Integrasi Quality Function Deployment (QFD) dan Conjoint Analysis untuk Mengetahui Preferensi Konsumen
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Keywords
Abstract
The advantages of QFD is to translate customer need into a technical response. But QFD has some disadvantages related to the difficulties in distinguishing the difference of needs between consumers, difficulties to fulfill the needs of different consumer groups, and the exietence of conceptual gap between consumers and companies. The proposed method to overcome these disadvantages is conjoint analysis. The main advantage of conjoint analysis is the ability to get the optimal design combination for products or services based on consumers' preference.
The result of conjoint analysis, estimation of perceived value, and integration of QFD can be used to know the preference market needs among consumers, identify the office desk, determine consumer segments and technical respons, and estimate the additional price of office desk attributes as an effort to the development of the office desk.
In overall the best Office desk combination results based on consumers' preference of Office desk is the white color without additional drawers or supporting features, with table size is 120x60x75 cm and footstool. Segmentation based on preferences resulting in three clusters, namely size, color, and availability of drawer. The highest technical response to be the company's priority in meeting the needs of consumers is to make the proper hole connection.
Based on the perceived value, the company is capable to predict that the additional prices of 1 drawer is Rp.1-Rp.500.000, the addition price of 2 drawers is Rp.800,000 - Rp.900.000, and the addition price of the foundation of the foot is Rp.50.000 - Rp.150.000, and the additional price of supporting features is Rp.150.000-Rp.250.000.
Keywords: Quality Function Deployment (QFD), conjoint analysis, segmentation and perceived value.
Abstrak
Keunggulan QFD adalah menterjemahkan customer need menjadi respon teknis. Namun QFD mempunyai kekurangan terkait sulit membedakan antara beragam kebutuhan konsumen yang bertentangan, sulit memenuhi kebutuhan konsumen yang berbeda kelompok, dan kesenjangan konseptual antara konsumen dan perusahaan. Untuk melengkapi kekurangan QFD, diusulkan metode conjoint analysis. Keunggulan utama conjoint analysis mampu mendapatkan kombinasi desain yang optimal untuk produk yang melekat pada preferensi konsumen.
Hasil integrasi QFD dan conjoint analysis serta estimasi perceived value dapat mengetahui preferensi konsumen meja kantor, mengidentifikasi segmen konsumen meja kantor, menentukan respon teknis, dan mengestimasi harga penambahan atribut meja kantor sebagai upaya pengembangan meja kantor.
Secara keseluruhan hasil kombinasi meja kantor terbaik berdasarkan preferensi konsumen meja kantor adalah warna putih, tidak membutuhkan penambahan fitur laci, tidak membutuhkan penambahan fitur pendukung, ukuran meja 120x60x75 cm, dan terdapat tumpuan kaki. Berdasarkan segmentasi preferensi terbentuk tiga klaster, yaitu klaster warna, klaster ukuran, dan klaster ketersediaan laci. Secara keseluruhan respon teknis yang menjadi prioritas perusahaan untuk memenuhi kebutuhan konsumen adalah pembuatan lubang sambungan yang tepat.
Berdasarkan hasil perceived value, perusahaan dapat memperkirakan harga penambahan 1 laci berkisar Rp.1 - Rp.500.000, penambahan 2 laci adalah Rp. 800.000 – Rp. 900.000, penambahan tumpuan kaki Rp. 50.000 – Rp. 150.000, dan penambahan fitur pendukung Rp. 150.000-Rp. 250.000.
Kata kunci: Quality Function Deployment (QFD), conjoint analysis, segmentasi, dan perceived value
The result of conjoint analysis, estimation of perceived value, and integration of QFD can be used to know the preference market needs among consumers, identify the office desk, determine consumer segments and technical respons, and estimate the additional price of office desk attributes as an effort to the development of the office desk.
