Design Methodology As a Migration From Analytic Methodology

By Mahdjoubi, Darius

As a mode of thinking, writes Darius Mahdjoubi, design’s value lies in its integrative perspective. In particular, he is interested in the use of models and proposes that a focus on modeling is critical common ground for relating the synthetic methodologies of designers, as they search for new solutions, with the analytic methodologies of scientists, who look for new theories. The limitations of analytic methodology and the need for nonanalytic varieties have spawned an extensive literature. This article introduces design methodology, which is often used by designers and practitioners. It may seem too theoretical and dry for some practitioners, but it intends to provide a new conceptual structure for design, as well as a practical tool.

It can be argued that Western education mostly focuses on analysis and that analysis is our traditional method of problem solving; through analysis we break down phenomena into smaller pieces. Michael Gibbons, et al.’ classify knowledge creation into two modes. The first mode applies the analytic method to more and more fields of inquiry to ensure compliance with what is considered sound scientific practice. However, Gibbons argues, a new, nonanalytic form of knowledge creation (mode 2) is emerging and is carried out mostly for application. We call this new approach to validate knowledge design methodology.

To understand design methodology, we must explore the other two areas of design: design activity and design planning. While the demarcation between the three areas of design is fuzzy at best, the classification does provide the basis for a conceptual structure.

Design activity

Design activity relates to the conceptualization stages of malting new products, usually organized under the rubric art versus technique. Design activity traditionally is classified under three main headings: form, function, and ergonomics. Academic disciplines and professional fields organize design activity into four groups: engineering design, architecture, applied arts and industrial design, and fine arts.

Design planning

Design planning is systematic thinking for actions that go beyond the conventional domain of design activity, in broader areas such as management or operation. While design activity relates to engineering, architecture, and art, design planning applies to a wide range of fields, such as business and military. Design planning relates to the conceptualization stages of planning, composing, decision-making, and management. Programming, composing, strategizing, and problem-solving are like synonyms for design planning; all of them imply a systematic process of thinking about action and implementation. Napoleon Bonaparte is one of the best known design planners. Napoleon allegedly said, “No successful battle ever followed its plan.” Yet he also made action plans for every one of his battles.

Design planning really happens before, during, and after an action. At the base of investigations of the design planning is a problem-solving process, in the widest sense possible. The view of Archer that “designing is the formulation of a prescription or model for a finished work in advance of its embodiment”2 relates to design planning rather than design activity, because the “work” is not confined to art, industrial design, architecture, or engineering.

Design methodology

Design methodology relates to methodologies of implementation. Design methodology may be better reviewed in comparison to analytic methodology. Edward De Bono compared analysis and design and wrote: “With analysis we are interested in ‘what is’ and with design we become interested in ‘what could be.’… Analysis would seek to discover a relationship which might exist (as in science) but design seeks to put forward a relationship which does not exist and perhaps has never existed (as in a new concept).”3

The character of design as a nonanalytic (synthetic) methodology also has been examined by other scholars. Herbert Simon, in The Sciences of the Artificial, contrasted the “natural sciences” and the “science of design”: “The natural sciences are concerned with how things are. Design on the other hand, is concerned with how things ought to be.”4 Simon claimed that design is concerned with synthesis. Science, on the other hand, is concerned with analysis. March compared design with science: “Science investigates extant forms. Design initiates novel forms…. In design the chief mode of reasoning is inductive in tenor, that is to say, synthetic rather than analytic.”5 Glegg compared designers and scientists and concluded: “A designer and a scientist travel the same road but sometimes in opposite directions. The designer goes from the abstract to the concrete, scientists from the concrete to the abstract.”6 This description applies to the comparison of the methodologies for design versus science. Luckman7 classified design under three topics: analysis, synthesis, and evaluation.

Consistent with the above views, one can envision design methodology used for expression and change (manipulation), where analytic methodology might be used for disciplinary scientific investigation. In other words, analysis is the methodology of disciplinary science, and design is the methodology of art, technology, change, strategy, and crossdisciplinary investigation. Science searches for a trutii; design, however, seeks change, expression, and implementation. As Nonaka and Takeuchi point out, the search for truth, which is the main goal of science, has been a philosophical topic since before the ancient Greeks. Modern science (which is based on the works of Galileo, Newton, Bacon, and Descartes) has further refined the search for truth as analytic methodology.8

To go back to Michael Gibbons’s terms, “Mode 1 refers to a form of knowledge production that has grown up to control the diffusion of the Newtonian model to more and more fields of enquiry…. For many, Mode 1 is identical with what is meant by science…. Mode 2 is different from Mode 1 in nearly every respect. Mode 2 operates within a context of application in that problems are not set within a disciplinary framework.”9

Design thinking is an emerging topic in management, and it has strong connections with both design planning and design methodology. David Dunne and Roger Martin describe design thinking as “approaching management problems as designers approach design problems.”10 According to Dunne and Martin, “Integrative design tiiinking uses adductive logic, which means the logic of what might be. Conversely, deductive and inductive logic, which are used in conjunction with analytic methodology, are the logic of what should be or what is.”

