How Big Data and Building Analytics Are Revolutionizing HVAC Efficiency—Part 1

In 2014, the world’s businesses generated a staggering 8.4 zettabytes—about 8.4 trillion gigabytes—of digital content, a jump from 2.7 zettabytes in 2012. This explosion of data is what drives the term big data: the practice of turning massive, varied information streams into actionable insights that shape smarter decisions and improved outcomes.

Applying big‑data techniques to building design and retrofits—what we call building analytics—is reshaping how architects, engineers, and facility managers create and operate commercial and residential spaces. The building analytics market is projected to reach $100 billion (€87.5 billion) within the next four years, underscoring the commercial momentum behind this discipline.

HVAC systems are the heart of most building analytics initiatives. Kevin Burns, president of Bob Jenson Air Conditioning, notes that HVAC not only drives a building’s comfort but also represents a huge opportunity for energy savings and operational excellence.

Inefficiency Costs Big Bucks

In residential properties, heating and cooling typically account for 25–30 % of total energy use; in commercial buildings the share climbs to 40–60 %. For example, a single chiller plant can consume roughly a third of all HVAC energy—about one‑fifth of a building’s total consumption.

Identifying waste through meter data alone is challenging because inefficiencies are often incremental and buried in a sea of numbers. However, targeted maintenance combined with data‑driven analytics can cut those high‑cost figures by almost half.

When big data is leveraged, thousands of gigabytes of HVAC telemetry can be archived, revealing historical trends, cause‑and‑effect relationships, benchmark performance, and cost‑efficiency metrics that were previously invisible.

Effective building analytics can reduce annual operating energy costs by up to 20 % once a building hits optimal efficiency, and downtime expenses can drop 35–45 %. In fact, the average return on investment for analytic solutions is more than $13 (€11.3) for every dollar invested.

Visibility at the Top

Many buildings are designed with HVAC components—coils, fans, valves—treated as a single block, ignoring the coupled dynamics that can create hidden inefficiencies. The sheer number of set points, levels, and feedback loops in ventilation systems demands a top‑down view to uncover opportunities for improvement.

The Latest in Algorithmic Learning

Machine‑learning algorithms enable building analytics to predict and adapt to changing weather, detect occupancy patterns, and distribute peak loads intelligently. The newest generation of deep neural networks (DNNs) ingests raw sensor data through multiple layers of abstraction, offering solutions that can slash energy use by up to 30 % in early implementations.

Author: Kevin Burns, president of Bob Jenson Air Conditioning

About the Author

Kevin Burns has led Bob Jenson Air Conditioning in San Diego for 29 years, gaining comprehensive expertise across all facets of HVAC. He mentors dozens of professionals and champions solutions that prioritize the needs of each home and customer.