In overall the best Office desk combination results based on consumers' preference of Office desk is the white color without additional drawers or supporting features, with table size is 120x60x75 cm and footstool. Segmentation based on preferences resulting in three clusters, namely size, color, and availability of drawer. The highest technical response to be the company's priority in meeting the needs of consumers is to make the proper hole connection.
Based on the perceived value, the company is capable to predict that the additional prices of 1 drawer is Rp.1-Rp.500.000, the addition price of 2 drawers is Rp.800,000 - Rp.900.000, and the addition price of the foundation of the foot is Rp.50.000 - Rp.150.000, and the additional price of supporting features is Rp.150.000-Rp.250.000.
Keywords: Quality Function Deployment (QFD), conjoint analysis, segmentation and perceived value.
Abstrak
Keunggulan QFD adalah menterjemahkan customer need menjadi respon teknis. Namun QFD mempunyai kekurangan terkait sulit membedakan antara beragam kebutuhan konsumen yang bertentangan, sulit memenuhi kebutuhan konsumen yang berbeda kelompok, dan kesenjangan konseptual antara konsumen dan perusahaan. Untuk melengkapi kekurangan QFD, diusulkan metode conjoint analysis. Keunggulan utama conjoint analysis mampu mendapatkan kombinasi desain yang optimal untuk produk yang melekat pada preferensi konsumen.
Hasil integrasi QFD dan conjoint analysis serta estimasi perceived value dapat mengetahui preferensi konsumen meja kantor, mengidentifikasi segmen konsumen meja kantor, menentukan respon teknis, dan mengestimasi harga penambahan atribut meja kantor sebagai upaya pengembangan meja kantor.
Secara keseluruhan hasil kombinasi meja kantor terbaik berdasarkan preferensi konsumen meja kantor adalah warna putih, tidak membutuhkan penambahan fitur laci, tidak membutuhkan penambahan fitur pendukung, ukuran meja 120x60x75 cm, dan terdapat tumpuan kaki. Berdasarkan segmentasi preferensi terbentuk tiga klaster, yaitu klaster warna, klaster ukuran, dan klaster ketersediaan laci. Secara keseluruhan respon teknis yang menjadi prioritas perusahaan untuk memenuhi kebutuhan konsumen adalah pembuatan lubang sambungan yang tepat.
Berdasarkan hasil perceived value, perusahaan dapat memperkirakan harga penambahan 1 laci berkisar Rp.1 - Rp.500.000, penambahan 2 laci adalah Rp. 800.000 – Rp. 900.000, penambahan tumpuan kaki Rp. 50.000 – Rp. 150.000, dan penambahan fitur pendukung Rp. 150.000-Rp. 250.000.
Kata kunci: Quality Function Deployment (QFD), conjoint analysis, segmentasi, dan perceived value
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References
[1] Sullivan, L.P. (1986), “Quality Function Deployment”. Quality Progress,Vol.34, No.6, hal. 39–50.
[2] Bossert, J.L. (1991), Quality Function Deployment: A Practitioner’s Approach, ASQC Quality Press: Milwaukee, WI.
[3] Cohen, Lou (1995), Quality Function Deployment: How to Make QFD Work for You, Addison-Wesley Publishing Company, New York.
[4] Reilly, Norman B. (1999),The Team Based Product Development Guidebook, ASQ Quality Press, Milwaukee Wisconsin.
[5] Herman, Steve dan Rob, Klein.(1995), “Improving the Predictive Power of Conjoint Analysis”, Marketing Research, Vol. 7 No. 4, Hal. 29-31.
[6] Orme, B. (2002). “Formulating Attributes and Levels in Conjoint Analysis”, Research Paper Series, Sawtooth Software, Inc.
[7] Pullman, M. E.,Moore, W. L. dan Wardell, D. G. (2002), "A Comparison Of Quality Function Deployment And Conjoint Analysis In New Product Design", The Journal of Produict Innovation and Management, Vol.19, hal. 354-365.
