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Where deviation from the expected case is large enough to rearrange the ranking of alternatives, additional work is needed to model the uncertainty and to characterize it in ways that assist the participants in understanding trade-offs. In particular, Table 7. The general public, decision participants, and policy makers will not have the technical background to combine these different sources of risk. Yet this information is critical to developing an understanding of how the different alternatives perform in preventing a catastrophic breakout.

It is up to technical specialists working with the decision participants to finish this task. The use of conservative modeling assumption should be avoided because. In an iterative, collaborative, and deliberative process, it is useful to list and organize each management alternative and each decision objective in a manner that allows the performance of the objective to be seen. A tabular display of this relationship is called a consequence table. Table 8.

The Consequences of Decision-Making - Nils Brunsson - Oxford University Press

In the illustrated case, decision participants sought a solution for conflicts among decision objectives related to generating power, avoiding floods, and enhancing ecological values. This table is likely to have more compact than would a consequence table developed for the Spirit Lake region for comparing system-wide alternatives for managing water and sediment. Development of a consequence table is a key milestone in the decision process.

Because it is built jointly through deliberation among decision participants who are themselves interested and affected parties , it becomes an important element of a valuation framework. Building a consequence table is an iterative process, and early versions may require heavy revisions to capture information properly.


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The ultimate goal is a table that is noncontroversial—that is, participants should see their decision objectives, measured in ways that are both rigorous and meaningful to them and, perhaps, used to evaluate alternatives they helped to develop. The process of developing a consequence table helps the group create legitimacy of subsequent decisions among themselves and with a broad group of interested and affected parties.

Box 8. The methods used may not always have been conducive to public support for management decisions. Comparison of alternatives remains difficult, however. Developing a colored, interactive consequence table can be helpful.

MSIC refers to a pragmatic estimation of the precision of each measurement approach used to populate a consequence table. For example, if the precision of financial models does not allow distinguish-. Alternatives within that range will be considered as equivalent. The color scheme in Table 8. The point of comparison is indicated in blue. Red cells in a particular row indicate alternatives with measures that are worse than the blue point-of-comparison cell; conversely, green cells indicate alternatives with measures that are preferable.

A cell with no color indicates those alternatives with measures that are roughly equivalent within the MSIC to the blue cell. An interactive spreadsheet allows this basis of comparison to be changed during discussion. This interactive visual tool is an excellent aid for exploring how management alternatives align with the decision objectives of the participants. This information may be used to rule out alternatives and criteria that are not key to the decision so that the group can focus on the main decision drivers.

It is important to have a technical discussion about the precision of data being used early in the decision process. The discussion is meant to focus participants on data that potentially drive decisions rather than on data differences that are inconsequential from a technical point of view.

Building key decision making skills

The discussion should be neither a value discussion nor a judgment on the importance of the decision objective to which the data relates. The relevance of this discussion becomes more clear later in the decision process when metrics and decision objectives that have similar measurements i. This early technical discussion can help to discourage later value-laden heated discussions over differences that are inconsequential from a technical point of view. It also provides a solid basis of understanding for discussions regarding the trade-offs across consequences among wider groups of interested and affected parties.

TABLE 8. Decision analysis practitioners have not developed a comprehensive approach to representing uncertainty in a consequence table Gregory and Keeney, If a key trade-off decision hinges on a risk-return consideration, a quick shortcut is to use the expected outcomes e. In the hypothetical example shown as Table 8. According to the chosen statistic, however, alternative 2 also delivers much less spawning habitat once every 10 years.

Choosing between alternatives 1 and 2 requires considering the relative importance of average versus downside impacts. Presenting this type of trade-off and talking about sensitivity to downside risk could be an important line of inquiry in a deliberative process.

Practicing Intelligence

This discussion can improve understanding about why different parties hold different views on the alternatives; about how susceptible the decision objective in question is to the occasionally poor outcome; and, perhaps, about how to identify ways to modify the otherwise preferred alternative to mitigate these rare occurrences. This approach is a substitute for generating a higher-quality inquiry. But it does not fully represent uncertainty because it only looks at two parts of a broader distribution.

Alternative 2 may also have a large but unlikely upside potential that is ignored by this shortcut. The certainty equivalent is the guaranteed amount that an individual would consider equivalent to a given distribution of uncertain amounts. The certainty equivalent differs from the expected value of the distribution according to the risk preference of the individual. A risk-seeking person would have a certainty equivalent greater than the expected value, while a risk-averse person would have a lower certainty equivalent Raiffa, Participants develop the certainty equivalent through a structured discussion.

Clemen and Reilly take this a step further by estimating, through a structured gamble exercise, a risk-aversion parameter for each individual so that uncertain outcomes can be translated mathematically into a certainty equivalent. These more theoretically consistent approaches suffer a similar drawback, however. They greatly increase the process burden, as each decision participant must develop a unique consequence table tailored to reflect his or her unique attitude toward risk.

Step 1: Identify Your Goal

Whether or not this incremental level of effort is warranted depends on the situation. Helping decision participants collaboratively explore multiple alternatives when there is significant uncertainty across multiple objectives is inherently challenging. Attempts to fully incorporate uncertainty can easily lead to an unwieldy and contentious set of deliberations. Nevertheless, upfront transparency regarding the available tools, coupled with an explicit effort to match the techniques to the needs of the participants, can only add legitimacy to the process.

Identifying and closely considering trade-offs is the last step of the decision process. It is useful at this point to recall that the overall purpose of the process is not to find some objectively defined optimal solution, but to. As noted earlier, a common mistake in collaborative decision making is to prioritize objectives too early in the process Keeney, Attempts to do so before decision objectives and their metrics are clarified and consequences are calculated will result in discussion at a level that is too high to uncover and resolve differences.

For example, asking a participant in the Bridge River water management process highlighted in. An effective decision process is based on the recognition that people develop their decision objectives and priorities as they deliberate and learn in a complicated, novel context Slovic, People do not know at the outset how their values interact with what can be changed on the system nor how changing the system leads to intended and unintended impacts to the things they care about.

The trade-off step is about exploring that decision space; looking for insights into how values are affected by the way in which the system reacts to changes; and looking for mutually advantageous solutions or, at least, solutions where important gains for some decision participants can be found without too much sacrifice of the interests of other participants. Developing consequence tables was discussed in the previous sections. The next sections describe practical steps through which decision participants may be led to ultimately highlight the important trade-offs among a small number of alternatives so that a decision may ultimately be made.

Pairwise comparisons of all the alternatives can show how they perform against each other. If an alternative is dominated—that is, not better than any other alternative with respect to all metrics, and worse with respect to at least one metric—it can be eliminated from further consideration. The application of this principle highlights the importance of including all relevant and significant metrics in the consequence table, lest an alternative be dropped prematurely.

Entries in a consequence table should reflect the best available knowledge and science. An early consideration of trade-offs in an iterative. Early in the process, before substantial investigation into all the performance metrics and consequences, some metrics will likely be based on judgment.