At Colgate, we have hundreds of models deployed at scale to help our scientists create better products, our marketers stay ahead of trends, and our sales teams optimize their portfolios. These business-facing models play a critical role in supporting decisions and uncovering new opportunities. Choosing the right model for the job is a crucial part of gaining business-acceptance and driving real value. Do we need Inference? Prediction? Prediction with Explainability? Inference with Prediction? This talk will go through some real-world case studies at Colgate where we balance parsimony, prediction, and explainability to deliver models that have tangible impact.