Although designers (broadly speaking) use analytic procedures and methods to evaluate an idea, the core of design is its integrative/ synthetic process, which allows the creation and then the implementation of new ideas.

Design methodology and models

Surprisingly, although design methodology, as it is described here, has always been part of the fabric of professional knowledge, it has not secured the attention of scientific circles in the way analytic methodology has. Maybe that is because, as Dasgupta” also points out, drawing and models, rather than writing and text, has been the preferred medium of thought and expression for designers and practitioners.

Science and analytic research are mostly theory-oriented, text- based, and formula-based, while design and technology are mostly action-oriented and model-based. Theories seek the truth, and a formula should define the relationships among the variables it covers as truly as possible. In contrast, a model is an abstract of reality that presents a simplified, incomplete version of something. Accordingly, all models are wrong; but some models are useful. The validity of a model does not lie in its Tightness, but in its usefulness. A good model, however, ought to be able to reveal new ideas that had not been specifically put into it.

Scientist and practitioners both use models, but for different purposes. Scientists use models to explore, explain and check theories, but designers and practitioners use models to explicate and justify their actions. Designers and practitioners tend to be uninterested in theories. The rift between scientists and practitioners in their views toward the role of theory and how theory links to practice demonstrates itself in the following anecdote: Scientists claim “There is nothing more practical than a theory.” Practitioners reply “In theory, there is nothing more practical than a theory; in practice, this is just a theory.”

Models play a key role in design activity, and conceptual model making plays a vital role in design planning and design methodology. Academic researchers also use models to explore and explain new theories or to check hypotheses, but practitioners use models to develop new contexts for application and solution. According to Argyris and Schon:

Practitioners share with academic researchers an interest in building explanatory models of organizational worlds. Like researchers, practitioners try to account for the data they consider relevant, and they often show a decent respect for disconfirming evidence. But practitioners’ models must also serve the purposes of designing. However appealing models may be as tools of exploration or explanation, they are judged by how well they “work,” in the sense of enabling practitioners to do something they wish to do. This decisively affects what criteria apply to the reasoning of practitioners, in what sense they experiment, and in what sense their experimentation may be appropriately called “rigorous.”" An example serves to demonstrate how scientists and practitioners use models for different purposes. Scientists and researchers have used an “input-output” model in a wide range of disciplines-from economics to accounting and from management to sociology-to develop new theories and check hypotheses. Practitioners have used a “black box” model to design and develop a wide range of artifacts, from cars to computers. Actually, both are based on similar principles. Black box and input-output models (Figure 1) consist of three sections: input, output, andfunction (process). Both models assume that functions have fixed structures that do not change much over time, and that functions predictably convert the inputs into outputs over and over again. In the context of the black box model, if we can find the rule of a function one time, then the rule applies indefinitely, and we can predict the output by knowing the input and function.

Figure 1. The black box (input-output) model.

The black box and the input-out models are also consistent with the Cartesian (analytic) approach of splitting big problems into smaller ones, and with ceteris paribus (all else being equal). The black box model assumes that the system under study is inside a super-system, and that the system can be, and indeed is, separated from any other parallel system (ceteris paribus). Inside a black box system, there might be other sub-systems, but they also behave as a series of baby (mini) black boxes, and are separable from each other. From this perspective, both the black box and the inputoutput model act as bases for the Cartesian (analytic) approach mentioned above. The black box has been used by practitioners for troubleshooting. For instance, if you cannot start your car, you would probably take it to a mechanic, who will see if the problem is due to a fault in the gas line or the electrical system. Mechanics are trained to break down each alternative into subsystems and check them out individually in order to isolate the main problem.

The black box and the input-output model are also consistent with the analytic research method of linear causality and dependent and independent variables: input = independent variable or cause, and output = dependent variable or effect. Theories that look for linear structures and linear cause and effect propositions follow a black box model, although many may not articulate it as their base model.

