Sonia is a program director for a major health insurance provider. Recently she has been reading in medical
journals and other articles and found a strong emphasis on the influence of weight, gender and cholesterol on
the development of coronary heart disease. The research she’s read confirms time after time that there is a
connection between these three variables, and while there is little that can be done about one’s gender, there
are certainly life choices that can be made to alter one’s cholesterol and weight. She begins brainstorming
ideas for her company to offer weight and cholesterol management programs to individuals who receive
health insurance through her employer. Sonia is concerned with helping those who have suffered heart
attacks. She wants to help them improve lifestyle choices, including management of weight and stress, in
order to improve their chances of not suffering a second heart attack. Sonia is wondering if, with the right
training data, we can predict the chances of her company’s policy holders suffering second heart attacks. She
feels like she could really help some of her policy holders who have suffered heart attacks by offering weight,
cholesterol and stress management classes or support groups. By lowering these key heart attack risk
factors, her employer’s clients will live healthier lives, and her employer’s risk at having to pay costs
associated with treatment of second heart attacks will also go down. Sonia thinks she might even be able to
educate the insured individuals about ways to save money in other aspects of their lives, such as their life
insurance premiums, by being able to demonstrate that they are now a lower risk policy holder.
To Do List:
A. Background: Describe the context and environment of the organization and analyze how the company is
currently leveraging data analysis and analytics tools to make decisions.
B. Data Sources: Evaluate the data sources the organization is currently using for their benefits and limitations
in meeting the goals the data is currently being used for. In other words, is the currently used data appropriate
for its current usage? Why or why not?
C. Data Needs: Analyze the various sources of data available to the organization or the data the organization
could potentially begin collecting that could add business value. In other words, what data (existing or
potential) could provide a benefit to the organization you chose to focus on, and how?
D. Data Analytics Initiative: How can you exploit data analytics to add business value or uncover new
opportunities? Identify the opportunity for a data analysis initiative that could provide additional business
value to the organization, and explain. (You do not necessarily have to solve a
problem or fill a gap within the organization. Instead, you could identify a new initiative that improves or adds
valuable insight or information to the organization for decision making.)