Linking Conjoint Analysis and QFD in the Development of Products

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References

Lehrstuhl für Marketing und InnovationsmanagementProf. Dr. Daniel Baierwww.marketing.tu-cottbus.de

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Diego AltamiranoLinking Conjoint

Analysis and QFD

Linking Conjoint Analysis and QFD in the Development of Products

Case Study: Smart Home for the group 50plus

Ing. Diego Altamirano

Supervisor: Ing. Samah Abu Assab, M. Sc.

Cottbus, 16.February.2011

Master Thesis

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Objectives

• To test the integration of QFD and Conjoint Analysis, in a similar way like Pullman et al. (2002), in the developing of a Smart Home for the group 50plus.

• To compare the results from QFD and Conjoint Analysis to determinate the difference and similarities between those methods in the product design.

1.Objectives

2.Introduction• QFD• CA• Pullman’s approach

3.Study Case

4.Results

5.Conclusions


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Analysis and QFD

Quality Function Deployment (QFD)

Source: Own representation acc. to Cristiano et al. 2000, p. 288

•1966: The first time the concept was implemented by YojiAkao in Japan

•1972: QFD was used at the Mitsubishi Heavy Industry

•1974: Toyota Motor Company applied QFD in Europe

•1983: article written by Kogure and Akaoin Quality Progress

•1986: Ford Motor Company was the first to apply QFD in the USA

Four-phase concept(ASI 1989)

1.Objectives


3.Study Case

4.Results

5.Conclusions


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Analysis and QFD

Quality Function Deployment (QFD)•QFD is a way to assure the design quality while the product is in the design stage (Akao 1990, p.15)

•QFD tries to enhance the linkage between the customers and stakeholder needs and desires (Picard 2006, p. 336).

Source: Own representation acc. to Cristiano et al. 2000, p. 288

1 VOC

2 Raking

3 Main customer requirements

4Technical requirements

5 HoQ matrix

6 Target values for technical requirements

7Concept development

8 Part deployment matrix

1.Objectives


3.Study Case

4.Results

5.Conclusions


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Analysis and QFD

Conjoint Analysis (CA)

Source: Own representation acc. to Bichler and Trommsdorff 2009, p. 59

•1964: “Simultaneous Conjoint Measurement” by psychologists and statisticians Luce and Tukey•1971: “Conjoint Measurement for Quantifying Judgmental Data” by Paul Green with his coauthor Vithala Rao•1985: Sawtooth Software Inc. released its first conjoint analysis software system called ACA

1.Objectives


3.Study Case

4.Results

5.Conclusions


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Analysis and QFD

Conjoint Analysis (CA)•“Conjoint Analysis is marketers’ favorite methodology for finding out how buyers make trade-offs among competing products and suppliers”. (Green et al. 2001, p. 56)

Adaptive Conjoint Analysis (ACA)

1.Objectives


3.Study Case

4.Results

5.Conclusions


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Analysis and QFD

Linking Conjoint Analysis and QFD• Urban and Hauser (1993)• Gustafsson (1996) • Baier (1998) • Pullman et al. (2002)

• Baier and Brusch (2005)• Kazemzadeh et al. (2007) • Abu-Assab et al. (2008)

Pullman’s Approach

1.Objectives


3.Study Case

4.Results

5.Conclusions


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Analysis and QFD

Pullman’s Approach(Case example: Harnesses)

• QFD and Conjoint Analysis have to be used as complementary approaches and should be conducted simultaneously to provide feedback between each other (Pullman et al. 2002, p. 363)

• Both methods look at the new product design problem through different lenses which could result in a more accurate design (Pullman et al. 2002, pp. 362)

• Pullman’s approach was tested also by Abu-Assaband Baier (2010) on the example of mobile phones for elderly people with similar results.

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Study Case: Smart Home for the Group 50plus

“Rentenalarm”

•Not enough young people who can take care of the growing number of elders

•The less percentage of population has to finance the social security system for the growing number of

retired people

“New market opportunity”

•The growing number of elderly people and their

increasing purchasing power turn the generation 50plus

into an important population group in the market

Source: DESTATIS, 2009, p.15

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Study Case: Smart Home for the Group 50plus

“Smart Home is understood as the integration of the technology and services involved in the house with the purpose of improving the security, communication, comfort and energy saving” (Georgieff 2008, p.34)

Source: Hampicke 2000

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Main Application Areas of Smart Homes in the Elderly

