Wert-Berater, Inc. is an independent restaurant feasibility study consultant preparing lender- and agency-ready analyses for new restaurants, acquisitions, expansions, full-service concepts, fast-casual operations, and other food-service businesses. Our studies evaluate trade-area demand by daypart, competitive concepts, average check, seat turns, achievable sales, food and beverage costs, labor, occupancy costs, development budget, stabilization, debt-service coverage, and downside sensitivity.
Prepared for lenders, CDCs, and federal agencies to SBA SOP 50 10 8, USDA 7 CFR Part 5001, and conventional underwriting standards. Fiduciary duty runs to the lender and the agency, never the borrower. 3,969 studies since 1998 covering $41.2 billion in evaluated project value. So far in 2026: 41 engagements and $1.54 billion evaluated — 17 SBA, 11 USDA.
Restaurant feasibility is the most operations-dependent analysis in commercial lending: trade-area demand by daypart, the concept's check-average and turn economics against the named competitive set, the site's visibility, access, and co-tenancy, and an operating model — food cost, labor model, occupancy ratio — tested against industry benchmarks rather than the operator's aspiration. Full-service, fast-casual, and QSR formats each carry distinct unit economics the study addresses specifically, and franchise concepts add royalty, advertising-fund, and territory analysis.
Methodology uses trade-area demographics and spending data, competitive census with observed traffic, RMA and industry operating benchmarks by segment, and franchise disclosure review where applicable. The model carries sales build-up by daypart, prime-cost sensitivity, and program coverage tests under conservative volumes.
Every Wert-Berater financial model is fully linked with no hardcoded values, so any reviewer can stress any input. Deliverables comprise a complete narrative report and the linked Excel model, with ten-year pro forma, sensitivity analysis at ±5, 10, and 15 percent, interest-rate stress from +0.5 to +3.0 percent, and ratio analysis benchmarked against RMA and IBISWorld data.
SBA engagements are prepared to SOP 50 10 8, including its debt-service-coverage minimums of 1.15x operating and 1.00x global. USDA engagements follow RD Staff Instruction 5001 across the Business & Industry, Community Facilities, REAP, and Value-Added Producer Grant programs. Conventional engagements are built to the lender's stated coverage standard, typically 1.20x. Roadside and transportation-service projects arrive under SBA 504 and 7(a) for owner-operators — with SOP 50 10 8 special-purpose property treatment addressed where it applies — USDA B&I at qualifying rural locations, and conventional structures for multi-site operators.
The firm’s food-service record includes a $6,333,516 food hall engagement built around an 18-pad food-cart pod anchored by a two-story 9,801-square-foot taproom and dining hall, evaluated under a conventional structure and returned favorable on management feasibility. It also includes a $4,840,000 six-court outdoor recreation and taproom social venue in the Austin metropolitan area, analysed for SBA 7(a) and 504 financing and returned favorable with a dedicated general-manager hire recommended as a condition — a food-and-beverage operation inside a recreation concept rather than a standalone restaurant, and cited here as that.
Restaurant components are also evaluated inside larger hospitality and retail developments, including travel centers and mixed-use projects where the food-service tenant is one revenue line among several. Independence is non-negotiable: determinations follow the evidence and are not revised under pressure, and studies are built to pass lender, agency, and third-party review without exception items.
A restaurant feasibility study consultant analyses whether a specific concept, at a specific site, can produce sales sufficient to cover food and labor cost, occupancy, operating expense, and debt service. Restaurants fail on operating economics far more often than on demand, so the analysis gives cost structure the same weight as the sales forecast.
A restaurant & food service feasibility study is not a business plan dressed in lender language. It is a structured determination of whether a specific concept, at a specific site, under a specific capital structure, can service its debt at the coverage ratios the program requires. The scope is set by the project type, not by what the operator wants to show. For a food-service engagement, that means the study must resolve trade-area demand by daypart, competitive supply by format and price tier, unit economics by line item, and program coverage under conservative volume assumptions — all before the lender commits a dollar.
