Are there any yield forecasting software tools that handle time-series data and scenario analysis well?

Yes — there are several good tools, but the “best” one depends on what you mean by yield (agricultural yield, manufacturing yield, investment yield, etc.) and how much scenario analysis you need.

Good options by use case

1) General time-series forecasting + scenario analysis

These are strong if you want to model historical yield data and then test “what if” scenarios:

• Python stack

  • pandas / statsmodels / scikit-learn
  • Prophet for easier trend/seasonality modeling
  • sktime or darts for more advanced forecasting workflows
  • PyMC or Stan if you want probabilistic/scenario-based forecasting
  • Best for: flexibility, custom scenario simulation, reproducibility

• R stack

  • forecast, fable, tsibble
  • Great for classical time-series forecasting and scenario testing

2) BI / planning tools with forecasting

If you need business-user-friendly scenario planning:

• Anaplan
• Adaptive Planning (Workday)
• Oracle Planning
• SAP Analytics Cloud
• Microsoft Power BI (basic forecasting; scenario modeling usually needs add-ons or DAX/Power Query)
• Best for: interactive planning, what-if analysis, collaboration

3) Industrial / agricultural yield forecasting platforms

If your “yield” is crop yield or production output:

• Climate FieldView
• Granular
• John Deere Operations Center ecosystem
• Trimble Ag Software
• Some specialized agronomy platforms also integrate remote sensing and weather data
• Best for: field-level yield prediction, weather/soil inputs, operational scenario analysis

4) Enterprise forecasting / optimization platforms

If you need scenario analysis across many drivers and constraints:

• Palantir Foundry
• C3 AI
• Dataiku
• Alteryx (with forecasting workflows)
• KNIME
• Best for: combining time-series with external drivers, automated pipelines, scenario comparison

What to look for

For “handles time-series data and scenario analysis well,” key features are:

• Multiple forecasting methods: trend/seasonality, ARIMA, Prophet, ML, probabilistic
• Ability to add external drivers: weather, price, input costs, operations data
• Scenario management: baseline / optimistic / pessimistic / custom assumptions
• Backtesting and error metrics
• Support for uncertainty intervals
• Easy integration with spreadsheets, databases, and APIs

Practical recommendation

• If you want maximum flexibility: use Python with Darts or Prophet + a scenario simulation layer
• If you want business planning and dashboards: Anaplan or SAP Analytics Cloud
• If you want agricultural yield forecasting: look at FieldView / Granular / Trimble type tools

If you tell me what kind of yield you mean and whether you want a no-code, low-code, or code-based solution, I can narrow it down to 3–5 best tools.