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A lot of efforts have been made by experts to shorten product development lead time, but only a few of them were questioning the customer surveys duration as a component of product development lead time. This paper proposes the use of claims and complaints data, and the company initiatives as an alternative input for product development programs. Data of claims and complaints as well as the company initiatives were processed as source of the voice of customer (VOC) replacing a customer survey. Data processing was performed by utilizing the Affinity Diagram and Tree diagrams. The claims and complaints data and the company initiatives were grouped and arranged to follow the QFD-Kano category and the structure of the product to be developed. A case study was taken at a National Telecommunication Company. The results of the case study show that the VOC from the customer service data are much simpler than those from customer needs survey and are matched to be used as the VOC of the QFD-Kano Approach.
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International Journal of Applied Engineering Research
ISSN 0973-4562 Volume 9, Number 22 (2014) pp. 15383-15393
© Research India Publications
http://www.ripublication.com
Paper Code:
Utilizing Claims, Complaints, and Company
Initiatives as Voc in a Product Development using
QFD-Kano Approach
Mokh Suef1, Suparno1, Moses L. Singgih1, Ronald Sukwadi2, Eny Widawati2
1Department of Industrial Engineering - InstitutTeknologiSepuluhNopember
Surabaya, Indonesia
E-mail: m_suef@ie.its.ac.id; suparno@ie.its.ac.id; moseslsinggih@ie.its.ac.id
2Department of Industrial Engineering, Atma Jaya Jakarta Catholic University,
Indonesia
E-mail: ronaldmanutd@yahoo.com; enny_widawati@yahoo.com
Abstract
A lot of efforts have been made by experts to shorten product development
lead time, but only a few of them were questioning the customer surveys
duration as a component of product development lead time. This paper
proposes the use of claims and complaints data, and the company initiatives as
an alternative input for product development programs. Data of claims and
complaints as well as the company initiatives were processed as source of the
voice of customer (VOC) replacing a customer survey. Data processing was
performed by utilizing the Affinity Diagram and Tree diagrams. The claims
and complaints data and the company initiatives were grouped and arranged to
follow the QFD-Kano category and the structure of the product to be
developed. A case study was taken at a National Telecommunication Company.
The results of the case study show that the VOC from the customer service
data are much simpler than those from customer needs survey and are matched
to be used as the VOC of the QFD-Kano Approach.
Keywords: Customer survey; Customer service; Customer satisfaction; NPD
lead time; QFD-Kano approach.
Introduction
The rapid technology development has accelerated customer need changes.
Acceleration of this customer needs has been responded by practitioners with
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increasing the frequency of new product launches. This situation results in a faster
product life cycle, and in turn, the product design lead time is getting shorter [1]. The
Traditional way to develop new product is no longer appropriate. It needs new ways
to reduce the product design lead time.
A lot of efforts have been made by experts to shorten the lead time [2], among of
those have been using such techniques like Quality Function Deployment (QFD),
Design For Manufacture (DFM), Design For Assembly (DFA), Concurrent
Engineering (CE), and so on. These techniques are not only reducing the lead time but
also improving the product design quality. However, these techniques do not address
how the design requirements, as an inputs for the product design, is obtained. The
design requirements are usually obtained by carrying out a customer survey.
Meanwhile, the time required to carry out the customer survey is quite long [3].
This paper proposes the use of claims and complaints data and the company
initiatives as an alternative input for product development programs using QFD-Kano
approach. Unlike the traditional QFD, QFD-Kano approach translates the voice of
customer (VOC) into technical response with regard to the customer satisfaction
impact of each technical response. It is proven by Kano, (1984) that the customer
satisfaction impact of some technical response is not always the same. High
performance of a certain technical response may result in low customer satisfaction.
This concept has changed the previous QFD researches. A lot of QFD-Kano
researches have been showing up revising the previous ones. It has been reported that
the QFD-Kano approach gives more accurate product design results and increases the
product quality [4–10]. Even though the QFD-Kano approach has got considerable
attentions, it still requires a customer survey and even longer. QFD-Kano requires not
only a customer needs but also a customer satisfaction rates. This is the reason why
the QFD-Kano approach does not support the product development lead time
reduction programs. Utilizing internal company data i.e. claims, complaints, and
company initiatives may be useful to overcome this QFD-Kano approach weakness.
