Adaptive decisions plan for change over time, such that management options can be tailored to different multiple plausible futures as they unfold, or as new information becomes available.

When to use

Adaptive decisions exploit the opportunity to change direction over time. The lack of information that defines multiple plausible futures might improve over time, making it possible, for example, to plan for a single best projection, use probabilities, or plan for the worst case. Our conceptualisation of the multiple plausible futures we face can also evolve.

As part of short-term decision making in the face of multiple plausible futures, we can consider what information we might gain over time, how future decisions could use that information, and what that means for the decisions we have to make now.


As an approach for coping with multiple plausible futures, adaptive decisions require [1]:
  • Sufficient flexibility to be able to change future decisions
  • Sufficient lead-time to change course and for the change to influence outcomes, e.g. completing implementation of infrastructural and non-infrastructural projects
  • Sufficient uncertainty over the planning horizon. Adapting over time involves transaction costs, and benefits over a static, non-adaptive approach should outweigh these costs

How

At its simplest, making an adaptive decision involves deferring management of an uncertainty to later. Effectively deferring uncertainty management requires clear delegation: the uncertainty does need to be managed before it becomes a problem, and the decision makers involved need to be aware they have been made responsible and have the capacity required. It is assumed that until the uncertainty is addressed, risk of unacceptable impacts from not taking immediate action is considered tolerable.

Management of the uncertainty can be deferred until:

  • The next stage of planning, e.g. at a more local level, a scheduled review of a plan, or next time the issue is raised.
  • A trigger event, i.e. based on monitoring of a system.

We can reason about information we might gain over time by developing monitoring plans and identifying signposts to look out for.

We can reason about how future decisions could use that information in terms of value of information and identification of triggers that would ensure objectives can still be met

In the short term, preparatory actions may need to be planned to keep options open or lay the groundwork for a possible change. No-regret actions can also be taken regardless of how the future unfolds.

Scenarios are a common element to all these planning analyses. They describe assumptions about the future which inform which changes in conditions we need to look out for and what effect possible actions might have in those different futures.

Adaptive pathways can describe sequences of actions and circumstances in which they can be taken. A number of approaches can be used to construct such sequences, e.g.

  • Adaptation pathways, deciding when and under which conditions acceptable actions need to be implemented
  • Dynamic Adaptive Planning or (Dynamic) Adaptive Policymaking, which outlines a set of actions used to increase robustness of an initial plan
  • Dynamic Adaptive Policy Pathways, which develops a robust and adaptive plan, combining adaptation pathways and dynamic adaptive planning concepts.

Selected examples

  • Beh et al. (2015) sequences water supply options in Adelaide, Australia.
  • Groves et al. (2008) considers near and long term urban water management actions for the Inland Empire Utilities Agency, California, USA
  • Resources

  • Maier HR, Guillaume JHA, van Delden H, Riddell GA, Haasnoot M, Kwakkel JH (2016) An Uncertain Future, Deep Uncertainty, Scenarios, Robustness and Adaptation: How Do They Fit Together?. Environmental Modelling & Software 81 (July): 154–64. doi:10.1016/j.envsoft.2016.03.014
  • Notes

  • [1] Maier HR, Guillaume JHA, van Delden H, Riddell GA, Haasnoot M, Kwakkel JH (2016) An Uncertain Future, Deep Uncertainty, Scenarios, Robustness and Adaptation: How Do They Fit Together?. Environmental Modelling & Software 81 (July): 154–64. doi:10.1016/j.envsoft.2016.03.014