AFS Launches Artificial Intelligence/ Machine Learning Center of Excellence

Artificial intelligence is fueling significant shifts in today’s competitive landscape, already having become the engine driving many of the world’s most successful businesses. AI and specifically Machine Learning are now necessary components to establishing strategic business targets and making sound business decisions in order to achieve those objectives.

The AI/Machine Learning Center of Excellence is (COE) focused on solving problems prevalent in CPG in general and specifically in food manufacturing, food distribution, and food retailing. Designed to deliver AI capabilities that enable both existing as well as potential new business models and capabilities, Dan Zywicki leads the COE, supported by Michael Scott who leads our G2 analytics team. Zywicki and his team launched an ML-based capability for Promotion Lift Analytics over a year ago and within that timeframe have been able to evolve the algorithm so that it regularly beats the accuracy of the predictions generated by all previous generations of technology.

Companies are making significant financial investments in AI, and the necessary skills and experience need to be brought to bear in terms of true partnerships to capitalize on the market opportunity. Just as e-commerce led to market ecosystems and partnerships centered on Big Data, we believe that our AI/ML focused capability will empower our current and future customers based on market-leading solutions available today, along with the ability to collaborate on leveraging the COE to innovate on new capabilities as the technology continues to evolve.

Many AI technologies are already in use across the marketplace. Machine Learning, for example, is born from statistical regression. The fact that at AFS we already had a market leading analytics group in place gave us a significant head start on our COE. Our ML-based predictive analytics work becomes a direct extension of our traditional analytical prediction solutions. In fact, we can take your data sets and run them through both our traditional prediction models as well as the ML-based models and actually walk you through the differences in how they predict the outcomes of your business decisions… pretty cool stuff. You will also gain an appreciation for the importance of your data sets and their role in establishing both the ML models as well as the training of the models to improve their performance over time.

Given that Machine Learning, as applied to business decision making/prediction, is a relatively new field of analytics, it will be important for any customers to establish internal support for the initiatives as well as champions for the technology across business lines. In a 2018 Deloitte survey, 45 percent of companies had already appointed senior executives across their companies as AI champions.

Current capabilities that are either available today or in the development/release process include Market Optimizer, Promotion Lift Prediction, Sales Opportunity Detection and Creation, Revenue Performance, Shelf Trend Prediction, Suggested/Predictive Orders, 360 Revenue Insights, Churn Reduction, Store Visit Plan Creation/Execution, Contract Automation, Settlement Automation, Voice Enabled Analytics, Voice Enabled Ordering, Virtual Delivery Assistant, and Predictive Inventory Purchasing.