Abstract
The generation of original and valuable solutions is critical to any design process, but which factors affect more the ideation phase?
Creativity has been widely considered as an essential element of the design process being responsible for the intuitive "creative leap" from problem to solution. Nevertheless, recent studies have proved that creativity could be seen as a process itself, dependent on many other factors including knowledge, data, experience, cross-functional view and random inputs. Accordingly, new models of creative design have been proposed to highlight this interplay and support the understanding of design activity. The principal outcome of these insights is the possibility to develop efficacious strategies to teach and improve the creative potential.
This paper aims to review the latest understandings about design ability and the current approaches used for enhancing generativity.
Introduction
Designing is something that all people do; something that distinguishes us from other animals, and (so far) from machines. The ability to design is a part of human intelligence, and that ability is natural and widespread amongst the human population [1]. Traditionally, designing has been considered as part of human daily life. Everyone was considered capable to do it at a certain degree and design thinking was simply considered a human cognitive ability. However, after the emergence of industrial society and the development of designing as a separate profession, it became apparent that even if many people possess a certain design ability, only a few people have a strong design talent. This observation raised the interest of several researchers to clarify the nature of designing. From that moment on, several studies have been carried out to understand which factors affect more the design ability and if there is a way to improve it. To this end, different models have been proposed over the last decades to describe the design process and its activities. Among the prescriptive models, the Archer’s model (1984) splits the process in three different phases: a first analytical phase, essential to clarify the task; a second one more creative, focused on the generation of the possible solutions; and a third phase finalized to the communication [2]. It seems likely that each phase is characterized by different tasks and thus requires different skills. Creativity, for instance, might be essential during ideation, but it is less relevant for the other steps, as the analytical phase.
The contribution of several factors is clearly shown in the block diagram reported in Fig.1, where the final solution is the outcome of multiple inputs: the client’s brief, the designer’s knowledge and expertise, and the collected data. Indeed, what emerges from literature is that the capability to propose a successful and innovative solution is obtained by a proper interplay between different elements. Creativity and intuition, for instance, besides being crucial in designing, are not completely innate and therefore not sufficient by themselves. Education and experience, as well as knowledge, data and cross-functional view, strongly affect the creative potential and the design strategy of a subject. Additionally, factors, such as pressure, time, team structure and leadership [3,4], might influence the generativity process and the overall quality of the proposed ideas. The present paper aims to review the latest insights about the mechanisms that characterize the generation process and the factors that affect more the capability to produce novel and valuable solutions. At the end, few strategies to enhance this creative potential are presented.
Figure 1 - Archer’s model of design process. The model split the design process in three principal phases: analytical, creative and executive. Reproduced by Cross N., 2001
Modeling creative thinking
The generation of a design proposal is what is commonly regarded to as the creative part of designing, hence clearly dependent on the creative potential of the involved designer. Before looking at the different factors that affect the design capability, it might be worth it to explain which kind of mechanisms characterize the ideation process. Over the last decades, research in design has been focused on the development of theories and models to describe the design activity. A turning point has been given by the latest advances in Design Science, that started to consider creative thinking as the design of an idea, revealing the association between ideation and cognitive process. Today, several references support the role of knowledge, data and experience as evolving sources that impact on creativity.
Figure 2 - C-K design process and its operators. Reproduced from Hatchuel et al., 2017
C-K Theory
A well-known model of the creative thinking is the C-K theory , introduced by Hatchuel and Weil in 2003 [5,6]. This theory defines the creative design as the interplay between ideation (space of concepts, C) and available knowledge (space of knowledge, K). Operatively, design begins with a proposition about a desirable unknown object, undecidable with existing knowledge. The process proceeds, as shown in Fig.2, with the progressive description of the object, basing on the available knowledge. To this end, the initial concept C0 is partitioned in space C, using propositions coming from K. These added attributes can be already known in K as property of that object (restricting partitioning) or not known yet (expanding partitioning). This expanding partitioning (i.e. the allocation of an innovative attribute to the initial concept) is what it is generally considered as the creative phase [6]. Interestingly, C-K theory underlines that the generation of new object can only appear if C expansion is warranted by K expansion. It means that each expanding partition must be verified and tested to transform it into a decidable proposition, ultimately producing new knowledge. According to the authors, this double expansion plainly describes a creative process that generates novel and valuable solutions, where novelty and value are clearly dependent on knowledge [6].
