Why California’s almond industry is distancing itself from USDA benchmarks
December 9, 2025 is the date that matters. On that day, the Almond Board of California voted to stop funding USDA-NASS’ California Almond Objective Measurement Report, the report that traditionally landed in early July, while the May Subjective Forecast continues.
The biggest loss is not “a report”, it is a mid-season truth point. The Objective Measurement was the more statistically rigorous estimate because it was built from actual almond counts in roughly 1,000 orchards, not only from survey responses like the May subjective process. For buyers, that July number often acted as the market’s recalibration moment for supply sizing.
Recent crop sizing shows why the market cared. USDA-NASS estimated about 3.0 billion pounds for the 2025 crop in the Objective Report, while ABC points to a 2024 harvest of 2.73 billion pounds and highlights that forecast error risk is real when weather and economics move fast.
Procurement relevance is the underlying driver. The industry is signaling it wants better ROI from its data spend and more reliance on alternative intelligence such as monthly movement and carry, especially after years of volatility tied to acreage shifts, orchard removals, and variable bloom outcomes. The direction is clear: reduce dependence on a single benchmark print.
A transition period is already underway. ABC has flagged changes to the 2026 USDA-NASS Subjective Forecast format, still released in May but reorganized, which is a practical hint that buyers should update internal processes and dashboards now, not later.
What changes for European and Italian procurement when the reference forecast breaks
The operational impact is immediate: without the July Objective Report, EU buyers lose a mid-season recalibration point. That affects volume coverage decisions, contract laddering, and budget re-forecasting. In practice, more decisions get pushed onto the May subjective number plus in-season shipment and inventory signals.
The risk exposure is large because the import channel is large. EU 2024 imports of shelled almonds (CN 080212) from the U.S. were about 229.1 million kg (about 229,081 MT) with a value around $1.002B. When the shared forecast anchor weakens, planning risk rises across a meaningful flow of raw material.
Italian procurement pain points show up in delivered cost and timing. More uncertainty tends to widen variance in CIF or CIP outcomes, complicate the timing of cover, and make price protection choices harder for industrial users that need consistent specs by variety and grade, including common commercial types such as Nonpareil and Carmel and defined size and quality parameters.
Negotiations also change because the shared reference shifts. Sellers and handlers are likely to lean harder on the Almond Industry Position Report, focusing on shipments, commitments, and computed inventory as the common language. Buyers need to be ready to challenge and validate those signals with independent evidence such as bearing acreage context, bloom and weather developments, and quality and reject indications.
Compliance and logistics do not get simpler just because forecasting does. European procurement still needs clean CN and TARIC classification discipline, especially the split between 080211 and 080212, because classification consistency feeds customs treatment, landed-cost models, and ERP master data.
The hidden risks: contract timing, price discovery, and inventory decisions built on shaky estimates
Contract timing risk increases when a repricing event disappears. Historically, May (Subjective) and early July (Objective) were key moments when the market repriced expectations. Removing July raises the chance you lock volume too early and later see softness, or you wait too long and face a short-cover squeeze if supply tightens.
Price discovery shifts from headlines to flow. The Almond Industry Position Report becomes a primary input, so buyers must interpret computed inventory, shipment pace, and commitments or sold position rather than relying on a single crop-size headline to anchor negotiations.
Inventory policy gets riskier when “gross crop” diverges from salable kernels. The market can look well supplied on a crop estimate and still be tight in deliverable quality because rejects and quality deductions reduce what can actually ship against contracts. Some handler commentary points to elevated rejects, for example around 2.6% versus a 2% assumption, and that difference matters because it directly reduces available inventory.
Basis and grade risk becomes more visible for processors. Without the objective benchmark, spreads between premium grades and industrial grades, or between origins, can widen faster. Procurement teams need to model spec flexibility in advance, including what can be substituted in recipes and what cannot, across forms like blanched, sliced, or diced.
Working capital risk rises because uncertainty tempts “insurance inventory.” Holding higher stocks in Europe adds financing and storage costs and increases quality degradation risk over time, so stock decisions should be tied to measurable triggers such as shipment pace, carry-in expectations, and reject trends rather than gut feel.
