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Harnessing Product Complexity: Step 1—Establishing Product Complexity Dimensions and Indicators

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  • Nihal Orfi
  • Janis Terpenny
  • Asli Sahin-Sariisik

Abstract

With today's level of market competition and demand for diverse product offerings, more companies are now pressured to increase product variety as a strategy to maintain and increase market share. In addition to its associated direct costs, variety is considered the main source of product complexity, which has been proven to negatively impact product development time, productivity, costs, and customer satisfaction. Although several researchers have tackled the issue, product complexity continues to be a theoretical concept with different definitions and measurements established based on research area, scope, and objective. This lack of a unified approach has made it difficult for companies to take full advantage of existing research to manage the impact of product complexity. This article introduces five main dimensions of product complexity based on identifying different complexity sources in product design, development, manufacturing, assembly, and supply chain, and on understanding the impact of these sources on different direct and indirect costs. Establishing the dimensions of product complexity is an essential first step in developing a unified product complexity metric to be used as a support tool to improve product design and systematically manage product complexity.

Suggested Citation

  • Nihal Orfi & Janis Terpenny & Asli Sahin-Sariisik, 2011. "Harnessing Product Complexity: Step 1—Establishing Product Complexity Dimensions and Indicators," The Engineering Economist, Taylor & Francis Journals, vol. 56(1), pages 59-79.
  • Handle: RePEc:taf:uteexx:v:56:y:2011:i:1:p:59-79
    DOI: 10.1080/0013791X.2010.549935
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    Cited by:

    1. Park, Kijung & Okudan Kremer, Gül E., 2015. "Assessment of static complexity in design and manufacturing of a product family and its impact on manufacturing performance," International Journal of Production Economics, Elsevier, vol. 169(C), pages 215-232.
    2. H. Khorshidian & M. Akbarpour Shirazi & S. M. T. Fatemi Ghomi, 2019. "An intelligent truck scheduling and transportation planning optimization model for product portfolio in a cross-dock," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 163-184, January.
    3. Tolonen, Arto & Shahmarichatghieh, Marzieh & Harkonen, Janne & Haapasalo, Harri, 2015. "Product portfolio management – Targets and key performance indicators for product portfolio renewal over life cycle," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 468-477.

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