A global pharmaceutical enterprise transformed its fragmented reporting ecosystem by adopting a PBIP-driven Power BI modernization strategy with MathCo. The initiative introduced version-controlled BI development, standardized KPI definitions, and enterprise governance, reducing report development timelines while enabling trusted, scalable analytics across R&D, commercial, and supply chain functions.
Case Study Topic: Data Analysis
Store-Level Assortment Planning and Simulation
An AI-powered store-level assortment planning solution enabled a leading CPG enterprise to shift from centralized decisions to localized, data-driven SKU strategies. With simulation-led scenario planning, teams optimized shelf allocation and SKU mixes, delivering $71M improvement in net revenue per store, ~2.5% sales growth across top clusters, and 70% faster assortment plan adjustments.
Creating a Single Source of Truth for Delivery Performance with an AI-Driven Health Index
A large enterprise transformed fragmented delivery metrics into a unified, decision-ready view with MathCo’s Delivery Health Index. The solution consolidated critical KPIs, delivered real-time performance visibility, and enabled early risk identification across operations, empowering leaders to shift from reactive monitoring to proactive, data-driven decision-making. Discover how we made delivery health measurable at scale.
Driving Proactive Operations Through AI-Powered Hotspot Analytics
A global technology enterprise modernized its reactive hotspot identification process with MathCo’s unified, ML-powered analytics platform. The solution automated detection, surfaced key drivers, and delivered intuitive insights, reducing customer disruption by 20% and enabling proactive operations. Discover how AI-driven hotspot analytics made it possible.
Enhancing Inventory Visibility Through Smart Inventory Estimation
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.
Automating Data Quality to Power High-Velocity MMM
MathCo transformed MMM for a global pharma leader by eliminating tagging errors, file delays, and manual data fixes through an automated DQ Rule Engine and Watchtower. This end-to-end framework reduced data quality issues by 70%, restored trust in inputs, and enabled fully on-demand MMM cycles for faster, more reliable decision-making.
Accelerating Obsolete Part Matching with an AI-Powered Cognitive Match Engine
Discover how MathCo helped a global manufacturer accelerate obsolete part matching using AI. Through the Cognitive Match Engine, we custom built a data extraction framework, unified fragmented data, achieved near 100% accuracy, and reduced response times from days to seconds, boosting efficiency, revenue, and customer satisfaction.
Optimizing Omnichannel Marketing Strategy with MTA
Discover how a leading global Pharma company transformed its rare disease omnichannel marketing strategy through Multi-Touch Attribution. By leveraging MathCo’s interpretable, data-driven MTA model, the client identified high-impact channels, optimized call strategies, and boosted NBRx outcomes, thus unlocking precision engagement in one of pharma’s most challenging markets.
Reducing Lost Sales Opportunities with Intelligent Product Substitution
A leading CPG giant faced major sales losses due to the absence of intelligent product substitution. Traditional safety-stock rules and manual substitution lists fell short, driving stockouts and revenue loss. Our AI-powered solution helped the client identify the ideal substitute product, influencing $133M through improved order fulfillment rate.
Enabling Scalable & Governed Data Ingestion
A global CPG manufacturer partnered with MathCo to modernize its data ingestion using a metadata-driven framework on Azure Data Factory. The solution standardized data pipelines, automated deployments, and improved governance through Unity Catalog and Azure Purview. It reduced data quality issues by 40%, saved 5,000+ hours in pipeline development, and accelerated data onboarding by 50%, enabling faster, trusted insights across analytics products.