  Companies may be achieving only a third of the value they could be getting
from data science in industry applications. In this paper, we propose a
methodology for categorizing and answering 'The Big Three' questions (what is
going on, what is causing it, and what actions can I take that will optimize
what I care about) using data science. The applications of data science seem to
be nearly endless in today's modern landscape, with each company jockeying for
position in the new data and insights economy. Yet, data scientists seem to be
solely focused on using classification, regression, and clustering methods to
answer the question 'what is going on'. Answering questions about why things
are happening or how to take optimal actions to improve metrics are relegated
to niche fields of research and generally neglected in industry data science
analysis. We survey technical methods to answer these other important
questions, describe areas in which some of these methods are being applied, and
provide a practical example of how to apply our methodology and selected
methods to a real business use case.
