Realizing modelling outcomes: A synthesis of success factors and their use in a retrospective analysis of 15 Australian water resource projects

• Published in: Environmental modelling & software : with environment data news 2017-08, Vol.94, p.63-72
• Main Authors: Merritt, W.S., Fu, B., Ticehurst, J.L., El Sawah, S., Vigiak, O., Roberts, A.M., Dyer, F., Pollino, C.A., Guillaume, J.H.A., Croke, B.F.W., Jakeman, A.J.
• Format: Article
• Language: English
• Subjects: Decision support; Evaluation; Integrated modelling; Project management; Projects; Social learning; Stakeholders; Studies; Success factors; Water resources
• ISSN: 1364-8152; 1873-6726
• DOI: 10.1016/j.envsoft.2017.03.021

We review several papers that have afforded insights into determinants of positive outcomes (e.g. the adoption of tools, improved learning and/or collaboration) from modelling projects. From a subsequent internet search in the environmental domain we identified 33 such factors that are then invoked in a transferable survey-based method to facilitate structured reflections by model developers on 15 projects. Four factors were considered most necessary to realize overall success for any modelling project. Three factors related to aspects of stakeholder engagement in the modelling process; the other to critical thinking around problem framing and the role(s) of models. The latter factor was considered reasonably well-achieved across the projects. Harder to control were the stakeholder engagement factors which, along with project management considerations, can constrain or enable achievement of other factors. The paper provides further evidence of the critical need to consider non-technical aspects in the design and implementation of modelling projects. •Synthesis identified 33 factors influencing the success of environmental integrated modelling or decision support projects.•We to initiate a line of quantitative evidence regarding the influence of these factors on the extent to which project outcomes are met.•Stakeholder engagement factors enable achievement of model development, use and evaluation factors.