Annual household food-away-from-home spending, applied to a trade-area population, is not a demand analysis. It produces a number that looks defensible and tells the lender nothing about whether this concept will fill these seats at these hours. Demand is analysed by daypart, because a site strong at one daypart can be empty at another and the revenue model depends on which hours actually perform.
Where applicable the study analyses breakfast, lunch, afternoon, dinner, and late night separately, identifying which generators feed each. Daytime employment and office density drive lunch. Residential density, retail, and entertainment drive dinner. Hotels and tourism drive breakfast and dinner with pronounced seasonality. Traffic volume matters for convenience-led dayparts but not for destination dining. A concept dependent on dinner alone in a market whose activity is concentrated at midday carries a structural problem no marketing budget corrects, and the study reports that rather than blending the dayparts into a single annual figure that conceals it.
Sales must reconcile from the physical capacity of the restaurant, not from a target the pro forma needs. The core calculation is available seats multiplied by turns multiplied by average check, applied by daypart, and it is built so the lender can see every input and test it.
Seat turns are constrained by the service model: a full-service dinner house cannot turn tables at fast-casual rates, and a projection assuming it has assumed away the concept. Turns are assessed against the kitchen’s throughput capacity, the service style, and the observed behaviour of comparable operations. Average check is built from a realistic menu mix by daypart rather than from the menu’s midpoint, with beverage and alcohol attachment modelled separately because they move the check materially. Takeout and delivery, bar, and catering revenue are modelled as distinct lines with their own margins — third-party delivery in particular carries commission that can consume most of the contribution, so it is never treated as incremental sales at dine-in margin.
The competitive set is defined by what the customer would actually choose instead, which is not the same as every restaurant within a radius. A fast-casual lunch operation does not compete with a destination steakhouse. The analysis identifies genuine alternatives by cuisine, service format, price point, and check average, then examines seating capacity, hours, access and parking, the age and condition of each operation, and how each is differentiated.
Online reviews and ratings are used only as contextual evidence — they indicate how an operation is perceived and where a service gap may exist, but they are self-selected, unverifiable, and are never converted into a demand input or a market-share figure. Positioning is then tested honestly: whether the proposed concept occupies a genuine gap, whether that gap exists because the market will not support the concept, and whether the differentiation claimed is something a competitor could copy within a season.
Prime cost — food and beverage plus total labor — is where most restaurant projections break. The study models food cost and beverage cost separately, since their margins differ sharply, and models hourly labor, management labor, and payroll burden including taxes, insurance, and benefits as distinct lines rather than as a single percentage.
No universal target percentage is published as a guaranteed rule. Prime-cost benchmarks vary by service format, menu, and market, and a figure that is healthy for a fast-casual operation may be unachievable for a scratch kitchen. What the study does instead is derive the project’s own prime cost from its own menu, staffing plan, and local wage rates, then test sensitivity to food and wage inflation. Labor availability is examined where the local market is tight, because a staffing plan that cannot be filled at the assumed wage is not a cost assumption but a capacity constraint, and minimum-wage schedules already legislated are carried forward rather than held flat.
Strong sales do not save a restaurant carrying excessive occupancy cost. A concept can hit its revenue forecast, run acceptable prime cost, and still fail to service debt because rent and its attendant charges consume the margin. Occupancy is therefore modelled in full: base rent or debt service on the owned asset, CAM, property taxes, insurance, utilities, and percentage rent where a lease includes it.
Occupancy cost is then tested as a share of projected sales, and the study reports the sales level at which the site becomes economically unviable regardless of operating performance. Escalation clauses are carried forward rather than held constant, since a lease stepping up through the ramp can push a project into deficit precisely when it is least able to absorb it. For owner-occupied SBA projects, the analysis compares the debt-service burden against a market rent for the same space, so the lender can see whether the real estate is carrying the operation or the operation is carrying the real estate.
