This is the second of two articles in which W. Mike Martin draws on his book Design Informed: Driving Innovation with Evidence-Based Design (John Wiley & Sons, Inc. 2010), co-authored with Gordon H. Chong, and Robert Brandt. The previous installment can be found here.
Evidence-based medicine is often cited as a relevant model for evidence-based design. Some disagree with comparing design practice and that of medical practice, even disparaging the notion that bioscience has any relevance to the art of architecture. They fear that a data driven approach will lead to the loss of creativity and the role of professional judgment. A closer look at evidence-based medicine reveals similar concerns within the medical community. Nevertheless, proponents argue that neither rigorous standards for evidence nor a practice model that encourages the use of evidence diminishes the role of the professional. Rather, both provide resources to extend professional knowledge and facilitate communication with patients, who increasingly seek to understand their options. The clinician maintains responsibility for understanding the patient’s life context, diagnosing the problem, assessing what data is relevant, and interpreting the best available evidence for application to specific medical circumstances. Far from actuarial, evidence-based medicine increases the reach of clinicians to experts and expertise far beyond his or her personal experience.
Nevertheless, major differences remain as different professionals consider how “evidence” should interplay with experience and expert intuition. The struggle with how to practically implement sustainable processes for developing evidence, in a world where fees and timing seem to diminish year by year creating major challenges for practices. Few design professionals are educated to understand research methods or, more basically, how to access and use research outcomes and evidence. Our academic settings as well as professional practices rarely place value on rigorous methodologies for creating and interpreting the information use to inform design. Even the basic steps of the scientific method—define the problem, create a hypothesis, test, and document—are seldom followed by designers. Consequently, the means for accomplishing specific design performance outcomes evaporate upon completion of the project. Little or no evidence of the basis for design decisions or transparent documentation of the value added in terms of performance indicators are archived for future use.
All of this dialogue—with and without agreement—makes an exciting time to develop an innovative and forward thinking approach for evidence-based practice and the creation of an infrastructure to produce and to archive evidence. The profession has progressed to a point where there is interest and awareness of its potential, yet some hesitancy as to how these future opportunities will influence practice. Some successes have established a foundation for additional research, yet ahead of us is the need to establish a set of standards and guidelines to assure high quality evidence and an effective system for creating, archiving, and dissemination this evidence. It is a daunting task. This is, however, the next major transformation of our profession, creating a context for significant innovative and future-oriented dialogue and collaborative work between the academies and the profession.
How to create better Evidence?
There are sets of conditions that are critical to making the future of evidence-based design useful, accepted, and sustainable.
- All evidence-seeking methodologies have merit; one is not better than another. All have capacities and limitations. It is best to use multiple approaches, each informing the other.
- A commitment to establishing a culture of architectural research in our profession is the mechanism to undertake this complex process of creating, translating, archiving, and using evidence in design. It must be focused and be a controlled examination of individual pieces of a built environment that affect human and building performance, such as light, comfort, acoustics, use, structural capacity, energy consumption, productivity, etc. There is a need for an iterative, “whole to part, part to whole” method that is best suited to architecture—unlike methods in some other disciplines.
- The evidence of “How” in architectural research has a set of traditions, understandings, acceptance, and application related to today’s technology and building systems. These methods are more developed, more measurable, and doable in terms of building performance outcomes. The “new frontier” is in human performance in the built environment or the “What” of design.
- There is a need to expand beyond the AEC industry to interdisciplinary collaborations bringing new research methods and evidence categories to the production and translation of evidence for application in designing, as we are already seeing with programs like LEED and BIM/Integrated Design.
- Depending upon expert intuition and experience alone is fallacious and does not serve our profession well. It is critical that an infrastructure be established that will transfer and archive data from individual projects to a context of shared, accessible, usable evidence, open to individuals, firms, the profession, and other stakeholders.
- There is a need for a realistic approach to: 1) getting research completed by knowledgeable sources—academics, professional researcher who practice, and other organizational structures committed to knowledge production; 2) sources of funding and business models that provide appropriate funding for these efforts; 3) make knowledge outcomes open and meaningful to the profession rather than held as proprietary or as a competitive advantage; and 4) create a system for translating outcomes to practitioners in a rapid and useable form.
- Establish clear and accepted standards and guidelines of what constitutes credible evidence, how it relates and adds to other evidence findings, and what are the methods and process for it creation and application.
Branding of Evidence?
There are three categories of evidence that provide a rich framework for informing our agendas as architects and designers. These three categories have some overlap with previous research and practice agendas, but the focus now is pn how these categories articulate an innovative future that is grounded in enhancing the levels of building performance, human experience, and enriching the formal process of designing and making physical environmental experiences. Some sub-components of each of these categories have evidence that is robust and is already used regularly. Others are quite new and are only beginning to have an impact on design decision-making as guarantors of performance outcomes. Still others sub-components are ideas and visions of how the future could be and are only in the incubator stage but show great promise. The three categories are:
- Modeling, Simulation, and Data Mining: Modeling, simulation, and data mining are a set of technologies that structure innovation, collaboration, and creativity in design by creating physical and virtual representations of objects under investigation. This activity is guided by a hypothesis or critical question that enables the designer to test components or systems as a thinking-by-doing activity.
