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Deployment of customer needs in the QFD using a modified Kano Model
Gerson TontiniABSTRACT
The quality of a product or service is key for customer satisfaction. The level of satisfaction is ultimately dependent on the fulfillment of customer needs. Quality Function Deployment (QFD) has been an important tool in the translation of the voice of the customer (VOC) into product's specification. Since de impact on customer satisfaction is different for each customer requirement, it is very important to determine which attributes of a product or service bring more satisfaction than others. It is also important to use this information in an appropriate way in the QFD process. The Kano Model of customer satisfaction can determine attractive or must-be requirements, and can be used in the QFD matrix to assure that the most critical needs are translated into the next phases of product development. This paper shows a modified Kano method to determine the degree that an attribute is considered attractive or must-be by the customers. It also shows how to integrate the proposed modified Kano method in the planning matrix of the QFD.
INTRODUCTION
As the competition for new markets and customers increased, the level of customer satisfaction also became a key factor for long-term business success. Satisfied customers are loyal customers and ensure a lasting cash flow in the future. According to Reichfeld and Sasser (1990), an increase in customer loyalty by 5% can increase the profit of a business by 100% due to the fact that satisfied customers purchase the products of a company more often and in greater quantities. In general, satisfied customers are less price-sensitive and more inclined to spend more on tried and tested products.
Quality Function Deployment, or simply QFD (Akao, 1990; Clausing, 1994; Cohen, 1995), has been an important tool in the translation of the voice of the customer (VOC) into product's specification. It has been widely used for product development and quality improvement around the World. It is a customer-oriented approach, supporting design teams in developing new products based on an assessment of customer needs. Basically, in the QFD, customer needs are translated into design attributes. The design attributes are then deployed in process and quality requirements.
The fulfillment of customer needs depends on the existence and performance of certain product or service features. In this paper we call these features as customer requirements. There are some requirements that bring more satisfaction than others. For example, in a restaurant, free dessert can bring satisfaction to customers, but a surprise gift at the end of the dinner can create an excellent impression and be a differentiation factor from other restaurants. If a business identifies these requirements in its products or services, it can achieve a high degree of customer satisfaction. Therefore it is very important to determine which requirements of a product or service bring more satisfaction than others.
The Kano model of customer satisfaction (Kano, 1984) can determine which requirements of a product or service bring more than proportional satisfaction to customers. Also, it determines which requirements don't bring satisfaction when present, but bring dissatisfaction when they are not met. By using the Kano Model and integrating it in the QFD, the design team can enhance the understanding of customer needs.
The rest of this paper is organized as follows. First, the QFD process is briefly introduced. Than we describe the Kano Model of customer satisfaction (Kano, 1984) and the Customer Satisfaction Coefficient (Berger et al., 1993). Then a modified Kano method and a modified Customer Satisfaction Coefficient are discussed. Finally we discuss the integration of the Kano model into the QFD.
QUALITY FUNCTION DEPLOYMENT
The QFD (Akao, 1990; Clausing, 1994; Cohen, 1995) is a design methodology based on customer needs. To start the design process in the QFD, the design team needs to listen the Voice of the Customer (VOC). The VOC should contain the customer needs and is expressed in customer words. Usually it is determined through personal interviews and/or focus groups. Then, customer requirements are determined based on the identified needs.
After the requirements were identified, a quantitative marketing research is conducted to evaluate the competitive position of the product in the market (in terms of customer satisfaction) and the importance that customers give to each of the requirements. Based on the competitive analysis, a target for customer satisfaction is set for each requirement. Than, an improvement ratio is calculated (target / current satisfaction). This improvement ratio is multiplied by the importance that the customer gives to each requirement (improvement factor X importance), and the relative weight of the requirements is than calculated (figure 1 shows a hypothetical example).
A set of design attributes that could fulfill the customer requirements is then determined. Customer requirements and design attributes are correlated in a matrix called House of Quality. The House of Quality, also called A-1 matrix, is the most commonly used matrix in the QFD methodology (Tan & Shen, 2000). This matrix translates the voice of the customer into product specifications (figure 2).
Relative weights for the design attributes are calculated based on the strength of correlation between design attributes and customer requirements, and the relative importance of the customer requirements. The specifications for the design attributes are defined after doing competitive analysis between the product being improved (or developed) and its competitors or similar products. The roof matrix identifies the physical relationships between the design attributes and is very helpful in making trade-offs. Sometimes the improvement of one attribute leads to degradation of other attribute.
