The above report displays the results of a real-world, predictive analytics and machine learning scenario within a healthcare organization. Its audience is the HR department and upper level management. These two groups will use this report to understand employee flight risk data and to uncover patterns at both a high level and a detailed, employee population level. In this model, high risk employees are considered likely to leave the organization.
This report consists of two visible pages and two hidden, drillthrough pages. It also has buttons throughout that link to bookmarks (configured page views) and aid navigation. The different pages and features give this report an application-like feel and work together to lead users to actionable insights.
The first page of the report introduces the user to the data and facilitates discovery at a high level. The user can click the buttons on this page to see configured views of the page for each flight risk, and as always, the visualizations on the page interact with each other when clicked.
The second page of the report lets users explore data further and gain an understanding of what employee populations are at risk of leaving and why. On this page, users can view data either as a scatter chart or a table by clicking the buttons in the bottom right corner. This page also has a multitude of slicers users can pick from as they conduct analysis. As users change slicer selections, the visualizations illustrate correlations between factors that play a role in employee retention and flight risk levels.
The two drillthrough pages allow users to explore either a certain job category or facility more closely. To get to either of these pages, users must right click on a visualization where either of those fields are used and select “Drillthrough”.Click around and explore the above report! What insights can you discover?