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. 4,000+ engagements 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.
Manufacturing feasibility joins market demand to production economics. The study establishes demand for the plant's output — contracted, identified, or market-derived — then tests the production model: capacity and utilization ramp, input cost structure, labor availability at the required skill level, and the capital budget against industry benchmarks. Solar, storage, and energy-equipment manufacturers add incentive-policy exposure (domestic-content provisions, tax-credit eligibility), technology-generation risk, and the offtake or pipeline evidence behind the volume assumption. Because USDA and SBA reviewers read manufacturing studies against job-creation and rural-impact criteria as well as repayment, the study documents employment, wage levels, and local economic effect to the standard the program requires.
Methodology combines industry production and pricing data, EIA and NREL deployment data, RSMeans location-adjusted facility budgets, BLS occupational wage data for the staffing model, and RMA and IBISWorld operating benchmarks. The financial model carries the utilization ramp, input-cost sensitivity, and program coverage tests across the firm's standard stress discipline, with every assumption sourced.
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. Manufacturing reaches us predominantly through USDA B&I — where rural plant economics and job creation align with program purpose — alongside SBA 504 for owner-occupied facilities and conventional lending; Value-Added Producer Grant studies are prepared to 7 CFR Part 5001 where agricultural producers integrate forward into processing.
The firm's manufacturing and processing record spans USDA B&I and SBA engagements nationwide, including cold-chain, food-system, and industrial projects; manufacturing studies are prepared with the same fully linked financial models and stress discipline as every Wert-Berater engagement. 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.
Screening the industrial market before committing to a full engagement? Manufacturing Market Risk Intelligence is a report prepared by our analysts to a published structure: supply, demand and the operating conditions in one market, with coverage shown before the order is taken. It is a market risk view, not a feasibility determination on your project, and it does not replace the study described on this page.
A feasibility study for an energy equipment or cleantech manufacturer must resolve questions that a standard industrial study does not face: whether the product qualifies under current domestic-content and tax-credit rules, whether the offtake or sales pipeline is contracted or merely projected, and whether the technology generation being manufactured is the one the market will still be buying when the plant reaches stabilized utilization. The narrative and model address each of those questions explicitly, not in a footnote.
Deliverables for this asset class include:
Demand analysis for an energy equipment manufacturer cannot rely on foot-traffic counts or lease-comparable data. The counting method begins with deployment data — EIA and NREL publish installation volumes, capacity additions, and technology-mix trends by region and sector, and those figures anchor the top-down market frame. The study then works inward: from total deployment volume to the segment the plant actually serves, then to the geographic reach the plant can competitively supply given freight economics and lead-time requirements.
Competitive-supply analysis draws on utility interconnection queues, which are public and identify projects by technology type, scale, and development stage. Equipment procurement filings in utility integrated resource plans, manufacturer capacity announcements in trade press, and import-export data from the U.S. International Trade Commission identify existing and planned supply. Where the borrower holds offtake agreements or letters of intent, the study evaluates counterparty creditworthiness, contract terms, and volume certainty. Where volume is market-derived rather than contracted, the study documents the absorption assumption explicitly and stress-tests it.
The competitive frame also accounts for technology-generation risk: a plant tooled for one product generation faces substitution exposure if the market moves to a successor specification during the loan term. The study identifies that risk, documents the product roadmap evidence available, and reflects the uncertainty in the sensitivity analysis rather than suppressing it in a base-case assumption.
Four inputs move the debt-service-coverage ratio for an energy equipment manufacturer more than any others. Each is tested explicitly rather than held at a single base-case value.
Every assumption is sourced in the narrative. No input is hardcoded in the model.
SBA reviewers applying SOP 50 10 8 require that the study demonstrate repayment capacity at 1.15x operating debt-service coverage and 1.00x global coverage. For a cleantech manufacturer, the reviewer will scrutinize the utilization ramp — because a plant that takes longer than projected to reach capacity can breach coverage in the early years — and the stability of the revenue assumption, particularly where pricing depends on incentive-policy conditions outside the borrower's control. The study must address those questions directly, not leave them for the reviewer to raise as exception items.
