Making sense of vast amounts of data is overwhelming, yet critical. But instead of starting with data, Schug and his team begin with the problem they need to solve. For example, they may need to analyze consumer demand over next year or how they can improve service to customers.
Then, his team considers the data needed by asking a host of questions. What data is already in hand, and what is its structure, frequency and granularity? They should consider whether it is internal, external or even possible to find. How can they gather it, store it and refresh it? And importantly, how can they use it to create a competitive advantage at the grocery store shelf?
This method has led to entirely new ways of approaching problems. It has also uncovered a big opportunity in unstructured data, especially in consumer sentiment to help predict what consumers may be looking for next. The team uses Artificial Intelligence (AI) and machine learning to analyze their data and generate the best set of insights for informed decisions.