What is agribusiness?
– Agribusiness is the full chain of activities that take raw biological inputs and turn them into products or services sold to consumers or other businesses. That chain includes farming, livestock and aquaculture, processing, distribution, machinery and chemical suppliers, and related services (logistics, finance, and agritourism). In short: it’s the business side of agriculture.
Key terms
– Agriculture: growing crops, raising animals and other organisms for food, fiber, fuel or other products.
– Livestock: rearing animals for meat, milk, eggs and related products.
– Forestry: managing trees for timber, paper, carbon sinks and other uses.
– Commodity: a standardized product (e.g., corn, wheat, soy) that is largely interchangeable regardless of origin.
Why agribusiness matters
– It supplies food and raw materials, supports rural employment, and often drives exports for economies with large farming sectors. Because many agricultural goods are tradable commodities, global prices, weather and trade rules can strongly affect local producers.
Modern practices and technology
– Precision farming: using GPS, satellite maps and field sensors to apply seed, water and chemicals only where needed.
– Drones and scouting: aerial imagery to detect pests, water stress and flood risk.
– Robotics and automation: mechanized planters, harvesters and processing lines that reduce labor needs and improve consistency.
– Biocontrol and bee vectoring: using beneficial organisms (or bees as delivery agents) to protect crops from pests and disease, reducing chemical use.
– Data and software: farm-management platforms, yield mapping and supply-chain traceability.
Major market forces shaping agribusiness
– Consumer demand: shifts in dietary preferences (e.g., less red meat, more fresh produce) change what gets grown and how.
– Climate and weather volatility: droughts, frosts and altered precipitation patterns directly affect yields and may require new crop choices or irrigation investments.
– Global competition and commodity pricing: standardized crops can be sourced from anywhere, so producers compete on cost and logistics.
– Regulation: changes to pesticide approvals, food-safety rules or trade policy can create sudden cost or market shifts.
– Consolidation and technology adoption: mergers, large-scale suppliers and high-capital tech raise barriers for small operators.
Common challenges and ways to address them
– Yield and cost pressure: raise per-acre productivity (better seeds, precision inputs) and reduce waste.
– Weather risk: diversify crops, use irrigation/storage, and consider insurance or hedging.
– Market risk: develop value-added processing, local branding, or diversify sales channels (exports, direct-to-consumer).
– Environmental constraints: adopt conservation practices, optimize input use, and track emissions to meet regulations or buyer requirements.
Checklist for agribusiness decision-making
1. Define the product and market: commodity vs. specialty; local, national or export target.
2. Assess climate and soil suitability: historical yields, frost/flood risk, irrigation needs.
3. Calculate break-even per acre/animal unit: include input, labor, machinery, processing and transport costs.
4. Evaluate technology ROI: sensors, drones, precision application — estimate yield gains and added costs.
5. Plan risk management: crop/livestock diversification, insurance, and contract or futures hedges for price risk.
6. Check regulatory and certification needs: pesticides, food-safety, organic or sustainability labels.
7. Develop a sustainability plan: water use, emissions, soil health and biodiversity measures.
8. Prepare logistics and market access: storage, transport, and buyer contracts.
Small worked example: evaluating a precision-tool investment
Assumptions (per acre for a crop):
– Baseline yield: 120 bushels/acre
– Price: $5.00 per bushel
– Baseline input + operating costs: $350/acre
– Precision tech adds $50/acre but increases yield 10%
Calculations:
– Baseline revenue = 120 bu × $5 = $600
– Baseline profit = $600 − $350 = $250/acre
– Post-tech yield = 120 × 1.10 = 132 bu
– Post-tech revenue = 132 × $5 = $660
– Post-tech costs = $350 + $50 = $400
– Post-tech profit = $660 − $400 = $260/acre
Result:
– Profit increase = $260 − $250 = $10/acre.
– Simple ROI on the added cost = $10 / $50 = 20% for the season.
Notes: change input assumptions (price, yield lift, or tech cost) and run the same calculation. For many investments, multiple seasons and adoption scale affect true payback.
Examples of agribusiness companies and segments
–
– Inputs and crop protection (seeds, fertilizers, pesticides, biologicals)
– Examples: Corteva Agriscience (seed/traits), Nutrien and The Mosaic Company (fertilizer), Bayer Crop Science (crop protection).
