Why Estimating Operating Expenses Without History Is One of Commercial Real Estate's Hardest Problems
Estimating operating expenses for a building that has never been occupied puts every assumption on trial. There are no prior-year reconciliations to anchor the numbers, no utility bills to average, and no service contracts to benchmark against. For tenant representatives, occupier advisers, and investment teams, the absence of an operating history is not a minor inconvenience — it is the primary underwriting risk in a new-building transaction.
The stakes are real whether the building in question is a newly delivered office tower, an industrial facility under a triple-net lease, or a mixed-use development still in lease-up. Lease-economics decisions made today will govern cash flows for five to fifteen years. Getting the expense estimates materially wrong — high or low — distorts the net present value of occupancy, misstates total occupancy cost, and can trigger painful lease reconciliation surprises in years two and three when actual bills arrive.
The methods that experienced practitioners use to solve this problem are not mysterious, but each carries specific assumptions, data requirements, and blind spots that must be understood before the numbers are relied upon. This article explores 6 ways to estimate operating expenses in a new building with no history, covering what each method demands, where it breaks down, and how they can be layered to produce a defensible underwriting position.
Method One — Comparable Building Benchmarking
The most accessible starting point is comparable building benchmarking, which involves sourcing audited operating expense data from buildings with similar vintage, construction type, mechanical systems, and market location. The goal is to find the per-square-foot expense load that a comparable building has actually incurred so that you have a grounded baseline rather than a developer's projection.
Good benchmarking data lives in several places. Lease abstracts from prior transactions in the same submarket will often carry actual base-year stops or gross expense estimates. Property managers in the same market frequently maintain portfolio-level expense summaries that can be shared in a client context. BOMA International publishes annual operating expense data organized by building class, region, and system type, and that data gives practitioners a defensible reference point when negotiating with landlords over projected expense schedules.
The limitation of pure benchmarking is that comparable buildings are rarely identical. A twenty-five-year-old office building and a newly delivered one may share the same submarket and class designation, but their mechanical systems, elevator counts, amenity loads, and energy profiles can differ substantially. Using an older building's expense history to underwrite a new building with a high-efficiency HVAC system will likely overstate energy costs while potentially understating management fees and common-area enhancement costs that come standard in new product.
Method Two — Developer Proforma Analysis
When a building is pre-leased or newly delivered, the developer or landlord will almost always have produced an operating expense proforma. This proforma is not independent evidence — it reflects the developer's interest in presenting the building favorably — but it is not useless either. A well-constructed developer proforma will itemize line-by-line expenses: real estate taxes, insurance, management fees, utilities for common areas, janitorial, maintenance, landscaping, and capital reserves.
The adviser's job when receiving a developer proforma is to stress-test each line, not accept or reject the total. Real estate tax projections are particularly prone to understatement in developer materials, because the assessed value used in the proforma may reflect pre-completion land value rather than the post-completion assessed value that will apply once the tax authority reassesses the improved property. Reviewing the jurisdiction's assessment methodology and comparable assessed values for similar delivered buildings is a necessary step.
Insurance projections in developer proformas deserve similar scrutiny. New buildings in coastal markets, areas with elevated hail risk, or jurisdictions that have seen significant premium increases following catastrophic events may carry insurance costs well above what a stabilized proforma assumes. Reviewing recent insurance renewal data from comparable assets in the same geographic market gives the adviser a check on whether the developer's insurance line is realistic.
Management fees are another frequent source of divergence between proforma and actual. Developers sometimes model management fees at the lower end of market range to make the proforma look attractive, while the actual property management agreement may carry additional oversight fees, accounting fees, and construction management fees that are legitimately passed through under a triple-net or modified-gross lease structure.
Method Three — Engineering-Based Cost Modeling
For large occupancies, complex facilities, and long-term commitments, an engineering-based cost model provides the highest analytical precision. This approach engages a building systems engineer or facility consultant to review the building's construction documents, mechanical and electrical specifications, and equipment inventory, then model expected maintenance and energy costs from the equipment up rather than from market comps down.
An engineering model will segment costs into categories that benchmarking data tends to blend: preventive maintenance schedules by equipment type, expected parts and labor costs based on manufacturer specifications, energy consumption projections derived from the building's energy model or ASHRAE calculations, and capital replacement schedules for major equipment with defined useful lives. Each category carries its own confidence interval, and a good engineer will distinguish between what can be modeled precisely and what requires a range.
