In This Issue
Spring Issue of The Bridge on Frontiers of Engineering
March 15, 2012 Volume 42 Issue 1

Using Information Technology to Transform the Green Building

Monday, April 30, 2012

Author: Christopher Pyke

The green building community is using information technology to drive fundamental changes in the real estate market.

The built environment shapes our lives both as individuals and as a society. It is not only a tangible library of our history, a reflection of our technology, and a window into our values and priorities, but also a platform for the future. The built environment greatly affects our health and well-being and is a major factor in our collective impact on the environment.

Today’s buildings are marvels of security, comfort, and accessibility, but we are becoming increasingly aware of their limitations in terms of energy and water consumption, greenhouse gas (GHG) emissions, and storm water runoff, as well as their contributions to diseases (e.g., asthma and obesity), exposure to toxic materials, and physical impairments. The impacts are felt both locally and over large geographic areas that are dependent on global supply chains. In fact, buildings are associated with 40 percent of global primary energy consumption—50 percent if we include the energy consumed in the production and distribution of steel, concrete, aluminum, and glass (IPCC AR4 WG3, 2007).

The negative impacts of buildings have historically been considered economic externalities, and, therefore, were unregulated and isolated from competitive forces in the real estate market. Nevertheless, their pervasive, often invisible, and unaccounted-for impacts have far-reaching implications. Ultimately, reducing the drivers of climate change, enhancing energy security, promoting public health, improving quality of life, and improving the health and well-being of current and future communities will hinge on our ability to create (and re-create) built environments.

In the last 20 years, efforts by the green building community in the United States to respond to these challenges have been led by interdisciplinary, practitioner-led coalitions seeking to advance the design, construction, and operation of built environments to promote human health, well-being, and the protection and restoration of the environment. The movement began with an image and a simple idea, a classic market-adoption curve (a conceptual illustration of the distribution of practice or performance in an industry, ranging from a few scofflaws on the low end through the average-performing majority, to a small group of innovators on the high end [Roger, 1962]). The idea was to use strategic market interventions to permanently shift distributions of practice toward higher performance and greater achievement.

Although the concept attracted some attention, the image lacked substance, mostly because very little information was available to describe distributions of practice and performance over relevant populations for real-world buildings. Empirical evidence for understanding or predicting the real-world impacts of potential market interventions and green building practices was also scarce. We simply did not have the data or tools we needed to provide an empirical foundation to support the founding vision.

Fortunately, the lack of experience and data did not delay action. Leaders of the movement first defined “green” and set an initial direction by defining “good,” “better,” and “best” practices and preferred levels of performance. In this way, they provided a credible directional signal to the industry—not perfect and not always rooted in data, but useful as a basis for action. The next steps were to develop a workforce and assess tools, policies, and programs for recognizing and rewarding high performance.

As a result of efforts by thousands of organizations, the movement soon made a real impact on the building industry. Today, hundreds of thousands of professionals have received green building training and personal accreditation, and thousands of individual projects have been evaluated and certified against third-party standards (Watson, 2011).

The next generation of green building will return to its beginnings, propelled by an emerging foundation of data and analytics that provide empirical support for the original vision. We can now cite data to describe the prevalence of performance and the distribution of actions among market participants. We can create the “curves” we have been talking about and promoting, powered by a state-of-the-art information ecosystem rooted in project performance and evidence-based practice.

Measuring Green Performance and Achievement

We now have tools and processes for designing and assessing high-performance green buildings and communities. The concept of a green building “project” has evolved to encompass commercial interiors, homes, commercial buildings, and even entire neighborhoods—ranging from less than 1,000 square feet to more than 50 million square feet. With thousands of projects completed and thousands more in the pipeline, green building projects are becoming the currency of data-driven market transformation.

Recognition for projects is typically based on the implementation of specific design and operational strategies (e.g., integrative design, energy efficiency, water conservation), the achievement of milestones (e.g., facilities management policies), and, increasingly, the performance of whole systems, ranging from interior spaces to neighborhoods (e.g., whole-building energy performance).1

Project-rating systems, such as the U.S. Green Building Council’s Leadership in Energy and Environmental Design (LEED™)2 and a number of analogous systems around the world define required levels of achievement and performance to meet a wide range of criteria (Cole, 1999). Projects that meet or exceed requirements are recognized by LEED certification and other designations.