[8] Katz, G. M. (2004),”Practioner Note: A Response to Pullman et al.'s (2002), Comparison of Quality Function Deployment versus ConjointAnalysis”, The Journal of Product Innovation and Management, Vol. 21, hal.61-63.
[9] Chaudhuri, A danBhattacharyya, M. (2005), “Linking Quality Function Deployment with Conjoint Study for New Product Development”,IEEE International Conference on Industrial Informatics (INDIN).3rd, hal. 396-401.
[10] Baishu, Li dan Fengli, Wu. (2011), “Analyzing the Variety of Customer Needs for Product Family Design by Integrating Conjoint Analysis and Quality Function Deployment”, International Conference on Digital Manufacturing & Automation, Vol.2, hal. 203-206.
[11] Dolan, Robert J. (2001), “Analyzing Consumer Preferences”, Harvard Business School. Document 9-599-112.
[12] Luce, D.R., dan Tukey, J.W. (1964). “Simultaneous Conjoint Measurement: A New Type Of Fundamental Measurement”, Journal of mathematical psychology, Vol. 1, hal. 1-27.
[13] Hair, Joseph F., et al. (2009), Multivariate Data Analysis: A Global Perspective, 7th ed”, Upper Saddle River: Prentice Hall, New York.
[14] Suharjo, B. (2001), “New Product Development with Conjoint Analysis”, Capricorn MARS Indotama.
[15] Krestonea, Rhoi Agung. (2010). Penerapan Metode Analisis Konjoin Terhadap Preferensi Konsumen Susu Rumah Tangga Untuk Pengembangan Konsep Produk Susu Cair Olahan Di Perusahaan Susu Sehat Mangli-Jember. Tesis, Statistika. ITS, Surabaya.
[16] Malhotra, N., K. (1993), Marketing Research. An Applied Orientation, Prentice Hall, New York.
[17] Weinstein, A. (2004), Handbook of Market Segmentation: Strategic Targeting for Business and Technology Firms, 3rd Edition, The Haworth Press, Inc, Binghamton, New York.
[18] Akao, Y. (1990), Quality Function Deployment-Integrating Customer Requirements into Product Design, Productivity Press. belkcollgefbusiness.uncc.edu/jaredhansen/Teaching/conjoint.pdf diakses 13 Mei 2014
[19] Daetz, D., Barnard, B., Norman, R., 1995. Statistical methods for rates and proportions. Wiley, New York, USA.
[20] She, X. X., Tan, K. C., dan Xie, M. (2000), “An Integrated Approach to Innovative Product Development Using Kano’s Model and QFD”, European Journal of Innovation Management, Vol. 3, No. 2, hal. 91–99.
[21] Woodruff, R. B. (1997), “Customer Value: The Next Source For Competitive Advantage”, Journal of The Academy of Marketing Science, Vo. 25, No. 2, hal. 139-153.
[22] Ravald, A. dan Gronroos, C. (1996), “The value concept and relationship marketing”, European Journal of Marketing, Vol. 30, No. 2, hal. 19-30.
[23] Ancok, D. 1997. Teknik Penyusunan Skala Pengukuran. Yogyakarta. Pusat Penelitian Kependudukan Universitas Gajah Mada.
[2] Bossert, J.L. (1991), Quality Function Deployment: A Practitioner’s Approach, ASQC Quality Press: Milwaukee, WI.
[3] Cohen, Lou (1995), Quality Function Deployment: How to Make QFD Work for You, Addison-Wesley Publishing Company, New York.
[4] Reilly, Norman B. (1999),The Team Based Product Development Guidebook, ASQ Quality Press, Milwaukee Wisconsin.
[5] Herman, Steve dan Rob, Klein.(1995), “Improving the Predictive Power of Conjoint Analysis”, Marketing Research, Vol. 7 No. 4, Hal. 29-31.
[6] Orme, B. (2002). “Formulating Attributes and Levels in Conjoint Analysis”, Research Paper Series, Sawtooth Software, Inc.
