Success and Failure of Decision Support Systems for Integrated Water Resource Management
in collaboration with UNESCO-ROSTE
and founded by the EC Human Resource Development Programme (Marie Curie Actions)
6-7 October 2005
Palazzo Zorzi
Venice, Italy
Last update: 8 September 2005
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Success and Failure of Decision Support Systems for Integrated Water Resource Management
in collaboration with UNESCO-ROSTE
and founded by the EC Human Resource Development Programme (Marie Curie Actions)
Workshop overview
The Decision Support Systems (DSS) are frequently defined as computer based systems able to improve the ultimate effectiveness of decision making involving ill- or semi-structured problems. Generally, although employing distinct approaches, DSS are expected to explore multiple perspectives of the problem at hand; enhance decision makers’ insight in the problems drivers and policy outcomes; and facilitate communication and knowledge transfer between the actors involved in or affected by the decision. In environmental policy fields, having to tackle complex and interwoven issues, DSS also play a crucial role as a catalyst of interdisciplinary research and promoter of scientific policy advice. Numerous DSS have been developed, integrating advanced modelling, simulation, optimization and knowledge-based tools with spatial data management functionality. These systems differ considerably according to the problems targeted, the scales considered, and the objectives aimed at. More recently, research and development projects have been funded under the 5th EU research framework (1999-2002) to address issues related to harmonising modelling tools and developing integrated DSS to assist the implementation of the Water Framework Directive (WFD).
Over the past decades the DSS seem to have been continuously loosing their appeal, most importantly because of their conceptual ambiguity and frustration related to the lack of successful implementation. Using DSS to solve real-world decision problems, however theoretically sound and justifiable they may be, is beset by several snags, and the risk of decision support systems failing to be up to the challenge of real-world problems is reported to be high. There are many reasons for a low acceptance of DSS among policy makers. In many cases the systems developed to tackle specific issues fail to address the problems’ changing context. System complexity, highly demanding user interfaces not geared to users’ skills, low transparency of the system’s mode of operation (‘black box’ technology), mismatch between requested and supplied functionality, failure to consider the institutional issue of DSS implementation are also frequently quoted reasons for DSS failure.
Cognitive obstacles, such as an aversion among senior executives to DSS technology, have been reported as significant in specific situations. In addition, the overwhelming majority of decision support systems have been developed in an academic environment, which implies limited scope to oversee the implementation process and the adaptation of the DSS to specific organisational contexts once the corresponding research project has been completed.
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