A new restaurant does not open at stabilised sales, and a projection that assumes it does understates the capital required. The study models the ramp explicitly: opening promotion and the trial traffic it generates, the honeymoon period and the decline that follows it, the conversion of trial customers into repeat business, staff training and the service inconsistency typical of early weeks, and the operating losses incurred before the concept stabilises.
Working capital is sized against that path rather than as a percentage rule. The analysis reports the cumulative cash requirement through the trough and the month at which the operation first covers debt service. Where the sponsor’s capital is insufficient to fund the ramp, that is identified as a condition precedent, because an undercapitalised opening is one of the most common causes of failure in an otherwise sound concept. Seasonality is layered onto the ramp, since a restaurant opening into its slow season faces a materially different cash path than one opening into its peak.
Break-even is calculated for the specific project rather than quoted as a benchmark. The study reports the sales level required to cover food and beverage cost, hourly and management labor, occupancy, operating expense, and management compensation, and the higher level required to cover all of that plus debt service at the proposed structure.
Both are expressed in the terms the operator actually manages — annual sales, weekly sales, and average covers per day at the projected check — so the lender can judge whether the required volume is plausible against the seat count and the trade area. No generic sales-per-square-foot threshold is published, because the figure is meaningless across service formats: a fast-casual operation and a full-service dinner house with identical square footage have entirely different break-even requirements.
Service format changes the demand model, the cost structure, and the report, so the study is scoped to the format rather than applied from a template.
Seat turns are limited by service pace and kitchen throughput, average check is higher, alcohol attachment is often material to the margin, and labor is the dominant cost line. Dinner concentration and weekend dependence make the daypart and day-of-week distribution central to the forecast, and management depth is examined because service consistency drives repeat business.
Higher throughput at a lower check, with counter service reducing labor per cover and takeout and delivery frequently carrying a substantial share of volume. Lunch is usually the dominant daypart, digital ordering and third-party delivery economics are modelled explicitly, and the analysis tests whether the site’s traffic and employment base can deliver the transaction count the format requires.
No brand recognition, no franchise support system, and no proven unit economics to reference, which places more weight on operator experience, the trade-area gap, and the ramp assumptions. The study examines the operator’s record in the format directly, since an independent concept is underwritten substantially on the person running it.
Where food service sits inside a hotel, marina, event venue, recreation facility, or mixed-use development, the restaurant is analysed both on its own economics and for its contribution to the host asset. Captive demand from the host is modelled separately from outside draw, and shared demand is never double-counted between the two. For the host asset itself see the hotel & motel feasibility study or the event venue & winery feasibility study.
Quick-service and drive-thru pads are underwritten on traffic capture, stacking capacity, and transaction counts rather than on seats and turns, and franchise economics usually govern the cost structure. Those projects are addressed separately in the QSR & drive-thru feasibility study.
Evaluating a drive-thru or quick-service pad? See our QSR & Drive-Thru Feasibility Study. That page covers the AADT-to-transaction methodology, drive-thru stacking and throughput, franchise royalty and advertising obligations, and break-even transactions per day — the analysis a pad-site project needs, which is materially different from the seats-and-turns model used for a full-service or fast-casual restaurant.
Demand analysis for a food-service project begins with the trade area, which is not drawn by zip code but by the friction the format actually imposes on a customer — drive time for a destination concept, walk distance for a transit-adjacent counter-service unit, or highway interchange geometry for a roadside fuel-and-food location. Once the trade area is established, the study layers in the data sources that are genuinely informative for this asset class.
Population and household data from Census Bureau products establish the resident base. Consumer expenditure surveys and restaurant-spending allocations from trade-association research quantify the addressable pool. Daytime population estimates from employment databases capture the lunch and coffee-break demand that often exceeds resident demand at urban sites. Hotel occupancy data and event-venue calendars are incorporated where tourist or event-driven traffic is material to the revenue thesis.