The practical limitation is cost and time. A thorough engineering review is not inexpensive, and for smaller occupancies or shorter lease terms, the cost of the analysis may not be proportionate to the economic decision. Engineering-based modeling is most defensible and most commonly used in owner-occupier transactions, ground-up build-to-suit deals, and large-block lease commitments where even a small per-square-foot variance in estimated operating expenses translates into a material dollar impact over the lease term.
One dimension that engineering models address well is the interaction between base building systems and tenant improvement buildout. A heavily built-out floor with server rooms, supplemental cooling, or high-density occupancy will draw more from base building systems than a standard office floor. Those incremental demands affect utility consumption, maintenance frequency, and equipment life — and an engineering model can account for them in a way that benchmark averaging cannot.
Method Four — Lease Comparables and Expense Stop Analysis
Every negotiated lease in a comparable building carries embedded intelligence about what sophisticated parties believed operating expenses would be at the time of execution. The expense stop, base-year gross-up figure, or estimated expense pass-through amount that landlords and tenants agreed to is a revealed preference, not an arbitrary number. Collecting and analyzing those data points across a cohort of recent comparable leases gives an adviser a market-consensus view of expected operating expenses.
Expense stops and base years are particularly informative in office markets. When a landlord and a creditworthy tenant negotiate a lease with a full-service gross structure and a first-year base, the base amount represents a negotiated estimate of what the building's operating expenses will actually be. Analyzing the distribution of base-year figures across comparable new buildings — adjusted for size, floor, and amenity load — produces a credible range that can be used to benchmark a developer's projection.
This method requires access to detailed lease data, which is not always publicly available. In markets where brokers actively share comparable transaction data, the information is relatively accessible. In less transparent markets, practitioners may need to combine public recording data, court filings, and direct network conversations to assemble a usable dataset. Commercial real estate intelligence platforms and lease analysis software tools have expanded access to this category of information substantially over the past several years, though the depth of line-item expense data varies by platform and market.
The lease-economics dimension here deserves emphasis. The difference between an expense stop set at an accurate market level and one set two or three dollars per square foot below market is not merely a budgeting difference — it compounds across the full lease term and can represent a material total occupancy cost variance when expressed in net present value terms.
Method Five — Supplier and Utility Quote Aggregation
A more granular approach to building a bottom-up expense estimate is to solicit quotes directly from the service providers and utilities that will supply the building. Property tax data is public in most jurisdictions. Insurance quotes can be obtained from the carrier market for a described risk. Janitorial and maintenance service contracts can be quoted based on the building's square footage, cleaning frequency, and specification level. Even utility costs can be estimated by applying the building's modeled energy consumption against published rate schedules from the serving utility.
This method is labor-intensive and requires coordination across multiple service categories, but it produces an expense estimate grounded in current market pricing rather than historical averages. For a build-to-suit or a new development in a market with limited comparable operating history — a newly developed submarket, a first-generation industrial park, or a transit-oriented development in an emerging corridor — supplier quotes may be the only reliable pricing source available.
The key discipline is to aggregate the quotes into the same line-item structure that the lease uses to define operating expense inclusions and exclusions. Leases vary significantly in what they include in the recoverable expense pool: some include management fees and others cap them; some include capital expenditures amortized over their useful life and others exclude capital entirely; some include insurance deductibles and others carve them out. The supplier quote exercise is only as useful as the precision with which it maps to the lease's actual expense definitions.
This method also forces the adviser to engage seriously with the specific exclusions and caps that tenants typically negotiate in modern leases. Controllable expense caps, management fee caps, and capital expenditure exclusions each reduce the tenant's exposure to operating expense growth, and the supplier quote model is the right tool for stress-testing whether those protections are likely to be meaningful given the building's cost structure.
Method Six — Sensitivity Modeling and Scenario Analysis
No single estimate of operating expenses for a building with no history should be treated as a point estimate. The honest analytical position is that the future operating expense load is unknown within a range, and the right financial tool is a sensitivity model that shows the occupancy cost and lease-economics outcome under a range of operating expense assumptions — not just the base case.
A well-constructed sensitivity model will hold all other lease variables constant — base rent, rent escalations, free rent, tenant improvement allowance, square footage — and vary the operating expense assumption across a low, base, and high scenario. It will then calculate the effective rent, the net present value of the total occupancy cost, and in a purchase or investment context, the return implications of each scenario. The result is not a single number but a range of outcomes that informs the occupier's or investor's risk tolerance.
