Vertical City Toolkit - Energy Analytics

What if condominium boards or property managers could accurately track how much energy they’re consuming—and, more importantly, catch when something goes wrong before it becomes costly?

That’s exactly what the Vertical City Toolkit is designed to do. When it was first tested, the Toolkit uncovered a hidden issue that had gone undetected for over two months. The result? More than $100,000 in waste—and no clear explanation until the data told the story. Before using this analytical approach, the corporation had no systematic way to detect such issues. High energy bills were typically attributed to seasonal weather changes, and the opportunity for early intervention was lost.

Why Utility Monitoring Matters

Utility costs are a major expense for most condominium corporations—often consuming up to a third of the annual operating budget. Despite this, most corporations lack the tools needed to monitor consumption effectively. When costs spike, the usual response is to dig through historical bills in PDF form or paper copies, a slow and often inconclusive process.

Even when corporations take a progressive step—logging utility usage into spreadsheets—it’s rarely enough. Without a predictive framework or a way to isolate the effects of weather, even diligent tracking can miss the bigger picture. That’s where our Toolkit comes in. (In the image below, the yellow line plots the consumption of each monthly bill.)

Understanding Utility Consumption with Data

The Vertical City Toolkit helps condo corporations move from reactive to proactive utility management. It does this by merging utility billing data with weather data from the Government of Canada’s historical climate records, creating a powerful picture of how consumption should behave relative to temperature.

Consider the example of a building's heating energy use. It’s common sense that more energy is required to heat spaces in colder months—but how much more? Is a sharp increase in consumption justified, or is it a sign that something's gone wrong?

From Weather to Predictive Modelling

Our Toolkit uses machine learning and statistical techniques—specifically polynomial regression—to model the relationship between temperature and energy consumption. This technique analyzes the historical data points of energy consumption at various temperatures and determines the line of best fit – a curve that most accurately represents the underlying trend. This line, along with the dispersion of the actual data points around it, allows us to estimate how much energy a building should reasonably consume given the average temperature for any billing period.

In the chart below, you can see:

• Yellow dots representing actual monthly energy usage,

• A blue curve showing the line of best fit, representing predicted usage based on historical patterns,

• And a surrounding light blue confidence range indicating expected variability.

When a building’s consumption spikes well above this range, we can say with confidence that weather alone does not explain the anomaly. And that’s when a closer look is warranted.

Detecting and Acting on Outliers

Once a prediction model is in place for each utility type—electricity, gas, water, steam—the Toolkit automatically compares each new bill’s consumption to what’s expected, flagging any outliers. This helps property managers spot red flags early, before minor inefficiencies become major expenses.

It’s worth noting: the Toolkit flags anomalies, but it doesn’t investigate them. That responsibility still falls to the property manager. In the initial test, the Toolkit helped uncover a critical issue: two HVAC systems—heating (steam) and cooling (air conditioning)—were running at the same time, battling each other to maintain a set temperature. This had been happening for two straight months, unnoticed, until the data pointed directly at the problem, accounting for the $100,000 in wasted energy.

The blue line in the example above indicates the expected range of consumption based on the temperature, and the yellow line shows the actual consumption - here showing much higher than the relationship of historical weather and bills say it should be. It wasn't an especially cold winter after all!

Why This Matters

Most condominium corporations still rely on anecdotal explanations when energy usage spikes: "It was a cold month." "Maybe the lobby doors were left open more often." These assumptions can delay meaningful action. Our experience shows that without accounting for weather systematically, even seasoned professionals can miss critical clues.

The Vertical City Toolkit closes that gap by:

• Digitizing utility data in a centralized dashboard,

• Integrating historical and current weather conditions,

• Applying statistical models to build predictive baselines,

• Highlighting where actual usage deviates from the expected range.

Final Thoughts

The Toolkit doesn't replace a sharp property manager—it gives them superpowers. With the ability to flag outliers that may have otherwise gone unnoticed, it offers an analytical lens for understanding and managing one of a building’s largest operating expenses.

Energy analytics might not sound glamorous—but when they save your corporation six figures, they suddenly feel essential. If you're a board member or property manager, we built this for you.