In effect, assessment systems and third-party certification tools have responded to historic deficiencies in information and market failures (e.g., the lack of information about energy efficiency or GHG emissions) by providing credible information about practices and performance levels. For example, LEED certification brings transparency to many aspects of green building, including location and transportation, design and engineering processes, construction activities, site planning, energy consumption and supply, water use, indoor environmental quality, and innovation. Such transparency improves the flow of information among market participants and creates opportunities for competitive differentiation. Fundamentally, the LEED standard provides the long-sought distribution of market conditions and rewards projects that demonstrate leadership in prevailing practices.

Over the past decade, the day-to-day tools for ensuring transparency have been rudimentary—a simple scorecard and, at the end of the process, a glass plaque displayed in a building lobby. Nevertheless, these simple steps have had a remarkable impact on the industry.

Using information technologies, we can now vastly accelerate and scale up the impact of our fundamental goals and concepts. In addition, we can now treat individual projects and collections of projects as testable hypotheses of the efficacy of green building processes, products, and services. Emerging information technology and data sources provide opportunities for reinforcing connections between design intent and real-world impact. The remainder of this article describes a preliminary vision for information-powered, data-driven market transformation.

Information and Efficiency

Classical economics begins with the assumption that market participants have equal and immediate access to relevant information (Fama, 1970; Malkiel, 2003), which is the basis for setting prices and valuing assets. Real estate markets, for example, have developed sophisticated tools that provide information on financial aspects of individual buildings and portfolios, and commercial information services provide benchmarking data related to capital costs, sales prices, tenancy, and numerous other factors. Markets for this information are mature and highly segmented, and market responses are complex, but reasonably predictable (Gatzlaff and Tirtiroglu, 1995).

However, comprehensive information on non-financial dimensions of properties, such as energy use, water consumption, and occupant experience, or on the efficacy of green building practices, such as energy efficiency technologies and water-conserving products is not readily accessible. The absence of this information contributes to inefficient markets, inhibits innovation, and sometimes contributes to market failures (Gillingham et al., 2009).

For example, inefficient, polluting assets may be overvalued, while cleaner, more efficient buildings are overlooked. The most effective practices may be undervalued, and less effective actions may be overrated. The resulting misallocation of resources is a predictable result of the absence of information, and this is now the defining challenge and opportunity for the green building movement.

The most direct remedy is to create public and private mechanisms to provide information on non-financial aspects of assets, such as the green dimensions of homes and commercial buildings, along with information about the contributions of specific practices. This can be accomplished through public labeling programs and private efforts to create information markets and analytical services. Some public programs have been initiated, such as the European Union’s building-level Energy Performance Certificates, green building certifications, and, in a few metropolitan areas, municipal energy benchmarks (IEA, 2010). Complementary private efforts may also be in the offing, but only a few have emerged publicly (e.g., Bloomberg New Energy Finance).

Taken together, however, these efforts barely scratch the surface. Ultimately, we must connect information about performance with essential contextual information in three essential areas: design intent (e.g., original plans), implementation actions and practices (e.g., technologies, management strategies, etc.) and normalization factors (e.g., occupancy schedules, occupant density, etc.).

Accelerating Innovation

Real-world data on how operational performance relates to design intentions and specific strategies, people, products, and services will be the foundation and currency for the next generation of green buildings. However, data per se will not necessarily lead to change. To accelerate market transformation, information must be interpreted and linked to mechanisms that create market opportunities for high-performing projects and, by extension, competitive risks for low performers.

At this point, the interests of the green building movement diverge from those of agnostic market analytics. Rather than improving reporting on the status quo, our goal is to use information to drive permanent, self-sustaining change in entire industries. Success will be measured by the rate and magnitude of those changes.