– Role: R&D and scale determine pricing power. Intellectual property (traits, chemistries) can create durable margins.
– Farm machinery and equipment
– Examples: Deere & Company (DE), CNH Industrial, Kubota.
– Role: Capital goods with cyclical demand tied to farm incomes, interest rates, and replacement cycles.
– Farm operations (production)
– Examples: large row-crop farms, vertically integrated dairy or poultry producers like Tyson Foods (vertical integration spans production to processing).
– Role: Directly exposed to yield, weather, input-cost volatility, and commodity prices.
– Food and commodity processing
– Examples: Archer Daniels Midland (ADM), Bunge, Conagra, JBS.
– Role: Converts raw agricultural commodities into food ingredients, feed, or consumer products; margins depend on processing spreads and scale.
– Distribution, logistics, and storage
– Examples: CHS Inc. (co-op with marketing and logistics), large grain elevators and port terminals.
– Role: Storage capacity and freight costs matter; seasonal working-capital swings can be large.
– Foodservice and wholesale distribution
– Examples: Sysco, US Foods.
– Role: End-market demand (restaurants, institutions) and inventory management.
– Retail and consumer packaged goods (CPG)
– Examples: Kroger, Nestlé, Unilever (food lines).
– Role: Brand strength, shelf space, and pricing pass‑through to consumers.
– Animal health, biotechnology, and agritech
– Examples: Zoetis (animal health), Bayer/Monsanto historically, small-cap precision-ag start-ups.
– Role: New tech (precision ag, genetics, sensors, software) can raise yields or lower costs; adoption is a separate commercial challenge.
– Livestock and aquaculture supply chains
– Examples: Tyson Foods, JBS, Cal-Maine (eggs).
– Role: Feed costs (corn/soy) create cost pass-through dynamics; disease risk and biosecurity are material.
– Farmland ownership and REITs
– Examples: Farmland Partners (FPI), Gladstone Land (LAND).
– Role: Land as an asset: income from lease/rent plus potential appreciation; return drivers differ from commodity processors.
– Cooperatives and trader/merchants
– Examples: CHS Inc., major commodity traders (ADM, Bunge previously mentioned).
– Role: Member-owned or merchant models that intermediate between farmers and end markets.
Key financial and operational metrics (with definitions)
– Yield per acre: crop production per acre (e.g., bushels/acre). Primary volume driver for producers.
– Price per unit: market price for crop/commodity (e.g., $/bushel). Revenue driver.
– Input cost per acre: fertilizer, seed, fuel, labor; used to compute profit/acre.
– Gross margin per unit: revenue per unit − direct cost per unit.
– EBITDA margin: EBITDA / revenue. Useful for processing and distribution firms.
– Working capital seasonality: inventory and payables tied to harvest and sale cycles.
– Throughput or processing capacity utilization: percentage of plant capacity actually used.
– Net leverage (Net debt / EBITDA): balance-sheet risk measure.
– Free cash flow (FCF): operating cash flow − capex. Signals ability to pay dividends, buybacks, or invest.
– Acres owned/managed or tonnes processed: scale metrics.
Step-by-step checklist to analyze an agribusiness company
1. Identify the segment and its fundamental drivers
– Is the firm exposed to commodity prices, technology
adoption, weather exposure, regulatory or trade policy risk, and degree of vertical integration (seed → farm → processor → distributor). For each driver, note whether it affects volumes (acres/tonnes) or prices (commodity or finished goods).
2. Quantify revenue drivers
– List revenue streams (commodity crops, processed foods, inputs, services).
– Estimate units sold (acres × yield, tonnes processed, liters sold) and likely selling prices.
– Worked example: a processor handles 50,000 tonnes/yr at $150/tonne → revenue = 50,000 × $150 = $7.5M.
3. Break down costs into variable vs fixed
– Variable (per-unit) costs: seed, fertilizer, fuel, direct labor. Fixed: plant overhead, depreciation, administrative.
– Compute gross margin per unit = price per unit − direct cost per unit.
– Worked example: crop sells for $600/acre, direct cost $350/acre → gross margin = $250/acre.
4. Calculate operating profitability and cash flow metrics
– EBITDA margin = EBITDA / revenue. Use to compare across firms.
– Free cash flow (FCF) = operating cash flow − capital expenditures. Indicates internal funding capacity.
