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Making an impact: how to design relevant and usable decision support systems for conservation

Rose, D., Despot-Belmonte, K., Pollard, J. A., Shears, O. and Robertson, R. J. (2020) Making an impact: how to design relevant and usable decision support systems for conservation. In: Ferreira, C. C. and Klutsch, C. F. C. (eds.) Closing the Knowledge-Implementation Gap in Conservation Science: Evidence Transfer Across Spatiotemporal Scales and Different Stakeholders. Springer. (In Press)

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Abstract/Summary

Decision support systems (DSS) aim to provide evidence in a usable format for decision-makers, thereby improving the prospects for evidence-informed conservation policy and practice. These systems are usually software-based either in computer or app-form, but may exist in other formats such as on paper. Conservation decision-makers are typically faced with complex socio-environmental landscapes, competing stakeholder interests, and irreducible uncertainty. Consequently, conservation has been the focus for numerous decision support systems, which can help users to face the challenge of making trade-offs. Despite the many systems designed for conservation, there is not an accepted framework for how to develop systems that make an impact in practice. There is much evidence, however, to suggest that many systems are failing to make an impact in practice. This chapter draws on lessons learned from conservation and related disciplines on how to design good decision support systems that are desirable to intended end users. To this end, we suggest a five-stage process for participatory user-centred design – (1) identifying the user, (2) proving system value, (3) assessing available infrastructure and focusing on ease of use, (4) adopting a good marketing plan, and (5) establishing a long-term legacy – a process which could be used by researchers and funders alike to ensure that systems will be used by their intended audiences. Above all, we need to change our own design behaviour to increase the relevance and usefulness of the systems we are building. Acknowledging the reality that decision support systems will be implemented in complex and potentially data-sparse environments, we also reflect on how decision support systems can help decision-makers to deal with uncertain information. This final element seeks to establish the value both of quantifying uncertainty and communicating it in accessible ways to decision makers.

Item Type:Book or Report Section
Refereed:No
Divisions:Faculty of Life Sciences > School of Agriculture, Policy and Development > Economic and Social Sciences Division > Food Economics and Marketing (FEM)
ID Code:89782
Publisher:Springer

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