Tag: design process

How to Convert Key Design Issues into Research Questions

in: AIACC / 0 Comments
AC_Shepley_Billboard

Architectural designers are prolific generators of research topics. The very essence of the design process is to identify questions and pose answers. This process, emphasized by William Peña and Steve Parshall in Problem Seeking (2012), is a fertile ground for the development of research hypotheses.

A hypothesis is a statement reflecting the opinion of a researcher regarding the impact of a phenomenon or an intervention. The researcher proposes an explanation for an event, the purpose of which is that, when specific circumstances repeat themselves, the results will be identical. Hypotheses are integrated in the scientific method, a series of stages involving identifying an issue, reviewing what is known about the issue, generating a hypothesis, conducting an experiment, analyzing the data, and drawing conclusions. Evidence-based design adheres to the same sequence of operations.

Programming and hypotheses

The distillation and prioritization of design research questions occurs during the programming process, when the primary design goals are generated. While the uninitiated may consider a building program a mere list of spaces, designers are aware that the crux of a good program is the identification of project objectives. These objectives are the equivalent of research hypotheses.

A traditional, competent building program includes:

  • Mission statement
  • Design objectives
  • Functional narrative
  • Adjacency diagrams
  • Space lists
  • Code analysis
  • Preliminary cost analysis, and
  • Support materials (site visit summaries, meeting minutes).

In the interest of substantiating these objectives, an evidence-based design (EBD) program would add:

  • Research articles that address the primary design objectives
  • Studies on EBD return on investment, and
  • Pre-occupancy data embedded in functional narratives, adjacency diagrams and space summaries.

Hypotheses and research topics
A design goal becomes a hypothesis when the designer attempts to gather data and draw conclusions about the effectiveness of the environmental intervention. A hypothesis/design goal may be motivated by one of three circumstances:

  1. A question that arises due to pressing research topics;
  2. A question in response to an untested design innovation; or
  3. An inquiry about the effectiveness of core design goals (Shepley, 2010).

Research topics. Examples of questions that might be considered to be pressing research topics in healthcare are:

  • What are the minimal goals for sustainable design in healthcare buildings?
  • What is the relative effectiveness of decentralized, centralized, or hybrid nursing stations?
  • Do single family NICU rooms have a positive impact on infant, family, and staff outcomes?
  • What are the pros and cons of LDR (Labor, Delivery, and Recovery) versus LDRP (Labor, Delivery, Recovery, and Postpartum) rooms?
  • What is the impact of satellite support spaces in inpatient units?
  • What is the impact of open versus closed nurse stations in psychiatric facilities?
  • Which has a greater impact on staff error reduction, same-handed rooms or mirrored rooms? and
  • Should windows to the outdoors be provided in all NICU (Neonatal Intensive Care Unit) single-family rooms?

Design innovations. Regarding innovation, frequently a designer will introduce a novel feature and need confirmation of its effectiveness. For example, when the first free-standing, single-room maternity care facility was built in California (at Grossmont Women’s Center, San Diego), the building was quickly imitated by hospitals seeking to provide similar care. When a building introduces an innovation that is likely to be replicated elsewhere, the responsibility to conduct research that confirms the appropriateness of the design solution is critical. This is necessary in spite of extensive action research that might have taken place prior to the schematic design process. In the case of the Grossmont Women’s Center, the hospital was advised by a consulting firm that was in the process of developing protocols for LDR/LDRP. Additionally, the design team visited the site where the first LDR/LDRP bed was specified, and built a 6-bed prototype, which was tested for more than a year.

One of the design goals of the Grossmont Women’s Center was to enhance the care of obstetric patients and their families. The research question, therefore, was: Does single-room maternity care enhance the experience of obstetric patients and their families? To address this question, specific hypotheses were developed and a post occupancy evaluation was conducted to confirm whether the design goals were met. Staff completed surveys and participated in interviews, and behavior of staff and patients was observed (Shepley, Bryant & Frohman, 1995).

Healthcare, Evidence-Based Design

Grossmont LDRP room – Photo © The Design Partnership LLP

Core design goals. Regarding research hypotheses that might be generated around design goals, the Bailey Boushay House, a facility for persons with AIDs, included the provision of access to nature as a healing design amenity among its primary design goals. According to the program,

A connection to the earth and its plant life, to fresh air and to sunlight are important attributes of any residential setting. They will be of particular significance in this unique residence. Every opportunity should be taken to promote access to these natural elements. (AIDS Housing of Washington, 1989)

Based on this design goal, a post-occupancy evaluation was conducted to determine whether staff and patients positively received the presence of nature features (solaria, green house, porch, patio). Hypotheses included, “Spaces that provide access to nature will be frequently used by patients and their families,” and “Spaces that provide access to nature will be preferred by staff and patients.” The post-occupancy evaluation included surveys, interviews, and behavior mapping, which corroborated the decision to incorporate these amenities, although in one case a patient lounge/atria was converted to another patient support space (Shepley, Frohman & Wilson, 1999).

