“Análisis e Implementación del Algoritmo KSMMAS”
2.4 Parámetros para el KSMMAS
The first example comes from Schilling & Paparone (2005) who apply the general modular systems theory developed by Schilling (2000) to military force development. In her original article, Schilling (2000), drawing on organisational modularity, developed a causal model that explained why systems migrate toward
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or away from an increasingly modular form. This framework is presented in the following figure.
Figure 2.7. Framework for a general modular systems theory (Source: Schilling, 2000).
Figure 2.7 shows that systems become increasingly modular when the heterogeneity of inputs and heterogeneity of demand are high, with both providing reinforcement effects for one another. Furthermore, urgency of technological advances and competition push a system toward an increasingly modular state indirectly through the reinforcement of the three primary constructs of the model. The idea of urgency here refers to speed of change, with a modular system encouraging speed of change as modules can be mixed and matched efficiently (Schilling, 2000). However, it is important to note that whilst it affords urgency of change, the changes that can occur at speed are those already defined within the system (i.e., the systems designer has included the required functionality in the specification before the change is required). Therefore, urgency of change, even in a modular system, is restricted by the design decisions made prior to production. In
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Schilling & Paparones (2005) study, they applied this framework to the context of US force development to understand why military task forces might shift toward greater levels of modularity, with the benefit of migrating towards modularity being that they can be rapidly configured to address tasks on a mission by mission basis. Thus, whilst the model they developed does not inform how to design for high variety, it does provide insight into why modular or integral systems are more beneficial for certain use contexts i.e., when a greater level of configurability afforded by modularity is needed or greater functionality and performance afforded by integrality is needed (Ulrich, 1995). In the application of the model, they found a number of reasons why a military task force would migrate toward and away from an increasingly modular state. These are presented in figure 2.8.
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Figure 2.8. Factors influencing the level of modularity in a system (source: Schilling & Paparone, 2005).
The primary benefit surrounding the framework and associated illustration in military force development is that it provides organisations with a causal model that can help them predict and explain a systems migration toward a modular or integral state and why each type of system may be better suited to different acts of value co-creation. In being able to plan and predict these conditions gives the organisation the ability to plan the design of their forces with greater confidence that the configuration is suitable for the context within which they will be operating. However, whilst beneficial to the focal beneficiary in use, their framework does not provide great insight into how an organisation can design for high variety and a number of the characteristics associated with use that have been identified throughout this review are not evident (e.g., agency, institutions etc.)
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within Schillings (2000) framework. However, it is important to recognise the contribution of the authors in one of the first attempts at generating a causal model that explains why systems migrate toward or away from modularity. Notably, the authors also conclude by stating that whilst their model may not provide all the answers and future scrutiny may find notable weaknesses in its assumptions, if it provides the foundation for a more comprehensive model, then their work has served a useful purpose.
The second example, Holmstrom and Partanen (2014) focussed on 3D printing technology and servitization enabled digital transformation. Within their study, they emphasise how the combination of digital manufacturing methods3 and equipment-in-use (i.e., during the customers’ experience of the offering) can lead to transformation via servitization and infrastructural evolution. Namely, when a product is deployed alongside digital manufacturing technologies, there is the potential for the equipment to be tailored to use. This can be done through the novel combination of 3D printing, use information collected by users and the infrastructure that allows digital models to be available for the customer at the point of use. In a separate study on 3D printing, Ihl and Piller (2016) also show how the close proximity to the customer allows access to ‘sticky’ customer information to be utilised for the manufacture of components via 3D printing so that they are better suited to individual customer requirements.
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Digital manufacturing methods refers to manufacturing techniques, such as 3D printing, that produce parts directly from a digital file without the need for tooling or mould set up (Holmstrom et al, 2016).
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By focussing on a digitally driven servitization transformation, the authors point out that OEMs could overlap product design and improving equipment in use to allow the organisation to move from designing product types (i.e., product families designed for low variety) to product instances (i.e., designed for high variety), where the focus is on the customers’ use of the asset and resource (re)configuration. They labelled this type of transformation as a form of product Darwinism where the physical assets configuration is continually assessed based on the customers ever-changing contextual requirements. In this instance, it is interesting to note that information is a primary and it is the information of the use context, the customers’ outcomes and their available resources that drive new combinations of the asset. This means the physical world is a derivative of the information and available resources in use with the unique affordance of digital materiality allowing the binding of form and function to be almost permanently delayed. This means digital materiality allows for the product or service is temporarily complete when a particular configuration of resources is required for outcomes in use (Yoo & Euchner, 2015). The concepts proposed within this study fundamentally conform to the illustration of designing for high variety contained within figure 2.4. Notably, the ability to focus on product instances where assets can be adapted, modified and altered on a mission by mission basis is increasingly relevant and popular within practice. This is evident from both the example in chapter 1 from the DoD and the fact that the concept was subject to a recent call
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for ideas from the Centre of Defence Enterprise (CDE)4, a department within the UK Ministry of Defence (MoD).
In the third example of designing for high variety, Parry et al (2016) focus on reverse supply chains and the operationalisation of the Internet of Things (IoT) for the development of four use visibility measures. Their study employed an exploratory case study research design to explore how the IoT can improve the accuracy and timeliness of use information to improve and inform reverse supply chain decision making. Within their study, they model use processes of individuals in their consumption space, using an IDEF-0 methodology illustrated with IoT and qualitative data, to generate an insight into their value creating activities over time. Their study proposes four use visibility measures: experience, consumption, interaction and depletion. Taken together, the four use visibility measures allow the organisation to generate an understanding as to the individuals use context through visibility of their homes. This includes interactions amongst different household resources and not just those resources created by the organisation. The implications of their study allows organisations operating reverse supply chains to better understand the process of use and the ways in which their offerings are used by individuals. By focussing on individual use processes, the authors emphasise the variety associated with different contexts of use and how reverse supply chains can be designed around these high variety contexts. This has implications for understanding and designing for different individuals patterns of use. In particular,
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For more information about the call for ideas please see
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the authors note that establishing an understanding as to the types of patterns of use of their offerings will create much richer data sets and as a result, could result in reduced uncertainty during sorting and diagnostic processes for reserve supply chain operators. Beyond the context of their study, it is possible to see the broader implications of their findings for designing for high variety. In understanding patterns of use and interactions between the organisations offering and other resources in context, it will present the organisation an opportunity to observe how their offerings are being used as platforms for engagement and value creation and how the organisation is best placed to compliment these value-creating activities over time.
In sum, the latter two studies addressed designing for high variety within different contexts and were enabled by different digital technologies. Two common themes were shared by both studies. First is that designing for high variety is process orientated and integration of resources in use forms a part of that process. Second is that both studies highlight the important role technology plays in designing for high variety and focussing on value in context. This aligns with propositions by Neely (2008) Ng & Wakenshaw (2017). First, Neely (2008) states digitization will not only support existing value propositions, but also enable new types to emerge. Second, Ng & Wakenshaw (2017) who posit that IoT would allow non-linear business models to emerge, enabling organisations to create thin crossing points (Baldwin, 2008) at the point of use where resources can be integrated efficiently and effectively to satisfy latent needs of individuals in use.
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