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Emerging consensus on desirable characteristics of tools to support farmers' management of climate risk in Australia


  • Hochman, Z.
  • Carberry, P.S.


The prospect that decision support systems (DSS) can help farmers adjust their management to suit seasonal conditions by putting scientific knowledge and rational risk management algorithms at farmers' fingertips continues to challenge the science and extension community. A number of reviews of agricultural DSS have called for a re-appraisal of the field and for the need to reflect on past mistakes and to learn from social and management theory. The objective of this paper was to investigate whether there is an emerging consensus, among stakeholders in DSS for Australian agriculture, about the lessons learned from past experience with DSS tools. This investigation was conducted in three parts. The first part was a distillation of suggestions for best practice from the relevant literature. The second part was a reflection on what the champions of five current DSS development and delivery efforts in Australia learned from their recent efforts. The third part tested the level of support for the combined findings from the first and second approaches by surveying 23 stakeholders in the research, development, delivery and funding of DSS. The key propositions relating to best practice that were supported by the survey, listed according to the strength of support, were: 1. It is essential to have a plan for delivery of the DSS beyond the initial funding period. 2. DSS need to be embedded in a support network consisting of farmers, consultants and researchers. 3. DSS development requires the commitment of a critical mass of appropriately skilled people. 4. A DSS should aim to educate farmers' intuition rather than replace it with optimised recommendations. 5. A DSS should enable users to experiment with options that satisfy their needs rather than attempt to present 'optimised' solutions. 6. DSS tools stand on the quality and authority of their underlying science and require ongoing improvement, testing and validation. 7. DSS development should not commence unless it is backed by marketing information and a plan for delivery of the DSS beyond the initial funding period. While the DSS stakeholders supported the proposition that it is essential to have a plan for delivery of a DSS beyond the funding period, the majority resisted the notion of DSS development being market-driven and especially commercial delivery of DSS. We argue that since public funding of the delivery of DSS for farmers' management of climate risk is highly unlikely, reaping the benefits of lessons learned from past efforts will require that DSS stakeholders change their perception of the commercial delivery model or find an alternative way to fund the delivery of DSS beyond the R&D phase.

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  • Hochman, Z. & Carberry, P.S., 2011. "Emerging consensus on desirable characteristics of tools to support farmers' management of climate risk in Australia," Agricultural Systems, Elsevier, vol. 104(6), pages 441-450, July.
  • Handle: RePEc:eee:agisys:v:104:y:2011:i:6:p:441-450

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    References listed on IDEAS

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    Cited by:

    1. Rose, David C. & Sutherland, William J. & Parker, Caroline & Lobley, Matt & Winter, Michael & Morris, Carol & Twining, Susan & Ffoulkes, Charles & Amano, Tatsuya & Dicks, Lynn V., 2016. "Decision support tools for agriculture: Towards effective design and delivery," Agricultural Systems, Elsevier, vol. 149(C), pages 165-174.
    2. repec:eee:agisys:v:159:y:2018:i:c:p:9-20 is not listed on IDEAS
    3. Monjardino, M. & McBeath, T. & Ouzman, J. & Llewellyn, R. & Jones, B., 2015. "Farmer risk-aversion limits closure of yield and profit gaps: A study of nitrogen management in the southern Australian wheatbelt," Agricultural Systems, Elsevier, vol. 137(C), pages 108-118.
    4. Kragt, Marit Ellen & Llewellyn, Rick S., 2013. "Using choice experiments to improve the design of weed decision support tools," Working Papers 147031, University of Western Australia, School of Agricultural and Resource Economics.


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