• InSite Intelligence


Sure, you took the “smart” approach. Automated systems, control of each HVAC duct, timers, and sensors seemingly everywhere, and yet, your utility bills are still outrageous. Various highly qualified experts have told you that you’re actually doing better than you could be. You have enough spaghetti graphs to confuse and fool others into making that case. 

Unfortunately, you just can’t turn your head and look away when you know that the money wasted could be better utilized. Your organization’s mission was not to be average and you didn’t get to where you are by being “slightly better” than the other candidates.

On the other hand, you didn’t intentionally put yourself in this spot. Unless you started from scratch, many of your systems or elements of your systems were already in place. Even with a significant capital investment, the ROI probably wouldn’t make sense. When you add the downtime disruptions, suddenly those legacy systems are starting to look pretty sleek and sexy.

Even if you have the latest and greatest systems that seem to be working well by themselves, are those systems working in concert to synergize into a more optimal state? HVAC and other utilities might be automated by sensors, but coordinated with security data or room scheduling not only have the potential to make environments more comfortable, but also more efficient as occupants avoid “cranking” up or down the temperature to meet their physical needs at the moment without regards to the extreme settings left for subsequent occupants.

Turning your head and looking the other way is sounding more and more attractive, but don’t lose hope. Here are three steps that applied to any operation configuration of all scales.

1. Shift how you use your data. Time-based comparisons (day-to-day, week over week, year over year, etc.) and peak analyses have their places, but other critical pieces of information can be extracted from the data that’s readily available to you. Where are the anomalies popping up? How do individual site performances differ from the aggregate? Is there a better way to prioritize maintenance and repairs?

2. Shift from reaction to anticipation. Moderating energy usage can be more efficient than reactive, dormant systems that operate on demand. Bridging your various systems to a common data language and equally accessible through centralizing software is the crucial first step.

3. Spend sooner. It’s pretty safe to say that operational spending is at the top of no one’s “fun ways to spend money list”. Sure, shifting your spend from repairs and replacements to maintenance is a much less bitter pill to swallow, but without a crystal ball, the question becomes more of a matter of when. Machine learning guided by human curation can unveil critical data points that can prevent costly repairs or replacements.

“Optimal” is a relative term and “your mileage may vary” certainly applies to operational effectiveness. Still, we can’t let machines do all of the learning. Together, with your greater, organizational strategies in mind, the data, technology, and human guidance can take your organization closer to that elusive inflection point.

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