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ORIGINAL ARTICLES

Product portfolio planning with customer-engineering interaction

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Pages 801-814 | Received 01 Apr 2004, Accepted 01 Oct 2004, Published online: 23 Feb 2007
 

Abstract

A critical decision that faces companies across all industrial sectors is the selection of an optimal mix of product attributes to offer in the marketplace, namely product portfolio planning. The product portfolio planning problem has to date generally been considered from a marketing perspective, with the focus being on customer concerns i.e., how alternative sets of product attributes and attribute-level options interact and compete among the target customer segments. From the engineering perspective, the operational implications of product portfolio decisions have been tackled with a primary concern about the cost and complexity of interactions among multiple products in a manufacturing environment with increasing variety. Consideration of the customer and engineering interaction in product portfolio planning is becoming increasingly important, manifested by the efforts observed in many industries to improve the coordination of marketing, design and manufacturing activities across product and process platforms. This paper examines the benefits of integrating customer concerns over product offerings with more engineering implications. To leverage both the customer and engineering concerns, a maximizing shared-surplus model that considers customer preferences, choice probabilities and platform-based product costing, is proposed to address the product portfolio planning problem. A heuristic genetic algorithm procedure is applied to solve the mixed-integer combinatorial optimization problem involved in product portfolio planning. Initial findings from a case study on notebook computer portfolio planning suggests the importance of the research problem, as well as the feasibility and potential of the proposed framework.

Acknowledgements

This research was supported by Singapore NTU-Gintic Collaborative Research Project (U01-A-130B). The authors would like to express their sincere thanks to Professors Mitchell M. Tseng, Martin Helander and Halimahtun M. Khalid, and their colleagues at the Global Manufacturing & Logistics Forum, Nanyang Technological University for valuable discussions. The authors would also like to thank the anonymous referees and the Editor for their constructive comments.

Notes

Contributed by the Engineering Design Department

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