  The data science revolution has highlighted the varying roles that data
analytic products can play in a different industries and applications. There
has been particular interest in using analytic products coupled with
algorithmic prediction models to aid in human decision-making. However,
detailed descriptions of the decision-making process that leads to the design
and development of analytic products are lacking in the statistical literature,
making it difficult to accumulate a body of knowledge where students interested
in the field of data science may look to learn about this process. In this
paper, we present a case study describing the development of an analytic
product for predicting whether patients will show up for scheduled appointments
at a community health clinic. We consider the stakeholders involved and their
interests, along with the real-world analytical and technical trade-offs
involved in developing and deploying the product. Our goal here is to highlight
the decisions made and evaluate them in the context of possible alternatives.
We find that although this case study has some unique characteristics, there
are lessons to be learned that could translate to other settings and
applications.
