# A Method for Modelling Business-Critical Architecture Decisions in Engineer-to-Order Companies
## 2 Theoretical Background
### Methods of Mapping and Improving Product Architectures  
To address problems related to product variety, researchers have produced a number of methods for mapping and improving product architectures [18]. An early example is the design structure matrix [19]. It was later used in a variety of contexts to generate binary overviews that indicate where design variety in one system affects the designs of other systems or value-chain activities (e.g., [19; 20]). As such, it has the potential to show dependencies across many different activities. Having said that, the method does not indicate the severity of a given dependency or the extent to which the dependency is critical for the cost and lead times of other activities in the value chain. [PERSON] [7] suggested using a graphical modelling technique called the Product Family Master Plan (PMFP), which can support the visualisation of how product variety impacts resources spent on mechanical engineering and product manufacturing. The graphical nature of the modelling technique means that the design of the analysed dependencies is clearly illustrated. This results in a more solution-oriented approach, as the design of dependencies can serve as a basis for further investigation into the design of product interfaces for separate modules. The modelling technique also employs a high level of abstraction, and, as such, it could be used to model other cross-functional engineering activities in the value chain. A recent example of this is the MESA tool proposed by [PERSON] et al. [21], which extends the PMFP by including electrical and software engineering dimensions. [PERSON] et al. [22] also shared their findings on a comparable topic by introducing a modified V-model. However, neither of the tools explicitly addresses non-design engineering activities, such as procurement or commissioning activities. Similar to the previous modelling technique, [PERSON] et al. [23] developed a modelling technique to help manage the impact of product variety: the Interface Diagram. It shares many of the benefits of the PMFP, such as enabling product teams to better make architecture design decisions that limit the effects of product variety. While these are valuable attributes, the modelling technique does not explicitly indicate the impact of product variety and, thus, business criticality. It does not evaluate which product variance critically affects the cost and lead time of other activities in the value chain. While [PERSON] et al. [11] provide relevant guidance on prioritising according to business criticality, their paper only looks across the product and production domains. From a more quantitative perspective, [PERSON] [24] developed a mathematical approach to modelling architecture decisions that focuses on determining the optimal number of platforms within an architecture. Similarly, [PERSON] et al. [25] investigated how choosing the optimal number of modular variants impacts production costs. In addition, [PERSON] et al. [26] employed a computational model to measure the cost implications on manufacturing. However, due to the model's focus on single pre-defined architectures, the design decisions modelled are inherently limited in flexibility to the extent that is demanded in ETO companies. [PERSON] and [PERSON] [27] proposed a comprehensive framework for modular product development based on knowledge obtained from six ETO companies. The technology domain of the framework focuses on the need for system integration across all parts of the value chain, which is particularly critical for ETO companies. Unlike the previously mentioned models, this framework gives ETO companies a broader overview of the changes needed for all parts of the company. This includes changes to the business, technology, processes, and people to achieve a successful system integration and decouple the design variety.