Post-Pandemic Analysis

How COVID-19 Changed SBA Feasibility Study Standards

By David Jones, MAI, CCIM · Published 2026 · 8 min read

Six years after the pandemic began, its fingerprints remain visible in how feasibility studies are constructed. The 2020-2021 shock disrupted every commercial real estate asset class in ways that forced analysts to rebuild methodology, and several changes from that period have become permanent features of institutional-quality feasibility work. Remote work patterns reshaped commercial demand models. Pandemic-era data required new normalization approaches. Lender risk tolerance shifted, particularly for high-contact service businesses. Consumer behavior patterns that changed during lockdown have not fully reverted.

This guide covers the lasting methodological changes, how to interpret historical data that spans the pandemic period, and how feasibility studies in 2026 differ from those prepared in 2019.

Asset Classes Permanently Reshaped by the Pandemic

Not every asset class has returned to pre-pandemic normal. Some have structurally changed in ways that affect long-term feasibility analysis.

The feasibility study in 2026 treats these shifts as the new baseline rather than as a temporary disruption. A hotel feasibility study that projects corporate travel demand back to 2019 peak levels is working from outdated assumptions. A suburban office project that assumes pre-pandemic demand growth trajectories overstates the market.

Remote Work Impact on Commercial Demand

The shift to hybrid and remote work has affected commercial real estate demand in ways that go beyond office buildings. The feasibility study's market analysis must account for these second-order effects.

Normalizing Historical Data Across the Pandemic Period

When a feasibility study uses historical financial data that spans 2019-2022, the 2020-2021 figures require special treatment. Using them at face value produces misleading projections in both directions.

The "three normal years" standard. For acquisition feasibility studies, the trailing financial analysis should draw from at least three "normal" operating years. Given the 2020-2021 disruption, this typically means 2023, 2024, and 2025 data for current studies. A study that uses 2020-2022 trailing data is working from a distorted baseline and may misrepresent the business's true operating performance.

The PPP and EIDL adjustment. Businesses that received Paycheck Protection Program loans or Economic Injury Disaster Loans during the pandemic may show revenue and expense patterns distorted by the treatment of those funds. The feasibility study should identify whether PPP forgiveness was recorded as revenue (inflating revenue in the forgiveness year) or as a non-operating item, and should exclude the effect when establishing trailing operating performance.

Pandemic Risk Scenario Modeling

Pre-pandemic feasibility studies rarely modeled business disruption scenarios beyond normal market downturns. Post-pandemic feasibility studies increasingly include a pandemic or major disruption scenario in the sensitivity analysis, particularly for asset classes with high vulnerability.

The pandemic scenario is not intended to predict another pandemic. It is intended to identify businesses that could not survive a temporary severe revenue shock, which signals vulnerability to any major disruption (pandemic, natural disaster, major economic shock, supply chain disruption). A business with adequate working capital, diverse revenue streams, and cost flexibility survives these scenarios. A business with thin margins and fixed cost structure may not.

Changed Consumer Behavior Patterns

Several consumer behavior shifts from the pandemic period have persisted beyond the acute crisis and affect demand analysis for affected asset classes.

Digital ordering and delivery. Restaurants that previously operated primarily on dine-in revenue now typically see 25-40% of revenue from delivery and takeout. Feasibility studies for new restaurants must model this mix, which affects kitchen design, labor structure, and revenue per seat calculations.

Drive-through and curbside persistence. Even non-QSR retailers maintain curbside pickup options that emerged during the pandemic. This affects parking requirements, operational layout, and revenue streams for affected retailers.

Drive-to destinations and outdoor experiences. Leisure hotels, glamping, RV parks, and agritourism operations benefited from pandemic-era preference for drive-to outdoor experiences. The elevated demand has moderated but remains above 2019 baseline for many properties.

Home-centered services. Home improvement, home fitness, and home entertainment grew significantly. Some of this growth has persisted as structural shift rather than temporary pandemic effect.

Reduced business travel. Business travel recovery has plateaued below 2019 peak levels. Hotel feasibility studies must model this persistent gap rather than projecting full recovery.

Lender Risk Tolerance Shifts

SBA lenders and the SBA itself absorbed substantial losses on loans that went into default during 2020-2021. This experience reshaped lender risk tolerance in ways that affect which projects get approved and under what terms.

The SOP 50 10 8 update effective June 2025 codified some of this tightening. The reduced Small Loan threshold ($500K to $350K) and enhanced ownership verification requirements reflect lender and SBA experience from the pandemic period.

Updated Data Normalization Approaches

Data sources that feasibility analysts rely on also adjusted their methodology during the pandemic period. Understanding these adjustments matters for interpreting current data.

STR hotel data. STR began providing multiple normalization approaches during the pandemic: with pandemic period included, with pandemic period excluded, and year-over-two-year comparisons (vs 2019). Current feasibility studies typically use post-2022 trailing twelve months as primary benchmarks with 2019 as a reference point.

CoStar office and retail data. Vacancy rates, rent growth, and absorption patterns all shifted during the pandemic. Current CoStar data reflects post-pandemic normalized conditions, but historical comparisons require careful interpretation.

Consumer spending data. Bureau of Labor Statistics and Census Consumer Expenditure data captured pandemic-era spending shifts. Current data reflects new baselines that may differ meaningfully from pre-pandemic patterns.

Labor market data. Wage growth accelerated during the post-pandemic period. Current BLS wage data reflects the new labor cost environment, which is meaningfully higher than pre-pandemic benchmarks for most service-sector positions.

What to Expect from a Current-Environment Feasibility Study

Feasibility studies prepared in 2026 should reflect post-pandemic realities explicitly rather than treating 2019 patterns as the reference normal.

Historical data should exclude or clearly flag pandemic-era years. Trailing averages that include 2020 materially misrepresent most businesses. The study should use 2023+ data as the primary reference with earlier data for context only.

Market analysis should reflect current structural realities. Remote work impact on office and urban demand, elevated travel patterns for leisure, persistent delivery and curbside models for retail and restaurant—these should be embedded in the market analysis rather than treated as temporary deviations.

Sensitivity analysis should include major disruption scenarios for vulnerable asset classes. Not pandemic prediction, but stress testing whether the business can survive a temporary severe shock.

Labor cost models should reflect current wage levels. Pre-pandemic labor ratios understate current costs for most service businesses. Feasibility studies using outdated benchmarks produce artificially favorable projections.

For detailed methodology on market analysis, see our market analysis methodology page. For financial projection approaches, see our financial projections methodology.