Healthcare, Evidence-Based Design

Bailey Boushay House – Photo © Bailey Boushay House

Components of Hypotheses
Most design hypotheses contain four components: the intervention or independent variable, the outcome or dependent variable, subjects, and responses. The physical environment is typically the independent variable, while the dependent variables are the variables that are assessed to measure the impact of the physical environment. The scale of potential independent variables is broad and ranges from the entire site to a piece of furniture. Other physical environmental variables include color, scale, climate, noise levels, and complexity. Dependent variables can be psychological (satisfaction, emotional impact, etc.), behavioral (frequency and duration of use, etc.), physiological (pupil dilation, heart rate, etc.) or mechanical (cost, air quality, etc.).

In the context of healthcare facilities, staff includes: patients, families, visitors, nurses, physicians, technicians, clerical staff, administrators, volunteers, housekeeping, maintenance, food services, and others. Data is frequently gathered about age, duration of employment, duration of visit, gender, etc., as required by some Institutional Review Boards.

Translating design goals into hypotheses
A well-constructed hypothesis should be specific in intent. The following three examples demonstrate this concept.

Case 1: A example of a design goal that has not undergone this refinement would be:

The infusion suite should support the patient’s experience.

This goal includes all four of the components mentioned above. The infusion suite is the independent variable, the outcome is comfort, the dependent variable is support of comfort, and the subjects are patients. However, to translate this into an hypothesis, more specificity is required. If this objective were to be converted for the purpose of a research project, a more appropriate design goal, which might lead to a hypothesis, would be:

The views of nature in the infusion suite should increase patient comfort.

This is more readily translated into a hypothesis, which might be:

Views of nature in an infusion suite increase comfort as measured by patient self-reported perception of comfort.

While some designers might be concerned that this level of specificity limits access to other information, from the perspective of a researcher the question has to be narrow to allow for exploration within a reasonable timeframe.

Case 2: Another example of a broad design goal would be the following:

The psychiatric facility should be designed to reduce undesirable resident behavior.

This would more readily be converted into a hypothesis, if it had a little more detail:

The psychiatric facility should have private rooms to reduce violent events;

which could be translated into the following hypothesis:

Psychiatric facilities with private rooms will have fewer incidents of aggression toward staff and patients than facilities with wards.

The interesting twist to this hypothesis is that it entails a comparison, which is a common technique for evaluating a design decision.

Case 3: A loose design goal might be:

Private NICU rooms are needed to support family-centered care.

A narrower design goal would be:

Private NICU rooms with family sleep space are needed to support family-center care.

To be an appropriate hypothesis, the outcomes need to be yet more specific.

Private NICU rooms with family sleep space result in greater family satisfaction and more time spent in the room with infants than open bay NICUs.

The primary differences among these three hypotheses and their associated design goals is the detail regarding the physical environment and the responses that need to be measured. A secondary difference is the transition from an intention to a statement regarding expected outcomes.

Steps in support of hypothesis generation
For those who are interested in viewing their projects as future research labs, establishing hypotheses is an advantage. To this end, several steps can be taken:

  1. Retain project mission and goal information. Often, once a project is in construction, the preliminary documentation is lost. If firms are interested in conducting research on their projects, the development of hypotheses should take place during the planning and programming phases and be re-visited periodically.
  2. Review EBD journals to examine the structure of hypotheses. Health Environments Design & Research, Environment and Behavior, and the Journal of Environmental Psychology are good sources for hypotheses.
  3. Generate identical hypotheses or design goals across projects, which will enable comparisons and generate more data.
    Create design goals that include independent and dependent variables, subject(s), and response elements.

“A problem well-stated is a problem half-solved.” The generation of hypotheses during the design process is likely to clarify design thinking, support problem solving, and provide the base for potential research.
__________

References
Peña, W. & Parshall, S. (2012). Problem Seeking. New York, NY: Wiley. 5th edition.
Shepley, M. (2010). Health Facility Evaluation for Design Practitioners. Myersville, MD: Asclepion Publishing.
Shepley, M., Bryant, C., & Frohman, B. (1995). “Using a post-occupancy study to validate a building prototype: An evaluation of a new women’s medical center.” Journal of Interior Design, 21 (2), 19–40.
Shepley, M., Frohman, B, Wilson, P. (1999). “Designing for persons with AIDS: A post-occupancy study at the Bailey-Boushay House.” Journal of Architectural & Planning Research, 16 (1), 17–32.

