This chapter focuses on the role of scores in supporting an organization's key business decisions. Scores are very important concepts in the world of data science. The purpose of the score technique is to look for groupings of common or similar variables and metrics that can be meshed together to create a score that can guide one's decision making. The beauty of a score is its ability to integrate a wide range of variables and metrics into a single number. The scores are critical components of the thinking like a data scientist process because they can guide the decisions the frontline employees are trying to make and/or predict the likelihood of a customer's actions, outcomes, or behaviors. A common example of a score is the intelligence quotient (IQ). FICO may be the best example of an organization that has built its business around the development of a score.