After determining product's specifications and their relative importance, other matrixes are developed to determine process specifications, quality control specifications and material requirements.
KANO MODEL OF CUSTOMER SATISFACTION
Kano Model (Kano, 1984) distinguishes between three types of product or service requirements that influence customer satisfaction (see Figure 3):
[FIGURE 3 OMITTED]
Must-be requirements. The must-be requirements are basic criteria of a product. If these requirements are not present or are insufficient, customers will be extremely dissatisfied. On the other hand, if these requirements are present or sufficient, they do not bring satisfaction. In fact, customers see these requirements as prerequisites. For example, if a restaurant is very clean, it will not bring satisfaction to the customers because "cleanness" is regarded as a must-be requirement. If a restaurant does not meet the minimum requirement for cleaning, customers will not go to that restaurant at all. Customers usually do not explicitly demand must-be requirements.
One-dimensional requirements. Regarding these requirements, customer satisfaction is proportional to the level of fulfillment--the higher the level of fulfillment, the higher the customer satisfaction and vice-versa. For example, for a given model of car, the higher the mileage per gallon, higher the customer satisfaction. If the mileage per gallon is under a certain level, customers will be dissatisfied. We can say that the lower the mileage per gallon, the higher the dissatisfaction regarding this requirement. In this example, the level of neutral satisfaction is the industry average for that class of car. Usually, customers explicitly demand one-dimensional requirements.
Attractive requirements. These requirements are key to customer satisfaction. The fulfillment of these requirements brings more than proportional satisfaction, but they do not bring dissatisfaction if they are not met. For example, if at the end of a dinner a restaurant gives a complimentary gift to its customers, it will bring satisfaction. If the gift is not offered, it will not bring dissatisfaction to customers. Attractive requirements are neither explicitly expressed nor expected by the customer.
Besides these three different types of requirements, we can identify two more: neutral and reverse requirements (we should call them characteristics, because they are not really a customer "requirement"). Neutral requirements (or characteristics) are those whose presence does not bring satisfaction, but the absence also does not bring dissatisfaction. Examples of neutral characteristics are those product features and characteristics that are never or rarely used by the customer. Reverse characteristics are those whose presence brings dissatisfaction. For example, for some people "Moon Roof" in cars is not welcomed. For these customers, "Moon Roof" can be considered as a reverse characteristic.
IDENTIFYING ATTRACTIVE AND MUST-BE REQUIREMENTS
The identification of attractive and must-be requirements in the Kano Model is based on a questionnaire where the customer states if he feels satisfied or dissatisfied with a hypothetical situation (Fig. 4). For each product requirement a pair of questions is formulated. To each question the customer can answer in one of five different ways (Kano, 1984). The first question, or functional question, identifies the reaction of the customer if the product has the requirement or if the performance of the requirement is sufficient. The second question, or dysfunctional question, identifies the reaction if the product does not have that requirement, or if its performance is insufficient.
CUSTOMER SATISFACTION COEFFICIENT (CS-COEFFICIENT)
Different market segments usually have different needs and expectations; so, sometimes it is not clear whether a certain product requirement can be assigned to the various categories. It is especially important to know the average impact of a product requirement on the satisfaction of all the customers.
The customer satisfaction coefficient states whether meeting a product requirement can increase satisfaction, or whether fulfilling this product requirement merely prevents the customer from being dissatisfied (Berger et al., 1993). The CS-coefficient indicates the percentage of customers that expressed satisfaction with the existence of a certain characteristic (or its sufficiency), and in case of its "non-fulfillment", the percentage of customers that expressed dissatisfaction.
To calculate the percentage of satisfied customers it is necessary to add the number of attractive and one-dimensional responses and divide it by the total number of attractive, one-dimensional, must-be and indifferent responses. For the calculation of the percentage of dissatisfied customers, you should add the number of must-be and one-dimensional responses and divide by the same normalizing factor (see Berger et. al., 1993). The CS-Coefficient may be calculated by the following equations:
Extent of satisfaction with existence or fulfillment:
%S = A+O/A+O+M+I
Extent of dissatisfaction with non-fulfillment:
%D = O+M/(A+O+M+I) x (-1)
A negative sign is put in front of the CS-coefficient of customer dissatisfaction in order to emphasize its negative influence on customer satisfaction if this requirement is not fulfilled. The positive CS-coefficient ranges from 0 to 1; the closer the value is to 1, the higher the number of customers that expressed satisfaction. A positive CS-coefficient that approaches 0 signifies that very few customers expressed satisfaction. At the same time, however, one must take the negative CS-coefficient into consideration. If it approaches -1, the number of customers that expressed dissatisfaction is very high if the particular requirement is not fulfilled. A value around 0 signifies that this requirement does not cause dissatisfaction if it is not met.