How to recalibrate: triangulating supply with alternative data sources and market signals
Triangulation replaces single-point forecasting. A practical stack is: USDA-NASS May Subjective Forecast for initial sizing, ABC Position Report for shipments, commitments, and inventory, trade flows such as EU imports by CN 080212 for demand reality, and independent market research for acreage and price-cycle context.
Flow math is the part buyers can actually run every month. The goal is to translate movement into internal KPIs such as months of cover and coverage percentage by quarter, then compare shipments to the run-rate needed to reach a target carryout. Many market participants already think in “monthly pounds needed” logic, and buyers can mirror that discipline in their own dashboards.
Quality and salability checks need to be pulled forward. Objective-style proxies such as kernel size outcomes, grade results, rejects, and meat yield matter because salable supply drives pricing more than gross pounds. Buyers should ask sellers to disclose expected grade mix and deduction schedules early, then update assumptions as receipts and processing results become clearer.
Broader USDA channels can still help, just differently. USDA-AMS Market News can add price and market commentary where available, and USDA-ERS outlook material can provide macro framing, but both should be reconciled against handler shipment and inventory realities rather than treated as standalone truth.
Origin optionality should be modeled, not improvised. Tracking Australia’s production outlook and EU or Mediterranean availability helps buyers evaluate diversification, build contingencies, and use credible alternatives in negotiation when California signals are less definitive.
Practical playbook for 2026–2027: contracting structures, trigger clauses, and stock policy under higher uncertainty
Layered cover becomes safer than “all-in.” A laddered strategy can split risk across the season, for example covering 30 to 40% early post-bloom, 30 to 40% after the May Subjective Forecast, and leaving the remainder to be executed based on flow signals, rather than concentrating decisions around a July print that no longer exists.
Trigger clauses should be tied to observable data. Position Report metrics such as computed inventory thresholds, commitments percentage, and shipment pace are measurable and shared. Objective proxies such as reject percentage and grade distribution are also measurable if you require disclosure and define how adjustments are calculated.
Contract types should match what you are trying to protect. Fixed-price can cover baseline needs. Index-referenced components can be used where acceptable internally. Volume flexibility bands, often in the range of plus or minus 10 to 15%, can help industrial users manage demand volatility without turning every forecast miss into a penalty dispute.
Stock policy should be defined in weeks and linked to lead time. A minimum safety stock can be set based on service level and replenishment time, then increased only when dashboard triggers fire, such as shipment deceleration, tightening computed inventory, or rising rejects.
Negotiation needs a cost-floor reality check. When grower economics tighten, sellers tend to defend price levels, and break-even narratives can influence posture. Buyers should be ready with counter-models grounded in delivered cost, substitution options, and hedged layers rather than debating a single crop number.
What to watch next: which indicators will replace the old benchmark and how to build an early-warning dashboard
The new benchmark stack is already visible. The May USDA-NASS Subjective Forecast remains the official seasonal anchor, and monthly ABC Position Reports are likely to become the primary shared reference set for in-season pricing and availability discussions.
A buyer-ready dashboard can stay simple if it is consistent. Core widgets should include shipments versus prior year and versus needed run-rate, commitments or sold percentage, computed inventory and implied carryout, export versus domestic mix, a quality proxy such as rejects or grade signals, and EU import arrivals by CN 080212.
Calendar alerts matter because almonds are seasonal even when contracts are annual. Bloom and weather risk sits in the January to March window, the Subjective Forecast lands in May, early crop-year receipts tend to build in late summer into autumn, and European demand peaks around pre-Christmas contracting for bakery and confectionery. Those dates should drive RFQ timing and coverage decisions.
Stress signals should be treated as early warnings, not noise. Widening spreads between grades or origins, persistent commitment lag, rising rejects, inventory restatements, or abrupt shipment deceleration can precede sharp basis moves even without a crop-size headline.
Governance is what keeps the system usable. Assign clear ownership across procurement, QA, and finance, set thresholds with action playbooks such as buy, hold, switch origin or spec, trigger optional volumes, and maintain an assumptions register because fewer authoritative anchor points means internal discipline matters more.