Cargill

AI-Driven Dairy Insights and Forecasting Platform

United States, Europe and global

This engagement focused on product leadership and unification of Cargill’s digital dairy platforms into a single, scalable web application serving consultants, technical teams, and external customers. The objective was to transform fragmented analytics and forecasting tools into a cohesive decision support platform that could deliver faster insights, improved usability, and a foundation for AI-driven intelligence across the dairy value chain. 

From a product management perspective, the core challenge was platform fragmentation and scale. Cargill had multiple mature tools supporting insights, performance analytics, and forecasting, built on different technologies and interaction models. While individually valuable, they created friction for users who needed to move between systems and limited the organization’s ability to evolve toward a unified, AI-enabled experience. I led discovery to define a single product vision, platform structure, and experience strategy that respected existing strengths while enabling convergence. 

A key focus of the work was designing a unified web platform that merged analytics, forecasting, and scenario modeling into a consistent user experience. This included defining personas, workflows, dashboards, navigation models, and performance requirements for users operating in time-sensitive, data-heavy environments. AI was positioned as a decision acceleration layer, supporting pattern detection, forecasting confidence, and insight prioritization rather than replacing domain expertise. 

The platform was designed to support both internal and external users, including dairy consultants, technical specialists, and customer-facing teams. I shaped how insights were surfaced, how forecasts were interpreted, and how users could move from high-level signals to actionable recommendations. The outcome was a scalable, modular platform definition aligned with long-term roadmap goals, multilingual needs, and future AI-driven enhancements.

Product Challenges Addressed

Unifying multiple mature products into a single coherent platform
Balancing deep domain analytics with usability for non-technical users
Supporting both internal consultants and external customers in one system
Designing for performance, scale, and future AI evolution

Business and Product Value

Improved speed and clarity of decision making for dairy consultants
Reduced friction caused by tool switching and inconsistent workflows
Stronger foundation for AI-driven insights and forecasting
Scalable platform aligned with global rollout and future growth

Illustrative Metrics and Signals

Consultant time spent per analysis
Forecast accuracy and confidence indicators
User adoption across regions and roles
Reduction in cross-tool navigation and manual work
Insight usage and scenario modeling frequency

Technologies and Capabilities

AI-assisted analytics and forecasting
Scenario modeling and predictive insights
Large-scale data visualization
Role-based dashboards and workflows
Scalable enterprise web platform
Cloud-native architecture

AgriTech, Dairy Analytics, Artificial Intelligence, Enterprise Platforms, Forecasting, Decision Support