Recent talk about Big Data and Smart Buildings has me reflecting on how sustainable development and green building principles have evolved over the past 20 years, and I’ve become increasingly concerned that sustainability professionals will pay too little attention to lessons learned from past mistakes as we dive deeper into a growing sea of data on energy use and other Environmental, Social, and Corporate Governance (ESG) metrics.

We have evolved from the early adopters, prescriptive standards, and disclosure initiatives, to a point where we are now flooded with data and are trying to make sense of what creates real environmental and business value and what is just noise. We have the Carbon Disclosure Project (CDP) evolving from simply disclosure to assessing performance, LEED v4 coming out with a deeper reliance on performance data, and a virtual explosion of energy dashboards and automated efficiency software. In this context, the increased access to mountains of building energy use data and lower cost barriers to outfitting buildings with sensors at the system, equipment, and individual workspace level is like candy in the hands of consulting firms, tech developers, and sustainability pundits. What we choose to do with this candy is critical in determining the future of high performance buildings and the sustainability movement. We have seen an evolution that looks something like the following timeline, when viewed in a linear and simplistic fashion:

Evolution of Green Buildings over the Past 20 Years

Looking across this exciting new frontier, it may be easy to forget some of the toughest lessons we have learned over the past few decades as we have sought to define sustainable development. We must avoid creating more processes where the end result is just reports on the shelf and “expected” or “modeled” energy, water, waste, and cost savings. Instead, we can use lessons of the last 20 years to leverage big data in a way that enables businesses and communities to be more productive with less resource consumption and healthier environmental conditions.

One of the most important of these lessons is that people, not machines, ultimately use our buildings and the built environment.  Already, there are signs that the big data phenomenon and rapid development of smart building technologies is moving out of step with the people that ultimately live in and control these buildings. As a result, my goal with this article is to resurface some lessons about the people-centric aspects of sustainability and offer some examples of how big data can play a positive or negative role.

Managing Mountains of Data

At Altura we have had a lot of fun recently and considerable success working with the explosion of data and smart devices in the real estate marketplace. Low cost access to energy, water, and waste data for systems and equipment within buildings has accelerated the pace at which we can build trends, isolate wasteful operating conditions, and fix problems. This is undeniably great news for business productivity. Whereas an energy conservation project five years ago meant spending significant cash to replace or add equipment in the hopes of eventually earning back your investment, today we can achieve similar savings at dramatically lower costs by using data collection and analysis to optimize existing operating parameters and conditions.

The “mountains of data” effect is perhaps most remarkable for companies who are participating in disclosure and reporting programs such as the Carbon Disclosure Project (CDP) and the Global Reporting Initiative (GRI). We are working with several clients with global real estate presences, and thus energy, water, and waste data that flow back to headquarters in a dizzying variety of formats and with widely varying quality. Getting a handle on standardized reporting and tracking may seem a big challenge, but it is ultimately the easy part. The big management consulting and technology development firms have been quick to the market with tools to collect and manage these large volumes of operational data. The hard part is figuring out what all of that information means to each business and how to use it to improve the core business of the company. At Altura, we combine our experience in building commissioning and energy analysis with financial analytics in order to identify the best bang-for-the-buck opportunities to improve the resource use intensity of a company’s operations.

The Social Component

One constant we have seen across these experiences is that sustainability and energy projects that start off as technical challenges always end up being about people. Viewed positively, people can use the information offered by smart buildings to conserve energy and better enjoy their workplace or home. Viewed negatively, people can defeat a smart building in a matter of seconds if the systems or equipment are preventing them from getting work done or being comfortable. Much has been written about occupant behavior in buildings as a relatively new frontier in the energy efficiency community and about the need for tangible metrics for the “social” component of the triple bottom line or the three-legged sustainability stool.

I’m talking about something much simpler here. People want to be empowered by information and technology – not belittled. For example, the building operator wants that fancy new dashboard to make it easier to avoid and respond to hot/cold calls and doesn’t want to feel like the analysis is really the product of some analyst in a distant room who thinks they know more than the people who live with and in that building. This relationship is analogous to the way we interact with voice controls on our smartphones.  When an app strikes the right balance of user control and “smartness” it gains wide adoption and consumer loyalty. If the first few times you try to navigate your phone by voice you don’t get what you want, the app is dead on arrival.

This people-centric path to success is particularly evident in retro-commissioning projects. We spend the bulk of our time gaining the trust of the building operators and facility managers and providing long-term training and education. These relationships not only ensure that the implemented energy conservation measures persist but they actually result in the discovery of more opportunities and richer opportunities for savings. There is a certain magic the operator shares with the commissioning engineer by divulging ideas they’ve been holding on to for years about how the building could run better.

Similarly, we experimented last year with an integrated lighting system in our office that combined LED lamps, low voltage wiring, and embedded motion, temperature, and light-level sensors at each fixture. Our office lighting was now a beehive of information, collecting data on space utilization, energy use by fixture, and space temperatures. Not surprisingly, this information was not incredibly useful right out of the box. There were technical calibrations to perform to get the timing of occupancy sensors right for the work style and preference of the staff, there were choices to be made about how to graphically display the data in a way that was actionable, and there were emotional concerns to discuss so that people didn’t feel like the system was being used to track their personal level of activity via motion sensor. We got the system to a point where it provided incredible value, but a key observation was that we invested nearly as much money in the form of time spent integrating the information tools into our operations as we did on the purchase and installation of the equipment. I don’t think I’m alone in observing that this time investment is chronically underestimated in projects of all shapes and sizes.

Education Becomes Even More Important

Recognizing that people will always hold the keys to turning on energy efficiency and sustainability improvement projects, we realize how important it is to evolve our education system and resources in line with our data analytics and technology. The process of leveraging “big data” on energy use to drive business value requires a combination of skills in business financial analysis, statistics, and building engineering that is extremely rare. It’s tempting to try to make it work with two of the three skills, but the results are not nearly as good.  Energy savings analyses are not likely to be fully implemented or persistent if they are not designed with a strong appreciation for how the building systems really work and are operated in practice. Similarly, good engineering ideas that are well tested in the field may also fall flat if the analysis does not follow recognized business finance methodologies.

In subsequent posts I will dive deeper into the skillsets that will best support the continued evolution of the sustainability community and effective techniques for providing the required education and training in the field.

Thanks for reading! Please post any comments or questions relevant to this discussion.


Greg Shank is a founding Principal at Altura.  He is the former President of CTG Energetics and has over 18 years of experience managing green building and sustainability projects.