Application Area Description Monitoring and Healthcare

• Improve emergency intervention• Automation of standard situation

Saving Resources • Leveraging and optimization of the existing equipment (energy saving)

• Improve the management of home services through improving their efficiency and increasing their accuracy

Safety •Property protection (burglary, access)•Personal protection (protection from falling / injury, automated vital signs monitoring, environmental control)•Accident prevention (fire, water)

Source: Own representation acc. to Krämer 2000, p. 13

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Conjoint Analysis: Attributes and Levels

5 Main areas:•Efficiency•Comfort•Safety•Entertainment•Price

7 attributes each with 3 levels

andthe price with 4 levels

Source: Own representation based on the information from Busch Jaeger

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Conjoint Analysis: ACA Survey Design

Program: SSI web v5

Predicted Time: 20 min.

Target group: people over 50

Questions: 8 ACA Rating

8 ACA Importance

15 ACA Pairs

1 ACA Calibration

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Conjoint Analysis: ACA Survey Design

• 5 minutes video: To explain about the selected attributes and levels to be evaluated

• Incentive:Possibility of taking part in a raffle (Sonny eBook)

• Information labels and windows:To remind or clarify the information of the video

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Conjoint Analysis: Data Collection

• All Germany (61% from Brandenburg-Berlin)

• 62% have a university degree

• 21% knew exactly what Smart Home is

• 15% had not ever heard about Smart Homes

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

QFD: Voice of the Customer (VOC)

Complete free phase:- What do you like most in your home? - What do you not like in your home? - How does the technology help you at home? - What would you like to make it easier by using technology at home?

Phase of motivation with video example (incentive)

Final question and quick questioner:“How much would you invest in a Smart Home?” Questioner to rank the selected attributes used in the Conjoint Analysis

Number of interviews: 15 people over 50 years-old

Average time: 28 minutes

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

QFD: Customer Requirements

30 respondents were asked to rank each customer requirement as well as the importance of each of the groups

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

QFD: House of Quality (HoQ)

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

QFD: Design Features

Source: Own representation based on the information from Busch Jaeger and additional internet research

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

QFD: Parts Deployment Matrix

Note: The correlation between price and parts characteristics was negative

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

QFD: Results of HoQ and Parts Deployment

Lighting control management was determined as the most important engineering characteristic followed by price

The high scores are a mirror of the high number of applications of the device in a Smart Home.

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Conjoint Analysis: Utility weights and importances

The price had the highest average importance with the lower price.

The home alarm system has the second place of importance.

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Comparison of design attributes importance and the levels with highest impact

Difference on recognizing the advantages of devices with high number of applications.

QFD allows to think outside of the box and to find the possible trade-offs between the different attributes.

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Design of a Smart Home for the group 50 plus

• There is not a standard Smart Home for elderly people.

• Two main areas where Smart Homes packages could be successful:

- safety (health and security) - saving resources.

• Price was considered the main concern about this product.

• The complexity of the management devices was seen as a disadvantage.

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD • Smart Homes is basically a network and each feature

can help to solve different customer requirements.

• To develop a Smart Home is important to know not only the customer needs, but also all the different applications that each feature has.

• The attributes and levels evaluated during the practical part of this work are not the only solutions.

Design of a Smart Home for the group 50 plus (2)

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

The use of QFD and Conjoint Analysis for developing new products

• The correlation between both results is very low in this experiment (0.021), much lower than in Pullman et al.’s experiment (0.319) and Abu-Assab/Baier experiment (0.390)

• Both methods agree in the customer needs; however, the way of solving these needs are completely different (different lenses).

• QFD is more fitable for thinking “outside of the box” (e.g. a switch antibacterial and trade-offs between the engineering characteristics and features)

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD • Conjoint Analysis represents more accurately what the

customers want.- Reduce the risk to lose the market orientation in the

course of the technical specification - Avoid also to be high dependent of the expert’s

knowledge and experience.

• It is concluded that Conjoint Analysis improves the objectivity of the QFD in the development of new products.

The use of QFD and Conjoint Analysis for developing new products (2)

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

References• Abu-Assab, S. and Baier, D. 2010. Designing products using quality function

deployment and conjoint analysis: A comparison in a market for elderly people. Advances in Data Analysis, Data Handling and Business Intelligence, 38. 2010, pp. 515 - 526.

• Akao, Y. 1990. Quality Function Deployment: Integrating Customer Requirements into Product Design. Cambridge MA : Productivity Press, 1990.

• ASI. 1989. Quality Function Deployment American Supplier Institute Inc. Dearborn, Michigan : s.n., 1989.