Affecting Factors
As stated by the C-K Theory, a creative generation process occurs when a subject is capable to properly use the background knowledge (general knowledge, experience, data, etc.) to ideate something new. A creative individual must be able to link different experiences and objects that have never been connected before. The designer’s background is like fuel to fire and it provides building blocks to create an idea. This is where curiosity finds its maximal results, because the more you know, the more connections you can create. In this respect, the biomedical engineers have an advantage in terms of creativity, due to their wider basic knowledge, not only in electronics, mechanics, chemistry or informatics, but also in physiology, biology and medicine. This interdisciplinarity could strongly enhance their creative potential. Besides creativity and knowledge background, the originality and value of the proposed solutions might be also influenced by the used design strategy, the time available to develop the project and the team structure.
Intuition & Creativity
Designers often emphasize the importance of intuition and creativity in the generation of innovative solutions [2,7]. Intuition is regarded to as an instinctive process, that does not require a conscious reasoning. This capability is essential in exploring new concepts space and can be clearly improved over time and with experience. Creativity, instead, is commonly described as the capability to think in a divergent and unconventional way. This ability to look at the problem from a different perspective enables the generation of an innovative solutions by a so-called "creative leap". A significant description of the creativity is given by Akin and Akin [7,8]. In their studies, the authors demonstrate that when people try to solve a problem, they are typically trapped into a reference frame, given by the more traditional solutions. The ‘sudden mental insight’, that characterize a creative problem solving, occurs only when subjects perceive their own fixation and enlarge the frame: looking “out of the box”. In the popular nine-dots problem (Fig.3), for instance, the implicit nine-dots square, where subjects usually assume that they have to draw, is the fixing reference frame. In order to solve the problem, this frame must be broken to extend the lines to new vertices outside of the square, defining a new and larger reference frame. Remarkably, several experiments show that expert designers are more able to identify and break the reference frame rather than the novices, who usually generate only conventional solutions [7,8]. These observations further support the idea that creativity is not a strict natural talent, but, instead, it is the result of training and experience.
Figure 3 – The ‘nine-dots’ problem. In this problem, nine dots are organized in a 3 x 3 square. The goal is to join all nine dots by drawing just four straight lines without removing the pen from the paper. People commonly assume that they have to draw within the implicit square, whereas the solution requires extending the lines to new vertices outside it.
Knowledge & Data
As mentioned before, knowledge plays a critical role, both in terms of general knowledge and specific competences. It derives from studies and experience and provides the elements to properly understand the brief and identify the most common issues one must deal with. Despite these positive effects, information can also have some drawbacks. Being aware of other solutions to the same problem, for instance, may prevent one to consider creative alternatives, making the subject fixed on the already known design. Interestingly, this fixation effect seems to be less incisive in designers, due to their education. Indeed, according to Purcell and Gero, designers are ‘fixated on being different’, and thus their knowledge is relevant to define what has been already done to deliberately overcome it [9]. Fixation might become positive when it means being tenacious on a problem frame until a solution is given. In that regard, Cross and Clayburn Cross have reported that outstanding engineering designers are used to frame the problem and continue searching for the solution that fit the frame [7,10]. Additional to knowledge, data might contribute to define the problem and generate innovation opportunities, especially in product design. The collection and the elaboration of downstream data, which come directly from customers or from a smart product, have raised the possibility to better understand the market needs and support a continuous adaptation of the product, service and system. What is relevant for our research is that this data availability has completely changed the way to do design, finally affecting the research of novelty and value from a customer perspective.