– Worked example: revenue $10M, EBITDA $1.2M → EBITDA margin = 12%. Operating cash flow $1.5M, capex $0.5M → FCF = $1.0M.
5. Assess balance-sheet strength and leverage
– Net leverage = Net debt / EBITDA, where Net debt = total debt − cash.
– Check interest coverage (EBITDA / interest expense).
– Rule-of-thumb flags: net leverage > 3–4x or falling interest coverage deserve closer scrutiny.
– Worked example: net debt $30M, EBITDA $10M → net leverage = 3.0x.
6. Model working-capital seasonality
– Identify timing of cash outflows (inputs before planting) and inflows (post-harvest sales).
– Calculate days inventory, receivables, and payables; convert to cash need in $.
– Example: harvest creates a 60-day inventory spike equal to $5M cost; if payable terms are 30 days, additional short-term financing may be required.
7. Evaluate capacity and utilization
– Compute capacity utilization = actual throughput / maximum throughput.
– Low utilization often means high unit fixed-costs; high utilization can amplify margins but raises exposure to supply disruptions.
– Example: plant capacity 100,000 tonnes, actual throughput 70,000 → utilization = 70%.
8. Review capital expenditure needs and maintenance capex
– Distinguish growth capex (expand acreage or processing) from sustaining capex (maintain existing capacity).
– Check management guidance, replacement schedules, and project timelines.
9. Price and yield sensitivity (scenario testing)
– Build three scenarios: base, downside, upside. Vary prices, yields, and input costs.
– Example sensitivity: baseline corn price $200/tonne; downside $160 (−20%) reduces revenue proportionally. Show impact on EBITDA and FCF in $ terms and as margins.
10. Valuation approaches suited to agribusiness
– Common multiples: EV/EBITDA, P/E, EV/tonne or EV/acre (useful for asset-heavy firms).
– DCF: discount forecast FCFs; include explicit seasonality and a terminal value.
– Formulas:
– EV = market capitalization + net debt.
– EV/EBITDA = EV ÷ EBITDA.
– DCF present value = Σ (FCF_t / (1 + r)^t) + terminal value / (1 + r)^T.
– Note assumptions: commodity-price forecasts and yield trends drive most valuation variance.
11. Operational and supply risks
– Weather/climate risk: drought, floods, unseasonal frost.
– Biosecurity: pests, disease outbreaks that can curtail production or cause recalls.
– Input supply concentration: single-source fertilizer or seed suppliers.
– Check insurance cover, hedging programs, and contractual protections.
12. ESG and sustainability factors
– Water usage, soil health, pesticide use, and greenhouse-gas emissions matter for long-term license to operate.
– Trackable metrics: water use per tonne, fertilizer application rates, deforestation exposure.
– These affect regulatory risk and access to premium markets.
13. Monitorable KPIs and a watchlist
– Monthly/quarterly: commodity prices, volume (acres/yield/tonnes), capacity utilization, inventory days, receivables days, payable days, EBITDA margin, FCF, net leverage, capex run-rate.
– Corporate actions to watch: changes in hedging policy, major M&A, shifts in planting strategy.
14. Red flags checklist (stoplights)
– Consistent negative FCF or rising working-capital needs.
– Rapidly increasing net leverage without clear capex returns.
– Falling utilization while volumes are stable (suggests demand/quality issues).
– Heavy customer or supplier concentration
15. Valuation approaches — quick guide
– Common multiples: EV/EBITDA (enterprise value to EBITDA) is widely used for capital-intensive agribusinesses because it includes debt; P/E (price-to-earnings) can be distorted by cyclicality and one-off items. Price-to-book (P/B) or replacement-cost methods matter when land, buildings, or specialized assets dominate value.
– Normalization: smooth earnings over several seasons (3–5 years) to remove cyclical peaks/troughs and extraordinary items before applying multiples.
– DCF basics: enterprise value (EV) = Σ [FCFt / (1+WACC)^t] + terminal value. Terminal value (Gordon growth) = FCFn × (1+g) / (WACC − g). Carefully justify the long‑term growth rate g (usually ≤ long-run GDP or population/food demand growth).
– Sensitivity: run scenarios for commodity prices, yields, input inflation, and WACC. Show at least base, downside, and upside cases.
16. Key formulas (define terms on first use)
– EBITDA margin = EBITDA / Revenue.
