Being able to quantify in real time the dimension of a humanitarian problem, possibly known but undervalued, is the key to deploying aid, channeling funding and improving decisions
The data has permeated the European strategic and political layer, proof of this is the recent EU data strategy that is part of a package of agendas that make up the digital strategy designed to shape the social and economic development of Europe. Without a doubt, it is time to analyze whether these trends lead us to meet the Sustainable Development Goals (SDGs).
The data has given rise to a new type of innovation that takes advantage of traditional sources and new ones as a result of the interaction of people with digital platforms. For about a decade, the United Nations, some research centers and companies began to explore how this innovation could help improve humanitarian action or development. We have seen, however, that even with the tools, the difficulties are still present in managing changes and capacities, sharing data from the private sector in real time and designing solutions that form an adequate mesh with the local dynamics of communities and regions.
The flip side of data and the SDGs is generating actionable insight. Many times, being able to quantify in real time the dimension of a humanitarian problem, possibly known but undervalued, is the key to deploying aid, channeling funding and improving decisions. But the reality is that we are reaching an overload of sterile indicators.
The data must be used to understand those relationships, a priori not obvious, that reveal systemic problems that hold back a more sustainable world without inequalities. Therein lies their true potential, to generate evidence with impact, which we can take advantage of if we establish a multidisciplinary dialogue with them.
The way that evidence is managed is also key and we are beginning to understand how to do it. More than definitive answers, they provide the basis for organic learning and intelligence generation. This implies preparation and anticipation creating teams with scientific capabilities that have direct influence on decisions.
Experimentation with data and evidence is also demonstrating its potential to manage alliances by aligning actors and being the basis of a consensus increased that joins efforts by providing transparency, rigor and points of support. Predictive analytics is, of course, a fundamental tool that should serve to build capacities against various scenarios including mitigation strategies. But we cannot fail to point out that there is a very serious risk in simplifying processes or instrumentalizing the use of data that can have exponential negative consequences.
If on this occasion we focus on Europe and the SDGs, the data strategy revolves around the proposal of a single market that favors its circulation, regulatory standards and the creation of infrastructures with special attention to data spaces.
Without a doubt, having data between different sectors can be a catalyst for a more interconnected production system. However, the transactional nature of this strategy poses serious difficulties in generating the collaboration and synergies necessary to achieve the SDGs, and even socio-technological leadership in a world that is changing its perception of value. Furthermore, this strategy does not identify necessary roles for the public sector, academia, research or the third sector. A vision of the sustainable digital future also needs data to serve to build a new social fabric supported by science.
The bet on data spaces as an interoperable infrastructure it is useful, but insufficient. The first step in a data strategy for the SDGs is to assess the current ecosystem and identify the gaps that allow us to use it to promote equality, social inclusion, better health or an education more suitable for future challenges. When they are incomplete they lead to skewed evidence with a negative impact of enormous proportions.
The governance of infrastructure, the conditions of access and regulation should gravitate around sustainability, resilience, or equality beyond competitiveness. There is talk of putting people at the center of technology, but we really need people at the center of the entire data value chain, with all the consequences.
To date, data holders effectively determine what to do with them, which has a direct impact on the prioritization of projects, alliances and initiatives for the SDGs. The role that the United Nations and multilateral organizations have in the last decade in developing countries to promote their use for development and humanitarian programs is vacant in Europe, and the SDGs are unavoidable in cities and rural areas. Europe’s vulnerability in the current covid-19 crisis is an example of this need for digital mechanisms at the service of society that we have only begun to implement in a reactive and hasty way.
Generating the connection of problems, sectors and actors through data requires resources. Currently there are no funding mechanisms to be able to bring fundamental research to an implementation that provides citizens and decision makers with adequate tools. The problem is exacerbated if we consider that the European strategy and practice lead us to a situation in which they have a very high cost. The data economy without principles and regulations aligned with the SDGs can have a totally inhibiting effect.