The client faced major challenges with inventory estimation and inventory visibility due to inconsistent reporting across retail stores where some updated daily, others weekly or monthly. This led to inaccurate tracking, operational inefficiencies, and increased inventory loss, driving frequent stock-outs, and planning disruptions. Our solution helped them improve stockout detection by ~21% and save $4.2M on infrastructure costs.
Technology: Snowflake
End-to-End Analytics for Sales, Marketing & Brand Performance
A global CPG leader partnered with MathCo to build a Snowflake-based analytics platform, unifying sales, brand, and consumer data. The solution enabled SKU-level insights, cut reporting time from hours to minutes, and provided a 360° view of brand and market performance across regions.
Transforming Manufacturing Efficiency with AI-Powered Scheduling Optimization
Discover how we helped a global beverage company save 24,000+ hours annually and cut waste by 40%. With an AI-powered scheduling platform, we eliminated manual tasks, unified workflows across six sites, and enabled real-time visibility, building a scalable foundation for growth and resilience.
AI-Driven Data Quality Monitoring Solution
A healthcare company used our GenAI engine to streamline data quality monitoring, cutting manual reporting time by 87% and accelerating root cause analysis by 40%. By unifying issue tickets, enriching context, and detecting patterns, the solution enabled real-time insights, proactive remediation, and stronger compliance across critical data systems.
Demand Forecasting for Optimizing Truckloads
Optimize truckload efficiency with data-driven demand forecasting. Discover how our custom solution helped a leading battery distributor achieve a 44% load factor reduction and a projected 7x ROI through advanced analytics, improved load planning, and operational enhancements.
Optimizing NPS with Advanced Biomarker Solutions
MathCo’s advanced biomarker solutions empowered our pharmaceutical client to significantly enhance testing rates and improve diagnostic accuracy across key cancer types like TNBC, mNSCLC, and endometrial cancer. Our data-driven approach optimized patient outcomes and identified high-potential areas for focused efforts.