• 03 Mar, 2025

Engine Data Science Wins Innovation of the Year Award at CMA 2025

Engine Data Science Wins Innovation of the Year Award at CMA 2025

ROGERS, Ark., March 3, 2025 -- Engine is excited to announce that our SVP of Data Science, Daniel Palmer, has been honored with the Innovation of the Year award by the Category Management Association (CMA) at their annual conference, held this year in San Antonio. This prestigious award recognizes groundbreaking strategies and technologies that significantly enhance category performance, resulting in a positive impact on sales growth and profitability.

Engine's team of data scientists have developed cutting-edge AI-powered solutions that enable CPGs and retailers to turn complex data into actionable insights. The team's work includes a suite of advanced tools that leverage demand signals to deliver tailored, prescriptive recommendations, helping brands and retailers optimize strategies and meet the specific needs of each category. 

"At The Association of Retail and Consumer Professionals (ARC), we take our role as industry thought leaders seriously," said Chris Conroy, VP of Content and Member Engagement at CMA, "We relentlessly pursue solutions that significantly improve our members' lives, helping them achieve their business and career goals more easily. Daniel's work, leveraging AI-powered insights to enable faster, more confident decisions and improved category performance, perfectly aligns with our mission. We are proud to recognize Daniel with ARC's Innovation of the Year Award for his outstanding contributions that advance our industry and make our members' lives better." 

Delivering Results at Unprecedented Speed 

Engine's AI-driven data science solutions have already made a tangible impact across the industry. A category team used Engine's recommendation engine to optimize the billion-dollar beer category at a major retailer, driving a projected 2.5% annual nationwide sales lift. Now that's a lot of beer! 

At its core, the AI-powered recommendation engine follows an iterative three-step process—generating initial recommendations based on merchant direction, refining them through AI-identified demand signals, and instantly recalibrating as users adjust parameters. This collaborative and iterative approach reduces what was once was a months-long process into just minutes, enabling teams to make faster, more precise decisions whilst ensuring compliance with category and retailer strategies. 

The Future of AI in Category Management 

Engine's latest data science solution, the Auto Insights Engine, acts as an "always on AI-analyst for CPG & Retail"—bringing proactive intelligence and efficiency to category management by analyzing data 24/7. 

  • Proactive Monitoring: Continuously monitors client data to proactively identify sales trends and opportunities.

  • Comprehensive Data Analysis: Analyzes real-time POS, inventory, and syndicated data across every point of distribution.

  • Root Cause Identification: Uses a sophisticated decision tree to uncover potential causes of sales fluctuations, from pricing and inventory changes to assortment shifts and external market factors.

  • Actionable Intel Brief: Receive a clear action list alerting you to critical changes in trends, root causes and potential impacts.

About Engine 

Engine is the leading omni-analytics and data science firm enabling CPGs and retailers to transform their data into actionable insights for smarter decisions that drive sales and optimize operations. 

Seamlessly connecting real-time POS, inventory and syndicated data from top retailers and distributors, Engine gives its clients unparalleled access to their data through customizable reports and an interactive data platform. 

With Engine's AI-powered data science solutions—including Planogram Automation, Auto Insights Engine, and Engine AI Assistant—teams can swiftly identify emerging challenges, unlock hidden opportunities, and implement data-driven assortment and shelf strategies that align with shifting consumer preferences and market trends. 

For more information, please contact

Josephine Hardy

josephine.hardy@engine.net

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