The building industry is making leaps and bounds in the direction of intelligent buildings as well as attaining a deeper understanding of the interdependent systems within these buildings. While this is true, technically, it’s the building owners and operators who most need to adopt, and adapt to, the capabilities of technological advances.

Owners and operators are universally motivated to decrease operating costs and increase the value of the asset. Sure, the context changes, but at its core operational and energy efficiency are always desirable things. The dilemma of course is that leveraging the capabilities of today’s technology requires a new approach to the old problem: to look at buildings holistically; to push for services and systems across the organization that have utilization of data as a core design tenet; and finally, to leverage the maximum out of the data you have. Or to paraphrase a line from The Martian, “You need to science the (expletive) out of your data.”

In this article we’ll explore how, in answering five key questions, building owners and operators can reap energy and operational optimization benefits.

1. How is data stored and accessed; what is the format?

Given the daily pressures of managing buildings and portfolios of properties, today’s thinking is usually about discreet product purchases versus planning ahead for future integration. Often, individual domain experts end up making decisions in a vacuum, such as looking for a fault detection solution separate from ticketing systems, separate from optimization services, and separate from occupancy detection sensors.

What ends up happening is siloed data and functionality that serves the immediate needs of the particular decision maker come first, with integrating the data getting kicked down the road as someone else’s problem. That’s inefficient and expensive.

Consider this simple example of lost opportunity and increased cost. Today’s fault detection and diagnosis (FDD) systems are good at finding things that go wrong, in a particular, known way. So the underlying data is built around discreet data streams and fault conditions. What if instead, the system could not only tell what single piece of equipment the symptoms are manifesting in but all related equipment as well? Shared data in this way transforms your simple FDD system into the foundation of a knowledge base that captures all related information — from work ticket resolutions, to preventative maintenance, to a slow increase in energy consumption over the course of months.

2. Is there an open API to the data?

Enter the new generation trying to address this problem of siloed data and how to manage that data for the betterment of optimizing assets. The tools and ability to analyze building data are more advanced than they ever were and can be put to work faster to drive change. Now, data can be farmed in a more efficient, effective and automated fashion, giving owner/operators more opportunity to make better business decisions.

When you start by thinking of the underlying data as a leverageable asset, you need to know how to use it. So having a set of functions and procedures that allow other applications to access data (an Application Programmers Interface, or API) is key. And it needs to be freely licensed to anyone.

This is essential. Too often data is locked away behind a licensed, fee-based API. This makes sense for computationally driven data generated by a company using patented technology, but hey, it’s your building; it’s your data. I would submit that a vendor that holds your data hostage is not your friend.

Let’s talk closed BACnet systems for a moment here. At BuildingIQ, we run into engagements where a building owner promises us access to BACnet points for our advanced analytics and diagnostic service (not rules-driven, but artificial intelligence-driven) only to find out they have to pay over $50,000 USD to access their data. That is a special kind of buyer’s remorse.

To underscore the need for accessing data, Navigant estimates the total revenue for emerging business models reshaping the intelligent buildings market is expected to grow to $582 billion USD in 2027. And what drives intelligent buildings? Data.

3. What about information that is tied to the data; how is it linked to core data?

When looking at a holistic building and data approach, how the data is linked is very important. Mixing metadata in a single file is perhaps efficient in one respect, but makes using analysis tools much harder.

Going back to our FDD example, let’s say you have a hot desking, open work environment. It stands to reason that over the course of time, some assets will get used more than others, e.g., the copier near the coffee room, automated blinds near the desks by the windows, or the chain of assets that keep high-use areas at a lower set point. When doing your forecast for equipment replacement, you’re going to want to know the projected likelihood of performance decay in the high-use assets. Meaning, you’re going to want to tie the energy cycle trends from those assets to the number of issues/faults/services for that asset plus the time (cost) of repairing that asset and the replacement cost. Note that all these parameters for making a financial forecast aren’t tied to the rule, but to the asset.

A decision made in isolation, with no consideration for other groups in the organization, can mean extra cost because there’s no data to support the increased energy use or higher number of cycles that could be used to predict a shortened useable life for the asset.

4. If I can share my data, what can I do with it?

Consider the way home networks have fundamentally changed the way people live and function. As few as 15-20 years ago, the concept of a wireless network in a house was very advanced. Now think how reliant most everyone is on the Internet in their home and all the ways that network is leveraged on a daily basis.

Home automation, smart thermostats, Alexa, etc., all thrive on shared data and cloud services to tie it all together. This is very similar to a holistic building.

The network in a building should be the foundation for smart buildings. Everything should be able to be tied together to eliminate redundancy in equipment and sensors, look for correlated actions, and more. Tying the system together creates the opportunity to analyze and optimize across the building, and not just one system at a time.

A simple example of this would be cooperatively optimizing the water and air-side of a building’s HVAC system. In the vast majority of cases, one or the other is optimized (if at all). Yet the two systems are inherently linked by outside air temperature and water temperature output from the chiller plant. Jointly optimizing them allows trade offs between each system to be weighed, leading both systems to using less energy.

5. How do I get value out of this system; how does it use data as a whole?

Along with the new technology, we need to think about an integrator that understands data. According to Casey Talon, research director at Navigant Research, “Real estate owners are poised to make major investments in smart building technologies, and they are looking for resources with scale and multi-dimensional skill-sets that can manifest and support their strategy and vision. A new breed of Master Systems Integrators may just be the link between vision and reality that the market needs.”

Companies like BuildingIQ have a data-first approach to building systems (in our case, the HVAC control system) wherein attaining, storing and leveraging the data is inherent in the design of the system. When you strip away the context of the devices and sub-systems, you’re left with enough data that you can compare, analyze and begin to see correlation and influence that crosses functional silos.

For instance, you can see that when windows are open on the south side of a building (via the window sensors) there is a corresponding increase in the variance of zone temperatures on the north side that is big enough that it’s causing an increase in comfort complaints. If you didn’t look holistically at data, albeit with the right tools, you’d never figure out that your HVAC system wasn’t the culprit.

Thinking holistically about data

The conditions are ripe for applying tools, capability and services in holistic ways to drive down operating costs and increase property values. This holistic view requires the right vision for the future, strategic thinking and a mindset change that no system should be purchased, acquired and designed in a vacuum. In understanding how we can leverage the data beyond the service, we can answer questions like how does my purchasing decision today bring value for this year, next year, 10 years or longer? How do we define value? And, what is my real ROI?