The story of the correlation between beer and diaper sales is commonly used to justify why analytics is useful in business and to explain product affinities in introductory data mining courses. Rarely does anyone ask about the origin of this story. Is it true? Why is it true? What does “true” mean anyway? The last question is the most interesting because it challenges the ideas of accuracy in data and analytic models. Mark Madsen examines the history of the “beer and diapers” story, explaining its origins and truth, based on repeated analyses of retail data over two decades. Mark will share how multiple contradictory results can come from analytic models and how they can all be true, leading to the questions of the value of “easy-to-use” analytics. The real lesson of the story is that interpretation of the results of analytic models is key, not the data or model. You can’t apply (effectively) what you don’t understand.