
• national systems for easy access and dissemination of national and sub-national data;
• a living database, including research projects, best practices and a roster of experts;
• the transformation of innovation into concrete and cost-effective methods for data collection, elaboration, analysis, and presentation, including for populations in emergencies.

How international agencies can build the momentum

As you can imagine, we have also been thinking about how international agencies can help build a demand-side approach to create data innovations that could then, once proven, be spread through the more traditional supply-side system. A process like the following might work:

• Create a fund and a fund manager or broker. The fund need not be a “physical” fund or an actual account; it could be a virtual fund that tracks the income, outgo, and usage of resources, and above all the results achieved, by various partners.
• Call for alliances between governments, data companies, universities, and civil society, or any combination, to solve very specific data problems that have plagued the sector for years.
• The fund manager ensures that the problems line up with the data needs in the SDGs.
• “Proof” that the proponents have sustainable ideas, not just innovative ideas, and are putting their own resources into the solution, would be required. In particular, the proponents should prove that the innovations are not supply-driven but are integrated into the systems and management processes that countries already use. In other words, the innovations would have to improve data supply in sub-systems that have a strong need for the data. Specific examples could be data on disabilities, or improved ways to measure early childhood development.   
• One supporting innovation would be a virtual exchange, with a pre-set list of priorities to ensure bids from the countries or groups of countries in greatest need, or with the highest priorities. There could be different mechanisms. Countries with similar issues could compare notes and exert collective pressure on the broker to fund a solution. Collective bids by a group of countries collaborating to solve a problem would receive priority.
• The virtual exchange would have stalls full of project catalogues. If for example, someone wants to know more about citizen-led projects to sample the equitable treatment of children with disabilities in education, they can find that information on the subject and its impact.  
• The fund or fund manager/broker, or a technical ally such as the UIS, could provide the forum where innovations already under implementation are exchanged and evaluated over time, but the ideas would have to prove their worth in comparison to other ideas, and in terms of peer review, not in the judgment of a central entity.
• As innovations prove their worth, more traditional supply-side approaches would be used, by more traditional entities, to disseminate them.

The idea is that as innovative techniques promoted in a demand-side way gain traction, the more technical solutions spread via supply-side mechanisms would gain a firmer footing, based on practical ideas that have been shown to work in a limited number of ‘lead’ countries.

This long-term, demand-driven approach could contribute to producing stronger and more innovative education statistical systems worldwide that can adapt to ongoing and new data needs.

Not surprisingly, all of this is the subject of much discussion by the UIS and partners. For our part, we are eager to see a central virtual fund—one of the possibilities noted above. It need not be the only fund, but it should be big enough and central enough to attract attention and support. It could be under the statistical or data control of one central broker, who tracks and publicizes how much money is coming in, how much leaves, for what purposes, and with what results.

Taken together, all of this would help to foster – and respond to – that all-important demand for data in innovative ways. We welcome a far-reaching and ambitious debate on such approaches with our partners.