The CS-coefficient is an indicative of how strongly a product requirement may influence customer satisfaction or, in case of its "non-fulfillment", dissatisfaction. Figure 6 shows a scatter plot of the CS-Coefficient for 8 requirements of Banking Services (availability of on-line banking, free coffee at branches, free checking, insurance services, phone banking, opening Sundays, ATM banking, branches in supermarkets). To compute the results, a sample of 200 customers of banking services was randomly chosen.
[FIGURE 6 OMITTED]
A MODIFICATION OF THE KANO METHODOLOGY
The identification of the degree of satisfaction or dissatisfaction that a specific requirement brings to customers is of the utmost importance to assure a high degree of business competitiveness. The original Kano method and the Berger's CS-coefficient do not identify the degree of satisfaction, but only the percentage of satisfied or dissatisfied customers. By analyzing figure 6, we may see that the rate of customers that state satisfaction with free coffee (77%) is close to branches opening Sundays (88%).
Tontini (2000) introduced a small variation in the Kano questionnaire in an effort to identify the degree of satisfaction. The answers of the questionnaire where modified accordingly to figure 7.
Figure 8 shows how to classify a requirement based on the answers for the modified Kano questionnaire, utilized in Tontini (2000).
The variation in the Kano model questionnaire, proposed in Tontini (2000), and the consequent modification in the calculation of the CS-coefficient, is in fact a mixture of the rate of satisfied customers with some evaluation of the degree of satisfaction. To get a more accurate measure of the degree of satisfaction or dissatisfaction, Tontini (2003) introduces a modification in the answers for the Kano model questionnaire using a Likert scale as shown in figure 9.
[FIGURE 9 OMITTED]
The CS-coefficients are defined as SI (degree of satisfaction with existence or sufficiency), DI (degree of dissatisfaction with inexistence (or insufficiency), and RI (degree of dissatisfaction with existence--measures a reverse index). The coefficients are calculated as follows:
SI = [SIGMA] degree of satisfaction with existence / Number of valid responses * 5 (only the [greater than or equal to] 0 at the existence column)
DI = [SIGMA] degree of dissatisfaction with inexistence / Number of valid responses * 5 (only the [less than or equal to] 0 at the inexistence column)
RI = [SIGMA] degree of dissatisfaction with existence / Number of valid responses * 5 (only the [less than or equal to] 0 at the existence column)
Figure 11 shows SI, DI and RI coefficients computed by applying this modified Kano questionnaire to the 200 banking service customers. The Berger's CS-coefficients showed at figure 6 where computed using the number of customers who stated satisfaction or dissatisfaction different from zero at the modified Kano questionnaire.
As expected, although the rate of customers that got satisfied with free coffee and opening Sundays is very high using the Berger's CS-coefficient, the degree of satisfaction is very different (0.36 for free coffee and 0.70 for opening Sundays) when calculated by the modified method.
CORRELATION BETWEEN BERGER'S CS-COEFFICIENTS AND THE MODIFIED CS-COEFFICIENT
Since the Berger's CS-Coefficient is calculated using the rate of customers that got satisfied, it will always be higher (or equal) than the modified CS-coefficient. In being so, the lines used in figure 6 for categorization should be modified to use with the modified CS-Coefficient. By adjusting regression lines among the requirements of 5 different studies realized by the author (figure 12), we can estimate that the 50% categorization lines of the Berger's CS-coefficient could be placed between 0.30 and 0.35 for the modified CS-coefficients (in fact, the exact location is a matter of judgment, and should vary from product to product).
Figure 13 shows the scatter plot for the modified CS-Coefficient for the Banking Services study. By drawing the categorization lines at 0.30 and -0.30, we may see that free checking and location of branches in supermarkets changed its category. Free checking became slightly one-dimensional, while branches in supermarkets became attractive.
