The preceding example illustrates a common survey instrument, which is used to ascertain the relative importance of one requirement versus another using a scale of five to nine points from the lowest degree to the highest. This tool is also often used in conjunction with a rank order scale, which asks customers to rank each requirement from 1-N so the company can identify the highest-ranking requirements.
The problem with this methodology is two fold. In many circumstances, the customers will say virtually every requirement is important or very important to them. There is no downside to ranking virtually everything as important or very important.
The other problem with this tool is there is no way to know which and how many requirements absolutely have to be in the product. Nor is there any way to know which requirements will be competitive differentiators and will delight the customer, resulting in them buying your product rather than the competition's.
These questions can be difficult to answer, but thankfully there is a tool to help us understand what functions or features need to be in a product, as well as which functions or features will delight our customers. This tool is called the Kano model.
Dr. Noriaki Kano, a Japanese professor and international consultant, first developed the Kano model. In the late 1970s and early 1980s, he laid the foundation for an approach to quality creation. Dr. Kano questioned the traditional ideal of customer satisfaction that more is better—that the better you perform on each product or service attribute or criteria, the more satisfied your customers will be. Instead, Dr. Kano held that performance in all product and service attributes is not necessarily equal in the eyes of customers. Better performance in certain categories of attributes produces higher levels of satisfaction than other categories. He wanted to explain and demonstrate how different classifications/categories of customer requirements and features have the ability to satisfy customers in different ways. By better understanding how customer requirements impact customer satisfaction, we can do a better job of taking the feedback we've received from our customers, and find the best features that will increase their satisfaction, thereby resulting in their choosing our product over the competition.
Before we discuss how to incorporate the Kano model into your customer VoC process, it is necessary to understand the components of the Kano model and how it helps us define needs and delighters.
The model begins with looking at customer satisfaction or perception. The Kano model draws customer satisfaction on the vertical axis and goes from total satisfaction or delight, to total dissatisfaction or frustration. The following image is a representation of the scale on this axis:
You may see this and think you must always be at the top of that scale in the Delighted area of the graph. While this is a noble goal, you will find it is a whole lot harder than you may think to occupy that space in a customer's mind, especially in a consistent way.
The horizontal axis represents the functionality the product delivers, or what the user gets when evaluating customer perception. You can also look at the horizontal scale as a function of how much effort a company put in to develop the product, the level of investment in the development of the product, or how well the functionality has been implemented in the product:
Together, the level of customer satisfaction versus the level of functionality gives us a good understanding of how our customers feel about out product's features. Let's see these features in detail:
As you can see, this a linear function and there is a direct correlation between how much additional functionality is added (say, mileage), and the level of our satisfaction. These too are often the product features that customers think about when describing an ideal product. They are likely to say they want a car with better mileage, a phone with a better battery, or internet speed that is faster. These are considered spoken needs.
It is worth noting, however, that higher levels of functionality also typically equate to the level of resources or investment that must be made to deliver it:
You can see this curve in Figure 8.5. Notice how it is very easy to add a little investment to increase customer satisfaction, but it is also worth noting that satisfaction never crosses into the positive side of the graph, regardless of how much more is invested. Once a basic level of satisfaction is met, it is impossible to increase customer satisfaction by an additional amount, regardless of the resources or time investment:
This effect can be shown on the curve in Figure 8.7. You can see how incremental investments into functionality can have a large effect on customer satisfaction. Of course, you can also see that additional investments beyond a certain point may not even fall on the curve and you could be making investments that will yield no additional return.
Exciters don't have to be a whole new platform or product that changes the landscape the way the iPhone did. I remember taking a drive with my fiancée, who had just purchased a Range Rover. It was March, and the clocks had just changed to Daylight Savings Time. My fiancée asked me to change the two clocks in her car—both the analog clock and the digital time readout—while she was taking me to the airport. Since the car was new and neither of us knew how to change the clocks, or were willing to read the manual, I thought I'd tackle the digital dashboard display as I was pretty confident I could navigate the menu structure to make that change. The analog clock I was less confident about, as there appeared to be no dials or switches to advance the time.