– Net leverage = Net debt / EBITDA, where Net debt = Short-term debt + Long-term debt − Cash.
– Inventory days = (Inventory / Cost of goods sold) × 365.
– Receivables days = (Accounts receivable / Revenue) × 365.
– Payables days = (Accounts payable / Cost of goods sold) × 365.
– Free cash flow (FCF) ≈ NOPAT + D&A − Capex − ΔWorking capital, where NOPAT = EBIT × (1 − tax rate); D&A = depreciation & amortization; Capex = capital expenditures; ΔWorking capital = change in net working capital.
Worked numeric example
Assumptions (simple):
– Revenue = $500m; EBITDA = $80m; D&A = $10m; Capex = $30m; Tax rate = 25%.
– Inventory = $40m; COGS = $350m; AR = $30m; AP = $25m.
– Net debt = $200m.
Calculations:
– EBITDA margin = 80 / 500 = 16.0%.
– Net leverage = 200 / 80 = 2.5x.
– Inventory days = (40 / 350) × 365 ≈ 41.7 days.
– Receivables days = (30 / 500) × 365 ≈ 21.9 days.
– Payables days = (25 / 350) × 365 ≈ 26.1 days.
– NOPAT = (EBIT = EBITDA − D&A = 70) × (1 − 0.25) = 70 × 0.75 = $52.5m.
– FCF ≈ 52.5 + 10 − 30 − ΔWC. If ΔWC = +5m (use of cash), FCF = 52.5 + 10 − 30 − 5 = $27.5m.
Notes: rounding approximations and accounting differences (e.g., tax timing, lease accounting) will affect real models.
17. Building a simple seasonal financial model — step-by-step
1) Start with monthly or quarterly revenue drivers: planted acres × yield per acre × expected realized price per unit.
2) Model input costs separately (seed, fertilizer, fuel, labor) per acre or per tonne; capture timing (some costs incurred pre-harvest).
3) Convert volumes/prices into COGS, then gross profit and operating expenses.
4) Build working-capital schedules: track inventory build/harvest, receivables timing (buyer payment terms), and payables timing (supplier terms).
5) Include hedging effects: model forward/lock prices or mark-to-market P&L if hedges are accounted that way.
6) Validate against historical seasonality; reconcile to reported quarterly/annual financials.
7) Run sensitivity tables for ±10–30% price and yield moves and for input-cost inflation.
18. Hedging and price risk — practical points
– Objective first: decide whether the company seeks to stabilize cash flow (budget hedge) or to lock value for a portion of expected production (price protection).
– Instruments: futures/options (exchange-traded), forwards/swaps (OTC). Each has margin, liquidity, and counterparty considerations.
– Watch for accounting: hedge accounting rules determine whether hedges reduce reported earnings volatility.
– Checklist before assessing hedging: volumes hedged (% of expected output), tenor of contracts, counterparties’ credit quality, collateral requirements, and policy transparency in filings.
19. Financing and capital structure considerations
– Asset-heavy firms often carry long-term debt secured by land, facilities, or storage; evaluate covenant terms (interest coverage, leverage ratios) and amortization profiles.
– Working-capital financing: seasonal lines of credit and receivable financing are common; check renewal history
– Inventory financing and warehouse receipts: companies may pledge stored grain, livestock inventory, or processed product as collateral under warehouse receipt financing. Key checks: the warehouse operator’s license and insurance, lien searches on receipts, storage shrinkage (“shrink”), and harvest timing. Example: a 10,000-bushel corn inventory at $5/bu can secure a $40,000 loan if the lender advances 80% after accounting for shrinkage and storage costs (10,000 × $5 × 0.8 = $40,000).
– Asset-backed and lease financing: tractors, combines, silos, and processing equipment are commonly financed via leases or equipment loans. Confirm remaining useful life vs. loan term and residual value assumptions.
– Interest-rate and currency risk on debt: floating-rate seasonal facilities expose the borrower to short-term rate moves; cross-currency borrowing may be used for imports/exports. Calculate interest cost sensitivity: a $10m seasonal loan at floating rate rising 200 basis points (2.0%) increases annual interest expense by $200,000.
– Covenants and stress-testing: lenders expect covenant compliance through price and yield stress tests. Example covenant: interest coverage ratio (ICR) = EBITDA / interest expense. If projected EBITDA is $3.0m and interest is $1.2m, ICR = 2.5x; a 20% drop in EBITDA reduces ICR to 2.0x. Track covenant triggers and remedial provisions.
