The treacherous use of indicators for SDGs

Mario Giampietro

The experience of the UNFCCC Conference of the Parties (COP) has shown the difficulty of  trying to achieve international consensus on required action to tackle global challenges such as the problem of climate change. The 2030 Agenda for Sustainable Development on the other hand, rather than looking for an international consensus on specific actions for achieving “peace and prosperity for people and the planet, now and into the future”, directly opted for a detailed formulation of targets and indicators. In 2015 the UN General Assembly provided no less than 17 Sustainable Development Goals (SDGs), 169 targets for the 17 goals, each of which has between 1 and 3 indicators to measure progress toward the targets. In total, 232 approved indicators to measure progress. However, as with the case of climate change, when looking at the results both on people (provided by UNHCR) and on the planet (in the latest IPBES report) there is no sign of an imminent wave of peace and prosperity.

The question we need to address here is the following: Is there is a systemic problem with the strategies selected by international bodies and national governments to deal with so-called “wicked” problems such as sustainable development and climate change?  Is the translation of a mission explained in semantic terms as peace and prosperity for people and the planet, now and into the future”  into a set of 232 pre-approved indicators a wise move? To address this question, I use the approach developed in MAGIC to look at three types of narratives that need to be integrated when discussing complex policy issues.

Justification narratives—To guide specific actions useful for society, it is essential first of all, to identify societal concerns i.e. the perception of a stress to be avoided or the existence of unsatisfied wants. Next step is to prioritise these concerns because valid justification narratives can be in contrast. For example, “aspiration for economic growth” (SDG 1 & 2) and “need to preserve the environment” (SDG 14 & 15). This entails that the priority given to justification narratives always depends on the context. Dealing with contrasting justification narratives is a political problem, not a scientific one.

Normative narratives—In the context of governance and politics, normative narratives identify actions needed to address specific concerns. However, the choice of a specific action depends not only on a previous prioritisation over existing concerns but also on the analysis of the consequences of the action in terms of winners and losers. When dealing with the goal of “zero hunger” (SDG 2) we can make several suggestions: (i) give funding to the ministers of agriculture of countries with malnutrition; (ii) making fertilizers available to poor farmers; (iii) distribute emergency food in refugee camps.  Trade-offs between these solutions will generate different types of winners and losers.  Implementing more effective agricultural policies may improve the situation in the future, but does nothing to help poor farmers now; starving people want food not fertilizers. The perception of the usefulness of the chosen normative narratives always depends on the feelings and values of stakeholders. When “considering the nexus between energy, food, water, land use, ecological services, across different scales and dimensions, the legitimate aspirations of individual countries, the whole planet, present and future generations” [1] it becomes obvious that the choice of a specific action(s) to be taken is a political problem, not a scientific one.

Explanation narratives—In modern society, when implementing policies, “scientific evidence” is commonly cast in quantitative form, and thus indicators become a privileged form of evidence. Indicators allow the analysis of relevant attributes to characterise the performance of proposed solutions with numbers. Fractal geometry [2] flags the problem faced with this solution when dealing with issues requiring a multi-scale analysis. Let’s imagine that we want to use indicators to select a passenger tour around the coast of UK that minimises the consumption of fuels and the number of overnight stops. Detailed maps and reliable information about fuel consumption and the speed of the means of transport will not enable the identification of a solution that can be used by different operators using both boats and buses. By boat (keeping a safe distance from the shore), the UK coastline is approx. 2800 km. By bus, using coastal roads, the distance is 3400 km. Fractal geometry [2] explains that the length of the UK coastline “changes” not because of lack of accuracy in its representation, but because of a different understanding of what can or should be measured. When different perceptions of the external world co-exist because of different concerns and different purposes, the need to adopt different scales and dimensions of analysis makes the use of quantitative indicators and targets treacherous. Indicators for poverty (SDG 1), justice (SDG 10) and biodiversity (SDG 15 & 16) will always be contested.

Conclusion

The identification of policies linked to the SDGs should be based on: (i) definition of priorities over concerns (for which justification narratives should be used on a case by case basis); and (ii) decision of how to deliberate on the existence of “incommensurable trade-offs” across scales and dimensions. Normative narratives should be selected, again, on a case by case basis. When dealing with the implementation of the SDGs, the issue of how to prioritise concerns and who should be involved (and how) in decision-making is a paramount political issue. This explains why, as illustrated by the experience of the climate COP, getting results through globalised political processes is not easy. However, the current solution through the 2030 Agenda for Sustainable Development is even worse. Given the unavoidable existence of trade-offs and uncertainty, SDG targets and indicators should only be considered after a political discussion of the proposed normative narratives in a specific context.  In specific situations none of the 232 approved SDGs indicators can be used as evidence of an “improvement” outside of a process of unpleasant political discussions about priorities and losers.

A fuller discussion about the use of scientific evidence for governance in complexity is available here.

 

 

References

[1] Giampietro M. and Funtowicz S.O. (2020), From elite folk science to the policy legend of the circular economy, Environmental Science and Policy 100: 64-72 https://doi.org/10.1016/j.envsci.2020.04.012

[2] Mandelbrot, B. (1967), How Long Is the Coast of Britain? Statistical Self-Similarity and Fractional Dimension, Science 156 (3775): 636–638. doi:10.1126/science.156.3775.636