Data of claims and complaints as well as the company initiatives have to
processed so that it can be used as an alternativesource of the (VOC) replacing a
customer survey. Outline of this paper will be as follows; in section 2, will be
explained the customer survey and its weaknesses. After that, customer service data as
an alternative source of VOC will be described in section 3 and then followed by an
explanation of the QFD-Kano approach in section 4. Section 5 will explain the
Affinity and Tree diagram as one of the quality planning tools. Case Study is also
written in section 6. Discussion and future research is outlined in section 7 and then
ended with the Conclusion.
Customers Survey
TheOne of the Total Quality Management principles is the focus on customers
[11,12]. The implementation of this principle requires companies to constantly hold
the customer survey. There are two kinds of customer surveys, i.e. customer
satisfaction survey and customer need survey. Customer satisfaction survey is usually
carried out by the company annually. This survey is intended to obtain information
Utilizing Claims, Complaints, and Company Initiatives 15385
about the company's performance from the customer side. Company asks the
customers whether the products and services provided are appropriate and gives high
satisfaction. This survey can be done either by using a questionnaire or through
interviews. In addition to the surveys, to obtain information about customer
satisfaction, the company can also provide a suggestion box, suggestion cards, or toll
free telephone.
Customer need survey is usually performed when the company wants to develop
a new product. Customer needs are the input for the product design and development.
The company should convince that the product to be developed is in accordance with
the customer needs. Knowing the customer needs is absolutely importance. The
customer needs should be regarded as a reference work for all product development
activities. All product design features have to be the response to the customer needs.
Thus, it can be inferred that the customer need is very important for the design
resulting in a product that will deliver customer satisfaction.
Customer need survey is more complicated than customer satisfaction surveys
[3]. Therefore, survey of the customer needs usually takes a longer time. Survey of
the customer needs have more stages than customer satisfaction surveys. Generally,
the steps that must be followed on the customer need survey include: (1) Phase of
market segment determination, (2) Phase of acquiring customer needs, (3) Phase of
the questionnaire preparation, (4) Phase of questionnaire distribution and collection,
and (5) Phase of Analysis and conclusions.
There are some customer need survey drawbacks that can interfere the results
[13]. The drawbacks can be classified into 3 groups as follows:
1. Bias; customer need survey may not reflect the actual customer requirements. This
arise for several reasons as follows:
a. Samples are taken from different populations
b. Limited word options
c. Inaccurate response
d. Respondents answer what he does not know about [14]
2. Response rate is low; this can be caused by:
a. Customers concern with privacy issues
b. Respondents consider that the survey does not provide a benefit for him but for
the company itself.
3. Requires long time; because of:
a. Usually involve a lot of respondents
b. Location of respondents could be scattered
c. Respondents do not immediately respond.
Customer Service Data
Most of companies have a division that is responsible for providing the best
service to all customers. This division communicates directly to the customers. From
the service activities undertaken by this division, customer service data will be
documented. This customer service data reflects the real customer needs since the
customers directly deliver their own needs. Unlike the results of customer needs
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surveys, the customer needs from the customer service data has much longer time
dimension. Data from a survey describes only for a certain time event, while data
from the customer service tell us many events from time to time [15]. The trends of
the data will be very useful information to respond a certain customer need.
Customer service data come from 3 groups of services, namely (1) Information
Services, (2) Complaints Services, and (3) Claims Services. Information service is
given when a customer wants to know a few things related to the company. Complaint
service is given when the customer is not satisfied with anything relating to the
purchased product conformity but not specifically stated to its normal purchase
documents. While a claim service is given to customers when they feel that the
purchased product is not in accordance with the written purchasing document within
the company warranty period.
Customer service data is usually well documented and reported periodically to
the company head. The company head use this report as part of the company
performance measurements. Up to now, utilization of customer service data is mostly
used to improve the customer service performance [16]. Exploration of the customer
service data utilization for improving the other business processes would be very
challenging and would give some opportunities for continuous quality improvement
programs in the process of product design, production processes, maintenance
processes, and so on.
QFD-Kano Approach
The most important step in the process of designing and developing a product
using QFD (Quality Function Deployment) approach is to determine customer needs
and priorities [17–19], . Priority of a customer need indicates the importance level of
the need that should be fulfilled by the company. It was assumed that fulfillment of
any customer needs will end up with customer satisfaction impacts.