As suspected, I was able to navigate the menus and make the changes to the dashboard time readout without looking through the manual. Much to my amazement, when I changed the time reading on the digital display, the analog clock hands magically moved forward on the face of the clock to mirror the time that was on the digital display. This is a good example, as it shows something does not need to radically change the way we use or interact with a product; it just has to be something that, when exposed to it, customers would say, "Wow… that is really nice!" Of course, if the exciter is for a whole new platform or product category, and ends up being a big innovation, this can also yield explosive results for a company, like the iPhone did for Apple:
Examples of this are the little additional programs that are often packaged with a new PC, or the Microsoft paperclip helper, Clippy. Most people did not like the little assistant and found it especially annoying as there was not an easy way to turn him off:
Figure 8.9 shows the complete Kano model. No doubt, if you were able to question customers on where your current product features lie, you would be able to see that many probably fall into the Performance and Must-Be categories. Hopefully, you don't have many that fall into the Indifferent category, and you have none that would fall into the Reverse category:
You can see in Figure 8.10 how delight decays over time. The key point to remember is that any analysis you do at any given point in time is simply a snapshot of today's reality. The market does not stand still, and customer expectations are ever-changing. The more time that passes after the snapshot you create today, the less valid it will be:
Now that we understand the components of the Kano model, the question is, how do we use it as part of our VoC process, and how can we plot our current and future products on the Kano model to understand our current position in the market, as well as those things that will delight our future customers?
In order to uncover our customers' perceptions of the features we have in our product, or are contemplating for a future release, we use a Kano questionnaire, also known as a Kano survey. The way a Kano questionnaire works is we construct a pair of questions for each feature or function we wish to evaluate. The first asks our customers how they would feel if they had this feature (a functional question) and the second asks them how they would feel if they did not have the feature (a dysfunctional question). For each of these questions, the customer has to choose from five possible responses to each question:
Let's use an example to illustrate the point. The following might be the types of responses we have gotten from potential customers for a set of downhill snow skis:
Taking the first customer request, Good grip on hard-pack snow, we could turn this request/feature into two questions we could ask other customers. The first functional question would be something like this: "If the edges of your skis grip the snow well on hard-packed ski runs, how do you feel?" The second dysfunctional question would be: "If the edges of your skis don't always grip the snow well on hard-packed ski runs, how do you feel?" The customer would then choose one of the five responses for each question:
How the functional and dysfunctional questions are answered tells us a lot about customer attitudes and preferences. If the customer answers the functional question with an "I expect it that way" response and the dysfunctional question with an "I dislike it that way" response, it is something that must be in the product. If the customer answers a functional question with an "I like it that way" response and the dysfunctional question with an "I expect it that way" or a "neutral" or an "I can live with it that way" response, is it something the customer is not expecting and would be a delightful feature in the product. If someone says they dislike the functional question and likes the dysfunctional question, they are clearly not interested in what we are offering and probably wish for the opposite. This is a new category, and it is called Reverse. If you get a large number of people responding with Reverse responses, you may wish to switch your functional and dysfunctional questions around.
It is also worth noting that you may sometimes get conflicting responses to some of your questions. As an example, if your customer responds "like" to both the functional and dysfunctional question, these answers are clearly suspect and you would have a "questionable" answer. Some of these are to be expected, but if you are getting too many, you probably need to re-evaluate your question text.
The following is what a traditional Kano matrix would look like:
The Kano matrix provides an evaluation table that combines the functional and dysfunctional answers in rows and columns to get to a specific Kano category. Every answer pair leads to one of these categories. The keys for each of the cells in Figure 8.13 are as follows:
While this is the traditional model, I find the model put forth by Fred Pouliot makes a little more sense and adds two additional questionable answers at locations (2,2) and (4,4), which looks like the following:
I believe it is important to have a baseline understanding of how each category is derived from each pair of customer responses:
In addition to answering the Kano questionnaire, I find it is also helpful for the customer to rank the individual feature/requirement to determine the relative importance of this feature versus the others as part of the questionnaire. This will aid in establishing customer priorities, as well as understanding the level of satisfaction each feature brings to the customer.
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