We intend to use data and information technology to accelerate the diffusion of innovation and the rate of market evolution, that is, the rate at which new practices are taken up by market participants and, critically, their impact on the performance of individual assets and the built environment as a whole. Our goal is to achieve a permanent, positive shift in prevalent practices and performance.

Although the building sector as a whole has not yet embraced these concepts, new data sources and information technologies are creating opportunities for scalable, information-based market interventions. However, realizing these opportunities will require three key components in the design of emerging data streams and information technologies for green buildings:

  • Define outcomes (i.e., performance dimensions subject to evaluation). “Green building” per se is not an outcome. It is a process and an evaluation framework. The next generation of assessments must strengthen connections between desired outcomes (intentions) and operational performance measures, which will lead to more specificity in design, engineering, operations, and evaluations.
  • Understand and reward relatively high performers. Data-driven evaluations of new performance dimensions can provide a basis for sorting and ranking projects; drawing inferences about underlying practices, products, and services; and creating performance-based reward systems.
  • Inspire and assist relatively low performers. Information creates opportunities to identify and improve low-performing projects and strategies in comparison to higher performing peers.


For the past decade, green building has been determined by a single performance dimension—the number of points a project achieves on a rating system. This dimension is typically divided into categories, such as LEED Certified, Silver, Gold, and Platinum levels. Sometimes, the act of certification itself or the level of certification becomes a goal in itself.

We have been exploring ways to expand the traditional focus by developing and implementing a multi-dimensional framework linking green building outcomes and practices. An initial framework was released with LEED 2009 (USGBC, 2008), in which every green building “credit” (a.k.a., optional strategy) was quantitatively associated with 13 environmental “impact categories,” such as GHG emissions, resource depletion, and smog formation (Figure 1). On this basis, weights (points) were assigned to individual credits. In addition, credit achievement could be used to track specific outcomes—literally unpacking the information collected during the certification process.

Figure 1

LEED 2012, which has seven core green building outcomes supported by more than 30 metrics (e.g., energy efficiency, renewable energy production), will be designed from the bottom up to associate actions with outcomes. In addition, every action can be critically evaluated with respect to operational performance. The outcomes or performance dimensions can be as “simple” as intensity of energy use (e.g., annual energy use per square unit of floor space) or much more complicated, synthetic measures, such as the 29 weighted factors included in the LEED 2009 GHG Index. Each metric provides a new dimension for ranking and sorting green building projects in terms of goals and outcomes.

High Performers

Each performance dimension is populated with real projects based on third-party verified data collected during the certification process giving us an opportunity to identify and reward high performers. The first test is simple scoring based on performance (e.g., an Energy Star score). However, the confluence of service-based, information technology architectures, highly scalable databases, and pervasive data collection is creating unprecedented opportunities for connecting design and engineering intent with execution and outcomes. Based on these data, we will be able to identify factors that contribute to different levels of performance and achievement (Figure 2).

Figure 2

Fundamentally, we want to understand how projects achieve a given level of relative performance. This will require identifying and tracking relationships among people, organizations, practices, technologies, and many other factors. Each high-performing project can then provide a benchmark for lower performing projects. Data on projects can be combined to evaluate the relative efficacy of green building practices.Today, we can use a demonstration system called the Green Building Information Gateway (GBIG) ( to begin to identify and explore high-performing projects based on multiple outcomes. For example, Table 1 shows the performance and achievement in six categories of an exemplary office building in Chicago, Illinois. The accompanying density plots compare the selected project (the dark triangle) with other projects certified on the same rating system, in this case LEED for Existing Building: Operations & Maintenance (more information is available from

Table 1

Our goal is to use this data and information technology to shorten cycles between innovations, market uptake, operational performance, and positive recognition. This will require creating highly scalable information systems to collect data on performance, practices, and technologies in near real time and provide dynamic, context-relevant benchmarking and recommendations. These data will provide decision makers with timely information for market and green “comparables,” which are not currently available in the real estate industry.

Low Performers

The green building community has always been comfortable recognizing high performers, but for every high performer there are a commensurate number of underperformers. Outside of Lake Woebegone, under-performers are statistically inevitable.