– Renewal and tenor mismatch: seasonal lines used for several years without principal amortization can conceal refinancing risk. Check historical renewal rates and backup lenders.
20. Taxes, subsidies, and government support
– Subsidies and direct payments: many jurisdictions provide production, price, or insurance subsidies that materially affect cash flow. Identify programs in company disclosures and quantify the percentage of EBITDA they represent.
– Tax treatments: inventory accounting (FIFO = first-in, first-out; LIFO = last-in, first-out) affects cost of goods sold and taxes in inflationary commodity environments. Deferred tax assets may arise from loss carryforwards; validate realizability.
– Example: if a farm reports $2.0m pretax income but receives $300k in direct subsidy, underlying pretax without subsidy = $1.7m — an analyst should model both cases for sensitivity.
21. Regulation, trade policy, and phytosanitary issues
– Tariffs, quotas, and export controls: changes in trade policy can alter demand and regional price bands quickly. Map product exposure by destination and percentage of sales.
– Sanitary and phytosanitary (SPS) measures: plant- and animal-health rules can shut export markets for a season. Check certification, traceability systems, and past SPS incidents in filings.
– Biotechnology and GMO regulation: seed approvals or bans change input costs and market access. Note major markets’ stances (EU vs. US vs. China) and any company reliance on genetically modified seeds.
22. Sustainability, environmental, social, and governance (ESG) factors
– Key ESG risks: deforestation risk (land-use change), water scarcity, fertilizer runoff (nutrient pollution), animal-welfare standards, and labor conditions. These can be operational and reputational risk drivers.
– Metrics and verification: scope 1–3 greenhouse gas (GHG) emissions, water use per unit of output, hectares under sustainable certification (e.g., Rainforest Alliance, where relevant). Third-party audits and traceability systems strengthen disclosures.
– Cost and opportunity: sustainability initiatives may require capital (irrigation upgrades, precision agriculture), but can open premium markets. Quantify capex vs. potential premium or cost savings.
23. Valuation and key financial metrics
– Seasonality-adjusted free cash flow (FCF): build a monthly or quarterly working-capital schedule. FCF = Net income + non-cash charges – capex – Δworking capital. For seasonal agribusiness, convert to 12-month trailing FCF or average FCF over a cycle.
– Commodity-price scenario modeling: run base, downside, and upside commodity-price cases. For example, model EBITDA sensitivity to a 15% decline in main commodity price.
– Common multiples: EV/EBITDA (enterprise value to earnings before interest, tax, depreciation, and amortization) and EV/acre or EV/bushel for asset-heavy, land-based operations. Use peer-group medians but adjust for subsidy exposure and yield differential.
– Worked simplified DCF example: company projects next-year EBITDA $8.0m, capex $2.0m, change in working capital +$1.0m, taxes 25%. Free cash flow = (EBITDA – capex – ΔWC) × (1 – tax rate) approximated = (8 – 2 – 1) × 0.75 = $3.75m. Discount with a cycle-adjusted WACC (weighted average cost of capital), stress-tested for commodity price swings.
24. Mergers, consolidation, and strategic drivers
– Why M&A happens: scale economies in procurement and processing, vertical integration (seed-to-shelf), geographic diversification against weather risk, and land consolidation.
– Due diligence checklist: land title and encumbrances, environmental liabilities (chemical usage, runoff, landfill), supply contracts and counterparty credit, seed and input agreements, regulatory compliance history, and workforce issues (union agreements, seasonal labor).
– Post-merger integration risks: IT and traceability systems, contract overlap, and cultural integration between farm/operators and corporate processors.
25. Red flags and warning signs
– Repeated covenant waivers or extensions.
– Large, growing receivables from a small number of buyers; single-buyer concentration risk.
– Inventory write-downs or increasing “shrinkage” with opaque storage practices.
– Rapid expansion financed primarily by short-term facilities with weak renewal history.
– Frequent changes in harvest or yield reporting methodology without explanation.
Practical checklist for analyzing an agribusiness (quick workbook)
– Production exposure: list main commodities, % of revenue each.
– Price exposure: for each commodity, note hedge policy, % hedged, and hedging instrument types.
– Working capital cycle: average days receivable, inventory days, and payables days; seasonal peak funding requirement.
