“Coming together is a beginning. Keeping together is progress. Working together is success.” —Henry Ford
Every year dozens of studies try to answer this simple question: Does it cost more to build green? And each study seems to come up with a different answer. We can accurately quantify everything. We know that ants are 33 percent of the terrestrial animal biomass on earth. We know that Shakespeare used 34,314 words to write “King Lear.” And we also know that a typical teenage boy in the United States gets 10 percent of his daily calories from soda. So why can’t everyone agree on what the cost is to build green?
The Complexity of Data
To better understand why there isn’t one answer to this question, we began by looking at 23 of the most commonly referenced studies that examine the capital costs associated with green building. While each study brings forward critical research, collectively examining to identify a universal cost premium of green buildings proved unsuccessful. The problem is not that there is a lack information on this topic, nor is there a shortage of data. The problem arises because the results from these studies draw from data sets with five major variables: (1) building type, (2) construction type, (3) rating system, (4) research methodology, and arguably most importantly, (5) the definition of green premium, making it difficult to find a simple answer to an inherently complex question (see side bar). Ultimately, these factors produced a wide delta in the cost data, from a low of zero to a high of 14 percent for the cost premium.
Another key discovery of our research lies in the connections between 13 of the referenced studies (see Figure 1). We found that a significant amount of the current research on green premiums cites data sets from earlier studies, which may compound assumptions, inadvertently pull findings out of context, or draw apples to oranges comparisons. This pattern also evokes the children’s game “telephone,” where one person begins by sharing a piece of information that is whispered to all participants one at a time in a circle, until the last person shares out what they think he or she heard. As anyone who has played the game knows, when information is passed through many ears, or sources, it often is inadvertently changed.
A Larger, Collective Picture
Moving forward, we propose a call to action. We now understand that without a common thread connecting the data points there will continue to be confusion in the marketplace. It is now common practice in the building industry to share ways to decrease costs associated with various sustainable strategies, but our imperative needs to be larger than that. We are now faced with the task of learning from our collective work.
The solution lies in the rigorous collection and dissemination of original data on green building cost premiums. The good news is that there is an abundance of empirical data. (In 2008, green buildings occupied nearly 10 percent of the total global construction market share). The bad news is that there isn’t one method for sharing the costs and savings of green buildings. If we can measure how many calories a typical teenager gets from soda, we should be able to track the cost associated with green building. We need to employ analytical cost-tracking methods to the entire green building process from start to end.
Our collective cost-tracking methods need to be based on data with the same basic characteristics: building and construction type, region, a single baseline standard (i.e. green building rating system), and a product of meticulous data collection and tracking. Building on the groundbreaking Packard Sustainability Matrix, published by the David and Lucile Packard Foundation in 1999, we need to establish the same baseline building for each building type in every region. This will eliminate any ambiguity.
The logical extension of the Packard Sustainability Matrix is to “harness the hive” to create a dynamic, user-generated, and ever-evolving green building cost database (a Wiki-like Web site). Current research suggests that individuals and organizations are beginning to realize that not sharing intellectual property limits opportunities and growth. Nearly 30 years ago Trudy and Peter Johnson-Lenz wrote that “collective intelligence can be additive (each adds his or her part which together form the whole) or it can be synergetic, where the whole is greater than the sum of its parts.” By taking an approach that is both additive and synergetic, we will harvest a common language and a transparent large pool of data, the first steps to aligning cost narratives to ultimately determine what it costs to build a green building.
Sidebar: Not Speaking the Same Language
How the data referenced in the 23 studies differs across five major variables
With no standard industry definition of green premium, project teams can classify green premiums very differently. Most agree that a premium on green building is how much more it costs to build green over a “baseline,” but as green building becomes more commonplace the baseline is ever evolving. One team may consider using low-VOC products a standard practice, while another team may consider it uncommon practice. Some local regulations may require stormwater control measures similar to LEED SS credit 6.1, while others do not.
Is meeting code a cost premium? Houghton, Vittori and Guenther’s report, “Demystifying First-Cost Green Building Premiums in Healthcare,” brings up an important and often overlooked point while examining the notion that it costs more to build a green hospital: More than what? Does a green hospital cost more than the exact same building without the green features? More than the available capital budget? Or more than a neighboring comparable building of the same size and complexity?
Variable 1: Building Type
Variable 2: Construction Type
• New Construction
• Renovations and retrofits
• Aggregated data from both new construction and renovation projects
Variable 3: Rating System
• Energy Star Rated
• BREEAM UK certification
• “Green building” without a common third-party rating system
• Any variation within the LEED framework
Variable 4: Research Methodology
• Data extracted from a controlled portfolio of projects
• Data extracted from a limited portfolio that is not building type, market sector or regionally diverse
• Data extracted from anecdotes and other qualitative data
Variable 5: Definition of a Green Premium
• Derived by comparing the construction costs of LEED buildings to similar buildings where LEED was not considered during design
• If the team met the sustainable goals within project budget - Whether or not the project team took into account strategy-specific green building incentives, like utility rebates