Competitive supply is counted directly, not estimated. Field observation, health-department licensing registries, state liquor-authority records, and local business-license databases are cross-referenced to build a current competitive census. Seat counts and estimated turn rates are observed or derived from format norms, not assumed. For roadside locations, traffic-count data from state department-of-transportation sources and interchange exit-ramp volumes are incorporated. The result is a demand-supply gap expressed in covers or transactions per daypart, not in vague market-size language.
Restaurant & food service feasibility studies are more sensitive to operating assumptions than almost any other commercial asset class, because the margin between a viable and an unviable unit is narrow and the inputs are interdependent. A lender reviewing the model should understand which levers move coverage and how each is tested.
Each lending program imposes distinct requirements on a restaurant & food service feasibility study, and a study prepared for one program is not automatically acceptable under another.
Under SBA SOP 50 10 8, the study must demonstrate 1.15x debt-service coverage on an operating basis and 1.00x on a global basis. For food-service projects, the agency is particularly attentive to the independence of the analyst, the reasonableness of the sales ramp, and whether the concept is a special-purpose property under the SOP's collateral provisions — a determination that affects loan-to-value treatment and that the study must address where the building is purpose-built for a single restaurant use.
USDA Business & Industry engagements under 7 CFR Part 5001 require the study to confirm that the project serves a rural area as defined by the program and that the economic benefit to the community is documented. Food-service projects at rural highway locations, agritourism destinations, or rural downtown revitalization sites frequently qualify, and the study must frame the demand analysis within that geographic and economic context.
Conventional lenders typically require 1.20x coverage and place additional weight on the operator's track record, the concept's competitive differentiation, and the lease or ownership structure of the real estate. A lender's credit committee reviewing a restaurant credit wants to see prime-cost discipline, not just top-line revenue, and the study is built to address that directly.
The engagement begins with a fixed fee quoted within one business day of the initial inquiry. The fee does not vary with the study's conclusion, and no portion of it is contingent on a favorable finding or on loan approval. That structure is not a marketing point; it is the condition that makes the study credible to a lender or agency reviewer who knows that a contingent fee corrupts the determination.
Standard delivery is ten to fifteen business days from receipt of a complete data room. The data room for a restaurant engagement typically includes the executed lease or purchase agreement, the franchise disclosure document where applicable, three years of operator financial statements for existing concepts, the proposed menu with pricing, construction or build-out cost documentation, and the lender's term sheet or loan application. Incomplete data rooms are the single most common cause of delay, and the firm identifies gaps at intake rather than midway through the engagement.
Rush delivery is available when the lender's commitment timeline requires it. Every engagement is published to a secure client portal where the fully linked Excel model remains live: a reviewer can change any input — check average, seat count, food cost, interest rate — and every downstream ratio recalculates instantly. The model contains no hardcoded values. The bound narrative report and the live model are delivered together, and the statement of conditions is a numbered exhibit, not a footnote.
Related project types analysed by the same team, each with its own demand model and its own report structure:
The consultant determines whether a specific concept at a specific site can produce sales sufficient to cover food and labor cost, occupancy, operating expense, and debt service. That means defining the trade area, analysing demand by daypart, examining the genuine competitive set, building average check and seat turns into a sales forecast, modelling prime cost and occupancy, sizing the opening ramp and working capital, and reporting break-even and debt-service coverage under base and downside cases.
Demand is built by daypart from the generators that actually feed each one — residents, daytime employment, tourism and hotels, retail, entertainment, and passing traffic — rather than by applying annual household food-away-from-home spending to a trade-area population. The forecast then reconciles against the restaurant’s physical capacity through seats, turns, and average check, so the sales figure is constrained by what the building can actually serve.