Models play two distinctive roles in the process of theory development: 1) an exploratory role, which leads to the creation of a new theory; and 2) an explanatory role, which hopes to develop a hypothesis to check the validity of an existing theory. The exploratory role happens before the emergence of a new theory; the explanatory role happens after the emergence of a new theory. The black box and input-out models have been used to explore many new academic theories, and are also used to check the validity of existing theories through developing new hypothesis that use dependent and independent variables.

The black box, or inputoutput, model however, is not the only tool in the arsenal of creative designers who have been able to design integrative works. Creative designers have used integrative design approaches to create bold new ideas. Napoleon Bonaparte, as mentioned earlier, was a great design planner and strategist; he was an innovator in numerous fields varying from military to public institutions. The Eiffel Tower in Paris (designed by Gustav Eiffel) is likely one of the best examples of a design that integrates design activity (form and function), design planning (for instance, using the lower levels of the Tower as a hoist to make its higher levels), and a creative mind to turn a simple pattern into a spectacular product. Gustav Eiffel was a structural/civil engineer by training and profession, and he analyzed the different aspects of his products diligently. Although Eiffel used the analytic procedures for structural analysis and to elaborate on the process of making his tower, the creative process that allowed him to design the structure was not confined to an analysis of the parts; he used his mind in a creative way to design and integrate all the aspects of his master work.

The model-based method of investigation

We can further explore the distinction between the analytic and design methodologies, as well as theory and model, if we consider, for instance, Andrew Van de Ven’s “diamond” model.” Using four bases- phenomena (reality), model, theory, and application (practice), the diamond model allows us to articulate the relationships among the distinct methodologies and paradigms that scientists and practitioners follow.

The diamond model lets us articulate two relationships and construct a foundation for a new, model-based method of investigation. Scientists use the analytic methodology to develop new theories from their observations from phenomena (to connect phenomena and theory). Practitioners often are not interested in theories; their main attention lies in implementing their ideas by connecting models into practice (application). In this context, analysis and design can be seen as two methodologies that are separate but interconnected (see Figure 2). Compared to the analytic methodology of science, which connects phenomena and theory, one can imagine design as a nonanalytic (synthesis) methodology that connects model and application.

In addition to using two different methodologies (analytic versus design), scientists and design practitioners also follow two different paradigms. A paradigm consists of a grand model and a validation method, which may be based on an analytic or a design methodology. The grand model defines the framework for the study, and the validation method justifies which types of procedures, activities, or actions are acceptable according to the selected methodology. Scientists and design practitioners tend to fall back on two differing paradigms that are distinguishable in the context of Van de Ven’s diamond model: the scientific paradigm, which is a triangle of phenomena (reality), model, and theory that uses analytic methodology to develop new theories; and the practitioner (design) paradigm, a triangle of phenomena (reality), model, and application that uses design methodology to develop new solutions and applications (see Figure 2). Along the same lines, Shrivastava and Mitroff14 have referred to the two different “frames of reference” that scientists and practitioners use.

If analytic and design methodology-the scientific, as well as the design, outlook-can be integrated, we can look toward a new platform of inquiry, here referred to as the model-based method of investigation (see Figure 3 on page 56). This approach apparently is more flexible than the scientific/analytic approach and underlines the pivotal role models can play in integrating the two distinct methodologies: analytic versus design. The model-based approach, however, requires new conceptual frameworks, ones that go beyond the scope of analytic methodology.

Figure 2. The relationship between analytic methodology and design methodology in the context of the diamond model.

By integrating analytic and design methodologies, the model- based method of investigation can be used for practical purposes, as well as in academic interdisciplinary and cross-disciplinary studies. Combining the knowledge bases of scientists and practitioners would produce a dazzling synthesis that could advance profoundly both theory and practice.

Disconnect between theory and practice

Numerous academic studies have sought ways to bridge theory and practice (application), but this still seems unattainable. The overlay of the scientific and practitioner paradigms also indicates an inherent disconnect between theory and practice-a disconnect driving from the distinctive paradigms that academics and practitioners use. The overlay of the scientific and the practitioner paradigms also demonstrates the key role that models play in linking theory and practice indirectiy. The indirect link between theory and practice through modeling seems very practical, although it has not yet been theorized.

The disconnect between theory and practice derives from the distinctive approaches and paradigms that academics and practitioners use. The disconnect cannot be traversed by expecting academics and practitioners to use similar paradigms and methods of validation, or by expecting designers and practitioners to just follow academic theories. Although a bridge between theory and practice may appear to be a pipe dream, theory and practice indeed are linked through the process of modeling. For exampie, Michael Porter’s Five Forces model has been used by many practitioners for industrial and regional planning. Yet, few of them are aware of, or would be interested in, the theoretical background of Porter’s model. No wonder many practitioners have used the Porter model outside its theoretical context.

