Buildings IoT

Building Analytics are Difficult – Don’t Let Anyone Tell You Otherwise

By Clint Bradford | July 10, 2018

There’s a paradox in the analytics landscape today, especially for building analytics. On the one hand, analytics seem to be everywhere. Take an autonomous vehicle like Tesla. When you buy a self-driving car today, the analytics system is not part of the sales pitch. But everyone knows they’re there. How else could a self-driving car work without analytic rules in the code and data scientists in the background?

Eventually, this will be true for all controllers as building analytics will be standard. But right now, IoT buildings diverge from the rest of the analytics industry in key ways. First, everyone in commercial real estate asks for analytics without understanding how those building analytics can be applied. Second, there’s misunderstanding on how building analytics may affect existing workflows. And finally, projects start without established goals for what the building analytics system should achieve.

The rise of analytics makes it easy to take for granted their implementation in smart buildings. Obviously, a building is not a self-driving car.

overview of building analytics

Factors That Contribute to the Difficulty of Deploying Building Analytics

Typical building projects fall victim to two major constraints – time and expertise. This leaves contractors in a bind and can result in cut corners on building analytics because they’re the last thing to get implemented into the system.

The reality of today’s building controls contractors is they’re using the same resource to manage the project, engineer the system, deploy it, integrate it, build the graphical user interface, deploy the building analytics and train the end user. No one can be good at all of that, especially on an abbreviated timeline.

The popularity of analytics also makes it seem like something easy to deploy. In my conversations with clients, it’s hard for most to explain how they will apply the analytics in their system, what specific rules they want to run, what insights and actions they want to gain from the analytics.

Even with the huge focus on analytics across industries, for smart buildings, analytics often become an afterthought. We find that’s because most people aren’t thinking beyond the initial roll-out. What happens when you receive analytics alerts or sparks? What are you going to do with monthly analytics reports? How will you respond to the inefficiencies that the analytics system identifies throughout your building?

False Claims About Building Analytics

First, we often hear people discussing how easy it is to gain access to a building database. I actually find this to be one of the most challenging aspects of integration and analytics. There are so many different, proprietary building systems with so many different communication protocols and obscure point-naming schemes. There is precious little standardization in this industry (efforts like Project Haystack are making huge strides which is exciting to see but these challenges still remain across the board).

As with accessing any database, there are also security concerns. Accessing building databases requires involvement from different players across teams, from facilities to IT, from a single location to a corporate headquarters. A good rule of thumb we follow is if it sounds too easy to be true, it probably is.

Too often we hear the market say “let us run analytics on your data.” Or “we can have analytics running against your data in minutes.” I strongly question these claims. No building is the same, and no database is the same. Deploying true building analytics that make an impact is hard, don’t let anyone tell you differently. Successful deployment of building analytics requires a talented team of engineers, data scientists and data analysts to truly make a building more efficient through analytics.

The Way Forward

To overcome these obstacles and join other industries in successfully utilizing analytics solutions, we need to treat buildings like living, breathing things. Analytics engines are only the first step in really understanding your building. In order to continue gaining value from the system, consider its future from the beginning. How will you continue to maintain the building efficiently? What plans are in place to fix issues once the integrator has moved on to other projects? Who on your team has the interest and expertise to manage the analytics long into the future? What training do you have in place to promote efficiency with your workforce?

We’ve found that it helps to have champions on your team who show interest not only in the energy and operational efficiencies of your buildings, but who embrace new technologies with a healthy dose of curiosity. It’s also important to have a plan for phase two of the analytics, when the deployment is complete and the alerts start rolling in. Clear delineation of maintenance and training responsibilities is crucial for continued success.

With the answers to these questions and a trusted partner who will be honest with you, you’ll be well on your way to a smarter, more efficient operation.

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