What a Wert-Berater feasibility study is built from: the evidence standard applied to every assumption, the third-party sources behind each analytical section, how the financial model is constructed, who reviews it, and what the work does not claim to do.
This page exists so that a lender, a credit committee, an agency reviewer or a project sponsor can see how our conclusions are reached before they read one of our reports. Nothing here is engagement-specific. It is the standing methodology the firm applies across feasibility studies, market and demand studies, and valuation work.
The governing rule is simple and it is applied without exception: every assumption in a study traces to a stated source, and every conclusion follows from the evidence on the page. A number that cannot be sourced does not enter the model. Where an input is an estimate rather than a published figure, the study says so, states the basis for the estimate, and tests the conclusion against a range rather than a point.
This matters because a feasibility study is read adversarially. A credit officer, an agency reviewer, or opposing counsel in a dispute will look for the assumption that carries the conclusion and ask where it came from. A study that cannot answer that question fails at exactly the moment it is needed.
The firm licenses and consults published third-party data rather than relying on sponsor-supplied figures. The sources below are the ones that recur across engagements; a given study names the specific releases, dates and geographies it used.
| Analytical section | Sources consulted | What they support |
|---|---|---|
| Industry structure & operating benchmarks | IBISWorld industry reports | Sector revenue and cost structure, margin ranges, competitive dynamics, industry-level growth outlook used to sanity-check sponsor projections |
| Labor market & wages | U.S. Bureau of Labor Statistics (OES, QCEW, CES, CPI) | Occupational wage rates by metropolitan area, staffing cost build-ups, employment base of the trade area, inflation adjustment of historical figures |
| Demographics & trade area | U.S. Census Bureau, American Community Survey, Esri demographic data | Population, household counts and formation, income distribution, age cohorts, commuting patterns, and the demand base for capture-rate analysis |
| Commercial real estate | CBRE, JLL, Cushman & Wakefield and CoStar market research | Submarket rents, vacancy, absorption, cap rates, construction pipeline and comparable transaction evidence |
| Hospitality | STR performance data, HVS market research | Occupancy, average daily rate and RevPAR for the competitive set; supply pipeline; penetration and fair-share analysis |
| Construction cost | RSMeans cost data | Independent verification of the sponsor's construction budget by system and by square foot, and the basis for a cost-contingency opinion |
| Energy & fuels | U.S. Energy Information Administration | Fuel and electricity price series, consumption and capacity data for energy, fuel-retail and industrial projects |
| Agriculture & food | USDA National Agricultural Statistics Service | Commodity prices, production and yield data, processing capacity and crush/throughput assumptions |
| Traffic & transportation | Federal Highway Administration and state DOT traffic counts | Average daily traffic at the site, capture-rate derivation for travel centers, fuel retail, hotels and roadside commercial uses |
| Operating & credit benchmarks | RMA Annual Statement Studies | Peer financial ratios by industry and revenue band, used to test the sponsor's projected margins, leverage and coverage against comparable operating businesses |
| Macroeconomic & credit conditions | Federal Reserve releases and FRED series | Interest-rate environment, index rates underlying debt-service assumptions, and the stress scenarios applied to them |
| Economic impact | IMPLAN and Bureau of Economic Analysis RIMS II multipliers | Direct, indirect and induced employment, output and fiscal effect where an engagement calls for impact analysis |
Where a project is genuinely niche — a specialised processing facility, an unusual institutional use, a market with no published coverage — published data will not answer the question on its own. In those cases the study relies more heavily on primary research, and says so plainly rather than borrowing a proxy industry and presenting it as though it fit.
Licensed data establishes the frame. It does not, by itself, establish that a specific project in a specific location will perform. Primary research closes that gap:
Comparable selection is defended rather than assumed: each comparable is verified to source, weighted on stated criteria, and adjusted through a documented methodology, with the indicated ranges reconciled to a conclusion rather than averaged.
The model is a deliverable in its own right, not a scratch pad behind the report. It is built so that a reviewer can open it and test the conclusion themselves.
A study is only useful to a lender if it is organised the way the reviewer reads it. The firm writes to the framework that governs the credit:
No report leaves the firm on a single analyst's signature. Each engagement carries a named analyst, a lead and a reviewer, and the reviewer's role is substantive rather than clerical. Before release, the model is recalculated from the assumptions tab forward and the report is cross-referenced against the firm's fixed internal checklists — a 20-point review of the narrative and a 22-point audit of the model — covering source attribution, internal consistency between the narrative and the exhibits, arithmetic integrity, and completeness against the governing framework. A study that fails any item goes back to the analyst rather than out to the client.
Every engagement is fixed-fee and quoted in writing before work begins. Compensation never depends on a finding, on a conclusion of value, or on whether financing is ultimately obtained. The firm does not arrange, package or place financing, holds no interest in the projects it studies, and takes no position on whether a lender should approve a credit.
The consequence is the point: where a project does not support the debt proposed, the report says so. That is the reason our reports are accepted for third-party review, and it is also the reason a sponsor should not retain us expecting a particular answer.
Stating the limits is part of the methodology, not a disclaimer bolted to the end of it.
Market data ages. A study reflects the market as of its stated effective date, using the most recent releases available at that time. Where a credit decision is made materially later than the effective date, the responsible course is a study update or recertification rather than reliance on stale figures.
Lenders and agency reviewers are welcome to ask how a particular conclusion was reached before commissioning work, and we will answer at the level of detail the question requires. Methodology enquiries go to Donald Safranek, MSc, President, who retains principal review responsibility on the reports the firm issues.
Independent feasibility studies since 1998. Fixed fee, quoted before any work begins, never contingent on the finding. Standard delivery 10–15 business days; RUSH delivery available at additional cost.