Integrated USDA & Market Data Infrastructure
Every number in ClearCut traces back to a publicly available government or exchange data source. No black boxes. No proprietary feeds. Just clean, auditable data powering transparent forecasts.
Transparent Data, Transparent Forecasts
At ClearCut, we believe every forecast is only as good as the data feeding it. That principle shapes everything we build. Rather than relying on proprietary black-box data sources or undisclosed third-party feeds, we anchor our entire forecasting engine to publicly available, government-reported datasets and regulated exchange data.
Why does this matter? Because when a forecast moves your purchasing decision by thousands of dollars, you deserve to know exactly where the underlying numbers came from. Every data point in ClearCut can be independently verified by going directly to the source—whether that's a USDA LMPR report, a NASS QuickStats query, or a CME settlement file. This isn't just a philosophical stance; it's an operational commitment to auditability and trust.
Our data infrastructure ingests, normalizes, and harmonizes information from five primary sources. Each source serves a distinct analytical role in our forecasting models, and together they provide the multi-dimensional view of the protein market that makes accurate price forecasting possible.
USDA Livestock Mandatory Price Reporting (LMPR)
The USDA's Livestock Mandatory Price Reporting program is the backbone of ClearCut's data infrastructure. Established by Congress to bring transparency to livestock and meat markets, LMPR requires packers above certain volume thresholds to report transaction prices, volumes, and terms. This data is the gold standard for wholesale meat pricing in the United States.
ClearCut ingests the following LMPR reports on an automated, recurring basis:
Beef Reports
- LM_CT150 — Comprehensive boxed beef cutout report. This is the primary daily summary of the composite beef cutout value, broken down by Choice and Select grades, with load counts and price ranges.
- LM_CT169 — Boxed beef cuts detail. Individual primal and subprimal cut prices reported by grade, providing granular visibility into which cuts are driving cutout movement.
- Report 2461 — Weekly cutout and primal values. A weekly summary that aggregates daily data into a broader view of primal-level price trends (chuck, rib, loin, round, brisket, short plate, and flank).
- Reports 2460, 2462, 2464 — Individual cuts by grade. These reports break pricing down to the individual fabricated cut level across Choice, Select, and ungraded categories, enabling precise spread analysis.
- Report 2459 — Forward commitments. Packer forward sales data showing committed volumes and pricing for future delivery periods—a critical leading indicator of near-term supply availability.
Pork Reports
- Report 2498 — Daily pork cutout and cuts. The pork equivalent of the beef cutout report, covering composite pork cutout value and individual primal prices (butt, ham, loin, belly, picnic, rib, jowl).
- Report 2506 — Pork forward sales. Forward commitment data for pork, showing negotiated volumes and prices for future shipment periods.
Production & Slaughter
- LS712 — Daily livestock slaughter data including federally inspected head counts and average dressed weights for cattle and hogs. Production volume is a fundamental supply-side input for price modeling.
These reports follow a mix of daily and weekly reporting cadences. Daily reports (LM_CT150, LM_CT169, Report 2498, LS712) are published each trading day, typically by mid-afternoon Eastern. Weekly reports (2461, 2460, 2462, 2464, 2459, 2506) are released on a fixed weekday schedule, usually Friday afternoon. ClearCut's ingestion engine handles both cadences automatically and reconciles daily data against weekly summaries for consistency checks.
USDA NASS — Cold Storage
The USDA National Agricultural Statistics Service publishes monthly Cold Storage reports that track total pounds of beef and pork held in commercial freezer warehouses across the United States. ClearCut accesses this data programmatically via the NASS QuickStats API.
Cold storage inventories are segmented by cut category—boneless beef, beef cuts, pork bellies, ham, pork trimmings, and other pork products. These inventory levels function as a leading indicator for wholesale cutout prices: when stocks build beyond seasonal norms, downward price pressure typically follows within two to six weeks. Conversely, drawdowns below historical averages signal tightening supply and potential price rallies.
ClearCut normalizes cold storage data against five-year seasonal baselines to compute a stocks-to-use ratio that feeds directly into our forecasting models. This monthly signal complements the higher-frequency daily and weekly LMPR data, providing a medium-term supply context that daily reports alone cannot capture.