Nevertheless, we have generally been less aggressive in searching out underachievers and trying to understand and assist them. To ensure continued progress, we recognize that we must pursue an understanding of these projects with energy equal to or greater than our pursuit of high performers.

Fortunately, we can adapt the same basic information technologies to identify underperforming projects (Figure 3), determine the factors that affect their practices, and recommend specific strategies for improvement based on practices by comparable higher performing projects. We may also be able to identify specific actions and circumstances that compromise outcomes. Our goal is to understand the challenges and, if necessary, create new or improved interventions to overcome barriers, such as technological limitations, lack of technical understanding, or cost.

Figure 3

GBIG can help identify and explore many outcome dimensions for relatively low-achieving projects. Table 2 shows selected metrics for a LEED for New Construction (version 2.2) project in Washington, D.C. (more information is available from

Table 2

Testing and Evaluation

The ability to understand, stratify, rank, and interpret performance and outcomes with respect to processes, products, and services creates immediate opportunities for encouraging constructive competition and competitive differentiation.It also contributes to a new framework for testing and evaluating green building strategies using projects as natural experiments.

However, realizing these opportunities will require a change in perspective. Today, the implementation of strategies is often considered a mark of achievement—an outcome in its own right. However, in the near future the value of green building strategies will be based on the reliability of their contributions to operational performance and intended outcomes.In this emerging, performance-oriented perspective, every project becomes a real-world experiment representing a unique combination of circumstances, intentions, strategies, and outcomes.

Many sectors have embraced such frameworks, sometimes called evidence-based practices, adaptive management, or continuous improvement (e.g., the familiar “Deming Cycle”). Typically, the goal is to treat practice as iterative experimentation. Every action has an intent, implementation strategy, and anticipated outcomes. The objective is to incrementally strengthen connections between intentions and outcomes.

For example, some physicians practice evidence-based medicine by using data on health outcomes to inform treatment decisions. Similarly, conservation biologists practice adaptive management using information about population trends to refine restoration and protection practices. Evidence-based practice in these domains is supported by closely coordinated monitoring, evaluation, and surveillance programs.

The architectural community is just beginning to recognize similar opportunities for “evidence-based design” (Mortice, 2009).Unfortunately, this industry generally lacks corresponding systematic data collection and systems, and interconnected data and analytics are prerequisites for evidence-based practice. This community will require an information infrastructure like the one envisioned for GBIG.

Green building will help lead this revolution. Every credit in every LEED rating system is defined with respect to a specific intent and documentation. Today, more than 1,000 credits are in regular use for nearly 100,000 projects, representing real-world opportunities for testing a wide range of hypotheses, some of which are more testable than others (Pyke et al., 2010).

In a recent study, we found that 50 per cent of LEED credit intents are currently evaluated based on consistency with a third-party authority or rule, such as purchase of a certified material or implementation of a specified policy (Figure 4). The intentions of the other 50 per cent of LEED credits require evaluations of operations, most often using information from physical measures or human experience in or around projects. Physical measures include energy use, energy production, water consumption, temperature, runoff, and other factors. Human experience reflects the health and well-being of occupants, which can be measured through physiological responses or opinions and perceptions.

Figure 4

Every time we link design or engineering intent and real-world actions with outcomes, we create new performance dimensions that can be used to stratify and compare projects. Combinations of intent, actions, and outcomes are enabled by search, compare, and benchmarking information technologies. The integration of these new streams of data and analytical tools will provide a foundation for the next generation of performance-oriented, evidence-based practices.

Clearly, we will have to place more emphasis on the management of information for the entire life cycle of a project, design and engineering intentions, documentation of actions and implementation strategies (e.g., service providers, products, etc.), and performance monitoring and evaluation systems explicitly linked to intended outcomes. All of these elements will be built into increasingly integrated information ecosystems that span the life cycle of built environments and the length and breadth of the supply chains that support them. This emerging ecosystem will support a pervasive network of data producers and information consumers seeking to create value and gain competitive advantage through superior performance.


