Optimizing CPG Trade Promotions

Situation

A leading food-sector Consumer Packaged Goods (CPG) company struggled to manage trade promotions effectively. Without a clear understanding of sales performance drivers, the company faced difficulty allocating expenditures, designing strategies, and making profitable investments.

Challenge

The company encountered significant hurdles:

• Data fragmentation, with insights siloed across various systems and retailers.
• Ineffective trade promotions, lacking a robust method to identify what worked and why.
• Heuristic decision-making, limiting the ability to align promotional strategies with growth objectives.

Approach

Mu Sigma deployed a comprehensive Strategic Revenue Management (SRM) framework built on advanced analytics and tailored for CPG growth:

• Data Foundation: Created a cloud-based data lake to unify over two million data rows from multiple sources, ensuring seamless integration, analysis, and storage.
• Analytical Foundation: Introduced machine learning models for deep sales driver analysis and optimization tools for promotional planning. The scenario builder allowed stakeholders to simulate various strategies for optimal results.
• Insight Consumption: Rolled out user-friendly tools to visualize and automate insights, offering flexible planning and third-party tool integration to ensure broad utility.

By bridging data silos and embedding analytical rigor, Mu Sigma enabled the company to transition from reactive decisions to proactive revenue growth strategies.

Impact

• $15 million in yearly profit increases, achieved through optimized trade promotions and smarter allocation of resources.
• Improved decision-making, driven by a data-driven, scenario-based planning approach.