CME Futures Data
Live cattle (LE) and lean hog (HE) futures contracts traded on the Chicago Mercantile Exchange provide the market's consensus forward view of livestock prices. ClearCut extracts settlement prices, open interest, and volume data across the full forward curve—typically six to eight active contract months at any given time.
Raw futures prices alone are not directly comparable to cash market cutout values. ClearCut computes basis-adjusted futures by calculating the historical spread between cash prices and futures prices, segmented by contract month and weeks-to-expiration. This basis adjustment transforms the futures curve into a forward estimate of cash prices that can be directly compared against our statistical forecasts, providing a powerful cross-validation signal.
Open interest and volume data serve as secondary indicators of market conviction. When open interest is rising alongside price movement, the trend is generally considered more durable than when open interest is declining. ClearCut incorporates these signals as confidence modifiers in our ensemble forecast weighting.
BLS Consumer Price Index
The Bureau of Labor Statistics publishes the Consumer Price Index (CPI) monthly, including the food-at-home sub-index that tracks retail grocery prices. ClearCut uses this data as a demand-side proxy in our forecasting models.
Consumer spending trends at the retail level influence wholesale cutout prices with a measurable lag—typically three to six weeks. When retail prices rise and consumer demand remains elastic, retailers may reduce orders from wholesalers, creating downstream pressure on cutout values. Conversely, periods of strong consumer spending and stable retail pricing support wholesale demand. The CPI food-at-home index, while not a direct measure of wholesale demand, provides a consistent and publicly available signal of consumer purchasing behavior that improves forecast accuracy when combined with supply-side USDA data.
Automated Ingestion & Normalization
ClearCut's data pipeline is designed for zero-touch operation. On application startup, the system checks the staleness of each data source. If any source has data older than five days, a full synchronization is triggered automatically—no manual intervention required. This smart staleness detection ensures that even after extended downtime or deployment to a new environment, the system self-heals its data state.
Beyond startup, a scheduled sync runs daily at 4:00 AM Eastern. This timing is chosen to capture the previous trading day's final USDA reports (typically published between 2:00–4:00 PM Eastern) while completing before the next business day begins. The scheduler is designed to be idempotent: if the same data has already been ingested, duplicate records are detected and discarded.
Data Cleaning & Normalization
Raw USDA and exchange data arrives in inconsistent formats—varying date formats, mixed units, inconsistent product naming conventions, and occasional null values. ClearCut's normalization layer standardizes all incoming data into a unified schema: ISO date formats, consistent product identifiers, prices in dollars per hundredweight ($/cwt), and weights in pounds. Missing data points are flagged rather than silently interpolated, preserving data integrity for downstream models.
Deduplication logic runs on every ingestion cycle. Each record is fingerprinted by source, report date, and product identifier. If a matching fingerprint already exists in the database, the incoming record is compared field-by-field. Only genuinely updated values trigger a database write, minimizing unnecessary storage churn and maintaining a clean audit trail.
Update Frequency & Reliability
ClearCut is built for autoscale cloud deployments where traditional cron-based scheduling may not fire reliably. Our architecture uses a combination of startup-triggered sync, in-process schedulers, and staleness detection to guarantee data freshness regardless of infrastructure behavior.
Daily Sources
- LM_CT150 — Boxed beef cutout (daily)
- LM_CT169 — Boxed beef cuts (daily)
- Report 2498 — Pork cutout & cuts (daily)
- LS712 — Slaughter & weights (daily)
- CME Futures — Settlement prices (daily)
Weekly & Monthly Sources
- Report 2461 — Cutout/primal values (weekly)
- Reports 2460/2462/2464 — Cuts by grade (weekly)
- Report 2459 — Forward commitments (weekly)
- Report 2506 — Pork forward sales (weekly)
- NASS Cold Storage — Inventory levels (monthly)
- BLS CPI — Food-at-home index (monthly)
All sync operations include retry logic with exponential backoff for transient failures (network timeouts, temporary USDA API outages). Persistent failures trigger alerts and are logged with full context for rapid diagnosis. The system is designed to degrade gracefully: if one data source is temporarily unavailable, forecasts continue running on the most recent available data rather than halting entirely.