Foresight Studies

The use of early warning systems, such as the Rapid Alert System for Food and Feed (RASFF) of the European Union, are reasonably well developed and effective in identifying and addressing short-term challenges; however, they are usually reactive in nature and at best can identify early ‘trends’ in emerging risks. Risk assessors, risk managers and policy makers however, must be ready to frame longer time horizons and prepare for developments beyond the typical four steps of the scientific risk assessment cycle (Van Leeuwen and Vermeire, 2007).

In the context of food systems, foresight approaches aim to anticipate emerging risks (and opportunities) that are difficult to characterise since they are the long-term outcomes of a range of operational and environmental factors, some of which may not be fully in play at the present time. Foresight employs methods to explore change in the mid-to-long-term future based on the assumption that developments outside the food supply chain and even outside the food system are either directly or indirectly related to the development of a particular food-borne hazard. Typical outputs from foresight studies are multiple scenarios that model systemic change in the food system in order to reveal potential unknown patterns of food related challenges. Such approaches demonstrate the potential for complementing the extensive and successful systems for monitoring the occurrence of hazards and risks within the food system.

2.1 Scenario planning (scenario development and analysis)

Scenario planning involves the development, analysis and use of scenarios for improved preparedness to emerging risks and strategic planning; i.e. assessing the robustness of strategies and policy approaches that withstand the risks presented by alternative plausible futures. Scenarios are a foresight tool used to explore uncertainty in complex systems. They are defined as a set of plausible, sequentially linked events that might potentially occur in the future (Jarke et al., 1998), and they are designed to understand, analyse and communicate information about the future, often with the intention to clarify current actions in the light of plausible and possible futures (Durance and Godet, 2010; Parson, 2008; Swart et al., 2004). Scenarios provide a framework for considering a wide range of interacting drivers and the potential consequences of events in order to think through possible responses to uncertainties in the future, using this knowledge to support development of effective, forward-looking policies that address risks. Scenarios help understand the social, economic and environmental impacts on food systems, using this knowledge to determine where future intervention is best directed. However, they do not predict the future; they rather aim to explore what the future could look like under the influence of specific driving forces (De Ruijter, 2014).

Scenarios should be: i) plausible and describe events and developments that fall within the limits of what might conceivably occur in the future ii) internally consistent, the combination of elements and factors in each scenario must be logical, compatible and consistent iii) fit for purpose, serving the aim of the foresight study, especially when looking at facilitating decision making, for example, if the aim of the exercise is to test the resilience of a regulatory system or a policy framework, creating a scenario that presents a 'perfect future' that is free of challenges would not serve the aim of the study iv) present multiple futures in order to capture alternative developments and better inform the foresight study. In such a case, care must be taken to ensure that the scenarios are diverse enough from each other, and not just a variation of a central theme, while at the same time not stretching them to such extremes that it threatens their plausibility.

An indicative foresight study process with specific reference to scenario development is indicated in Fig. 1.

Figure 1: Foresight study process

Environmental scanning: defining driving forces Scenario development: alternative plausible futures Scenario analysis: future challenges and opportunities Evaluation & potential policy responses

2.1.1 Environmental scanning: defining driving forces

A key common approach to scenario development is to identify those elements that are crucial and can bring change to the topic/system of the study; i.e. driving forces. The methodology used to identify relevant drivers of change can vary between foresight studies, but often employ variants of the PESTLE (political, economic, social, technological, legislative and environmental factors) framework (Brown 2007). Depending on the scope of the study, drivers can be macro/high level (e.g. trade, economic growth, food chain structure, consumer perception or values, food prices, climate change), or detailed and specific to a limited process (e.g. a specific category of primary production in the food chain), or even a combination of both. Once a set of drivers have been identified and clearly described, it is important to gain insights for each driver, current knowledge, trends, potential developments and related future hypothesis. This is usually done via a literature review and in consultation with experts, often through workshops, interviews or more structured Delphi exercises. The objective is to assess varying assumptions about food system conditions in order to reveal areas of uncertainty. Such analysis help to clarify what logical relationships exist between drivers to inform how they may lead to change in the system.

2.1.2 Scenario development: alternative plausible futures

Setting up scenarios is a creative process with no ready-made recipes. The basic principle of scenario analysis is that the full extent of risks and their interconnectedness is assessed. Every potential risk, both on the micro- and macro level, that influences the safety of the food system has to be used in the scenario analysis.

Scenarios are developed using a holistic approach that adopts analytical and deliberative/participatory techniques such as workshops, expert elicitation and computer-based modelling to build a spectrum of plausible alternative futures. A key aspect of the approach involves assessing how the drivers of change, based on factors that currently exist or are likely to emerge, evolve and interact with each other in the future. Usually two drivers are selected, on the basis of their importance and uncertainty, to help construct the scaffolding and axes of a scenario. The scenarios are broadly defined using the extremities of these axes. A 2 x 2 matrix is created, based typically on an assessment of the most critical uncertainties. Each quadrant of the matrix represents the skeleton of a different scenario, where the relationship between other drivers are described and characterised to establish the scenario context. The selection/prioritisation processes to designate the two main drivers, or the procedure to characterise the behaviour of the other drivers, can vary, e.g. by order/score of strength of impact on the system in question, via carefully created scoring criteria, by voting on driver importance and uncertainty, or by specifically selecting drivers that fit the study aim.

Additionally, beyond driver description, scenarios can feature also narratives (i.e. scenario descriptions). Narratives can be stories, days in the life of fictional characters, report-like descriptions of the current situations etc. Narratives help to better visualise a scenario, and offer room for more in-depth technical description of the dynamics of the system. Scenario narratives are developed through deliberation with key stakeholders and subject experts, and relay plausible future developments of the whole system, based on a coherent and internally consistent set of assumptions about key

relationships and driving forces. The shorter the time horizon of a scenario, the lower the chance of uncertainty, excitement and surprise. Scenarios with a longer time horizon make it easier to get people out of fixed mindsets, i.e. to ‘step out of the box’, which is crucial in forward looking exercises and can prove to be a major hurdle when involving in the process academic/technical experts with considerable experience in a narrow aspect of the topic. However, extensively long horizons undermine the relevance of the scenarios, and make them non-binding. Careful consideration of the scenario horizon to be used is therefore important.

2.1.3 Scenario analysis

Once scenarios have been fully described, information pertinent to the object of the study can be extracted. Problems, issues, challenges, opportunities and specific situations that appear in the scenario can be identified, analysed and used towards the aim of the study, e.g. proposing actions, measures, for today that can tackle or even prevent the problems of tomorrow. In this way, scenario planning establishes a context for dialogue and foresight in decision-making by providing a framework for assessing the robustness of policy approaches and risk governance.

A number of scenario development studies have been applied to assess the resilience of food systems (O’Keefe et al., 2016; Lakner and Baker, 2014; Vervoort et al. 2014; Chaudhury et al., 2013). These scenarios deliberately challenge the mental maps of food system actors, exploring deviations expected from a ‘single’ future that typically arise from trends and events outside the vision or awareness of those involved in the scenario development process. The following examples showcase how forward- looking studies employing scenarios can inform decision making in the field of EU food policy.