Jennifer Sokolowsky

Infosys created a transformative solution to help a leading global food and beverage company determine competitor product recipes, a key part of competitive intelligence. Traditionally, the customer relied on food labs to determine the makeup of competitor products, an expensive and time-consuming process. Using Azure ML, Infosys developed ML models that automatically reverse-engineer product formulations using publicly available information, such as nutrition data and labels.

Demand disruption has been a huge challenge for consumer packaged goods (CPG) supply chain management in 2020, and it will continue to be a big issue going forward. As we discussed in an earlier blog post, one part of solving supply-chain demand disruption is to improve planning. Sophisticated forecasts and demand sensing, powered by machine learning (ML), are key for making planning more accurate and efficient. Order allocation, which is critical for optimizing operations and maximizing revenue, is even more important for responding to demand volatility.