Guidance for Interactive Decision Support Systems (DSS)

Multiple-objective planning increasingly relies on interactive decision support systems (DSS) that provide transparency and stakeholder engagement. The need for a robust, transparent interactive DSS tends to increase with the number of planning objectives and the complexity of the tradeoffs among planning options. At the same time, the data requirements, technical challenges, and cost of DSS implementation also increase. This page provides guidance for using interactive DSS to support coastal and marine management, including ecosystem-based management (EBM) and marine spatial planning (MSP).

Keep users’ needs at the forefront when developing DSS.

Prior to investing time and money in technology development, it is essential to determine what type of DSS will be most useful for users. Some key questions to consider include:

  • Who will be using the DSS, and what role will it play within an EBM or MSP decision-making process?
  • Will users be staff members at government agencies involved in decision-making, stakeholders at a workshop, or stakeholders logging in from their home computers?
  • What skills are required to develop the DSS platform?

Based on the needs assessment, detailed technical specifications should be developed and used as the blueprint for building the DSS. Note that it may be necessary to modify the DSS as user needs evolve.

Enable users to explore tradeoffs and develop potential solutions themselves.

There are three general approaches to decision support for multiple objective planning:

  • Pre-defined Scenarios: The DSS presents a pre-defined set of alternative solutions for users to consider.
  • Trade-off Analyses: The DSS allows users to weigh the tradeoffs between objectives without actually determining solutions. The utility of weighing objectives is to discuss these spatially explicit relationships in decision-making forums.
  • User-developed Solutions: The DSS enables users to explore management scenarios by developing their own solutions or proposed alternatives.

In many cases, the third approach is preferable because it increases the transparency of the process and helps build ownership for the decision among stakeholders. In addition, it allows for multiple stakeholders to review a large amount of information collaboratively and to discover relationships and proposed solutions together.

Recommended Features

A decision support system for multiple objective planning should include or link to the following features:

  • An intuitive user interface
  • A concise description of the role of the DSS in the planning process
  • Easy comparison of management alternatives and tradeoffs
  • Authoritative data with accepted standards endorsed by government
  • Downloadable data that can be moved easily among different platforms
  • A straightforward, understandable explanation of uncertainty, accuracy, and limitations associated with the tool and underlying information
  • Technologists who are available throughout the MSP process to provide user support and to refine the DSS as needed to meet planning

Ease of use of DSS technology is paramount.

Stakeholders and partners usually have very limited time available for participating in multi-objective planning, and it is important that they do not encounter barriers such as difficult-to-use DSS. Similarly, government agencies need DSS that integrate easily with their existing databases and technological formats, do not require technical expertise to use, and need little maintenance.

The most useful DSS can be used in data-rich and data-sparse areas.

In some planning areas, large amounts of data are available, while other planning areas have extremely sparse data with little possibility of collecting new data quickly enough for a planning effort. DSS should be developed and tested in data-rich and -poor regions to ensure that they work in both settings. Some analytical methods that might be incorporated into DSS are only appropriate for data-rich settings and would be impractical or would produce invalid results in data-poor settings. Following this advice is especially worthwhile in large-scale, national efforts that seek to use consistent planning methods in multiple regions.
Adapted from: Beck, M.W, Z. Ferdaña, J. Kachmar, K.K. Morrison, P. Taylor and others. 2009. Best Practices for Marine Spatial Planning. The Nature Conservancy, Arlington, VA. (pdf, 2MB)

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