Editor's note: Vince Farace, president, and Mike Swenson, consultant, are with Satisfaction Management Systems, Inc., Minneapolis.

"It's not good enough to go to your customer after you have sold them the product and ask them how satisfied they were. What you need to do is go to your customers before you develop the product or service and find out what is important to them." -- Arnold Weimerskirch, vice president for corporate quality, Honeywell, in a Minnesota Quality Award interview, Twin Cities Business Monthly, November 1997.

As this comment illustrates, satisfying customers begins the moment an organization decides to market a product, a service, or a product and service bundle. This article describes a measurement process for assessing - and predicting - customer reactions to the features included in the product/service bundle.

Efforts to improve customer satisfaction often lead companies to the conclusion that products or services need to be redesigned, because no lesser action truly satisfies. Further, companies are motivated to introduce new products and services by changes in available technology, by competitor initiatives, and by the classic business desire to reap the profits of an effective differentiation strategy.

In many companies, the drive to create new product/service bundles arises entirely from within the organization, based on deep and heartfelt convictions about what is "right" for the customer. But the investment for a new product/service bundle can be staggeringly high - concept development in the millions, with manufacturing, advertising and distribution costs that are orders of magnitude higher. Further, there is a significant opportunity cost - the dollar and human costs at stake if a product fails in the marketplace.

Those companies with a genuine customer orientation change the product development equation - they supplement and guide internal development efforts with a more thorough understanding of customer requirements. In that way, they go into product development opportunities with the belief that they will be more successful in the market if they design-in customer requirements up front. They recognize that this makes the ultimate goal of customer satisfaction that much easier to achieve.

Product feature generation

Once the broad decision is made to develop a new product, there are many ways that the initial list of potential features is developed:

  • creative scientific or entrepreneurial genius, whether one individual or a larger development group;
  • internal groups engaged in brainstorming or visioning exercises.

These sources may be expanded with inputs from various "voice of the customer" systems:

  • root cause analysis of product complaints;
  • observation of product or service use by customers;
  • qualitative in-depth interviews with customers/end users;
  • customer focus groups, directly asking for suggestions.

This process may also be guided by any of a variety of structured product concept development processes.

Product feature development is an expansive process. In some cases hundreds or even thousands of potential feature changes and variations are generated through these techniques. Some of these features are clearly understood by the product development team. Others are not. Some are fairly easy to deliver, others are fraught with technical and cost challenges. At this point it may become necessary to do some feature triage - to decide which features to offer and which to leave behind.

Feature triage

At this point in the product development process companies begin to prune the list of features down to those that they believe are most critical to the introduction of a successful product. Again, the choice is to do this entirely based on internal wisdom, or, alternatively, to bring customers into the decision process - to give the customer a voice at the table in product feature decisions.

Feature triage often starts with affinity or categorization exercises to create feature families. Some features/families may be immediately eliminated because no reasonable/cost-effective means to provide the envisioned feature is available. For other features, an evaluation and planning process that relies heavily on internal experience and secondary data can be used to further help decide which features stay and which go.

When customers are brought into the decision process, one common technique is to ask them to rate the importance of a long list of potential features. However, customers may rate all of the features fairly high, with little differentiation. One weakness of this result is that it does not reveal the underlying structure of the feature in terms of how it will impact customer decisions to purchase the product and their eventual satisfaction with the product.

The Kano method 1

Responding to this need, Professor Noriaki Kano addressed this question in his development of a measurement model that has now been named after him. The Kano model seeks to differentiate between features in four broad categories - between features that:

1. Must-be included

2. Are desirable - more is better

3. Are exciting - the "wow" factor, and

4. Yield indifference - "who cares?"

By understanding the role each potential feature plays in the purchase likelihood and eventual satisfaction of customers, organizations can maximize the business benefits of new products while avoiding unnecessary extras that would add cost but with little added benefit. The four Kano categories are described more fully below.

Exciting - While the absence of this feature has little if any negative effect, introducing it generates excitement and satisfaction. (These are also called latent features.) For example, a few years ago, cupholders were new to mini-van buyers and gave the first manufacturers who introduced them a temporary edge. Tamper-proof tops on containers in the consumer market are another example, as are the first portable computers.