 

Expert Intuition and Evidence Based Design, Part II

in: Emergence / 4 Comments
bookcov650

architecture, health, healthcareThis 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:

  1. 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.

  2. 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.

  3. 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.

 

Expert Intuition & Evidence-Based Design, Part I

in: AIACC / 1 Comment
architecture, health, healthcare

architecture, health, healthcareThe first of two articles in which W. Mike Martin draws on his book Design Informed: Driving Innovation with Evidence-Based Design, co-authored with Gordon H. Chong, FAIA, and Robert Brandt.

Why Evidence?
Architecture is grounded in ideas, visions, and a passion for making environments that inspire our senses. This article is about taking that starting point—a formal concept or a statement about the spatial, geometric, and aesthetic context for inhabitation—and expanding the agenda by bringing evidence to the forefront.

The 2002 Nobel Laureate Daniel Kahneman, a Princeton University psychologist, has studied the concept of expert intuition for decades. He defines expert intuition as the ability to deal swiftly and decisively with difficult circumstances—making a quick chess move, responding to an emergency medical condition, or in our case understanding the complex spatial relationships and configurations of human inhabitation. Many times, under such conditions, the person is not even consciously aware of the decision process that determines the outcome.

This is an exciting time in our profession. New technologies and materials, concern for human performance and experience, and critical agendas like sustainability, energy conservation, globalization, work productivity, healing, and learning are providing important challenges. These challenges are in fact opportunities to refine, expand, and improve our abilities to make places for human experience and add services for our clients.

In this context, understanding the relationship between expert intuition and evidence-based design can be transformative. Such an understanding honors our values and traditions as architects while expanding our capacity to deliver not only inspirational buildings, but ones that increase building performance, enhance human experience, and contribute to making a more sustainable planet. The following set of questions seeks to present the challenges and opportunities in this transformative agenda.

What is Evidence?
During a 2008 interview on National Public Radio, New York Times political commentator David Brooks referred to some of the people being considered as running mates by then President-Elect Barack Obama as being “evidence-based.” This characteristic, according to Brooks, “created potential bridges between Obama and people with sometimes divergent opinions—disciplined consideration of the facts (evidence) would enable them to make reasoned decisions.”

By contrast, when design is cast as an act of expert intuitive creativity, uniquely owned by the designer, it sets a context of ambiguity and uncertainty. Many architects shroud their decisions under a cloak of mystery, inaccessible to their clients, who are expected to approve these decisions through acts of faith. The notion that there is a need to make transparent the basis on which design decisions are made is unsettling to many designers, as it challenges their expert intuition.

Yet every design decision, no matter how small or large, how simple or complex, is grounded in some form of evidence. There is a continuum of evidence found in experience; evidence drawn from expert intuition; evidence grounded in rigorous processes of inquiry; and a mixture of other sources of knowing. The evidence is all around us, but we, as designers, have difficulty acknowledging its importance, it power, its potential for innovation. And we have difficulty making it transparent to others.

This misunderstanding of what practitioners actually do and how they use evidence has generated widespread misunderstanding of the design process and has diminished the perceived value of architects and architecture to society. The public may be enamored by a structural tour de force or a landmark design that captures their spirit, but when they put on their client hat, they know they are responsible for delivering value to their organization, institution, or family. Rarely will the hospital, school, commercial organization, or family judge a building on the basis of aesthetics alone. Rather, it will be judged on its contribution to organizational or individual goals. The fundamental question is, “Do the performance outcomes provide a good return on the resources invested?”

Why Are We Fearful of Evidence?

Most designers, when asked if they use evidence in their design process, will answer, “Of course.” But if you probe a bit deeper, you find concerns about the underlying concept of evidence. There is a belief that evidence binds the designer to a purely rational process of decision-making, limiting the freedom to be creative—to employ expert intuition. Or evidence may expose professional secrets that guide their work and may provide some type of competitive advantage. Much of the reason for this situation comes from our educational and professional training, in which we learn that creativity is supreme and must be protected at any cost.

Another major concern is related to our cultural understanding of the meaning of evidence. Evidence is a legal term, associated with judicial proceedings. That evidence is either true or false, right or wrong. It is about establishing certainty grounded in facts. Yet design challenges typically do not have a right or wrong response; some responses are merely better or more appropriate than others. This creates room for misunderstanding of how best to judge the outcomes of design action.

Designers and clients believe that students learn, patients heal, office workers produce better in certain types of environments; that, in fact, the physical environment can influence human performance and wellbeing. And there is mounting evidence that we can influence organizational performance through design. Yet rarely is this evidence used to ensure those outcomes. Why do we continue to fall back on a model of designing that relies on expert intuition and experience rather than one that melds expert intuition with defensible and transparent evidence?

