A. WHO causes complexity?
For the SMS, we used relevant keywords that exemplify the respective interacting objects in design. We describe each of the viewpoints along with their respective SMS results in the upcoming paragraphs. Furthermore, Table 6 shows the number of papers per solution direction coded with the respective keywords of the complexity viewpoints. The length of the bars is proportional to the total papers per solution direction, expressed by n.
The social complexity viewpoint was found in all the reviewed papers from the solution directions of knowledge, model, and process, particularly using the keyword designers. A little less so was the keyword organization, although that one was still highly mentioned in the knowledge and product directions. In contrast, the model and tool solution directions were remarkably low compared to the other directions.
The keyword process was found in all the reviewed papers related to the model, DSM, process, and product solution directions. The keywords activity and project were less often found, particularly infrequently in the directions of DSM and tool.
Regarding the system viewpoint, for the DSM solution direction we note a lack of the keyword design knowledge being mentioned, as well as the infrequent use of the discipline keyword. In the knowledge direction, the system keyword is the one with the most limited use. The model direction is the one with the most mentions of keywords related to the system viewpoint, however, the design knowledge keyword is particularly underrepresented. Regarding the process solution direction, again the keyword design knowledge is the most infrequently mentioned. The product solution direction scored notably low in the system viewpoint, with the keywords discipline, system, and design knowledge mentioned only in slightly more than half the papers. Finally, the tool solution direction had particularly low mentions of the keyword design knowledge.
The keyword tool was particularly infrequently used in the DSM solution direction, and in a slightly minor way in the product direction. The rest of the solution directions often refer to the tooling viewpoint.
B. WHY does complexity occur?
Regarding the results of the complexity drivers, in Fig. 8 we show the distribution of the found complexity drivers in the two-dimensional mapping structure: complexity viewpoint vs. attribute group. Additionally, Fig. 9a, shows the number of mapped complexity driver references per complexity viewpoint and Fig. 9b depicts the number of mapped complexity driver references per attribute group. Next, we detail the complexity drivers findings per attribute group.
1. Complexity drivers related to quantification
This group contained 130 out of the 135 surveyed papers (see Fig. 9b). The complexity drivers related to the system viewpoint were the highest in the mapping. The number and/or size of: systems, subsystems, components, functions, parameters, variants, of constraints, lines of code, disciplines, technologies involved, information sources and models, as well as all interfaces associated with those concepts, constitute the majority of the examples we found (Amorim, Vogelsang, Pudlitz, Gersing, & Philipps, 2019; Arnould, 2018; Biffl, Lüder, & Winkler, 2016; Levy, Hadar, & Aviv, 2019; W. qiang Li & Li, 2018; Liebel, Marko, Tichy, Leitner, & Hansson, 2018; Mordinyi, Serral, & Ekaputra, 2016; Pla, Gay, Meléndez, & López, 2014; Sabou, Kovalenko, Ekaputra, & Biffl, 2016; Schapke, Beetz, König, Koch, & Borrmann, 2018; Shani & Broodney, 2015; Sukumaran & Chandran, 2015; Sztipanovits et al., 2018; Vaneman & Carlson, 2019; S. Zhang, 2019).
For the social viewpoint we found slightly more instances referencing the number of individual designers and engineers, compared to the number/size of teams or organizations. This was similar when commenting on the role of the dependencies, interactions, and information flows as complexity drivers. Those drivers were found more frequently referenced to individual designers (found in 39 out of 135 references) than larger forms of organizational units (found in 10 out of 135 references).
In terms of process, associations were found with the processes’ number, scale, activities, and phases, as well as with the number of process models, the degree of process concurrency, the number of iterations, the degree of bureaucracy and formalization, and to the number of decisions made during the process.
For the tooling viewpoint, the number and interactions of tools scored the highest, however, other forms of quantification were also found such as the number of data exchange standards and formats, the number of needs the tools must cover and the size/order of the files/models that the tools have to handle.
2. Complexity drivers related to diversity
The complexity drivers related to diversity were the third largest mapped group (see Fig. 9b). Out of the mapped references for diversity, the majority was again found in the system viewpoint. Diversity in terms of discipline relates to: abstraction levels, jargon, concepts and perspectives, development times, interfaces, and system structures. Diversity in terms of the system references system views/definitions, the system types and goals, interfaces, requirements, and functions. In terms of data, information and knowledge, diversity relates to abstraction levels, variables, parameters, information types, and structures.