The trade area is defined by drive time and observed customer draw rather than by a fixed radius, and it differs by daypart and by format. A fast-casual lunch operation draws from a few minutes of drive time around employment density, while a destination dinner concept can draw from a much wider area. The study establishes the boundary from the concept’s own draw characteristics and the road network, then tests demand within it.
Each daypart is projected separately with its own demand generators, its own turns, and its own average check. Breakfast, lunch, afternoon, dinner, and late night are analysed where applicable, since a site strong at one can be empty at another. Day-of-week and seasonal distribution are layered on top, because a concept dependent on weekend dinner performs very differently from one carried by weekday lunch, and an annual average conceals that difference.
Average check is built from a realistic menu mix by daypart rather than from the menu’s midpoint, with beverage and alcohol attachment modelled separately because they move the check materially. It is benchmarked against comparable operations in the market at the same service format and price point. Where the projection assumes a check above what the trade area demonstrably supports, the study reports coverage at the supportable check instead.
Turns are modelled against the service model and the kitchen’s throughput capacity, not assigned as a target. A full-service dinner house cannot turn tables at fast-casual rates, and a projection assuming otherwise has assumed away the concept. Turns are set by daypart, tested against comparable operations, and checked against kitchen capacity at peak, since a dining room that can seat more covers than the kitchen can produce has a constraint the seat count does not reveal.
Food and beverage cost are modelled separately because their margins differ sharply, and labor is split into hourly, management, and payroll burden rather than carried as one percentage. Costs are derived from the project’s own menu, staffing plan, and local wage rates, then tested for sensitivity to food and wage inflation. Legislated minimum-wage increases are carried forward rather than held flat, and labor availability is examined where the local market is tight.
The competitive set is limited to what a customer would genuinely choose instead, identified by cuisine, service format, price point, and check average, then examined on seating, hours, access and parking, condition, age, and differentiation. Online reviews are used only as contextual evidence of how an operation is perceived; because they are self-selected and unverifiable, they are never converted into a demand input or a market-share figure.
Break-even is calculated twice for the specific project: the sales required to cover food and beverage, labor, occupancy, operating expense, and management compensation, and the higher level required to cover all of that plus debt service. Both are expressed as annual sales, weekly sales, and average covers per day at the projected check, so the required volume can be judged against the seat count. No generic sales-per-square-foot threshold is published.
It varies by format, market, and marketing, so the study models the project’s own path rather than applying a standard period. The ramp accounts for opening promotion and trial traffic, the decline after the honeymoon period, conversion of trial customers into repeat business, staff training and early service inconsistency, and seasonality — a restaurant opening into its slow season faces a materially different cash path. The analysis reports the cumulative cash requirement through the trough and the month debt service is first covered.
A business plan is prepared by or for the borrower to present the project, and its purpose is to make the case. A feasibility study is prepared by an independent third party for the lender and the agency, and its purpose is to test the case. Wert-Berater’s fiduciary duty runs to the lender and the agency rather than to the borrower, the fee is not contingent on the finding, and the study can and does return unfavorable determinations. Lenders and SBA generally require the independent study, not the plan.
The fee is fixed and quoted within one business day of the initial inquiry. It does not vary with the study's conclusion and is never contingent on a favorable finding or loan approval. Because scope drives cost, the quote is based on the concept type, site complexity, and whether a franchise disclosure review is required. Contact the firm directly for a same-day quote.
Standard delivery is ten to fifteen business days from receipt of a complete data room. Rush delivery is available when a lender's commitment deadline requires it. The most common cause of delay is an incomplete data room — missing lease documents, franchise agreements, or operator financials. The firm identifies gaps at intake so the clock starts on a solid foundation.
Yes. Studies are prepared to SBA SOP 50 10 8 standards with the lender and the agency as intended users, and special-purpose property treatment is addressed where it applies to a purpose-built restaurant. The report tests whether the project can service the proposed debt and states the conditions attaching to that conclusion. It supports the credit decision; it does not approve the loan, and no determination is contingent on the financing outcome.
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