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#1 Posted : Friday, July 18, 2014 10:29:52 PM(UTC)
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Risk Managers, like other professionals, are often challenged to obtain data for inherently subjective matters. For a Risk Manager, this may involve conducting surveys to identify top risks or prospects, or combining expert opinions of likelihood or consequence to arrive at an average or consensus estimate of a risk level. Opinions and surveys are sometimes the only interrogative prerogative for arriving at numerical values for the naturally qualitative, and at other times, they are a convenient supplemental validations for more scientifically derived estimates. While polls and opinions are helpful in sorting items in a sequential ranking, they often provide little by way of relative importance of the items under consideration.

To support managers interested in a more meaningful approach to surveys, we offer a reminder for a simple method called analytical hierarchy processing of pairwise comparisons. In this approach, you can establish a set of risks or prospects or really anything, as well as a common set of dimensions for comparison. For example, if you are dealing with a set of prospects, you may wish to include dimensions such as Market Share Potential, Capital Requirements, Concentration of Supply, Profit Margin, and other attributes. With the subject set complete and the dimensions defined, you can begin surveying participants.

The survey is a little different from other surveys, and a little more time consuming because the responses are multi-dimensional. Respondents begin by ranking the dimensions according to their own opinion as to the order of importance, and then indicate the relative importance of each dimension to the attribute ranked above it. For example, if the respondent thinks Margin is the most important, followed by Capital, they do not just rank Margin first and Capital second, they also provide a relative score to indicate how much more important Margin is. So if Margin is twice as important than Capital, Capital would receive a rating of 2.

Next, respondents enter a score (1-9) for each dimension (e.g., capital, margin, etc.) for each item in the set (e.g., each opportunity or risk). Once this is done, the respondent has completed the survey, and the results are converted formulaically to an index of all items in the set based on cross-comparisons (pairwise comparisons) of each attribute across the subject set using the respondents relative ranking and ratings of dimensions. The index will include scores between 0 and 1 for each item in the set, with the highest score for the top item.

The risk manager can simply combine the scores for each respondent to analyze composite scores. The risk manager can also capture respondent information to sort, filter or weight scores for more insight.

You can learn more about AHP on the web. In the hopes that you find this informative and helpful, we are happy to include a worksheet that automates this analysis for you here AHP in Excel. Note this is an Excel .xlsm file with macros that you may need to enable to use.

If you have any questions or need assistance, just let us know.

Edited by user Saturday, July 19, 2014 2:36:26 AM(UTC)  | Reason: Not specified

Thank You
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