In the social viewpoint, majority of diversity related to the keyword designer (mapped in 60 out of the 135 surveyed papers) in contrast with organization (found in 37 out of the 135 surveyed papers). For the designer, diversity was found in responsibilities and roles; in personality, mentality, attitudes, and moral values; in workforce age; in educational backgrounds; in experience level; in jargon; in time horizons; and in priorities and perspectives, etc. The diversity in organizational structures, in cultures, in strategies, in languages, in location, between management and practitioners, and type of customers, are examples for the keyword organization.
In the processes, the surveyed papers referred to complexity drivers such as diversity in ways of working; in the types and purposes of process models; in the process distribution; the lifecycles and iteration perspectives; in the process phases; in the process standards; and in the intended results of the processes. Diversity complexity drivers related to the project are found in project management styles and strategies, in teams, between projects, and between the project-level and the organizational-level needs.
Finally, in the tooling viewpoint, we found the semantic gaps and overlaps between the databased and tools to be one of the major complexity drivers in terms of diversity. Next to this, we mapped the diversity: in versioning concepts, in infrastructure and enterprise architectures, in the multiplicity of tools, in the tool management strategies, in fidelity, in the internal data structures, and in the data exchange standards.
3. Complexity drivers related to uncertainty
Uncertainty was the least mapped group of complexity drivers (see Fig. 9b), with most references found in the system viewpoint. Instances of uncertainty of the system related to the use of new technologies or combinations; the fulfillment of customer needs; the system boundaries and external environment; the verification quality and testing capabilities; and to the consequences of trade-offs and design decisions. In terms of data, information and knowledge, uncertainty was associated with the information contained in the artifacts; the boundaries of the information; and the migration and sharing of data and information. For the discipline keyword, uncertainty related to the required functionality or performance, and the ambiguity of the disciplinary boundaries.
Uncertainty in terms of the social viewpoint, had similar number of references for both its keywords. For the organization, uncertainty was related to environmental conditions for organization’s survival, adaptation, and profitability; return of investment of new products and strategies; and the skillsets and required resources. With respect to the designer, uncertainty was associated with knowledge gaps; design risks and design decisions; changing paradigms; and human nature (interactions, misunderstandings, misinterpretations, etc.).
Some of the complexity drivers found for the process keyword uncertainty are: a) ambiguity in the general understanding of the process; uncertainty inherent in process models; b) uncertainty associated with the risks, innovativeness, c) creativity of the process; uncertainty in priorities and decisions; d) uncertainty in process performance; e) uncertainty due in process trial-and-error approaches and iterations. For the project keyword, most references mentioned uncertainty: in priorities, in logistics, in required resources, and due to project risks.
Finally, for the tooling viewpoint, we only found a few relevant complexity drivers namely the uncertainty in the tools’ performance (in model and simulation exhaustiveness), the uncertainty related to the use or migration of tools, and uncertainty in tool’s appropriateness and adaptation to the users’ needs and processes.
4. Complexity drivers related to dynamics
For the dynamics complexity driver group, the SMS showed more balance in the number of references found. Examples of dynamics complexity related to the system keyword are: (unforeseen) design changes; behavior and emergence; changes in technologies; dynamics of the demands on the system, the probability of change initiation; and systems scalability and evolvability. With respect to the discipline keyword, dynamics related to discipline paradigms, technologies, and discipline dominance. The dynamic nature of design knowledge, information, and data, as well as their collection, transformation, and exchange, were also mentioned as complexity drivers.
Some of the main examples found for the organization are the dynamics of: the organizational and workforce structure; the organizational conventions, strategies, operations, and policies; the culture and internationalization of the working environment; the market, economic and technology trends, and boundary conditions; the relationships with supply chain and customers; and the legislative and regulations. With respect to the designer, dynamics related to changes in position, roles, and responsibilities; group and competence dynamics; (unforeseen) design changes and their effects; as well as individual mentality, paradigms, and culture.
The papers surveyed in the SMS mentioned the changes in the process; (unforeseen) design changes and how the process deals with them; the level of standardization of the process; as well as the dynamic and interconnected nature of the design process as the core complexity drivers. In particular, the paper by Stacey et al. (2020b) offers an in-depth view of the reasons for the dynamic nature of the design process.