Precedents for Evidence-Based Design
Evidence is not new to architects. Throughout history, vernacular building forms have used prototypes to ensure a level of predictability about functional effectiveness. Similarly, structural systems have utilized precedent to predictably improve construction stability.

Codes and standards, a basic set of tools of architecture, are validated by systematic testing and past performance evaluations. ASTM was founded in 1898 to address public railway safety through standards that would decrease rail breakage. The organization claims that the consensus standards it issues are the work of its 30,000 members. What better example of collecting experience and applying it to future decision-making?

The U.S. Green Building Council (USGBC) provides widely accepted guidance for design decisions through the Leadership in Energy and Environmental Design (LEED) Green Building Rating System. LEED is an evidence-based tool intended to verify that a building project will be environmentally responsible, profitable, and healthy. Certification through LEED requires a systematic application of performance guidelines that reflect the experience of professionals as well as standards of professional organizations.

ASTM and USGBC are but two of many organizations that seek and use evidence to predictably improve design outcomes. Certainly, both have widespread endorsement by designers. It seems that the use of evidence is well accepted when it relates to building performance as measured by physical testing and building science.

There’s less precedent for the widespread use of evidence to anticipate human performance, but it is there. The Environmental Research and Design Association (EDRA) and others have a long history of seeking linkages between design and behavior. The roots of architectural programming, now a core practice within architecture, can be traced to behavioral design and the application of social science methods to design questions—from which the analysis of user needs evolved into a design strategy. Even so, only a subset of architects uses evidence from the social sciences to make design decisions.

The Need for Confident Closure
In the design world, we tend to focus on artifacts—the building or interior environment that results from the design process. We struggle to define what is an “evidence-based” hospital or school, seeking highly predictive guidelines that can be directly applied to our work and ensure desired outcomes. We struggle to define an evidence-based product.

Perhaps we might look instead toward an evidence-based process. When making design decisions about complex functional and technological environments, we need a more transparent basis for the client and design team to understand and assess choices collaboratively and to reach confident closure. This no longer is just a desire, but has become a requirement on many projects.

In our day-to-day work with our clients, architects and other designers talk about our work in terms of transforming the lives of the people who inhabit the created environments. Too often, however, we lack the evidence to communicate how this is accomplished. Expert intuition suggests that certain design actions will yield a desired response. Do we, however, really know? Do we have the evidence to give confidence to our client? In many case we don’t.

Unlike Barack Obama’s potential teammates in David Brooks’s commentary, architects pervasively lack sufficient evidence about the impacts of design and their decision making process to enable critical assessment by other who participate in that process. Our clients seek to understand how design choices will affect their organizational performance, but we lack the transparent evidence needed for meaningful, critical dialogue. The myth of architecture as a mysterious act of creativity separates the designer from the client. The architect’s expert intuition may inspire, but it cannot by itself create trust.

Evidence Across the Discipline
In recent years, a number of design professionals have embraced the notion of evidence-based design practice, as a model for rigorously seeking or conducting research to predict how well specific design proposals will support desired performance outcomes or, conversely, cause harm. Our profession has tried to learn from similar movements in other professions—medicine, education, engineering—and we’ve explored the relevance of lessons from those fields for the practice of architecture. We’ve challenged both the quality of non-scientific evidence and the applicability of scientific method.

Despite differences of opinion within the profession about the role of evidence and its associated methods, we’ve reached a point of considerable consensus that evidence is a core component of the design process. The health of our profession, measured by the perceived and delivered value of our services, depends on our embracing our clients’ mandates, to provide physical environments that support organizational performance objectives. In this world, the impacts of design on the people who use the environments and the performance of building systems must be anticipated and represented, so that performance outcomes are documented. We must demonstrate in a transparent manner how these performance outcomes are facilitated, so that the proposed design outcomes justify the resources expended.

Many proponents of evidenced-based practice agree that we need to look beyond our individual practices and share what we learn across the profession, just as we have traditionally worked together to create and document technical data in codes and standards that provide performance standards for determining appropriate action. Much can be learned from program analysis, client web surveys, and other techniques that are project-specific, but evidence-based practice must ground itself in broader, deeper data, possible only in a system that enables us to draw evidence from sources beyond the individual project, one that creates an open infrastructure for evidence accessible to everyone involved in the design process.

To be continued . . .

Robert Brandt, Gordon H. Chong, and W. Mike Martin’s Design Informed: Driving Innovation with Evidence-Based Design (John Wiley & Sons, Inc. 2010) is available here.