To successfully operationalize machine learning (ML) algorithms, data science teams must be able to continuously update their models so they can improve their predictive performance. The champion/challenger approach is a well-documented method for optimizing models and making adjustments that accounts for changes in the nature and quality of data inputs. Altair’s ML products make it easy to incorporate champion challenger processes into data analytics workflows.