[7] Pullman, M. E.,Moore, W. L. dan Wardell, D. G. (2002), "A Comparison Of Quality Function Deployment And Conjoint Analysis In New Product Design", The Journal of Produict Innovation and Management, Vol.19, hal. 354-365.
[8] Katz, G. M. (2004),”Practioner Note: A Response to Pullman et al.'s (2002), Comparison of Quality Function Deployment versus ConjointAnalysis”, The Journal of Product Innovation and Management, Vol. 21, hal.61-63.
[9] Chaudhuri, A danBhattacharyya, M. (2005), “Linking Quality Function Deployment with Conjoint Study for New Product Development”,IEEE International Conference on Industrial Informatics (INDIN).3rd, hal. 396-401.
[10] Baishu, Li dan Fengli, Wu. (2011), “Analyzing the Variety of Customer Needs for Product Family Design by Integrating Conjoint Analysis and Quality Function Deployment”, International Conference on Digital Manufacturing & Automation, Vol.2, hal. 203-206.
[11] Dolan, Robert J. (2001), “Analyzing Consumer Preferences”, Harvard Business School. Document 9-599-112.
[12] Luce, D.R., dan Tukey, J.W. (1964). “Simultaneous Conjoint Measurement: A New Type Of Fundamental Measurement”, Journal of mathematical psychology, Vol. 1, hal. 1-27.
[13] Hair, Joseph F., et al. (2009), Multivariate Data Analysis: A Global Perspective, 7th ed”, Upper Saddle River: Prentice Hall, New York.
[14] Suharjo, B. (2001), “New Product Development with Conjoint Analysis”, Capricorn MARS Indotama.
[15] Krestonea, Rhoi Agung. (2010). Penerapan Metode Analisis Konjoin Terhadap Preferensi Konsumen Susu Rumah Tangga Untuk Pengembangan Konsep Produk Susu Cair Olahan Di Perusahaan Susu Sehat Mangli-Jember. Tesis, Statistika. ITS, Surabaya.
[16] Malhotra, N., K. (1993), Marketing Research. An Applied Orientation, Prentice Hall, New York.
[17] Weinstein, A. (2004), Handbook of Market Segmentation: Strategic Targeting for Business and Technology Firms, 3rd Edition, The Haworth Press, Inc, Binghamton, New York.
[18] Akao, Y. (1990), Quality Function Deployment-Integrating Customer Requirements into Product Design, Productivity Press. belkcollgefbusiness.uncc.edu/jaredhansen/Teaching/conjoint.pdf diakses 13 Mei 2014
[19] Daetz, D., Barnard, B., Norman, R., 1995. Statistical methods for rates and proportions. Wiley, New York, USA.
[20] She, X. X., Tan, K. C., dan Xie, M. (2000), “An Integrated Approach to Innovative Product Development Using Kano’s Model and QFD”, European Journal of Innovation Management, Vol. 3, No. 2, hal. 91–99.
[21] Woodruff, R. B. (1997), “Customer Value: The Next Source For Competitive Advantage”, Journal of The Academy of Marketing Science, Vo. 25, No. 2, hal. 139-153.
[22] Ravald, A. dan Gronroos, C. (1996), “The value concept and relationship marketing”, European Journal of Marketing, Vol. 30, No. 2, hal. 19-30.
[23] Ancok, D. 1997. Teknik Penyusunan Skala Pengukuran. Yogyakarta. Pusat Penelitian Kependudukan Universitas Gajah Mada.
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Published
Apr 21, 2016
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How to Cite
[1]
D. Y. Irawati, M. L. Singgih, and B. Syarudin, “Integrasi Quality Function Deployment (QFD) dan Conjoint Analysis untuk Mengetahui Preferensi Konsumen”, J. Optimasi Sist. Ind., vol. 13, no. 2, pp. 618–640, Apr. 2016.
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Author Biography
Desrina Yusi Irawati, Jurusan Teknik Industri, Fakultas Teknologi Industri, Institut Sepuluh Nopember