USDA Business & Industry reviewers under RD Staff Instruction 5001 add rural-impact and job-creation criteria. A cleantech manufacturing plant in a rural location must document employment levels, wage rates relative to the local median, and the broader economic effect on the community. REAP engagements add renewable-energy or energy-efficiency nexus requirements specific to that program. The study is built to satisfy those criteria as primary deliverables, not as supplemental exhibits.
Conventional lenders typically require 1.20x coverage and focus heavily on collateral adequacy and liquidation value for specialized manufacturing equipment — energy equipment tooling and production lines carry narrower secondary markets than general industrial equipment, and the study acknowledges that constraint rather than ignoring it. Where equipment is highly application-specific, the narrative addresses the collateral limitation explicitly so the lender can structure around it with full information.
The fee is fixed and quoted in writing within one business day of an inquiry. It does not change based on the finding, and no portion of it is contingent on loan approval or a favorable determination. That structure is not a policy preference — it is the condition that makes the study credible to a lender or agency reviewer who knows that a contingent-fee study has an incentive to reach a particular conclusion.
Standard delivery is ten to fifteen business days from a complete data room. The data room for an energy equipment manufacturer typically includes audited or reviewed financials, the capital budget with contractor or vendor support, the offtake or sales pipeline documentation, any domestic-content or incentive-eligibility correspondence, the site control documentation, and the proposed loan terms. Incomplete data rooms extend the timeline; the engagement letter identifies the required documents specifically so that delay is avoidable.
Rush delivery is available and is quoted at the time of engagement. Every engagement is published to a secure client portal where the linked Excel model remains live: a reviewer can change any input — selling price, utilization rate, interest rate, input cost — and every output recalculates instantly because no value is hardcoded. The model does not need to be re-sent each time a lender wants to run a scenario. The narrative report includes an explicit statement of conditions — the material assumptions on which the determination rests — so that any party reading the study knows exactly what would have to change to alter the conclusion.
The fee is fixed, quoted in writing within one business day, and does not vary based on the finding or loan outcome. Because project scope, data availability, and program requirements differ, the quote is specific to each engagement. No portion of the fee is contingent on approval or a favorable determination.
Standard delivery is ten to fifteen business days from receipt of a complete data room. Rush delivery is available and is quoted at the time of engagement. The most common cause of delay is an incomplete data room; the engagement letter identifies required documents specifically so sponsors can prepare in advance.
Three factors distinguish this asset class: revenue that may depend partly on incentive-policy conditions outside the borrower's control; a utilization ramp that can suppress coverage in early years before the plant reaches nameplate capacity; and technology-generation risk, where a product specification can be displaced by a successor generation during the loan term. A credible study addresses all three explicitly.
Not automatically. SBA and USDA B&I share coverage-ratio discipline but differ on rural-impact documentation, job-creation criteria, and program-specific requirements under RD Staff Instruction 5001. Studies intended for USDA review are built to that instruction from the outset, not retrofitted from an SBA format.
The study documents whatever evidence exists: executed offtake agreements, letters of intent, identified pipeline with stage and probability, or market-derived absorption supported by deployment data. The volume assumption is stated explicitly in each case, and the sensitivity analysis shows coverage at lower volumes so the lender can see where the repayment case holds and where it does not.
Yes. Every model is a fully linked Excel workbook with no hardcoded values, published to a secure client portal where it remains live. Any reviewer can change an input — interest rate, loan amount, utilization assumption, selling price — and every output recalculates immediately without requiring a revised report or a new file from the firm.
Financing resource. Review SBA financing options for eligible energy and manufacturing businesses. Manufacturers are considered separately under qualifying NAICS 31–33 classifications; manufacturing energy equipment does not itself guarantee program eligibility, loan terms or approval. SBA rules and participating-lender underwriting apply.
Qualify a project. Tell us about the project and the program. We will tell you the truth about it — scope, timeline, and fee confirmed before work begins.
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Wert-Berater, Inc. is an independent provider of feasibility studies and other related services. The firm does not provide financing or equity investment advice, and does not arrange, broker, or place debt or equity capital of any kind.
All appraisal assignments are performed by Bruce E. Jones, MAI, ASA-GC, BCA, CMEA, a member of the Appraisal Institute since 2006, a staff member of Wert-Berater, Inc. and owner of Special Purpose Realty Valuation.