This blog was originally published in the C40 Knowledge Hub and is reposted here with C40’s permission.
The task is clear: in most cities, action to reduce greenhouse gas emissions needs to address how buildings use energy. To do this successfully, cities must design ambitious plans and programs with data at their core. Specifically, cities need to decide what building data should be collected, how to analyze it, and how the information can be used to drive deeper carbon reductions.
At the Institute for Market Transformation (IMT) we specialize in driving market demand for better, high-performing buildings, and work with governments and real estate decision-makers to create and deploy effective solutions that drive action and reap long-term benefits. From our work with cities, these are the things we’ve found to be central for cities to effectively use building performance data. While grounded in experience the United States, the broad lessons are applicable to cities seeking to better deploy building data to develop better policies and tackle climate change across the globe.
First, design policies to collect data.
To use data, you have to first collect it. The first step here for many cities is to enact benchmarking and transparency laws, which require building owners to report building performance data. Cities then share that information with the public. To date, in the United States, more than 30 cities, several states, and one county have mandatory policies in place for private-sector buildings.
The data produced by benchmarking and transparency ordinances helps real estate market actors factor resource efficiency into the transactional and management decisions they make about their properties. Benchmarking data can also be used by utilities to improve the marketing and design of their energy efficiency programs, and by researchers to study the impact of energy efficiency policies and programs on building energy consumption. Critically for cities, these policies offer the ability to collect more granular data than is typically reported publicly. We recommend that city policies require access to monthly data at minimum, but many jurisdictions are looking at policies that require more than simply reporting energy use. These policies, like the one recently passed in Philadelphia, require energy audits of facilities, or retrocommissioning or retuning of building systems. When it comes to data, these policies allow a city to collect specific asset-level information on a building.
Second, make sure it’s good data.
All of the uses for benchmarking data rely on the assumption that the data is accurate and reliable – in other words, ‘good.’ If benchmarking datasets are inaccurate to a significant degree, then they could lead real estate stakeholders to dismiss benchmarking data as useless, misinform the analyses of cities, utilities, and researchers alike, and erode trust in the implementing department. It is critical for cities to carefully consider the accuracy and reliability of the building performance data they generate, collect, and publish. This means instituting processes that ensure the data is usable and reliable, integrating all agencies that deal with buildings and standardizing data collection, and creating a centralized database for building-related information.
Third, put the data to work.
Gathering the data is great, but what a city does with it is more impactful. At IMT we spent three years working with the District of Columbia and New York City looking at how these two front-runners of benchmarking are deploying the data collected by their programs. The full takeaways are available in a toolkit called Putting Data to Work, but one example is that monthly consumption data gathered through benchmarking and transparency programs can yield powerful new insights on seasonal energy consumption patterns and anomalies, for both individual buildings and groups of buildings. Using these insights, cities can then provide feedback and support to building owners, and work with utilities and energy efficiency program implementers to refine program offerings to best suit the jurisdiction’s building stock.
In another example, energy audit data collected in New York City allowed the city, via its Retrofit Accelerator, to design targeted campaigns around high-potential energy conservation projects such as its Better Steam Heat campaign. This program targets one of the most prominent heating system types in New York City with simple, packaged upgrades and it is designed to help building owners address the system as a whole to maximize potential savings.
The role of data will only grow.
As more cities take up climate action and, in turn, address how their buildings use energy and other resources, the collection and deployment of high-quality, robust data will become increasingly important. Already, three jurisdictions in the United States—the District of Columbia, New York City, and Washington State—have passed new, advanced building performance standards that require improvements across wide swaths of existing buildings. Data on how buildings are using energy and how they are improving or meeting baseline performance standards are foundational components of these new laws. This trend will only grow: more than ten other jurisdictions have reached out to learn more about these policies, indicating not only an ever-growing appetite to take serious climate action via buildings but also increasing interest in how our buildings are performing. Designing policies and programs from the outset with data collection in mind will result in more effective, accurate, and actionable information for cities and building owners alike.