Kano (1984) has corrected this view [5]. It is not always the case that customer
requirements fulfillment resulting in a customer satisfaction. Kano divided customer
requirements into 5 groups [7]: (1) Must-Be Attributes, (2) One-dimensional
Attributes, (3) Attractive Attributes, (4) Reverse Attributes, and (5) Indifferent
Attributes as shown in figure 1. The last two had been paid less attention in the
implementation.
Utilizing Claims, Complaints, and Company Initiatives 15387
Figure 1. Kano Customer Requirement groups.
Must-be Attribute is behaviour of a customer need that customer has low
satisfaction when the requirement is fulfilled or even considered as some things taken
for granted. But if it is not met, it will cause great dissatisfaction. These properties are
similar to the nature of a complaint. Satisfaction of complaining customer, if the
complaint is solved, is usually small or even considered normal. However, if the
complaint is not solved the customer will be very disappointed. One-dimensional
Attribute is the properties of a customer need that customer will be satisfied when it is
fulfilled and customer will be disappointed if it is not fulfilled. These properties are
similar to the nature of the claims. Customers will be satisfied if the claims are
fulfilled otherwise customer will not be satisfied. Attractive Attribute is
characteristics of the customer need when it is met it will result in a very high
satisfaction and otherwise it will not be a problem. These properties are similar to the
nature of innovation. Customers will be very glad when there is an innovation and
will not be disappointed when it does not exist. Figure 2, illustrates the
correspondence between Kano Category and the complaint Claims, and innovation.
Figure 2. Kano Category and Internal Company data correspondence
Affinity and Tree Diagram
15388 Mokh Suef et. al
Management Planning tools consist of seven tools and sometimes referred as the
Seven New Tools [20]. The tools are: (1) Affinity Diagram, (2) Arrow Diagram, (3)
Tree Diagram, (4) Matrix Diagram, (5) Interrelationship Diagram, (6) Prioritization
Matrix, and (7) Process Decision Program Chart.
Affinity diagram is a powerful tool for organizing qualitative data. It provides a
mean for grouping and structuring the data. The qualitative data are spread out so that
we can take a look entire the data. The similar idea of the data is then intuitively
rearranged to be one group. Each group should be named as the group data
similarities. After obtaining all of the data groups, we build the structure from bottom-
up. Like the Affinity diagram, the Tree diagram is one of the management planning
tools providing a hierarchical structure of a qualitative data which is build from top-
down. The Tree diagram starts with choosing the most abstract group and goes to the
concrete one. The most abstract group becomes the primary level and the following
groups become the second, third, and so forth. We have to examine each level of the
Tree diagram whether all data logically go together. The Tree diagram usually
initiates with the results of the Affinity diagram.
Case Study
A case study has been conducted at a national telecommunication company in
Indonesia. The company has a Customer Service division to provide the best service
to all customers. Company revenue has not earned purely from product selling, but
rather a combination of products and services, which is often referred to as a Product
& Service System (PSS) [21]. PSS has the structure of (1) Physical Product, (2)
Service Product, (3) Service Environment, and (4) Service Delivery [22], as shown in
Figure 3.
Figure 3. Product & Service System Structure
Complaints and Claims data were obtained and summarized from the Customer
Service Division for 2013 activity report as written in table 1 column 2. Company
initiatives data were obtained from the company's strategic plans which are translated
into the customer service division.
Utilizing Claims, Complaints, and Company Initiatives 15389
Furthermore, in order to give direction to the quality function deployment
process, the customer needs have to be projected into the PSS structure. Quality
characteristics and domain of each data should be determined in advance. Quality
characteristics of each data can be obtained by considering the intrinsic behavior of
each data. Domain of each data can be obtained by determining whether the each data
is located at (1) Physical Product, or (2) Service Product, or (3) Service Delivery, or
(4) Service Environment. Quality characteristics of the PSS and the domain of each
data can be seen in table 1, column 3 and column 4.
Using the Affinity Diagram we classified the data into PSS group structure as
shown in figure 4. We have five quality characteristics in the physical product i.e.
Easy Access, Connection Stability, Sound Clarity, Reliability and Company
Innovation. In the Service Product we have three quality characteristics i.e. Easy
Service, Reliability and Company Innovation. In the Service Environment we only
have the Office Condition quality characteristics. While in Service Delivery we have
quality characteristics of the Officer Responsiveness, Company Innovation, and
Reliability. Number of data included in each groups are outlined in figure 4.
