recovering from an outage at reasonable levels” (Irias and Cicala 2013). In an initial study, EBMUD used Info-Gap to weigh two options: construct new water pipeline or tunnel crossings to the island or improve the seismic resilience of an existing pipeline. Their goal was to ensure that at any time, one crossing would survive a seismic event, and a second crossing could be returned to service quickly. The key uncertainties were the probabilities of failures and the length of time needed to conduct repairs, which is a sum of the time of individual repair steps: discovery, setup, investigation, and repair. The Info-Gap analysis is currently under way and is helping EBMUD answer two important questions (Irias and Cicala 2013):

- a. _How wrong can we be about the probabilities of various types of failures, and still have an acceptably large overall probability that a crossing survives?_

- b. _For any given design and construction alternative, how wrong can we be about the duration for return to service and still be within the maximum allowable down time?_

# <mark>E. CONCLUSIONS</mark>

67. **Investment decision making is already difficult for any diverse group of actors with different priorities and views.** But the presence of deep uncertainties linked to climate change further challenges decision-making by questioning the robustness of all purportedly optimal solutions. We suggest that decision makers can continue to use the decision metrics they have used in the past. Cost benefit, cost effectiveness, and multi-criteria metrics are still valid for measuring decision options. They differ in their strengths and drawbacks, but these characteristics are distinct from the challenges of applying these metrics in a deeply uncertain world.

68. We suggest that decision makers consider **alternative** decision processes **to traditional ones, especially** those that lead with analysis and end in agreement on decisions. Agree-on-Decision methods start by “stress-testing” options under a wide range of plausible conditions, without requiring us to agree ex ante on which conditions are more or less likely, and against a set of objectives or success metrics, without requiring us to agree ex ante on how to aggregate or weight them. As a result, these methods are easier to apply in contexts of large uncertainty or disagreement on values and objectives.

69. **This inverted process promotes consensus around better decisions and can help manage uncertainty** . Analyses performed in this way do not make the decisions for decision makers or provide a single “best” solution, _deus ex machina_ . Instead, they help decision-makers debate important questions: “Are the conditions under which an option is vulnerable sufficiently likely that we should choose a different option? What tradeoffs do we wish to make between robustness and cost, or between various objectives and policy goals? Which options leave us with most flexibility to respond to changes in the future?” These can be difficult debates. But, they are much more useful than debates about the unknowable future.

70. **A growing set of case studies shows that these methods can be applied in real-world contexts and do not need to be more costly or complicated than traditional approaches.** While this paper focuses on climate change, a better treatment of uncertainties and disagreement would in general improve decision-making and development outcomes.

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