Figure 3. The model-based method of investigation.

Conclusion

It can be argued that design methodology is actually a migration from analytic methodology. Where analytic methodology is used to investigate disciplinary sciences, design methodology relates instead to methodologies of innovation, change, and implementation, as well as to nonanalytic methodologies for cross-disciplinary studies. Compared to the analytic methodology of science, which connects phenomena and theory, design is a nonanalytic (synthesis) methodology that assists practitioners to connect models and application.

Models play a pivotal role in the development and application of both analytic and design methodologies, and in fact the model-based method of investigation depicts the relationships among analytic and design methodologies, in the context of Andrew Van De Ven’s diamond model. By comparing the scientific and the design practitioner paradigms, the model-based method of investigation demonstrates the key role that models play in linking theory and practice (application). Because of the distinctive paradigms used by scientists and design practitioners, a natural disconnect has always existed between theory and practice (application). However, theory and practice can indeed be linked through the process of modeling.

Reprint #07184MAH50

Design planning is systematic thinking for actions that go beyond the conventional domain of design activity, in broader areas such as management or operation.

Design thinking is an emerging topic in management, and it has strong connections with both design planning and design methodology.

In the context of the black box model, if we can find the rule of a function one time, then the rule applies indefinitely, and we can predict the output by knowing the input and function.

In addition to using two different methodologies (analytic versus design), scientists and design practitioners also follow two different paradigms.

Combining the knowledge bases of scientists and practitioners would produce a dazzling synthesis that could advance profoundly both theory and practice.

The disconnect between theory and practice derives from the distinctive approaches and paradigms that academics and practitioners use.

1. Michael Gibbons, Camille Limoges, Helga Nowotny, Simon Schwartzman, Peter Scott, and Martin Trow, New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies (London: Sage, 1994), p. 1.

2. Bruce Archer, “Systematic Method for Designers,” in Nigel Cross (ed.), Developments of Design Methodology (New York: John Wiley, 1984), p. 57.

3. Edward De Bono, Serious Creativity (New York: Harper Business, 1992), p. 63.

4. Herbert Simon, The Sciences of the Artificial (Cambridge, MA: MIT Press, 1969), p. 5.

5. L. March, “The Logic of Design,” in Nigel Cross (ed.), Developments of Design Methodology (New York: John Wiley, 1984), p. 266.

6. Gordon Glegg, The Science of Design (Cambridge, UK: Cambridge University Press, 1973), p. 1.

7. J. Luckman, “An Approach to the Management of Design,” Operational Research Quarterly, vol. 18, no. 4 (1967): pp. 345-358.

8. Ikujiro Nonaka and Hirotaka Takeuchi, The Knowledge-Creating Company (New York: Oxford University Press, 1995), p. 23.

9. Gibbons, op. cit., p. 2.

10. David Dunne and Roger Martin, “Design Thinking and How It Will Change Management Education,” Academy of Management Learning & Education, vol. 4 (2006), pp. 512-523.

11. Subrata Dasgupta, Technology and Creativity (New York: Oxford University Press, 1996), p. 13.

12. Argyris and Schon, op. cit., p. 36.

13. Andrew Van de Ven, “Professional Science for a Professional School,” in Michael Beer and Nitin Nohira (eds.), Breaking the Code of Change (Cambridge, MA: Harvard Business School Press, 2000).

14. P. Shrivastava, and I, I. Mitroff, “Enhancing Organizational Research Utilization: The Role of Decision-Makers’ Assumptions,” Academy of Management Review 9 (1984): pp. 18-26.

Darius Mahdjoubi, PhD, Visiting Scholar, Innovation, Creativity and Capital (IC2) Institute, University of Texas, Austin

Darius Mahdjoubi is a visiting scholar at the Innovation, Creativity and Capital (IC^sup 2^) Institute of the University of Texas at Austin, and adjunct professor of entrepreneurship at St. Edward’s University in Austin and at the Institute for Innovation and Entrepreneurship of the University of Texas at Dallas. Mahdjoubi has an interdisciplinary PhD in innovation and entrepreneurship from the University of Texas at Austin. He studies, teaches, and provides consulting services on action business planning, business ideation, and innovation commercialization. He is also a professional engineer and focuses his practice on management of innovation, engineering management, and factory design. He can be reached by e-mail .

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