About Our Methodology

How we build feasibility studies that satisfy SBA lenders, CDCs, and credit committees

Every feasibility study we produce follows a three-pillar analytical framework: market analysis, financial modeling, and site/regulatory assessment. These three pillars are not independent exercises. They feed into each other. Market demand drives revenue projections. Site constraints shape operating costs. Regulatory requirements define the project's feasibility envelope. The final DSCR calculation synthesizes all three pillars into the single metric that determines whether your loan gets approved.

Our methodology is informed by USPAP (Uniform Standards of Professional Appraisal Practice) analytical principles and calibrated to the prescriptive underwriting standards introduced in SOP 50 10 8. Every data point is sourced, every projection is independently constructed, and every conclusion is defensible under lender scrutiny.

Pillar 1: Market Analysis and Demand Quantification

The market analysis is the foundation of the entire study. If the demand case is wrong, the financial projections are meaningless regardless of how precise they appear.

The same three-pillar methodology governs every asset-class engagement, including hotel feasibility studies, car wash feasibility studies and multifamily feasibility studies. Worked examples appear in the Leander hotel and Round Rock car wash case studies.

Trade Area Definition

We define the trade area based on the specific dynamics of your property type, not arbitrary radius circles. A gas station's primary trade area is defined by drive-time corridors and daily traffic patterns. A hotel's trade area is defined by the demand generators (corporate offices, tourist attractions, medical centers, airports) that produce overnight stays. A self-storage facility's trade area is defined by population density rings and competitive supply locations. Each asset class has a different spatial logic, and applying the wrong framework produces misleading conclusions.

Trade area boundaries are established using a combination of drive-time isochrones, natural and man-made barriers (rivers, highways, railroad tracks), competitive facility locations, and demographic clustering. We use GIS-based mapping tools to visualize these boundaries and validate them against observed consumer behavior patterns.

Demand Quantification

We quantify demand using multiple independent methodologies and cross-reference the results. This triangulation approach produces projections that are more defensible than any single method alone.

Competitive Supply Inventory

We inventory every competing facility within the defined trade area, not just the obvious ones. This includes facilities under construction, approved but not yet built, and proposed projects in the permitting pipeline. Planned supply additions are the single most common element that low-quality feasibility studies miss. A market that appears undersupplied today may be oversupplied 18 months from now if three competitors break ground next quarter.

For each competitor, we document location, size/capacity, pricing, occupancy or utilization (where observable), age and condition, amenity package, brand affiliation, and any known expansion plans. This inventory feeds directly into the competitive positioning analysis and the capture rate assumptions in the financial model.

Data Sources

Our market analysis draws from institutional-grade data platforms, not free online sources. The specific sources vary by property type, but our standard toolkit includes:

We subscribe to these platforms on a standing basis. Data procurement costs are absorbed in our fees, not passed through to the client.

Pillar 2: Financial Modeling and DSCR Analysis

The financial model translates market demand into projected cash flows and determines whether those cash flows can service the proposed debt.

Independent Projection Construction

We build revenue and expense projections independently from the borrower's business plan. This is not a negotiation between the borrower's optimism and the analyst's skepticism. It is a separate, parallel analysis constructed entirely from market data, industry benchmarks, and comparable facility performance. If our independently derived projections align with the borrower's assumptions, that alignment strengthens the case. If they diverge materially, the divergence is documented and the lender can evaluate the gap.

Revenue projections are built bottom-up from the demand analysis. We project unit volume (room nights, wash counts, fuel gallons, square footage leased) from the capture rate and demand quantification work, then apply pricing derived from competitive benchmarking. This approach produces projections grounded in market reality rather than aspirational targets.

Operating Expense Benchmarking

Operating expenses are modeled against published industry ratios from RMA, IBISWorld, and comparable facility financials. We benchmark each major expense category (labor, utilities, insurance, maintenance, management fees, marketing, property taxes) against industry norms and adjust for local cost factors. If the borrower's expense assumptions deviate significantly from industry benchmarks, we flag the variance and model both scenarios.

DSCR Calculation and Stress Testing

The DSCR calculation is the deliverable that credit committees care about most. We calculate it under three scenarios:

Base case: Revenue and expenses modeled at the most probable levels based on market evidence. This is the scenario we consider most likely.

