Which Buildings to Retrofit First: Using Portfolio Data to Prioritize Capital

A single building is an engineering problem. A portfolio is a triage problem. When you manage dozens of buildings and can fund a handful of major projects a year, the expensive mistake is not choosing a bad measure. It is putting good capital into an average building while a genuine energy sink two blocks away keeps burning money. The buildings that most need help are rarely the ones that generate the loudest complaints.

Portfolio data fixes this, if you use it well. Benchmarking metrics like energy use intensity and cost intensity turn a wall of invoices into a ranked list, and a ranked list is what a capital committee can actually act on. The NRCan benchmarking initiative exists precisely because comparison across buildings drives better decisions than looking at each in isolation.

This piece lays out a practical way to prioritize: the metrics that matter, how to find true outliers rather than just big buildings, how to layer in cost and carbon, and how to move from a ranked list to audits and funded projects without over-analyzing.

Start with energy use intensity, but do not stop there

Energy use intensity (EUI), energy per unit floor area per year, is the natural first lens because it normalizes for size. A 5,000 square metre building and a 50,000 square metre building become comparable. As ENERGY STAR explains, EUI lets you compare a building to its type's median and to your own other sites.

But raw EUI alone will mislead you in two ways. First, building type matters: a hospital or a supermarket runs at a far higher intensity than an office by design, so a high number is not automatically a problem. Second, a high EUI in a small building may represent less total waste, and less savings potential, than a moderate EUI in a very large one. Prioritization needs EUI in context, not EUI as a leaderboard.

Find the real outliers

The buildings worth acting on are the ones performing worst relative to what they should achieve, not simply the ones with the highest absolute use. The right comparison is against a peer benchmark for the same property type, whether that is the ENERGY STAR percentile score where the type is eligible, or the NRCan Canadian national median values for types that are not scored.

• Benchmark each building against its property-type median, so a hospital is judged as a hospital and an office as an office.
• Express the gap as a percentage above the median, which puts every building on one comparable scale regardless of type.
• Multiply that intensity gap by floor area to estimate the annual energy, cost, and emissions on the table. This is what turns a percentile into a dollar figure.
• Rank by the size of the prize, not by raw intensity. A large building at 20 percent above median often beats a small building at 60 percent above.

Layer in cost and carbon

Energy intensity ranks buildings by physics. Capital decisions also answer to finance and, increasingly, to emissions targets. Adding two more lenses sharpens the list considerably.

A building can be middling on EUI yet expensive because of demand charges or an unfavourable rate, which points to a controls or load-shifting project rather than an envelope retrofit. Another can look fine on cost but sit high on carbon because it burns a lot of gas, which matters if you have an emissions target or face a building performance standard. Ranking on all three, then reconciling, gives a list that survives scrutiny from both the CFO and the sustainability lead.

From ranked list to funded projects

A prioritized list is the input to auditing, not a substitute for it. The efficient pattern matches the depth of investigation to the confidence you need, using the ASHRAE energy audit levels described in industry guidance and in the U.S. DOE's portfolio auditing work.

1. Screen the whole portfolio with benchmarking data. No site visits, just clean utility data and intensity comparisons, to produce the ranked shortlist.
2. Run a Level 1 walkthrough audit on the top-ranked buildings to confirm the data reflects real conditions and to spot low-cost measures.
3. Commission Level 2 audits on the confirmed priorities, producing specific measures with estimated savings, cost, and payback.
4. Reserve Level 3 investment-grade analysis for the largest capital projects, where detailed modelling justifies the spend.
5. Fund by return and strategic fit, then re-benchmark after completion to verify the building moved and to refresh the ranking.

How MartinAI helps

Portfolio prioritization lives or dies on whether you can compare buildings on a like-for-like basis, and that requires clean whole-building records across every site and fuel. MartinAI reads utility bills and interval data into gap-checked consumption per building, then computes energy use intensity, cost intensity, and emissions on a consistent basis so the comparison is real rather than an artifact of messy data.

Because each building is benchmarked against its property-type peers and weather-adjusted for its location, the outlier list reflects genuine performance gaps rather than climate or building type. The intensity gap, multiplied by floor area, sizes the opportunity in energy, dollars, and carbon, which is the form a capital committee can rank. When a project completes, re-benchmarking from the same data confirms the building moved. The platform does not choose your projects, but it makes the shortlist defensible and keeps it current.

Conclusion

The buildings that deserve your capital are the ones with the largest gap between how they perform and how a comparable building should, scaled by how big they are and reconciled against cost and carbon. Portfolio benchmarking gets you that ranking cheaply, before you spend a dollar on audits. Then match investigation depth to the stakes, fund by return, and re-benchmark to prove the money worked. The alternative, spreading capital by intuition or by whoever complains loudest, reliably funds the wrong buildings first.