The discipline of scenario analysis also structures the negotiation conversation. When the sensitivity model shows that operating expenses three dollars per square foot above the developer's projection would shift effective rent materially — by a hypothetical example, increasing the present-value cost of occupancy by a meaningful percentage over a ten-year term — the adviser has a concrete basis for negotiating expense caps, audit rights, and base-year gross-up provisions that protect the client against the downside scenario.
For a new building with no operating history, that visibility into the assumptions layer is exactly what a scenario model requires — the ability to see which inputs are driving the outcome and to test alternatives without losing the connection between the analysis and the client brief.
Combining Methods — Building a Defensible Underwriting Stack
No single method described above is sufficient on its own. Defensible operating expense underwriting for a new building with no history requires layering multiple methods so that each one provides a check on the others. The combination that most experienced advisers use in practice starts with comparable benchmarking to establish a market-level baseline, overlays the developer proforma to identify where the developer's assumptions diverge from the benchmark, and uses supplier quotes or engineering data to resolve the most significant divergences.
The layered result is then run through a sensitivity model to bound the uncertainty. The final deliverable to the client is not a single projected operating expense figure but a documented range with a recommended planning assumption, a description of the methods used to derive it, and a clear statement of which assumptions carry the most risk. That documentation matters both for the initial leasing decision and for the ongoing management of the lease relationship through reconciliation cycles.
The layered approach also creates a natural checklist for lease negotiation. Where operating expense uncertainty is highest — energy costs in a market with volatile utility rates, or property taxes in a jurisdiction with aggressive post-completion reassessment practices — the negotiating priority is to secure caps, audit rights, and gross-up provisions that limit the client's exposure to the upside of that range. Where the estimate is relatively reliable, negotiating resources are better spent elsewhere.
Common Pitfalls in New-Building Expense Estimation
One of the most persistent errors in new-building expense estimation is treating the developer's operating expense projection as a negotiated number when in fact it has not been tested. Advisers who accept the developer's proforma line items without independent verification are effectively outsourcing their client's underwriting to the counterparty. The right posture is to treat the developer's projection as a starting hypothesis and to apply each of the six methods to test it.
A second common error is failing to account for the lease-up period. A building that is thirty percent occupied in its first year will have a very different operating expense structure than the same building at stabilized occupancy. Some expenses are largely fixed regardless of occupancy — property taxes, insurance, certain maintenance contracts — and in a low-occupancy scenario, those fixed costs are spread across fewer tenants. The gross-up provision in the lease is designed to address this dynamic, but its application requires careful modeling, particularly in a new building where occupancy trajectory is uncertain.
A third error is ignoring the distinction between controllable and non-controllable operating expenses. Property taxes and insurance are conventionally treated as non-controllable, meaning the tenant has no ability to influence them through the landlord's management decisions. Maintenance, management fees, and administrative expenses are controllable, and many modern leases cap the annual growth of controllable expenses. Understanding which expense categories fall into which bucket — and verifying that the lease language matches the conventional treatment — is a prerequisite for accurate scenario modeling.
Finally, advisers should be careful about the vintage effect in benchmarking. A new building with high-efficiency systems may have lower energy costs than an older comparable building, but it may also have higher management costs, amenity costs, and technology infrastructure costs that were not part of older buildings' expense structures. Using benchmark data from a different building generation without adjusting for these structural differences can produce misleading results.
Practical Workflow for the Deal Team
Translating the six methods into a practical deal-team workflow requires assigning ownership of each data-gathering task before the analysis begins. The tenant's adviser typically owns the lease comparable research and the sensitivity modeling. The building engineer or facility consultant owns the engineering-based cost review if one is engaged. The tenant's legal counsel reviews the lease's expense definitions to confirm that the supplier quote categories and negotiated protections align with the actual contract language.
The final step before presenting the analysis to the client is to review the sources and assumptions behind each expense estimate against the actual documents or data points from which they were derived.
Advisers who bring clients a documented, source-backed operating expense analysis — one that shows the method, the data, the range, and the lease protections designed to manage the uncertainty — are delivering a materially higher level of service than those who hand over a single-line expense figure with no supporting methodology. For a new building with no history, that documentation is not a nice-to-have. It is the core of the occupier's or investor's ability to make a genuinely informed decision.
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