Modeling is a representational process that tests the characteristics and limits of specific parts or aspects of an artifact, its form, its materiality, its strength, and its capacity to perform.Simulation is a process for understanding the interactions of the parts of a system and the system as a whole. A system is an entity that maintains its existence through the interactions of its parts or components with a focus on their relationship. Simulation is generally referred to as a computational version of a set of models.
Data mining is the extraction of hidden relationships from large databases. This is a powerful new technology with great potential in helping organizations focus on the most important information in their data warehouses—their intellectual capital. The literature refers to this process a “super crunching.” The data crunched captures and records found relationships from diverse sources i.e., personal experience, completed projects records and documentation, and other artifacts developed to support organizational activity. Data mining suggests predictive future trends and behaviors and identifies important questions or hypotheses about future activities and directions within a project or organizational setting.
- Environment and Social & Psychological Behavior: The use of evidence gained through study of the social sciences provides understanding of human behavior. It is an explorative process to gain understanding of human desires, preferences, attitudes, perceptions, and motivations, from a diverse and broad spectrum of generally aligned disciplines, such as history, economics, sociology, cultural anthropology, linguistic, communications, political science, philosophy, cultural studies, and psychology.The discipline of environmental psychology specifically addresses the convergence of the two fields, but other social science research, such as developmental and cognitive psychology, can enrich a designer’s understanding of the behaviors to be supported—or transformed—by the environment. Social science contributes to informed design by providing methodologies through which place-behavior relationships can be studied, as well as knowledge about why people behave as they do and why they might respond to physical surroundings in predictable ways.
- The Physical and Natural Sciences: Within the sciences, the physical and natural sciences are often seen as a single category. While they are both considered “hard sciences,” utilizing similar research bases and methodologies, they are in fact two very distinct sciences when related to architecture.The physical sciences, especially physics, have a long history that provides a foundation for the design of structures, mechanical and electrical systems, and the processes of “making.” Today, the physical sciences continue to provide a rich area of evidence in issues related to building performance.The natural sciences, with a foundation in biology, have had less direct impact on architecture when compared to the physical sciences. However, that’s about to change. Within the past twenty-five to thirty years, the fields of neuroscience and biomimicry have created an renewed interest, respectively, in the relationship of human environmental response and brain activity, and in how natural systems provide frameworks for creating places for human inhabitation.
How to establish the market place for a new brand of Evidence?
The dialogue that will establish this new market place and clarify a direction for this innovative and forward thinking in the architectural profession is critical. This effort will define our roles as design professionals and set agendas for our academies and establishes the standards and guidelines for the next generation of professionals.
As a starting point if is important to acknowledge four conditions:
- The use of evidence is not new to design. However, evidence-based practice is new to architecture. There are ample opportunities to innovate as we refine the sources of evidence and the methods by which it is developed and disseminated.
- One of the major challenges ahead is to instill in the designer a way of working and thinking, based on greater transparency of our methods and how the resulting evidence informs our decision outcomes. It is critical to seek evidence to understand what others have learned about the questions asked and critically assess the source, method, and relevance of the evidence to the question. As the design is developed, there must be metrics that capture the performance outcomes and share them, so that as a profession we collectively build increasingly better evidence and a knowledge base to inform our actions as designers.
- We don’t have all the evidence we need. “Everyone knows” is a much-overused phrase in design. We suspect; we intuit; we sometimes even have some reason to believe. But there are still too many invalid assertions from unsubstantiated sources passing as evidence. It’s in our best interests as professionals to acknowledge that we must step up the quality and quantity of evidence for use in design.
- Evidence-based design is not a panacea. Evidence does not ensure predictable results. Despite the attraction of predictable results, complex environments don’t lend themselves to high degrees of predictability. We can describe relationships between outcomes and whole environments as well as specific design characteristics; but we overstep when we over promise that those relationships will be replicated in different situations. Evidence-based design can help us predict, but the designer’s expert intuition and judgment will be needed to infer the relevance to each new design context.
A Closing or Maybe Just a Beginning?
Over time, it may be discovered that one method of understanding design impacts is more valuable than others. However, for now an approach that supports diverse types of evidence seems most fertile, one that assures evidence has been developed through a process that meets standards and guidelines of practice and is communicated so that the outcomes are transparent to all of the stakeholders in the design process.
In summary it should be clear that evidence-based design is not a substitute for expert intuition, but is a method to increase and support our role as professionals. It is one way to recapture our importance in society for designing places that encourage and facilitate human experiences adding to our quality of life. Transparent evidence, supported by our expert intuition can only increase our contribution to society through value added services. It may also even help with our compensation issues.