FROM DILIP MUKERJEA'S ITINERANT TOOLBOX: ATTRIBUTES GRID

[continued from the Last Post.]

Exercise:

Pair rank the following list of leisure activities for your workforce:

picnic, movies, beach bar-b-q, dinner & dance, and group vacation

Percentile Weighting

When we addressed weighted ranking earlier, it was based on intuition. True weighted ranking, in its arithmetically correct form, is the distribution of percentile values amongst selected items (criteria, attributes, features, etc).

Their sum must equal 1.0. For example, let us consider the following criteria (list of attributes) that we would like to apply when ranking the leisure activities in the preceding exercise:

setting, bonding, relaxation, fun, and savings

We now pair rank these criteria (total votes = 10), and say, our rankings are:

fun, bonding, relaxation, setting, and savings, in descending order of importance. From this prioritised arrangement, we can make a shortlist for weighting; let us take the top three criteria, and give them percentile weights as follows:

fun 0.5
bonding 0.4
relaxation 0.1

TOTAL 1.0

We now construct a grid or matrix that allows us to tabulate our weighted rankings for the leisure activities.

Using one criterion at a time, pair rank the leisure activities. Let us say the outcome was as follows:


We now multiply each category score by its weight, total the scores, and then establish the final ranking, as shown below:


[To be continued in the Next Post. Excerpted from 'Surfing the Intellect: Building Intellectual Capital for a Knowledge Economy', by Dilip Mukerjea. All images in this post are the intellectual property of Dilip Mukerjea.]