Desired - These requirements correlate to satisfaction in a more or less straight-line fashion, where "none is bad, a little is good, and more is better." One example would be gas mileage in a car, where low mpg can result in customer dissatisfaction, higher numbers will improve on that, and (other things being equal) mpg that is higher still will take satisfaction even higher. Reliability and longevity are typical other examples.

Indifferent - Sometimes customers will say they want something, but in reality, it plays no real role in producing satisfaction. This type of requirement might occur, for example, around expectations like "good for the environment" or "help society" which can foster satisfaction in some contexts but have no effect in others.

Must-be - These requirements are necessary for a product to even be considered. They are the equivalent of "table stakes." Once that level is achieved, "more" has little or no impact on satisfaction. For example, an airline must meet certain standards or travelers will not fly on it. But once the standards are met, meeting higher standards may have little or no impact on satisfaction. (This obviously can vary by market segment.)

The Kano measurement model

The Kano survey process is designed to classify requirements into one of the four categories (exciting, desired, indifferent or must-be), and also to yield other valuable insights into customer needs. Although infrequently used as a measurement process, it is receiving more attention in current times. 2 Kano does this through a highly structured questioning technique that involves functional (positive) and dysfunctional (negative) question pairs to explore each feature being considered. For example, a functional question like "How do you feel if gas mileage is good (or some specific value)?" is followed by its dysfunctional equivalent - "How do you feel if gas mileage is poor (or a lower specific value)?"

An example of the paired questioning method
Functional

1a. If the gas mileage is 35 miles per gallon for highway driving how do you feel?

1. I like it that way

2. It must be that way

3. I am neutral

4. I can live with it that way

5. I dislike it that way

Dysfunctional

1b. If the gas mileage is 20 miles per gallon for highway driving, how do you feel?

1. I like it that way

2. It must be that way

3. I am neutral

4. I can live with it that way

5. I dislike it that way

Note: Other wording for the categories has been tried, with varying degrees of success. Also, particular care must be taken in different cultural settings to convey the proper ideas.

Stated importance

Very often a more standard importance question is asked in addition to the Kano pairs. This can be assessed by a variety of methods including the anchored 10-point scale, from "Not at all important" to "Very important." If time allows, or money is available for a separate survey process, we recommend asking importance using a constant sum measurement process. By asking respondents to distribute 100 points across a set of features based on how important the features are to them, we are able to achieve better variation between features.

  • Data collection - Data for Kano analysis can be collected by means of standard survey processes, whether paper, telephone interview or Internet/Web survey.

  • Data analysis - The Kano process includes a very specific approach for plotting responses in an evaluation table and then offers various methods for doing further analysis. The final result is an exceptionally clear set of statements about what customers want and the precise nature of those expectations. By helping make decisions on product function, this data can also guide the allocation of R&D resources and even the structure of production or service delivery processes. It yields a product/service bundle with functional characteristics that will maximize customer satisfaction, but without unnecessary extras that add cost but no further satisfaction gains.

For each pair of questions a new variable is created that classifies each respondent's answers to that pair of questions into one of the categories used below. Those new variables can then be used in a variety of analytical procedures.

And the customer requirement is:

A: Attractive/Exciting

M: Must-be

R: Reverse

O: One-dimensional/Desired

Q: Questionable result

I: Indifferent

When analyzing at the aggregate level some companies classify the feature by its mode. In our view this approach ignores valuable information. We prefer to report the full frequency response of categories. We then work with our client to develop a weighting scheme for each classification. For example if the client thinks that a "must be" response is twice as important as a "one-dimensional/desired" response, then you could weight each "must be" a value of 10 and each "one-dimensional/desired" response with a value of five. Once a weighting scheme has been agreed upon an aggregate priority score can be calculated for each feature.

In addition to the basic classification decisions and representation, data can be analyzed and summarized in a variety of other ways.

  • Significance testing between known segments can be conducted.
  • If the data is translated into dummy codes it can be used for cluster analysis to develop need driven segmentation schemes.
  • Stated importance can be integrated or considered separately.
  • Data representation - It helps to keep the diagram on page 61 in mind while envisioning what customers are contributing to the feature triage process.

