What Nobody Tells You About Building Accurate Argus Models

This article explains how building an Argus model in commercial real estate is far more than a mechanical data-entry exercise. It walks through the critical pre-modeling steps—understanding lease structures, mapping stacking plans, analyzing expense recoveries, normalizing operating expenses, and incorporating market leasing assumptions. Using examples from the U.S. office market, it highlights how detailed lease and asset-level insights directly impact valuation accuracy.

Argus Modeling: More Than Just Data Entry

Building an Argus model is not merely about inputting numbers into software—it requires a deep understanding of the asset, its tenants, and the underlying lease structures. The accuracy of any valuation depends on how well this groundwork is done before opening Argus.

A strong model reflects reality. That reality is shaped by lease nuances, expense recoveries, and market dynamics, all of which must be carefully interpreted and translated into the model.

Mapping the Stacking Plan Accurately

The first technical step in modeling a multi-tenant asset is creating and validating the stacking plan. This involves identifying:

• Which tenant occupies which suite or floor.

• Which lease document governs each space.

In practice, this is not always straightforward. A single tenant may occupy multiple suites under different lease agreements due to expansions, renewals, or amendments.

For instance, a tenant in a Chicago office building might:

• Initially lease 10,000 square feet on the 5th floor.

• Later expand into an additional 5,000 square feet on the 6th floor under a separate lease.

• Have different rent commencement dates, free rent periods, and tenant improvement (TI) allowances for each space.

Confusing or merging these leases incorrectly can significantly distort projected cash flows.

Accounting for Lease Nuances and Remeasurements

Lease-specific nuances such as free rent periods, TI allowances, and rent escalations must be carefully captured.

Expansion spaces often differ from original leases. For example, a tenant expansion in Los Angeles may include:

• Longer free rent to incentivize growth.

• Higher TI allowances due to updated building standards.

Another important consideration is building remeasurement. In many U.S. markets, buildings are remeasured using standards like BOMA. However, existing leases typically continue with their original square footage until renewal.

This creates a timing difference:

• Current rent is based on old area measurements.

• Future renewals reflect updated (often higher) rentable areas.

For example, a suite originally leased as 9,500 square feet may be remeasured to 10,200 square feet. The higher area—and therefore higher rent potential—only applies upon lease rollover, directly impacting valuation.

Understanding Lease Structures First

Before starting any modeling exercise, the most critical task is to understand how tenant leases are structured.

In the U.S. commercial real estate market, lease types commonly include Triple Net (NNN), Modified Gross, and Full Service Gross. Each type determines how operating expenses are shared between landlord and tenant.

For example, in a Manhattan office building:

• A law firm under a Full Service Gross lease may pay a fixed rent with minimal direct expense exposure.

• A tech tenant in Austin under a Modified Gross lease might reimburse increases over a base year.

• A suburban office tenant in Dallas under a Triple Net lease could be responsible for property taxes, insurance, and maintenance separately.

Without understanding these distinctions, any Argus model risks misrepresenting cash flows.

Analyzing Expense Recoveries in Detail

Once lease structures are understood, the next step is analyzing recovery methods.

Expense recoveries in U.S. leases can vary widely:

• Some tenants reimburse only specific expenses (e.g., electricity).

• Others reimburse all controllable operating expenses above a base year.

• Certain leases allow recovery of capital expenditures through amortization (e.g., HVAC replacement spread over useful life).

• Management fees may be capped or excluded for some tenants.

For example:

• A Washington, D.C. office tenant might reimburse operating expenses over a 2023 base year, excluding capital repairs.

• Another tenant in the same building may pay a fixed percentage of all operating costs, including management fees.

Even details like gross-ups matter. A landlord may gross up variable expenses such as utilities or janitorial services to 95% or 100% occupancy for recovery purposes—but only if the lease allows it.

These differences must be carefully mapped before modeling.

Normalizing Operating Expenses

A detailed operating statement must be converted into a format suitable for Argus modeling.

This often requires breaking down broad expense categories into finer components. For example:

• Utilities may need to be split into electricity, water, and gas.

• Cleaning expenses may need to be separated from general maintenance.

This is important because different tenants reimburse different components.

For instance:

• A tenant in San Francisco may reimburse only electricity.

• Another tenant in the same building may reimburse all utilities.

Creating standardized expense categories ensures that recoveries are applied correctly across tenants. These categories also become the reference accounts used in Argus.

Incorporating Market Leasing Assumptions

After lease and expense analysis, market leasing assumptions must be developed.

This involves preparing a Market Leasing Assumption (MLA) based on:

• Location within the building (floor height, view premiums).

• Market rents for comparable properties.

• Expected leasing incentives such as free rent and TI allowances.

In U.S. markets, these assumptions can vary significantly:

• Class A office space in New York may command premium rents but also require substantial TI packages.

• In markets like Atlanta or Denver, lower rents may be offset by shorter lease-up periods.

For example, upper floors in a Seattle CBD office tower may achieve higher rents due to views, while lower floors may require additional concessions.

These assumptions directly impact projections for lease renewals, downtime, and future leasing.

Bringing It All Together

An accurate Argus model is the result of careful preparation, not just software proficiency.

Every input—rent, expenses, recoveries, and leasing assumptions—depends on a thorough understanding of:

• Lease documents,

• Tenant occupancy,

• Expense structures, and

• Market conditions.

Skipping these steps or oversimplifying them can lead to material errors in valuation.