Differentiation and customer decoupling points: An integrated design approach for mass customization

Abstract

Mass customization draws a twofold benefit: cost reduction, inherited from mass production techniques, and good response to customer requirements, inherited from customization. Two main decisions, relevant to design and manufacturing, are required for the proper implementation of mass customization. First, product features should be split between standard and customizable ones. This will position the product differentiation points. Second, processes should be split between make-to-stock and make-to-order. This will position the customer-order decoupling point. Most often, these two decisions are made separately. In this article, the authors advocate that both decisions should be made simultaneously. They propose an integrated method for design for mass customization. It is based on simultaneously evaluating the impact of these two criteria on enterprise and customer value through the modeling and simulation of value networks. A real case study on Alpina footwear industries is simulated and analyzed. The computational results highlight the joint impact of the two decisions on the overall performance. These two levers should then be considered, simultaneously, when designing the mass customization strategy.

Demand-driven supply chain operations management strategies – a literature review and conceptual model

“…As product differentiation increases, so does the need for segmentation (Smith, 1956;Su et al, 2005). Hence, the segmentation strategy is also closely related to the CADP, for instance, where the positioning of the CODP constrains the ability to offer customizations (Daaboul et al, 2015;Olhager & Östlund, 1990;Squire et al, 2006) and as such, the length of A D . Moreover, as segmentation brings about different ways of achieving customizations, this results not only in multiple CODPs but also multiple CADPs and thus, multiple A D s.…”

“…Consequently, customization could vary, ranging from a simple modification of a standard product all the way to a complete delivery unique and bespoke (one of a kind) product (see, e.g., Alford et al, 2000;Coronado et al, 2004;Davis, 1989;Lampel & Mintzberg, 1996;Ross, 1996;Sharma, 1987;Da Silveira et al, 2001). Whether a modification or a complete bespoke product, the point where the customization is made has been referred to as the point of differentiation (e.g., Tang, 2006), differentiation point (Wikner & Wong, 2007;Wong et al, 2009), point of product differentiation (e.g., García-Dastugue & Lambert, 2007;Mason-Jones & Towill, 1999b;Naylor et al, 1999;Nieuwenhuis & Katsifou, 2015) and product differentiation point Daaboul et al, 2015). To keep the discussion general, not only to focus on products, the term used in this paper is point of differentiation.…”

Mixed integer programming models for concurrent configuration design and scheduling in a reconfigurable manufacturing system

“…Reconfigurable manufacturing system (RMS) as a responsive manufacturing system is composed of easily reconfigured hardware and software components and is able to quickly be reconfigured to change capacity and functionality in response to altering market demands for products within a family (Koren et al, 1999). RMS is one of modular manufacturing systems based on products’ modularity and commonality (Fixson, 2007) and is conceived as a new manufacturing system ready for mass customization (Daaboul et al, 2015). A unique characteristic of RMS is the ability to offer exactly functionality and capacity needed for each demand period (DP) by changing RMS’s configuration with time.…”

Granular computing–based development of service process reference models in social manufacturing contexts

“…Since relational data representing influences, interactions, and dependencies among service activities are of highest importance, the developers tend toward reusing the existing data to establish process reference models for the new services instead of modeling from scratch. These so-called reference models serve as a sustainable service blueprint (Geum and Park, 2011) for the existing best practice approaches and can be adapted to fulfill the individualized needs of customers (Daaboul et al, 2015). Designing for product variety is also an important goal of constructing these historical knowledge as reference models (Prasad, 2016b).…”