Better Decision Tools for Farmers
Published on 30 March 2010 in Sustainability and Communities
Introduction
One of the expected outputs from ongoing research on sustainable farming systems is an evidence of base of options for farmers which are “good for the environment and good for business”. One unwritten implication of this expected output is that options which satisfy both business and environmental objectives are not automatically obvious to farmers (if they were, research to compile the evidence base would not be necessary). A second implication is that there is a trade-off to be resolved between, on the one hand, the policy objective of getting farmers to do things which are “good for the environment”, and, on the other, the farmers’ objective of doing things which are “good for business”. Of course, the conflict between these objectives should not be over-emphasised since a financially vibrant and sustainable farming community is itself part of the wider rural sustainability policy objectives of Scottish Government.
However, the type of partial trade-off issue identified here is common in policy implementation problems. In general, progress to a solution is dependent on: (1) the existence of un- or under-used but feasible pieces of behaviour for farmers, and; (2) a sufficiently large portion of the farmer population changing behaviour to make a positive difference in the state of the targeted environmental goods. The traditional role of science in this context is to identify the pieces of behaviour that will allow the trade-off to be solved and to invent the means to encourage farmers to adopt the relevant farming practices. In other words, to do applied research and then get its results into practice by some mechanism of knowledge exchange (KE). Given the importance of the research-KE process to the impact of Scottish Government’s supported science, and the size of the financial investment in it, we consider it worthwhile to ask methodological questions in order to identify generic approaches that can be used irrespective of specific details in particular cases. This is especially true when the KE mechanism proposed by research is a new decision tool which is supposed to facilitate a change in behaviour if adopted by farmers or those who help farmers make decisions. This briefing paper reports on just such methodological research.
Key Points
By considering the policy-setting-research-KE process from first principles of information theory as an example of message transmission and knowledge updating, a generic set of questions can be derived that allow a pre-screening of potential decision tool or evidence base projects to be conducted. This pre-screening procedure is likely to have two main effects:
- It will help to unify the policy formulation, science, KE, and implementation phases into a single process encompassing all stakeholders and facilitate an iterative approach to solutions satisfying both environmental and business objectives (see Figure).
- It provides a means to carry out analyses of predicted cost-effectiveness for projects that involve deployment of a new decision tool or specific KE mechanism which is intended to bring about behavioural change.
The proposed methodology involves asking and evaluating the answers to two sets of questions.
Questions which should be asked in a joint planning session between policy-makers/research funders and researchers:
1. What scale of change in the long-term value of environmental benefit is desired/needed?
2. What is the minimum change that you would accept?
3. What proportion of the farming population (or area of land) do you need to reach in order to achieve this target?
4. Are the long-term data available (or failing that, a point estimate) of the current value against which to measure change?
5. What is the distribution of prior probabilities for selecting unfavourable (to you) practices in the farming population (questions 8-10 address this issue)?
6. What is the inherent predictability of the type of event which the evidence base will be required to deal with? (i.e. what order of information quality is likely to be achieved from research given the level of available funding?).
7. Is this sufficient to deliver what is needed, given the answers to questions 1, 2, 3, and 5?
Similarly, participative assessment carried out by researchers and end-users should consider the following questions:
8. What do you think the chances are of you losing money if you adopt [fill in alternative practice] instead of/in addition to what you are currently doing?
9. What do you think your loss would be relative to your current position?
10. How sure would you need to be that no loss would occur in order to switch to a new practice?
Research Undertaken
The research, which links Programmes 1 and 2 with Programme 3, has involved two strands of work. In one of these we have returned to the underlying principles of information theory, probability theory and decision making to develop an analytical framework for ex ante analysis of research impact. In the second strand we have looked at case studies in crop protection and invasive species risk assessment to examine the implications of the analytical framework in practical contexts.
Policy Implications
The suggested methodology has several implications for future policy development including:
- A migration towards more participative and inclusive policy development
- An increase in solutions to policy problems that focus on deliberative and social learning approaches and a decreased emphasis on one-shot technological fixes
- An increase in the timescale from statement of the policy objective to deployment of a solution, but an increase in acceptability and uptake of solutions
Author
Dr Neil McRoberts, SAC neil.mcroberts@sac.ac.uk
Topics
Sustainability and Communities