Optimistic case: Revenue at the upper bound of supportable projections with expenses at the lower bound. This scenario tests whether the project has upside potential beyond debt service.

Pessimistic case: Revenue reduced by 15 to 25% from base case with expenses at the upper bound. This scenario tests whether the project can survive adverse conditions while still meeting minimum DSCR thresholds.

SOP 50 10 8 requires a minimum 1.15x DSCR for Standard 7(a) loans and 1.10x for Small Loans. Most CDCs apply 1.20x to 1.25x for 504 transactions. Our stress testing explicitly validates performance against these thresholds.

Sensitivity Analysis

Beyond three-scenario modeling, we conduct single-variable sensitivity analysis to identify which assumptions have the greatest impact on project viability. For a hotel, this might reveal that a 5% drop in occupancy reduces DSCR from 1.30x to 1.05x, making occupancy the critical variable. For a gas station, it might show that fuel margin compression from $0.25 to $0.18 per gallon pushes DSCR below 1.00x. These insights help the lender understand exactly where the risk concentrates.

Pillar 3: Site and Regulatory Assessment

The third pillar evaluates whether the physical site and regulatory environment support the proposed project. A project with strong demand and viable financials can still fail if the site cannot accommodate the concept or if regulatory barriers make development impractical.

Physical Site Evaluation

We assess site visibility and access (ingress/egress quality, traffic signal proximity, highway frontage), parcel size relative to the proposed use, topography and grading requirements, utility infrastructure (water, sewer, electric, gas, broadband capacity), parking adequacy per local code requirements, and compatibility with adjacent land uses. For property types where site characteristics materially affect revenue (gas stations, car washes, hotels), we weight these factors more heavily in the overall feasibility determination.

Zoning and Entitlement Analysis

We verify that the proposed use is permitted under current zoning and identify any variances, special permits, or conditional use approvals that may be required. We review the project against local development standards (setbacks, height limits, lot coverage, signage restrictions) and flag potential conflicts. For projects requiring zoning changes, we assess the timeline and political viability based on local precedent.

Environmental and Regulatory Screening

Our feasibility studies include an environmental screening that reviews FEMA flood zone status, wetlands proximity (National Wetlands Inventory), known contamination sites (EPA databases), and any state or local environmental constraints. This screening identifies red flags that may require further investigation but does not replace a Phase I Environmental Site Assessment. We review any existing environmental reports provided by the borrower and incorporate material findings into the feasibility determination.

How the Three Pillars Converge

The final deliverable synthesizes all three pillars into a cohesive narrative supported by quantitative evidence. The market analysis establishes whether demand exists. The financial model demonstrates whether that demand translates into sufficient cash flow. The site assessment confirms whether the project can be physically and legally executed. The go/no-go recommendation reflects the intersection of all three.

A project can be feasible in the market but not on the proposed site. It can be feasible on the site but not at the proposed scale. It can be feasible at the proposed scale but not at the proposed financing terms. Our methodology tests each dimension independently and then evaluates them together, giving the lender a complete picture rather than a summary conclusion.

Quality Standards and Independence

Every study we produce meets three non-negotiable standards.

Independence. We have no financial interest in whether your loan is approved. We do not accept referral fees from lenders, we do not hold equity in client projects, and our compensation is not contingent on loan outcomes. Our obligation is to the accuracy of the analysis, not to the borrower's desired conclusion.

Reproducibility. Every data point in our studies is sourced and cited. A third-party reviewer should be able to trace any number in the report back to its origin. This standard protects both the borrower and the lender in the event of SBA examiner review.

Defensibility. Our conclusions are supported by quantitative evidence, not professional judgment alone. When we project 72% occupancy for a hotel, the projection is anchored in comp set performance data, seasonal demand curves, and absorption rate analysis. When we project $1.2 million in Year 1 revenue for a gas station, the projection is built from traffic counts, capture rates, and per-gallon margin benchmarks. The lender can evaluate the inputs, challenge the assumptions, and test the sensitivity without relying on the analyst's reputation alone.

Each completed study includes a reliance letter permitting the lender and the SBA to rely on the analysis for underwriting and compliance purposes. We remain available for lender Q&A, credit committee presentations, and revision requests throughout the underwriting process at no additional charge for the first round. For lenders evaluating feasibility studies from any provider, see our 15-element quality checklist.