– Balance-sheet health: leverage (net debt / EBITDA), interest coverage, and covenant thresholds.
– Land and asset quality: owned vs. leased acres, title clarity, irrigation access, storage capacity.
– ESG and
– ESG and traceability: document greenhouse-gas emissions scope (direct and indirect), water use and source, pesticide/fertilizer intensity, land‑use change (deforestation risk), worker safety and labor practices, community relations, and certification status (e.g., GlobalG.A.P., Rainforest Alliance). Note any gaps in traceability for primary inputs or final products; lack of traceability raises reputational and supply‑chain risks.
– Management and governance: board independence, management tenure and experience in agriculture, incentive structure alignment (bonus metrics tied to sustainable yields vs. short‑term revenue), related‑party transactions, and history of restatements or regulatory fines.
– Market and counterparty risk: customer concentration (top 5 customers % of sales), supplier concentration (seed, fertilizer, fuel), credit quality of major buyers, and single‑buyer or single‑supplier exposure clauses in contracts.
– Regulatory and trade risk: tariff exposure, export permit dependence, subsidies and quota changes, phytosanitary restrictions, and likely regulatory changes (e.g., fertilizer restrictions, methane/land‑use rules).
– Climate and physical risk: reliance on rainfed versus irrigated production, historical yield volatility, exposure to extreme weather events, and availability of crop insurance or parametric products.
– Technology and productivity: adoption of precision agriculture, seed genetics, irrigation efficiency, and digital traceability; assess R&D pipeline and capital intensity for productivity improvements.
– Financial reporting quality: look for one‑off gains/losses, changes in revenue recognition or inventory valuation methods, related‑party sales, and frequency/timing of auditor changes.
Practical step‑by‑step worksheet (how to run a quick analysis)
1) Gather baseline data
– Most recent 3 years of income statements, balance sheets, cash‑flow statements.
– Segment revenue by commodity and geography.
– Working‑capital line items: accounts receivable (AR), inventory, accounts payable (AP).
– Debt schedule (short‑ vs. long‑term), interest expense, cash balance.
– Hedging position details: volumes/value hedged, instruments, maturities.
2) Compute core ratios (formulas and example)
– Days receivable = (AR / Revenue) × 365
Example: AR = $50m, Revenue = $500m → 36.5 days.
– Inventory days = (Inventory / COGS) × 365
Example: Inventory = $80m, COGS = $350m → 83.4 days.
– Payables days = (AP / COGS) × 365
Example: AP = $40m, COGS = $350m → 41.7 days.
– Working‑capital cycle = Inventory days + Receivable days − Payables days
Example: 83.4 + 36.5 − 41.7 = 78.2 days.
– Net debt / EBITDA = (Total debt − Cash) / EBITDA
Example: Debt = $200m, Cash = $20m, EBITDA = $50m → (200−20)/50 = 3.6x.
– Interest coverage = EBIT / Interest expense
Example: EBIT = $40m, Interest = $10m → 4.0x.
– Hedge coverage (%) = (Hedged volume or value / Total exposure) × 100
Example: 60,000t hedged of 100,000t exposure → 60%.
3) Quick stress tests (scenarios to run)
– Price shock: simulate a −20% commodity price for main crop; assume variable costs unchanged to show gross‑margin impact. Compute change in EBITDA and free cash flow under that shock.
– Volume shock: simulate −15% yield or sales volume during a drought year; recalc working‑capital need and liquidity.
– Interest‑rate shock: increase interest expense by 200 bps and recompute interest coverage and covenant headroom.
– Counterparty failure: assume top customer (X% revenue) defaults; estimate receivables at risk and impact on liquidity.
Worked price‑shock example (simple)
– Revenue = $500m; main commodity = 60% of revenue → $300m.
– Price drop 20% → direct revenue loss = 0.20 × $300m = $60m.
– If gross margin on that commodity was 40%, lost gross profit ≈ $24m; approximate EBITDA falls by $24m (adjust for fixed costs).
– If baseline EBITDA = $50m, post‑shock EBITDA ≈ $26m → net debt/EBITDA (with net debt $180m) rises from 3.6x to ≈6.9x, a large deterioration.
Red‑flag checklist (prioritize these)
– Rapidly rising receivables or inventory relative to sales.
– Consistent negative operating cash flow despite reported