• Backhaus, K., et al. 2008. Multivariate Analysemethoden: Eine anwendungsorientierte Einführung. Leipzig : Springer, 2008.

• Baier, D. and Brusch, M. 2009. Erfassung von Kundenpräferenzen für Produkten und Dienstleistungen. Conjointanalyse: Methoden - Anwendungen- Praxisbeispiele. Leipzig : Springer, 2009, pp. 3 - 18.

• Bichler, A. and Trommsdorf, V. 2009. Präferenzmodelle bei der Conjointanalyse. [book auth.] D. Baier and M. Brusch. Conjointanalyse: Methoden - Anwendungen-Praxisbeispiele. Leipzig : Springer, 2009, pp. 59-71.

• Buslei, H., Schulz, E. and Steiner, V. 2007. Auswirkungen des demographischen Wandels auf die private Nachfrage nach Gütern und Dienstleistungen in Deutschland bis 2050. Berlin : Deutsches Institut für Wirtschaftsforschung DIW, 2007. http://www.diw.de/documents/publikationen/73/55742/diwkompakt_2007-026.pdf.

• Cabrera, M. and Rodríguez, C. 2005. The role of Ambient Intelligence in the Social Integration of the Elderly. [book auth.] G. Riva, et al. Ambient Intelligence: The evolution of technology, communication and cognition towards the future of human-computer interaction. s.l. : IOS Press, 2005. www.neurovr.org/emerging/book5/14_AMI_Cabrera.pdf.

• Cattin, P. and Wittink, D. R. 1982. Commercial Use of Conjoint Analysis: A Survey. Journal of Marketing. Summer, 1982, Vol. 46, pp. 44-53.

• Cristiano, JJ, Liker, JK and White, CC III. 2000. Customer driven Product development through quality function deployment in the US and Japan. Journal of Product Innovation Management. 2000, Vol. 17, pp. 286-308.

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

References• DESTATIS (Statistisches Bundesamt Deutschland). 2009. Bevölkerung

Deutschlands bis 2060. Wiesbaden : Statistisches Bundesamt, 2009. Webpage: www.destatis.de.

• Green, P. and Srinivasan, V. 1978. Conjoint Analysis in Consumer Research: Issues and Outlook. Journal of Consumer Research. September, 1978, Vol. 5.

• —. 1990. Conjoint analysis in marketing: New developments with implications for research and practice. Journal of Marketing. October, 1990, Vol. 54, pp. 3-19.

• Green, P., Krieger, A. and Wind, Y. 2001. Thirty Years of Conjoint Analysis: Reflections and Prospects. Interfaces. March, 2001, Vol. 31, 3 - 2, pp. 56-73.

• Gustafsson, A. and Huber, F. 2000. Das Voice of the Customer- Konzept. [book auth.] A. Herrmann, et al. Kundenorientierte Produktgestaltung. Munich : s.n., 2000, pp. 179-193.

• Orme, B. 2010. ACA screening for internal validity. Sawtooth Software Forum. [Online] Sawtooth Software, July 23-26, 2010b. [Cited: December 3, 2010.] http://www.sawtoothsoftware.com/forum.php?cmd=show&thread=1347&posts=4.

• Pullman, M. E., Moore, W. L. and Wardell, D. G. 2002. A comparision of quelity function deployment and conjoint analysis in new product design. The Journal of Product Innovation Management. 2002, Vol. 19, pp. 354 - 364.

• Sawtooth Software Inc. 2006. SSI Web Manual. Sequim, WA : s.n., 2006. • Strese, H., et al. 2010. Smart Home in Deutschland: Untersuchung im Rahmen der

wissenschaftlichen Begleitung zum Programm Next Generation Media (NGM) des Bundesministeriums für Wirtschaft und Technologie. Veröffentlichungen. [Online] May 2010. [Cited: December 29, 2010.] http://www.iit-berlin.de/veroeffentlichungen/iit-studie-smart-home.

• van de Poel, I. 2007. Methodological problems in QFD and directions for future developement. Research in Enginnering Design. 2007, Vol. 18 (Nr. 1), pp. 21 - 36.

• Wittink, D., Vriens, M. and Burhenne, W. 1994. Commercial Use of Conjoint Analysis in Europe: Results and Critical Reflections. International Journal of Research in Marketing. 11, 1994, pp. 41-52.

1.Objectives

2.Introduction

3.Study Case

4.Results

5.Conclusions

References


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Analysis and QFD

Thanks for your attention

Questions?