Design Strategy
The choice of a specific design strategy is another relevant element which influence the final design performance. A design process begins with a brief statement of requirements and it ends with one or more solutions. This initial brief is usually described as an ill-defined problem, due to its vagueness and unclearness. This lack of precision leads to the definition of the requirements over time, by proposing solutions and sketching tentative ideas [2,7]. This problem-solution coevolution has been widely studied over the last decades, showing the employment, by designers, of different cognitive strategies to solve the same problem. The two main variants are the problem-driven design strategy and the solution-driven design strategy, respectively focused on the problem analyses (prior to solution proposal) or on solutions generation (prior to problem structuring) [2,7,11]. Data suggest that solution-driven strategy present a higher creativity score and a higher number of solutions generated, but the overall quality of the proposed solution is higher with a problem-driven strategy [11]. Remarkably, problem-driven strategies are typically associated to engineers, because they are taught to analyze the problem accurately before looking for an optimal solution. On the contrary, solution-driven strategies are mostly related to designers, which tend to generate different original solutions to a less defined problem.
Ways to improve creative potential
Since ideation started to be regarded to as a cognitive process, several researches have been focused on the development of structured design methods capable to strengthen the design ability. Although many designers are still reluctant to use a systematic process for design, literature data demonstrate that ‘flexible methodical procedure’ are efficacious to produce novel and valuable solutions [7]. Le Masson, Hatchuel and Weil, for instance, have supported the idea of a ‘logic of generativity’ [12]. The results of their studies show that a strong generativity is commonly related to a specific knowledge structure, derived from education and expertise. In this regard, the authors have recently analyzed the courses taken by Itten and Klee at the Bauhaus industrial design school. The exercises given to the students were mainly focused on teaching how to use the possessed knowledge to generate their own style, instead of simply providing a stabilized one [12]. These observations clearly demonstrate the critical role of education in the development of a creative mind. What affects the performance is more than the simple knowledge, it is the way one can use it. Another well-known tool to support the ideation process is the traditional use of sketches. This classical method of design-by-drawing enables to identify critical details and recall relevant knowledge. Designers use sketches to explore the problem and the solution together, providing further insights into the problem and supporting the generation of unconventional alternatives [13]. Apart from this traditional approaches, other innovative creative design methods have been proposed over time. The main goal of these methods is to stimulate the creative thinking, basically by releasing the flow of ideas, removing the cognitive biases that commonly limit creativity. Several studies in cognitive sciences have highlighted the obstructing role of these mental blocks (e.g. fixation effect) during ideation process and different methods have been proposed to overcome them. One of the most widely known approach is the brainstorming, where no criticism is allowed, and humor is welcome. Other strategies are based on the use of analogies or random inputs to enhance creativity. Random inputs, particularly, can belong to whatever source - e.g. a word form a dictionary, an image on the tv, a picture from a magazine - and can generate cognitive cross-links [7]. Another way to enlarge the search space is the provision of expansive examples. These inputs commonly provokes participants to propose solutions of a higher originality, supporting the delineation of each one reference frame and providing the momentum to enlarge it [14].
Conclusions
The considerations above support the idea that the generation of a novel and valuable solution is the result of a complex interplay of multiple factors. Despite being essential, creativity is not innate, and it is strongly dependent on the ability to cross-link each one knowledge and data background. The potential of information, however, is ambiguous due to the risk of cognitive bias, that might limit the creative potential, fixing the designer in a restrictive reasoning space. Hence, knowledge is needed to feed creativity, but creativity is crucial to break out the cognitive bias generated by knowledge. To conclude, the factor that probably affect more the ideation process is the ability to make creativity and knowledge cooperate, without relying only on one or the other. Education and experience are keys in providing this cross-functional view, and recent design strategies could be applied to escape the mental blocks and unleash original ideas.
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