The success of green building over the past decade attests to the efficacy of using relatively simple
information-based interventions to produce demonstrable market transformations.In the coming decade, we will need new tools and approaches to bring these concepts to scale and to generate the pace of change necessary to achieve our mission of creating sustainable, healthy, high-performance built environments.

I believe this change will be powered by a new generation of data and information technologies specifically designed to promote market-based competition across multiple performance dimensions, to understand and learn from high performers, and to recognize and improve low performers. Every performance dimension we track provides an opportunity for competitive differentiation. Every high-performing project we identify and rank provides an opportunity for learning, recognition, and reward. Every low-performing project we touch provides an opportunity for education, investment, and improvement.

The critical technologies, such as customized search engines, distributed sensors, social media, service-based software architectures, and cloud solutions, are either already in hand or are rapidly emerging. With these tools, we will be able to engage orders-of-magnitude more projects and, ultimately, move from episodic certification to continuous performance and real-time monitoring. We can already see the contours of this new world, its sweeping implications for green building practices, and the built environments we may someday inhabit.


Cole, R.J. 1999. Building environmental assessment methods: clarifying intentions. Building Research and Information 27(4/5): 230–246.

Fama, E. 1970. Efficient capital markets: a review of theory and empirical work. Journal of Finance 25(2): 383–417.

Gatzlaff, D.H., and D. Tirtiroglu. 1995. Real estate market efficiency: issues and evidence. Journal of Real Estate Literatue 3(2): 157–189.

Gillingham, K., R. Newell, and K. Palmer. 2006. Energy efficiency policies: a retrospective examination. Annual Review of Environment and Resource Management 31: 161–192.

Gillingham K., R.G. Newell, and K. Palmer. 2009. Energy efficiency economics and policy. Resources for the Future Report No. RFF-DP-09-13.

IEA (International Energy Agency). 2010. Energy Performance Certification of Buildings. International Energy Administration Policy Pathway Report. Available at pdf.

Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Working Group III (WG3) (2007), B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, and L.A. Meyer, eds. Climate Change 2007: Mitigation of Climate Change, Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, ISBN 978-0-521-88011-4 (pb: 978-0-521-70598-1).

Malkiel, B.G. 2003. The efficient market hypothesis and its critics. Journal of Economic Perspectives 17(1): 59–82.

Mortice, Z. 2009. Evidence-based design: the deeper meaning to sustainability, building performance, and everything else. AIArchitect 16. June 26, 2009. Available online at evidence.cfm.

Nadel, S., J. Thorne, H. Sachs, B. Prindle, and R.N. Elliott. 2003. Market transformation: substantial progress from a decade of work. American Council for an Energy-Efficient Economy, Report No. A036.

Pyke, C.R., S. McMahon, and T. Dietsche. 2010. Green Building & Human Experience: Testing Green Building Strategies with Volunteered Geographic Information. Research Program White Paper. June 10, 2010, 14 pages.

Roger, E.M.  1962. Diffusion of Innovations, 1st edition. New York: The Free Press.

UNEP SBCI (United Nations Environment Programme, Sustainable Buildings and Climate Initiative). 2010. Common Carbon Metric for Measuring Energy Use and Reporting Greenhouse Gas Emissions from Building Operations. Available online at Pilot_Testing_220410.pdf.

USGBC (U.S. Green Building Council). 2008. LEED 2009 Credit Weighting. Washington, D.C.: USGBC. Available online at

Watson, R. 2011. Green Building Market and Impact Report. GreenBiz Group. 50 pages.


 1 The term “performance” refers to a measurement, typically a quantitative metric, such as energy efficiency, renewable energy generation, water consumption, or occupant satisfaction. The term “achievement” refers to binary or qualitative activities, such as policies, procedures, or discrete choices (e.g., green cleaning, commissioning, or the use of third-party certified building products). The two terms are often used together as “performance and achievement” to reflect the typical range of green building practices.

2 See for more information.







About the Author:Christopher Pyke is vice president of research for the U.S. Green Building Council.