Currently, models are experiencing a continuous transition, often motivated by the need to address complex problems in organizations. As described by Janczak (2005),
“Organizations are associations of persons grouped together around the pursuit the specific goals”. Good examples of complex organizations are The North Atlantic Treaty Organization (NATO) and the United Nations (UN), because they are comprised of multiple levels of hierarchy and thousands of units and millions of elements.
Consequently, higher hierarchical levels are often exposed to higher levels of complexity (Bartolomei et al., 2012). As a result, actors (decision makers, engineers, designers, etc.) often do not entirely understand the elements of the system they have to work with (O’Donovan et al., 2004). Therefore, the decision-making process is difficult to perform and manage efficiently when different levels of complexity are dealt with.
Because the design activities and development of methods and patterns are vital to the organizations’ performance, this motivates further research to improve the understanding of processes and how to support them (Parraguez et al., 2016; Wynn and Clarkson, 2018).
Research points out that a systematic approach may help to deal with the above-mentioned problems in several ways. In line with the literature, this dissertation was performed in the context Finnish pulp and paper industry, with a focus on a systematic approach.
The scope of this research is in the Finnish pulp and paper industry. All the empirical materials and data have been collected there. Also the results are only validated within this boundary. Some characteristics, which strongly reflect in the issues raised in the study, relate to the structural properties of the industry. These characteristics and issues have been the focus for data collection, analysis and questions in the research. Firstly, the pulp and paper industry is very capital-intensive industry, because the investments incurred are huge, and the lifetime of those investments is often more than 30 years.
Secondly, the industry is raw materials related, thus the pulp mills require to be located in close proximity to forests. Thirdly, the heavy process industry is inevitably burdening the environment, both using the natural resources and generating emissions. The CO2
emissions are currently a very relevant issue due to climate change, even though the pulp and paper industry as such functions on a sustainable basis, because it operates using biomass and generating emissions that the forest would release overtime in any case.
Fourthly, the market of paper industry is changing rapidly, because the printed paper market is shrinking rapidly due to digitalization. Other new products are emerging to replace the traditional products, such as compostable and disposable paper cups.
The Systems Approach sets out a debate between several parties, each of whom advance their individual, distinctive approaches to the one central problem, in this case the understanding of the engineering systems which we live with (Martin, 1996; Blanchard and Fabrycky, 2013). A systematic approach showcasing the best practices might be helpful to “rationalize creative work, to reduce the likelihood of forgetting something important, to permit design to be tough and transferred, to facilitate planning, to mitigate
complexity and to improve communication between disciplines involved in design”
according to Gericke and Blessing (2011).
Novel applications of systems engineering include, for example, in the area of public sector decision-making (Eppinger and Browning, 2012; Furtado et al., 2015). Decision-making problems may appear at each step of the process design, partly due to the need to deal with technical options (Clark et al., 2009). This type of problems are often linked to several (and in some cases conflicting) requirements, where a creative resolution results in good design (Blanchard and Fabrycky, 2013).
The range of the engineers’ tasks has been shifting from the regular problem-solving role (analytical) into a broader problem-framing role (normative) (Bañares-Alcántara, 2010;
Taeihagh et al., 2009). Consequently, engineers and especially the systems engineers should participate in the decision-making process (Bañares-Alcántara, 2010). Moreover, the area of application of systems engineering is further broadening. For example, in the case of sustainable development, both objectives and criteria for success should be established carefully as part of the decision process.
Decision-making is often a difficult task in complex systems. Decision-making has been present at least since the beginning of management and leadership, but probably longer (Bennet and Bennet, 2008). From at least the 1990s, decision-makers became well-versed in mathematical and statistical techniques, and began to investigate the “qualitative” side of decision-making, dealing with probabilities, preferences and propensities (Bennet and Bennet, 2008). Furthermore, decision-makers are often in situation where they have to trust their gut or intuition. Therefore, this added complexity to decision-making still needs to be further studied.
Research on engineering systems, complex systems and decision-making process has been of interest for many decades a growing phenomenon due to the importance of technical and organizational complexity and social intricacy of human behavior (Bartolomei, 2007; Rouse, 2007). Engineering systems can also be socio-technical systems that provide solutions to central economic and societal challenges (Bartolomei et al., 2012). Moreover, engineering systems combine engineering with perspectives from management, economics and social science in order to address the design and development of the complex, large-scale, socio-technical systems that are so important in all aspects of modern society (Bartolomei et al., 2012). The intersection of the research fields in design, management and social sciences results as engineering systems, shown in Figure 1, and contains the focus of this dissertation.
: Focus area of the research: Mitigating the complexity by structuring and managing complex design activities in complex systems
Figure 1. Positioning of the study within literature
Examples of engineering systems include generation and distribution of energy, enabling global communication, creating affordable healthcare, managing global manufacturing and supply chains or building and maintaining critical infrastructure (ESD, 2008).
These systems have the following things in common: they are complex technically and organizationally are affected by the social aspects of human behavior, and experience a certain level of uncertainty over the span of their operation. In order to address these challenges, an interdisciplinary approach is needed. The approach must target the three major research fields: Social Science, Management of Engineering Systems and Design of Engineering Systems (Bartolomei et al., 2012).
Thus, complexity is generated at the point of interaction or interrelation of elements within a system, and also with elements from the environment of the system (Bennet and Bennet, 2008). According to Bennet and Bennet (2004), complexity is a condition or situation of a system that depends on too many variables and relationships, so it cannot be analyzed or understood by simple analytic methods. Within this context, the problems or situation requiring a decision are “likely to be unique, dynamic, unprecedented, and difficult to define or bound, and have no clear set of solutions” (Bennet and Bennet, 2008).