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Strategic management of logistics service: A fuzzy QFD approach

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  1. Strategic management of logistics service:A fuzzy QFD approach 指導教授:童 超 塵 老師 作者:Eleonora Bottani and Antonio Rizzi 出處:International Journal of Production Economics 103 (2006), P.585-599 主講人:陳 建 旻

  2. Outline • Introduction • The fuzzy QFD approach • Application of the methodology • Conclusions

  3. 1. Introduction last decade Brand power has decreased Technology diffusion Strategy Customer service management Literature Deploy the HOQ to effectively and efficiently improve logistics processes and customer satisfaction Logistics performance

  4. Logistics service which can be summarized in the following steps: • understanding the customer’s voice; • assessing customer’s service perception; • identifying viable steps that can be implemented to improve customer satisfaction; • identifying costs and benefits related to each step; • implementing the most efficient actions for customer satisfaction by means of a cost/benefit analysis.

  5. A cost/benefit analysis is also introduced to identify and rank the most efficient steps toward improvement of logistics processes and customer satisfaction. • A fuzzy approach is adopted since the methodology mainly relays on qualitative judgments given by panel of experts and by customers.

  6. 2. The fuzzy QFD approach • 2.1. QFD fundamentals This approach is composed of four successive matrices: Customer requirement planning matrix Product characteristics deployment matrix Process and quality control matrix Operative instruction matrix

  7. 2.2. The proposed methodology Improve logistics processes Logistics performances

  8. In our approach, four new fuzzy elements have been added to the traditional HOQ, namely: • the weighted importance of service factors; • the weighted importance of strategic actions; • the cost for the implementation of strategic actions; and • the marginal benefit of strategic actions.

  9. 2.2.1. Weighted importance of service factors From a mathematical point of view, given two fuzzy sets A and B, the Hamming distance between two fuzzy numbers belonging to A and B respectively, can be computed as

  10. The di parameters are then calculated according to Eq. (3). Then, the weighted importance Wi* of SFs can be derived as follows:

  11. 2.2.2. Weighted importance of strategic actions Tkjcan be interpreted as the incremental changes of the degree of attainment of the jth ‘‘how’’ when the attainment of the kth one is unitary increased. Using this definition, the weighted importance RIj* can be computed as follows:

  12. In the lower part of the HOQ a fuzzy parameter Cj has been added to ponder the cost of implementing the jth strategic action. The marginal benefit Uj of strategic actions can be calculated through the ratio between benefits and costs, as expressed by the following equation:

  13. Starting from a fuzzy triangular number a(l,m,u), the defuzzified value is computed as

  14. 3. Application of the methodology • 3.1. The company The company • Established in 1973 in Northern Italy • Designing and manufacturing special piping components • An industry leader in the domestic market of special piping parts • Logistics performance • Customer satisfaction The automobile and mechanical industries

  15. 3.2. Results and discussion The importance of each customer has been weighted through the percentage of profit margin generated, as shown in Table 3.

  16. ‘‘whats’’

  17. ‘‘hows’’

  18. 4. Conclusions • An original methodology has been proposed and adopted to rank viable strategic actions a firm can undertake to improve logistics performances. • The weighted importance of service factors allows the firm to identify the key factors of intervention in order to improve the perceived service. • Fuzzy logic has allowed to cope well with uncertainties and incomplete understanding of the relationships between ‘‘hows’’ and between ‘‘hows’’ and ‘‘whats’’.

  19. Thanks For Your Listening!