[FIGURE 13 OMITTED]
Free coffee and existence of insurance services got even. This means the average satisfaction or dissatisfaction caused by the existence or inexistence of these requirements is the same, although the percentage of satisfied customers is different. If we divide SI by %S (and DI / %D) we will get the degree of satisfaction (or dissatisfaction) a requirement brings to those customers that expressed some satisfaction (or dissatisfaction). Figure 14 shows that, although existence of ATM brings satisfaction to only 29% of the customers (%S in figure 9), the degree of satisfaction of these customers is very high.
If for a certain requirement the average satisfaction (SI) or the rate of satisfied customers (%S) is low, but the satisfaction for those customers is high, we may study to see if there is a specific market segment where it is a competitive advantage.
In the case of existence of ATM banking, the customers who got higher satisfaction are those with no Internet access and full time jobs. As for the ones that did not get any satisfaction or think it is a must-be requirement, the majority does have access to Internet and may have part time or full time jobs.
IMPORTANCE RATING x KANO MODEL CLASSIFICATION
Traditionally the QFD process has used importance rating to determine the most critical customer requirements. It assumes that the most important requirements will bring more satisfaction, i.e., they are one-dimensional. As discussed in the previous sections of this paper, we can't assume that. Besides, the answers of customers to questions concerning the importance of some product requirement are most likely to be dependent on the customer's earlier experiences (Parasuraman et al., 1985; Bitner, 1991). Huiskonen (1998) discuss some situations in which the traditional evaluation of importance may lead to misinterpretations regarding the real customer requirements and, hence, sometimes to inappropriate actions. These situations depend on how the requirement is classified according to the Kano Model, the importance rating given by customers and the performance level of the requirement. They can be classified as follows:
a) Must-be requirement, high importance. In this case an inappropriate action would be to raise the performance level of the attribute. It would not increase customer satisfaction and therefore this action would not lead to a competitive advantage.
b) Must-be requirement, low importance. Satisfactory earlier experiences may produce low importance ratings, which may weaken the attention of the design team over the requirement. In this case, with a must-be requirement, dissatisfaction is caused even if a minor decrease in the performance level is perceived, which may lead to competitive disadvantage.
c) Attractive requirement, high importance. In situations where company's performance in some important requirement is worse than competitors, this requirement is usually regarded critical and should be improved. However, if this requirement is of attractive type, there is no critical competitive disadvantage being behind competitors. In this case resources could be allocated more effectively by making improvement elsewhere.
d) Attractive requirement, low importance. In traditional surveys the attractive type of requirement may be rated as less important because it often represents a requirement which customers do not have earlier experiences. In this case, opportunity for competitive advantage may remain unnoticed.
These four types of possible misinterpretations are present in the QFD process when it uses the importance rating. By using the Kano Model classification of customer requirements, the design team could identify the critical requirements and the ones that could bring a competitive advantage. But how can the design team integrate the Kano Model into the QFD?
INTEGRATING THE KANO MODEL IN THE QFD
Matzler & Hinterhuber (1998) describe the utilization of the customer satisfaction coefficient (Berger et al., 1993) as a supplementary tool in the QFD process. They say that the product should conform to expectations in must-be requirements, be competitive in one-dimensional requirements and stand out regarding attractive requirements, but they do not describe in detail ways of integrating the Kano Model in the QFD process.
Tan & Shen (2000) present a method for integration of the Kano Model in the QFD by introducing an adjustment in the improvement ratio according with the equation: I[R.sub.adj] = (I[[R.sub.0].sup.12/k]
Where I[R.sub.adj] is the adjusted improvement ratio, I[R.sub.0] is the original improvement ratio, and k is an adjustment factor. The value of k varies according with the Kano category. Finally, the final weight of a requirement is calculated by multiplying the raw importance by the adjusted improvement ratio. The authors leave the definition of k values to the design team, but suggest that one possible set of values would be k = 0.5, 1 and 2 for must-be, one-dimensional and attractive requirements, respectively. Also, the authors state that the adjustment factor is valid only for must-be, one-dimensional and attractive requirements, not being applicable to other possible categories in the Kano Model.