After grouping and determining the quality characteristics, the data were arranged
as the structure of the QFD-Kano approach. We use the Tree diagram. Using the Tree
diagram we obtained the VOC structure from the internal company data as depicted in
figure 5. This figure is useful input for the QFD-Kano House of Quality (HOQ).
Table 1. Complaints, Claims, and Company initiatives data
No Internal Company Data Quality Characteristics Domain
Complaints
1
Disconnected line during
communication Con. Stability PP *)
2 Many dials needed to connect Easy Access PP
3 Technician invitation difficulty Easy Service SP
4 Complicated complaint procedures Easy Service SP
5 Busy line disturb calling Easy Access PP
6 Communication failure at a certain area
Easy Access PP
7 Lack of responsiveness to customers Responsiveness SD
8 Information changes over time Reliability SD
9 Call centre difficult to contact Responsiveness SD
10 The sound can not be heard clearly Sound Clarity PP
11 Too long subscribe procedure Easy Service SP
12 Many often noise disruption Sound Clarity PP
13 Company Website is not informative Easy Service SP
14
Service Centre far from customer
residence Office Condition SE
15 People voice changes in the phone Sound Clarity PP
16 Other people voice interference Sound Clarity PP
17 Difficult subscribe process Easy Service SP
18 Very difficult unscribe procedure Easy Service SP
15390 Mokh Suef et. al
19
Technicians only install on working
hour Easy Service SP
20 Handling customer complaints slowly Easy Service SP
21 The number of office is limited Office Condition SE
22 The sound disappear and then reappear
Con. Stability PP
23 Difficult to connect to a certain area Easy Access PP
24 The phone is not clear when it is rain Con. Stability PP
25 Installation process is very long Easy Service SP
26 Office condition is not comfortable Office Condition SE
Claims
27 Customer pays as they use Reliability SP
28 Customer do not pay the bad network Reliability PP
29 Customer do not know the bill Reliability SP
30 bill is not as it should be paid Reliability SP
Compaby Initiatives
31 Company targeting new segment Innovation PP
32 New products design Innovation SP
33 Offers its products through website Innovation SD
*) PP = Physical Product; all parts related to the network *)
SP = Service Product; all services supporting the business
SE = Service Ervironmet; situation and condition following service delivery
process
SD = Service Delivery; all provided processes given to the customer
Utilizing Claims, Complaints, and Company Initiatives 15391
Figure 4. Affinity diagram of the internal companydata
Figure 5. Tree diagram of the internal company data
Discussion and Future Research
It is very convenient getting the VOC using the complaint, claim, and company
initiative data. The time needed to obtain the VOC is much shorter compared to those
using a customer survey. We do not need to classify the data into Kano category as
required in the QFD-Kano Approach since they have already separated as the
complaints, claims, and company initiatives which are matched with the Must-be,
One-dimensional, and Attractive attributes. The data processing may take a few hours
while customer survey may take several weeks or even months. It should be
emphasized that we need a documented report of the customer service department.
Otherwise we have nothing for the data processing. That is why this approach is not
suitable for new companies.
VOC resulted from this scheme may differ from those using a customer need
survey. A customer need survey is usually conducted with a sampling method.
Sampling errors may occur everywhere within the sampling steps. VOC resulted from
the customer need survey may not lead to the real customer needs if the survey is not
treated carefully especially when selecting respondents and answering the questioner
questions. Whiles, complaints and claims are the real customer needs that should be
handled by any company. It is also true that we could not ask to the customer about
what the customer does not know. The company has to initiate some things that
possibly make customer excited. So, VOC resulted from this scheme is more valid.
15392 Mokh Suef et. al
For the future research, it might be useful to process the data using text and data
mining [23]. Processing the data using text and data mining could result in more
objective groups and structures rather than the subjective ones.
Conclusion
This paper has proposed a new way for identifying the VOC using complaints,
claims, and company initiatives in a product design with QFD-Kano approach. This is
the alternative way for getting VOC from the customer survey. The time needed for
getting the VOC is much shorter. But the customer service reports must be well
documented. Data of complaints, claims, and company initiatives should be arranged
so that it follows the VOC structure of QFD-Kano model. In order to sort, group, and
structure the data, subjectively we can use the Affinity and Tree diagram. It might be
useful to follow this research with the text and data mining for more objective results.
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