When we say BIS builds “data-driven building operations,” that doesn’t mean installing a piece of software — it means running a repeating process. This post walks through what that process looks like step by step, and why each step has to be the foundation for the next.
1. Measurement
Everything starts with measurement — not measuring the building’s aggregate consumption, but real-time, zone-level, system-level data (heating, cooling, lighting, ventilation). This is the level at which decision-grade data exists in the first place.
As we covered in an earlier post, a static energy certificate is no substitute for this, because it describes a standardised estimate, not this specific building’s actual behaviour.
2. Data collection & integration
Raw measurement data isn’t analysis on its own. The second step brings data from different sources — sensors, existing BMS systems, billing data — onto a single, reliable platform: timestamped, validated, and accessible.
This step is also what makes a digital building logbook possible, which upcoming regulation increasingly requires.
3. AI-powered analysis
From the integrated data, the system builds the building’s behavioural baseline and compares incoming data against it continuously. This is where patterns surface that no one-off inspection would ever catch: overnight heating, uneven zone temperatures, gradually degrading efficiency.
We covered exactly how this analysis tells a genuine fault apart from normal seasonal variation in this post.
4. Intervention
Most of the problems this surfaces — in our own project experience — turn out to be control-level interventions, not plant replacements: schedule correction, zone-level fine-tuning, occupancy-based control. This is the step where the analysis becomes an actual change in the building.
The best intervention is the one that needs no demolition, and whose effect is measurable within weeks.
5. Optimization & verification
The last step isn’t “done” — it’s continuous verification. After an intervention, measurement keeps running to document the actual effect, compared against the prior state on a weather-normalised basis. This is what turns a claim (“heating energy use dropped 24%”) into an auditable fact, not just marketing copy.
We walked through this full cycle on a real project in an earlier case study, where exactly these five steps led to a 24% reduction in heating energy use, with no demolition.
Why this is a cycle, not a one-off project
- Occupancy and weather keep changing — the baseline has to track that.
- An intervention’s effect can decay over time (a schedule can drift back) — continuous measurement catches that too.
- The verified result is documentation that’s usable for grant applications, audits, and future decisions alike.
If you’d like to see what these five steps would look like in your building, get in touch, or read a more detailed walkthrough of the process.