In fact, the proposal of Tan & Shen (2000) increases the weight of must-be requirements (k = 0,5) and decreases the weight of attractive requirements (k = 2). In this case, the design team will put extra effort in improving must-be requirements, and may loose the opportunity of paying attention to attractive requirements. Customers tend to rate attractive requirements as less important, due to lack of knowledge and previous experience with them. With the k = 2 for attractive requirements, the design team may end with a product or service that is excellent in basic requirements, but that will not bring superior satisfaction to customers due to lack of attractive requirements. Also, Tan & Shen approach does not decrease the problems that arise with the traditional importance rating (discussed at section VIII of this paper). On contrary, their approach may increase the problems in some cases.
A way of decreasing the problems that arise with the traditional importance rating and integrate the Kano Model in the QFD is to use the modified customer satisfaction coefficients (SI and DI) presented in this paper.
The importance column in the QFD A-1 matrix could be substituted by the result of the following equation: Adj. Factor = 1 + Max (|SI|, |DI|) Where "SI" and "DI" are the modified satisfaction and dissatisfaction indexes presented in this paper and in Tontini (2003).
Figure 15 shows the adjustment factor for the requirements of the banking services study. The adjustment factor puts more weight in the requirements that bring more satisfaction when present, or that bring more dissatisfaction when absent. In this case, attractive, one-dimensional and must-be requirements will be taken in consideration depending on the degree of satisfaction or dissatisfaction that they bring to customers.
Figure 16 shows the calculation of the weights in the QFD using the adjustment factor. In this case, the weight is given by the equation: Weight = Improvement x Adjustment Factor
Figure 16 shows the calculation of the weights in the QFD using the adjustment factor. In this case, the weight is given by the equation: Weight = Improvement x Adjustment Factor The level of satisfaction that the customer responds in the Kano questionnaire may still be influenced by customers past experiences with the product or service. But, since Kano Model questionnaire ask customers to state their satisfaction or dissatisfaction with a hypothetical situation, integrating Kano Model in the QFD, as showed in figure 16, has less impact of past experiences than Tan & Shen approach (2000). It is true because this new approach does not use the raw importance together with Kano categorization to calculate finals weights. It uses only the degree of satisfaction or dissatisfaction brought to customers in the hypothetical situation.
By keeping a column with the Kano Model categorization, SI and DI for each requirement, the design team may decide to incorporate, or not, an attractive requirement. For example, for the banking services case, the design team may decide not to incorporate the requirement of opening Sundays (due to cost constrains, for example), without causing dissatisfaction to customers.
CONCLUSION
Kano Model can help businesses to find out which requirements they must fulfill (must-be), which requirements they should be competitive (one dimensional), and which requirements bring a differential in the eyes of the customer (attractive).
This paper presented a modified Kano Model questionnaire using a Likert Scale in order to identify the degree of satisfaction or dissatisfaction a certain requirement brings to the customers. Based on Berger et al. (1993) CS-Coefficient, a Modified CS-Coefficient was introduced for using with the degree of satisfaction scale. This modified CS-Coefficient can identify those requirements that really bring distinction to the product or service, and therefore bring competitiveness. It also can identify those requirements that are critical to the customers, and therefore can bring dissatisfaction if they not fulfill customers' expectations. Using a study of 200 banking service customers, the paper showed the correlation between the Berger's CS-Coefficient and a Modified CS-Coefficient.
Using the Modified CS-Coefficient, the paper also presented a method of integrating the Kano Model in the Quality Function Deployment (QFD). This new approach overcomes some constrains of previous works by using an adjustment factor to correct the improvement rate in the QFD A-1 Matrix. The adjustment factor is based on the degree of satisfaction or dissatisfaction that a requirement brings to customers instead of the importance rating.
