Providing the right products at the right time with machine learning

The journey toward successfully deployed machine learning operations (MLOps) starts with data, says global head of machine learning operations and platforms at Kraft Heinz Company, Jorge Balestra. Curating well-organized and accessible data means enterprises can leverage their data volumes to train and develop AI and machine learning models. A strong data strategy lays the foundation for these AI and machine learning tools to use data to detect supply chain disruptions, identify and address cost inefficiencies, and predict demand for products. "Never forget that data is the fuel, and data, it takes effort, it is a journey, it never ends, because that's what is really what I would call what differentiates a lot of successful efforts compared to unsuccessful ones," says Balestra. This is especially crucial but challenging within the CPG sector where data is often incomplete given the inconsistent methods for consumer habit tracking among different retailers.