For the tooling viewpoint, the dynamics complexity driver group had two main sources: firstly, the tools and the infrastructure themselves, and secondly, the dynamics of the other viewpoints and their effect on the tools. From the first, complexity drivers included the dynamics of the information technology, infrastructure and software and the changes in versioning and storage concepts. Regarding the system viewpoint, we have the effects on the tooling of both the system design changes and the requirements. With relation to the social viewpoint, the dynamics of the tools are affected by the needs for inter- and intra-organizational collaboration and user diversity. Finally, related to the process, the dynamic nature of the design also drives dynamic complexity of the tooling.
5. Complexity drivers related to limitations
In the limitations group, the social viewpoint was the most frequently mapped. The limitation complexity drivers from the keyword organization are related to: resources (money, tooling, human, and time); pressures (market, quality, and competitors); change resistance; psychological climate and motivation; strategies and practices; knowledge limitations; workforce age. From the designer limitations found were: knowledge, experience, training, individual psychological and motivational climate, individual abilities and skills, individual cognitive capacities, limitations by other organizational stakeholders or legislative barriers, and personal biases and preferences.
Most of the references from system viewpoint related to the knowledge, information, and data keyword. Those limitations relate to: the quality of existing information and knowledge; the extraction of tacit/explicit design information, rationale, and semantics; the formalization tension; the consumption needs through the lifecycle; the information overload; and the intangible nature of information and knowledge. The system limitations related mainly to technology and system pressures. In terms of discipline, the limitations were associated with traditions or boundaries; and the tension between the disciplines’ objectives and their optimization.
The limitation instances found for the process were: the intangibility; the difficulty to express and represent; the immaturity of existing methods; the difficulty of practical adoption; pressures of productivity and efficiency; tensions between the various lifecycle stages; genericity and customization tension; the tension between the process creators and followers; the process overload; the appropriateness of the process to a specific purpose; dependency of the process success on resources; the dependency to the organizational structure; and the idealized hierarchy of processes. With respect to the project our findings show limitations related to the resources; the dependency to the organizational structure; and the distance between technical and project management tools.
Finally, for the tooling viewpoint, the limitations group was the largest, which can indicate there are many limitations for this viewpoint. The major tooling limitations found were in terms of functionality, performance; capabilities, and maturity; in the data structures and tooling architectures;; in the exchanges and consistency management; tool vendor restrictions; in the technology infrastructure platforms; tensions in the tools’ genericity vs. specificity; in the tools’ practical application; in the demands of security; tension between technical and human aspects of tools; the tool overload; and dependency on processes and roadmaps, and the quality of tool selection.
c. WHAT are the effects complexity?
The effects are considered the generalized complexity challenges and are derived from the relationships among the complexity viewpoints. The findings are described below as well as in Table 7.
1. Alignment of the system and the social viewpoints
This complexity challenge was by far the most referenced one in the papers checked from the SMS (see Table 7). It was identified in all the solution directions, most notably in the model and knowledge direction. In terms of process, product and tool directions, the challenge was less frequently mentioned, with the tooling one being the least focused on this challenge.
2. Alignment of the process and the social viewpoints:
This challenge was the second most mentioned challenge, although still there was a big difference in the number of references found compared to the alignment of the system and the social viewpoints. For this challenge, naturally, the process solution direction is predominant. In the other directions, we found far fewer references to this challenge (around half of the ones from process in proportion). Particularly in the tool direction, there were the fewest mentions of this challenge, with only 3 out of 15 references.
3. Alignment of the system and the process viewpoints:
This challenge was the least frequently found in the literature. In total, around 30 out of the 135 papers analyzed made any reference to the alignment of the system and the process viewpoints. While about half of the papers of the process direction alluded to this challenge, the other directions, such as knowledge, model, and product, did much less so. Notably, directions such as DSM and tool did not mention this challenge at all.
4. Management of the social viewpoint (human factors):
This challenge was also not frequently found in the analyzed papers; however, the difference is that it was indeed found in all the solution directions, albeit few times. The process direction mentioned it in about half of the analyzed papers, while the fewest mentions were in the DSM, product, and tooling directions.
5. Alignment of the tooling viewpoint with the system, the process, and the social viewpoints:
This challenge was the third most mentioned in the analyzed literature. As expected, the challenge was well covered in the tool direction. Furthermore, in the model direction we also found this challenge in more than half of the papers, and in the DSM in about half of them. For the other directions, we found it only in about a third (9 out of 30) of the papers.
For each complexity challenge there are one or more complexity management strategies. Those will be studied in a follow-up paper, which will cover the solution domain of the study of complexity.