FIGURE 1--CUSTOMER REQUIREMENTS EXTRACTION AND PRIORITY DEFINITION
Compet. Analysis
We (our Competitor
Customer Requirements Importance product) A Target
Accessibility
Branch located in 5 3 4 5
Supermarkets
Open Sunday 4 2 2 3
Online Banking 5 5 4 5
Phone Banking 5 4 5 5
ATM 5 3 5 5
Alternative Services
Insurance services 3 2 4 4
Free Checking 4 2 5 5
Branch comfort
Free Coffee 2 3 4 4
Space 2 5 4 5
Weight
Improvement (Improvement Relative
Customer Requirements (Target/We) X importance) Weight
Accessibility
Branch located in 1.67 8.5 15.4
Supermarkets
Open Sunday 1.5 6 10.9
Online Banking 1 5 9.1
Phone Banking 1.25 6.25 11.4
ATM 1.67 8.5 15.5
Alternative Services
Insurance services 2 6 10.9
Free Checking 2.5 10 18.2
Branch comfort
Free Coffee 1.33 2.66 4.8
Space 1 2 3.6
FIGURE 2--HOUSE OF QUALITY
Product Requirements
Variety of
Number of Online
Branches in Open services Number
Customer Requirements Supemarkets Sunday available of ATM
Accessibility
Branch located in ***
Supermarkets
Open Sunday ***
Online Banking ***
Phone Banking
ATM ***
Alternative Services
Insurance services
Free Checking
Branch comfort
Free Coffee
Space
Weight 92 65 54 141
Relative Weight 15 11 9.2 24
We 3 N 10 20
Competitor A 4 N 8 50
Target 6 Y 10 50
Product Requirements
Variety of Number of
insurance free checks Free Branch
Customer Requirements services per month coffee area
Accessibility
Branch located in
Supermarkets
Open Sunday
Online Banking
Phone Banking *
ATM
Alternative Services
Insurance services ***
Free Checking ***
Branch comfort
Free Coffee *** *
Space ***
Weight 65 109 28 37
Relative Weight 11 18.3 4 6.4
We 3 40 N 200
Competitor A 5 80 Y 150
Target 5 80 Y 200
We (our Competitor
Customer Requirements Importance product) A Target
Accessibility
Branch located in 5 3 4 5
Supermarkets
Open Sunday 4 2 2 3
Online Banking 5 5 4 5
Phone Banking 5 4 5 5
ATM 5 3 5 5
Alternative Services
Insurance services 4 2 4 4
Free Checking 4 2 5 5
Branch comfort
Free Coffee 2 3 4 4
Space 2 5 4 5
Weight
Improvement (improvement Relative
Customer Requirements (Target/We) X importance) Weight
Accessibility
Branch located in 1.67 8.5 15.4
Supermarkets
Open Sunday 1.5 6 10.9
Online Banking 1 5 9.1
Phone Banking 1.25 6.25 11.4
ATM 1.67 8.5 15.5
Alternative Services
Insurance services 2 6 10.9
Free Checking 2.5 10 18.2
Branch comfort
Free Coffee 1.33 2.66 4.8
Space 1 2 3.6
* Weak (1)
** Medium (3)
*** Strong (6)
FIGURE 4--KANO QUESTIONNAIRE (MATZLER ET AL., 1996)
By combining the two answers in the following evaluation table, the
prdouct requirements can be classified as shown in figure 5.
Functional form of the question
If the edges of your skis grip well 1. I like it that way
on hard snow, how do you feel? 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 form of the question
If the edges of your skis do not 1. I like it that way
grip well on hard snow, how do you 2. It must bet that way
feel? 3. I am neutral
4. I can live with it that way
5. I dislike it that way
FIGURE 5--CATEGORY EXTRACTION (MATZLER ET AL., 1996)
Dysfunctional (negative) question
Customer 4. live
requirements 1. like 2. must be 3. neutral with 5. dislike
Functional
(positive)
question
1. like Q A A A O
2. must-be R I I I M
3. neutral R I I I M
4. live with R I I I M
5. dislike R R R R Q
Customer requirement is ...
A: Attractive
M: Must-be
R: Reverse
O: One-dimensional
Q: Questionable
I: Independent
FIGURE 7--MODIFIED KANO QUESTIONNAIRE (TONTINI, 2000)
Figure 8 shows how to classify a requirement based on the answers for
the modified Kano questionnaire, utilized in Tontini (2000).
Functional form of the question
if the restaurant has li ve music, 1. I feel very satisfied
how do you feel? 2. I feel satisfied
3. It must be that way
4. I am neutral
5. I can live with it that way
6. I feel dissatisfied
7. I feel very dissatisfied
Dysfunctional form of the question
If the restaurant does not have 1. I feel very satisfied
live music, how do you feel? 2. I fee satisfied
3. It must be that way
4. I am neutral
5. I can live with it that way
6. I feel dissatisfied
7. I feel very dissatisfied
FIGURE 8--EVALUATION TABLE OF CUSTOMER REQUIREMENTS (TONTINI, 2000)
Insufficiency Very Satisf. Must Neutral Live Dissat.
