Page 196 - The Six Sigma Project Planner

Next, we must determine importance placed on each item by customers. There are a
number of ways to do this.
• Have customers assign importance weights using a numerical scale (e.g., “How
important is ‘Easy self-help’ on a scale between 1 and 10?”).
• Have customers assign importance using a subjective scale (e.g., unimportant,
important, very important, etc.).
• Have customers “spend” $100 by allocating it among the various items. In these
cases, it is generally easier for the customer to first allocate the $100 to the major
categories, then allocate another $100 to items within each category.

• Have customers evaluate a set of hypothetical product offerings and indicate
their preference for each product by ranking the offerings, assigning a ‘likely to
buy’ rating, etc. The product offerings include a mix of items carefully selected
from the list of customer demands. The items are selected in such a way that the
relative value the customer places on each item in the offering can be determined
from the preference ranks. This is known as conjoint analysis, an advanced
technique that is covered in most texts on marketing statistics.
• Have customers evaluate the items in pairs, assigning a preference rating to one
of the items in each pair or deciding that both items in a pair are equally
important. This is less tedious if the major categories are evaluated first, then the
items within each category. The evaluation can use either numeric values or
descriptive labels that are converted to numeric values. The pairwise
comparisons can be analyzed to derive item weights using a method known as
the analytic hierarchy process (AHP) to determine the relative importance
assigned to all of the items.

All of the above methods have their advantages and disadvantages. The simple
methods are easy to use but less powerful (i.e., the assigned weights are less likely to
reflect actual weights). The more advanced conjoint method requires special skills to
analyze and interpret properly. We will illustrate the use of AHP for our hypothetical
software product. AHP is a powerful technique that has been proven in a wide variety
of applications, yet it can be analyzed with spreadsheet software. In addition to its use
in determining customer importance values, it is useful for decision-making in general.

Category Importance Weights
We begin our analysis by making pairwise comparison at the top level. The affinity
analysis identified five categories: “easy to learn,” “easy to use quickly after I’ve learned
it,” “Internet connectivity,” “works well with other software I own,” and “easy to
maintain.” Arrange these items in a matrix as shown in Figure 35.

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