Knowing supply means knowing your market position.
WeatherYield provides a window into supply, showing grain handlers areas of over/under supply before they occur. This allows you to reliably adjust your bid structure throughout the season, which can dramatically increase confidence in your market positioning. WeatherYield also empowers you to make timely decisions on bunker and emergency space, schedule labor more efficiently, and optimize fleet positioning and deployment.
The WeatherYield crop forecast is based on our proprietary 1.3B samples of yield, carefully collected across millions of acres and 26 states – as well as 20 years of detailed weather matched to the sample locations. These proprietary samples allow WeatherYield to offer forecasts unconstrained by county boundaries.
Custom reports show hyper-local forecasts for corn and beans, revealing areas of over/under supply.
Buy a WeatherYield™ Seasonal Subscription
A WeatherYield Seasonal Subscription gives you the power to anticipate your service area’s corn and soybean production, accurately.
Pricing is discounted and billed up-front, for six months of hyper-local forecasting per season.
HOW IT WORKS
Main Street Data leverages the power of data giant IBM, applying machine learning and human intelligence to massive amounts of weather and related data.
- Hyper-local views, customized for your territory
- Highlighted factors, such as weather, that affect hyper-local grain forecast
- Pricing is discounted and billed up-front, for six months of hyper-local forecasting per season
Access our proprietary data science via a weekly PDF, emailed right to your inbox. To view the standard SaaS agreement, click here.
Crop Forecasting Features
- Continual awareness of accurate yield expectations
- Updates and forecasts during the growing season
- Specific factors affecting your forecast, from an expert agronomist
- Instant gap analysis comparing this year’s forecast to the prior three seasons
Crop Forecasting Benefits
- View areas of over/under supply before they occur
- Reliably adjust your bid structure throughout the season
- Make timely decisions on resources, storage, labor, and deployment
- Quickly identify risk levels
- Monitor Risk & relative performance to prior years, state forecasts and other internal data points
What Drives the Crop Forecasting Model?
- Real-time local weather, applied to sophisticated crop stage modeling
- Meticulous data analysis produced by a unique data set, carefully curated and subjected to a superior level of quality assurance
Our subscriptions can be custom designed to meet the needs of your enterprise. To find out more about these agile solutions, contact one of our sales executives.
Tim Davis
V.P. AG MARKETS & BUSINESS DEVELOPMENT
Cooperatives, Grain Marketing Advisors, & Ethanol facilities
217.652.2612
EMAIL
Michael X. Feeney
V.P. GRAIN MARKETING & BUSINESS DEVELOPMENT
Traders, Risk Managers & Hedgers, Cooperatives
217.480.7563
EMAIL
Ag Data Science Done Right
The Main Street Data forecasting model leverages a massive amount of yield and weather data elements to identify and interpret causes, as well as measure, monitor, and forecast a wide variety of outcomes. This crop forecasting model is based on MSD’s proprietary Crop Stage approach, applying machine learning to billions of samples of yield and 10s of billions of field and weather-related data elements. The analytical interpretations derived from this powerful forecasting model are valuable to a wide range of users, including growers, traders, insurers, lenders, agronomists, and co-ops.
See How Human Intelligence is Transforming Data Science.
Data Elements Include:
- soil characteristics
- water holding capacity
- water availability at multiple depths
- trillions of historical weather data elements
- weather forecasts ranging from 15 days to 6 months
- 1.3B yield samples across 26 states
Ag Insights
Knowing Better Means Knowing Sooner
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Bringing Human Intelligence to Data Science in the Ag Space
Main Street Data
6701 W. 64th Street | Building 5, Suite 320 | Mission, KS 66202 | 816.533.7247