On foresight and trade-off analysis for agriculture and food systems

ON FORESIGHT AND TRADE-OFF ANALYSIS FOR AGRICULTURE AND FOOD SYSTEMS

by Keith Wiebe and Steven Prager | February 22, 2021

The inaugural (January 2021) issue of Q Open, a new open access journal that is a collaboration between the European Agricultural and Applied Economics Publication Foundation and the Oxford University Press (OUP), includes a collection of papers coming from a research project undertaken by the Independent Science for Development Council (ISDC) of CGIAR that examines the role of foresight and trade-off analysis in terms of organizational reform and future research agendas.

We were invited to write a commentary on this collection, and this blog is a summary of some key comments (read full commentary here).

The papers and ideas on foresight and trade-off analysis presented in this issue are very timely. They come as our agri-food systems are experiencing severe shocks (immediate as well as longer term) that call for unprecedented responses under a high degree of uncertainty. At the same time, a key part of the international agricultural research system, CGIAR, is undergoing a fundamental restructuring that challenges us with both need and opportunity to rethink research priorities to inform decision making and improve agriculture and food system outcomes.

Thinking about the future and weighing alternative options are, of course, nothing new. What is new in the context of agri-food systems in recent years is the scale, complexity, and interconnectedness of these systems themselves. As noted by Barrett et al., these systems have largely evolved in an uncoordinated way, given that they are driven by the individual decisions of hundreds of millions of producers and billions of consumers around the world, not to mention countless intermediaries and highly heterogeneous environmental and economic contexts. All this poses massive challenges to identifying and implementing the needed policy responses to help balance multiple goals ranging from environmental sustainability and food security to equity in access to economic opportunities across the value chain.

The number of studies and reports on foresight and trade-offs related to agri-food systems has grown rapidly alongside these challenges—indeed to the point where it is difficult to keep up with them. One of the services that this collection of papers offers is to review a subset of those reports. Zurek et al. focus particularly on a selection related to climate change and the environment, while Lentz focuses particularly on foresight related to gender, poverty, and nutrition. Antle and Valdivia in turn note the importance of analysis that explicitly recognizes and evaluates the trade-offs between multiple and diverse goals and outcomes at a range of scales.

On focus

Antle and Valdivia observe that many reports on the future of agri-food systems present ideas about what needs to be done, but fewer explore how. Lentz finds that visioning studies tend to make strong assumptions about pathways to achieve desired future outcomes, while Zurek et al. note the difficulty of reaching consensus on options for change, particularly when systems and stakeholder interests are complex and diverse. Authors also find that foresight analysis of agri-food systems tends to focus on major trends in population, income, diets, and climate, but with much less attention to systemic shocks (such as those we are experiencing in 2020 related to COVID-19, pest and disease outbreaks, and short-term climate extremes). Foresight analyses also vary in their attention to different types of outcomes, with many models tending to focus more on commodity production, markets, and calories, and much less on livelihoods, inclusion, and nutrition (and the interactions between these and climate change, for example). Finally, the authors find insufficient attention given to innovation systems and particularly adoption pathways for new technologies, to the governance challenges that (among other things) shape and constrain those adoption pathways, and to trade-offs across diverse outcomes and scales.

In our commentary we point to some of the important recent research that helps address these gaps.

On process

At least as important as the findings on research gaps are the insights on processes for integrating foresight and trade-off analysis into decision making and research priority setting. Each of the papers highlights the importance of engagement with stakeholders in the identification of questions, goals, and challenges, as well as using a mix of qualitative and quantitative methods. Similarly, there is a common emphasis on transparency in analysis and discussion to enhance understanding, legitimacy, and credibility of results. Finally, all papers support using foresight and trade-off analysis to inform rather than to drive decision making.

While we broadly agree, we also note that the papers seem to draw an artificial distinction between foresight and trade-off analysis.  In contrast, we argue that foresight and trade-off analysis are two parts of the same approach: systematically evaluating alternative futures and their impacts on multiple outcomes.

Moving forward on foresight

As with any research in the agriculture development arena, it is important to be intentional and clear about the impact pathway associated with foresight and trade-off analysis. Every analysis should begin with a clear understanding of why it needs to be done (what decision(s) it will support), who is potentially affected, and who should participate. Closely related factors include identification of the appropriate spatial, temporal, and institutional scales that are relevant for the systems of interest, the associated decision-making processes, and, ultimately, the corresponding choices regarding approaches to the analysis. These issues should be clearly articulated and revisited periodically throughout any analysis.

The value of foresight and trade-off analyses and results is enhanced with ongoing engagement between research producers and research users as questions, methods, data sources, assumptions, interpretations, and implications are debated, clarified, and improved. For this reason, investment in foresight and trade-off analysis should be looked at in the context of overall mission performance, rather than as occasional exercise for particular activities or projects.

Putting foresight and trade-off analysis into practice is especially relevant during the current CGIAR reform process. Moving toward One CGIAR, in which multiple and diverse viewpoints and inputs are clearly required, will benefit from the diverse future-oriented perspectives that foresight can help bring together.

The need to deal with a complex and uncertain future is not new, and neither is our natural tendency to evaluate alternative options. However, the increased scale and interconnectedness of our global agri-food system today, combined with its inherent lack of coordination, requires that we in the international agricultural research community use foresight and trade-off analysis much more deliberately and systematically, drawing on multiple approaches and sources of expertise to address multiple options to achieve multiple goals at multiple scales. As a step in this direction, the papers in this collection recommend integration of foresight and trade-off analysis into ongoing, systematic, iterative processes including decision-makers, other stakeholders, and researchers—and on this point we fully agree. This will be difficult and costly—but less so than the alternative.


Keith Wiebe is a Senior Research Fellow at the International Food Policy Research Institute, and Steven Prager is Principal Scientist for Integrated Modeling and Strategic Foresight, Decision and Policy Analysis at the Alliance of Bioversity International and CIAT. At PIM, Keith and Steve co-lead the research cluster on Food Systems Futures within Flagship 1: Technological Innovation and Sustainable Intensification.

 

Photo: CIAT/Neil Palmer

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