Situation
A multinational consumer goods company operating across 13 African markets suffered from siloed data, analyst-dependent reporting bottlenecks, and inaccurate commercial forecasting — limiting strategic agility at both regional and global levels.
Task
Build and scale a modern data lakehouse, enable 150+ business users to self-serve, and deploy predictive models to optimize commission structures and churn behavior across diverse markets.
Architecture & Action
Architected and deployed a Snowflake-based lakehouse. Built Tableau self-service layers aligned to strategic KPIs defined in partnership with market general managers. Developed XGBoost and time-series ML models for commission optimization, churn prediction, and demand forecasting. Embedded pre/post-campaign analytical loops into the sales lifecycle to generate continuous incrementality signals.
Outcomes
150+ self-service BI users enabled, +7pt forecasting accuracy, +13% incremental revenue, and 40% retail sales contribution achieved in Year 1 of omnichannel strategy deployment.