To maximise their production and its fiscal reciprocation for the long-term, farmers face a variety of decisions that require accurate predictions for timespans reaching multiple years or even decades in the future.
Furthermore, such predictions must take into account variegating of factors and correlate different types of data pertaining to weather and climate, soil condition, etc. Additionally, an effective analysis cannot be limited to local data, but also consider global evolvements and market trends.
Lastly, such analysis must lead to actionable suggestions, directly applicable and translatable to specific in-field actions and business moves.
Having a strong baseline of predictive analytics technologies, a decision support system should further extend to build strategies for multiple farming processes like the regulation of irrigation and drainage systems, the identification of most effective time windows for planting and harvesting different crops, etc.
Moreover, we believe that the analysis enabling decision support must operate over weather and climate data at a global scale and encompass economic and market data when available. Effective production and price prediction and the provision of adaptation actions regarding investments and pricing can reduce risk and promote a stabler investment field for farmers and other participants in the food supply chain.
Using advanced mathematical optimization, multiple criteria decision analysis and game theory techniques we offer decision support tools for:
- improving crop field operations
- optimum field-level investment decisions
- negative soil impact mitigation
- commodity marketing and price planning