Building Energy Regulations: Getting (and Staying) Ahead

Introduction

This week, leaders from around the world are meeting for COP26 in Glasgow in the hopes of securing pledges for national emissions reduction targets.

Down here in the real world, anything with teeth is coming from local governments.

Back in May of 2019, before the world was turned upside down, New York City passed the Climate Mobilization Act. Part of this package, Local Law 97, mandates that buildings larger than 25,000 square feet must meet emissions targets by 2024 and deeper reductions by 2030, or face fines.

Less than two years later, Washington DC established Building Energy Performance Standards that will impose fines, according to a special task force’s determination, for buildings larger than 50,000 square feet.

And then last month, Boston announced a significant update to its Building Energy Reporting and Disclosure (BERDO) law from 2013, which sets minimum building emissions performance standards, with $1,000 a day fines for noncompliance.

What do all of these have in common? Each of these cities had required owners to submit utility data to an energy benchmarking program in the years leading up to this legislation.

In fact, those benchmarks have informed regulators on where to draw the line in the sand.

Arguments can be made that these laws are heavy handed, that they are poorly designed, or don’t incentivize what they intend to.

That’s all fair, but there’s no fighting the larger trend.

In fact, it’s likely to get much more difficult. Some say that US building energy laws are about 5-10 years behind European Laws.

In London, rules are set to go into effect in 2023 that will ban buildings with poor efficiency from signing new leases, essentially making 20 million square feet, or 10% of all offices, obsolete overnight.

The calculation

Some portfolios have taken a rational economic approach to impending fines. Let’s add up how much the fines will be, and how much it will cost to retrofit our buildings and/or purchase offsets, see which one is lower and do that.

There are a few problems with this.

First, Fifth Wall estimates that New York landlords would collectively face fines of $10 billion per year if the law went into effect today. The same white paper estimates that the cost of improving efficiency will be about $1 billion a year.

But those are aggregates, there may be individual cases where the status quo is less expensive than the fines.

The problem is the potential for binary penalties that, like London’s new law, make properties or entire portfolios obsolete.

The most salient example of this is GRESB. While a voluntary framework for ESG reporting, it is following the same trend as the regulations. Now that there is a strong benchmark with which to work, investors are starting to draw lines in the sand.

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As this grows more prevalent, the problem isn’t that raising capital will be more difficult, it’s that it will be impossible. By then, it’s too late to “turn on” the energy efficiency.

The blueprint

While deciphering the laws, and their associated penalties, can be wildly complicated, the steps to future-proofing a portfolio are relatively straightforward.

The first step is to collect and centralize building-level utility data. This one is easy and affordable and most portfolios are doing it already.

The idea is that a software platform integrates with the various utility accounts and pulls in the cost and consumption data monthly. In some cases, portfolios have opted to pull the data from smart meters to get real-time utility data; however, this is often not necessary for the purposes of reporting and budgeting.

The second step is to get more granular. Here, the industry diverges tremendously in the digital transformation journey. Some portfolios have nothing, many have something, and a few have it completely figured out.

This granular data can be spilt into three buckets:

1. Equipment data
2. Tenant data
3. Work order data

The goal is to rollup and combine these data sets to provide operational intelligence for asset management at the portfolio level.

The trick is that there has to be a business case to capture this data, no one invests in data for it’s own sake. It’s only as useful as the action it drives.

So, let’s quickly review the “why” from the property’s perspective.

Equipment data

This one is relatively straightforward. The critical base building equipment (elevators, chillers, boilers, pumps, HVAC units, etc.) are the most direct opportunity to improve efficiency.

Ideally, this real-time data can be pulled from a building management system (BMS). However, there are cases where the BMS cannot be connected to through an open protocol, it doesn’t cover all critical equipment, or doesn’t capture energy data. In those instances, equipment monitoring sensors can be installed to fill the gaps.

In either scenario, algorithms can analyze the data and identify specific opportunities to improve efficiencies.  

Tenant data

Tenants generally make up around 70% of a building’s total consumption. While owners have historically been hands off, they no longer have much of a choice and are looking for ways to engage tenants on improving efficiency.

An often overlooked opportunity is tenant utility billing, the process by which landlords divvy up monthly utility costs. Some properties are still doing this using spreadsheets and there are plenty of legacy providers that perform the service, but they are not setup to be a data or engagement partner.

Modern software not only generates bills, but provides tenants with real-time transparency into their consumption. Even the bills themselves can be a powerful touchpoint, such as using benchmarking within the building to drive behavior change.

Work order data

As much excitement as there has been about AI-driven smart buildings, the truth is that buildings will continue to depend on the actions of humans.

Work orders may seem disconnected from energy efficiency, but they are in fact a critical piece of the puzzle.

First and most directly, poor maintenance practices lead to higher energy consumption.

Second, work orders are a treasure trove of data about how the building is operating. For example, service requests from tenants, particularly hot and cold calls, are one of the biggest reasons for energy inefficiencies, as those changes are often forgotten and left permanently.

Tying it All Together

Now, many portfolios have these data streams in some form (not to mention air quality and occupancy data, which could be added to this list).

The problem is that they are siloed across many different software providers and/or spreadsheets.

Because of this, portfolio managers are stuck with high-level building data. There’s no transparency into the key drivers at any given property.

Operational intelligence flows directly from consolidating these data streams. This is not only important for transparency, but will be critical to navigate the ever-more stringent regulatory and reporting environment.

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