Observations and lessons

1. Like any measurement process, the clarity of thought that goes into the design foreshadows the clarity of results achieved. For the Kano method, proper specification of feature levels is critical. However, mis-specification of feature levels is quite possible. We came across a situation where a feature fell into the "indifferent" category. When we analyzed it further we found that customers described both the functional and the dysfunctional descriptions of the attribute as "must-be." Instead of seeing a new capability as a substitute for an old capability, customers felt that the new capability was a complement. They expected both features.

2. There is some flexibility in the way the paired functional/dysfunctional questions are asked. The gas mileage example provided above shows a form that has worked well for us.

3. While Kano is principally a measurement process, its effectiveness is increased if it is embedded in a structured consulting process in which the research practitioners are given a seat at the table during the feature development process. A full understanding of what the development team is seeking is critical in constructing the proper questions. Similarly, once the results are back, the practitioner should be prepared to work with the development team to interpret the results and the light they shed on the program's next steps.

4. Muddied results can sometimes be due to confusion in the underlying market segmentation on which the Kano data are drawn. If basically dissimilar market segments are represented in the sample, the fact that the results are difficult to interpret may mean that one segment views the attribute in a different light than the other segment's respondents. The solution, of course, is to anticipate segmentation possibilities for the product early on in the design stage of the Kano process. By including potential segmentation variables from databases, or asking segment identification questions you increase your ability to clarify the results through analysis.

Link to conjoint

Kano may serve as a precursor to a conjoint analysis3 study, a powerful technique for assessing the impact of various levels of feature dimensions on customer preference. Conjoint studies give valuable insight into the interaction of various features and their levels, but it suffers from exponential growth in possible combinations as features and levels are added. Kano is better at dealing with a large number of features, though one dimension at a time. Kano is also far less complex to administer. Kano is a process whose question form makes intuitive sense to clients and respondents, a significant factor especially in business-to-business research. Finally, Kano may prevent you from wasting conjoint resources varying the level of a "given" variable, thus releasing you to focus the conjoint analysis on combinations of desired or exciting features.

Links to CVM

In a related article4 along with many other sources5, customer value management (CVM) has been used to provide strategic navigation to an organization, enabling the organization to differentiate itself and grow its business by providing greater relative value in the marketplace. Customer value attributes at the broadest level consist of the benefits customers expect and the costs they anticipate paying. Each of the benefits translates into lower-level attributes expressed in the product/service bundles the organization delivers to the marketplace. Basically, the Kano method becomes a precise technique for assessing the role of prospective product features in supporting the overall strategic directions of the organization, as presented in its customer value equation.

Achieve goals

By responding to customer requirements in the product/service development process, a company can achieve its ultimate customer satisfaction goals more easily. Once the set of features for the new product is identified, the Kano method offers a way to bring customer input formally into the product development process. Including customer requirements up front makes it more likely that customers will purchase the product, and, in the end, be satisfied with it. Kano studies can aid in choosing a more focused set of attributes for a conjoint study. And finally, Kano studies may also be used to clarify the structure of product features that feed into broader product/company attributes used in CVM evaluations.

References

1 See Center for Quality Management Journal, 2, 4, Fall 1993. "Special Issue on Kano's Methods for Understanding Customer-defined Quality."

2 Lee, Mark C., and Newcomb, John F. Applying the Kano Methodology to Meet Customer Requirements: NASA's Microgravity Science Program. QMJ 97 4, no. 3, 95-109.

3 Green, Paul E., and Krieger, Abba M. "Using Conjoint Analysis to View Competitive Interaction through the Customer's Eye": in 1997. Wharton on Competitive Dynamic Strategy, editors, George S. Day and David J. Reibstein, New York, Chichester, Weinheim, Brisbase, Singapore and Toronto: John Wiley & Sons.

4 Farace, Vince and Meola, Jeri. Gaining strategic business advantage through customer value measurement. Quirk's Marketing Research Review. October 1997.

5 Gale, Bradley T. 1994. Managing Customer Value: Creating Quality and Service that Customers Can See. New York, N.Y.: Simon & Schuster.