Sufficiency Satisf. be with
Very Satisfied ? A A VA VA O
Satisfied ? N A A A O
Must-be ? ? ? N N M
Neutral N N N N N M
Can Live With it R R R N N M
Dissatisfied R R R R R ?
Very Dissatisfied R R R R R ?
Other ? ? ? ? ? ?
Insufficiency Very Other
Sufficiency Dissat.
Very Satisfied O ?
Satisfied O ?
Must-be VM ?
Neutral VM ?
Can Live With it VM ?
Dissatisfied ? ?
Very Dissatisfied ? ?
Other ? ?
VA--very attractive A--attractive O--one-dimensional N--neutral
M--must-be VM--very must-be R--reverse
FIGURE 10--RESULTS TABULATION
Live music Free dessert
Respondent Existence Inexistence Existence Inexistence
1 5 -1 4 0
2 3 0 5 -1
3 5 -3 2 -3
. . . . .
. . . . .
100 3 -2 1 -1
Cleaning
Respondent Existence Inexistence
1 0 -5
2 1 -4
3 0 -5
. . .
. . .
100 2 -4
FIGURE 11--MODIFIED CS-COEFFICIENTS APPLIED TO THE BANKING SERVICES
Availability If offers If offers If offers
Modified on-line Free free insurance
CS-Coefficients banking Coffee checking services
SI 0.53 0.36 0.39 0.37
DI -0.54 -0.06 -0.57 -0.06
RI 0.00 0.00 0.00 -0.01
Berger's
CS-Coefficients
%S 0.80 0.77 0.45 0.63
%D -0.72 -0.16 -0.81 -0.13
Existence If it Existence Branches
Modified phone opens ATM Located in
CS-Coefficients banking Sunday banking Supermarkets
SI 0.28 0.70 0.26 0.53
DI -0.62 -0.06 -0.87 -0.23
RI 0.00 -0.02 0.00 -0.03
Berger's
CS-Coefficients
%S 0.35 0.88 0.29 0.87
%D -0.86 -0.09 -0.91 -0.52
FIGURE 12--CORRELATION BETWEEN BERGER'S CS-COEFFICIENT AND THE MODIFIED
CS-COEFFICIENTS
95% Interval R2
Regression Low Up
Banking Services SI = 0.66 %S 0.55 0.77 0.64
Video Rental SI = 0.73 %S 0.70 0.76 0.97
Graduate Students SI = 0.80 %S 0.71 0.89 0.87
Arline SI = 0.73 %S 0.64 0.82 0.86
Flower Shop SI = 0.77 %S 0.74 0.80 0.93
95% Interval R2
Regression Low Up Interviews
Banking Services DI = 0.75 %D 0.62 0.89 0.89 200
Video Rental DI = 0.60 %D 0.52 0.66 0.92 58
Graduate Students DI = 0.71 %D 0.62 0.8 0.93 200
Arline DI = 0.48 %D 0.42 0.54 0.94 180
Flower Shop DI = 0.67 %D 0.64 0.70 0.96 73
FIGURE 14--DEGREE OF SATISFACTION AND DISSATISFACTION FOR AFFECTED
CUSTOMERS
Availability If offers If offers If offers
of offers Free free insurance
line banking Coffee checking services
SI/%S 0.66 0.47 0.87 0.59
DI/%D * -1 -0.75 -0.37 -0.70 -0.49
Existence If it Existence Branches
phone opens ATM Located
banking Sunday banking Supermarkets
SI/%S 0.81 0.80 0.90 0.61
DI/%D * -1 -0.72 -0.69 -0.96 -0.44
FIGURE 15--CALCULATION OF THE ADJUSTMENT FACTOR FOR THE BANKING
SERVICES CASE
Requirement SI DI Max(|SI|,|DI|) 1+Max(|SI|,|DI|)
Branches in 0.53 -0.23 0.53 1.53
Supermarkets
Open Sunday 0.70 -0.06 0.70 1.70
Online Banking 0.53 -0.54 0.54 1.54
Phone Banking 0.28 -0.62 0.62 1.62
ATM 0.26 -0.87 0.87 1.87
Insurance services 0.37 -0.06 0.37 1.37
Free Checking 0.39 -0.57 0.57 1.57
Free Coffee 0.36 -0.06 0.36 1.36
FIGURE 16-QFD MATRIX USING MODIFIED CUSTOMER SATISFACTION INDEX
Kano
Model Adjustment
Customer Requirements Categorization SI DI Factor
Accessibility
Branch located in A 0.53 -0.23 1.53
Supermarkets
Open Sunday A 0.70 -0.06 1.7
Online Banking O 0.53 -0.54 1.54
Phone Banking M 0.28 -0.62 1.62
ATM M 0.26 -0.87 1.87
Alternative Services
Insurance services A 0.37 -0.06 1.37
Free Checking O 0.39 -0.57 1.57
Branch comfort
Free Coffee A 0.36 -0.06 1.36
We (our Competitor Improvement
Customer Requirements product) A Target (Target/We)
Accessibility
Branch located in 3 4 5 1.67
Supermarkets
Open Sunday 2 2 3 1.5
Online Banking 5 4 5 1
Phone Banking 4 5 5 1.25
ATM 3 5 5 1.67
Alternative Services
Insurance services 2 4 4 2
Free Checking 2 5 5 2.5
Branch comfort
Free Coffee 3 4 4 1.33
Weight
(improvement Relative
Customer Requirements X Adj. Factor) Weight
Accessibility
Branch located in 2.56 12.6
Supermarkets
Open Sunday 2.55 12.6
Online Banking 1.54 7.6
Phone Banking 2.03 9.9
ATM 3.12 15.4
Alternative Services
Insurance services 2.74 13.5
Free Checking 3.92 19.3
Branch comfort
Free Coffee 1.81 8.9
REFERENCES
Akao Y., Quality Function Deployment: Integrating Customer Requirements into Product Design, Productivity Press, Cambridge, MA, 1990.
Clausing D., Total Quality Development: A Step-by-step Guide to World-class Concurrent Engineering. ASME Press, New York, 1994.
Cohen L., Quality Function Deployment: How to Make QFD Work for You, Addison-Wesley Reading, MA, 1995.
Berger C., Blauth R., Boger D. et al., "Kano methods for understanding customer-defined quality", Hinshitsu: Journal of the Japanese Society for Quality Control, fall, 1993, 3-35.
Bitner M.J., "The evolution of the services marketing mix and its relationship to service quality", In: S.W. Brown, E. Gummesson, B. Edvardsson, B.O. Gustavsson (Eds.), Service Quality, Multidisciplinary and Multinational Perspectives, Lexington Books, USA, 1991, 23-37.
Huisknoen J. and Pirttila T., "Sharpening logistics customer service strategy planning by applying Kano's quality element classification", International Journal of Production Economics, n 56-57, 1998, 253-260.
Kano N., "Attractive quality and must-be quality" Hinshitsu: Journal of the Japanese Society for Quality Control, April, 1984, 39-48.
Matzler K., Hinterhuber H. H., Bailon F., Sauerwein E., "How to delight your customers", Journal of Product & Brand Management, v. 2, 1996, 6-17.
Matzler, K. and Hinterhuber, H. H., "How to make product development projects more successful by integrating Kano's model of customer satisfaction into Quality Function Deployment", Technovation, v.18,(1), 1998, 25-72.
Parasuraman A., Zeithaml V.A., Berry L.L., "A conceptual model of service quality and its implications for further research", Journal of Marketing, v.49, (4), 1985, 41-50.
Reichfeld F.F. and Sasser W.E., "Zero-defections: quality comes to services", Harvard Business Review, September/October, 1990, 105-111.
Tan K.C., Shen X.X., "Integrating Kano's model in the planning matrix of Quality Function Deployment", Total Quality Management, v. 11, n. 8, 2000, 1141-1151.
Tontini G., "Identification of customer attractive and must-be requirements using a modified Kano's method: guidelines and case study", Proceedings of the 54th American Quality Congress, Indianapolis, 2000, 728-734.
Tontini G., "Determining the degree of satisfaction of customer requirements: A modified Kano method", California Journal of Operations Management v1, n1, 2003, 95-103.
Gerson Tontini, Regional University of Blumenau--FURB, Brazil
Dr. Gerson Tontini earned his PhD in Mechanical Engineering at Federal University of Blumenau--Brazil, in 1995. He is currently professor at the MBA Program of the Regional University of Blumenau--FURB, in the southern region of Brazil. He was head of FURB's Planning Office from 1999 to 2002, and President of Fritz Mueller Foundation from 2000 to 2002. His main research interests are in the field of Quality Management, Operations Management and Marketing.
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