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 four pages. It uses Power BI’s built-in AI features and visuals to augment the dataset, leading to faster, more actionable insight. It has buttons throughout that link to bookmarks (configured page views) and aid navigation. The different pages and features work together to showcase the multiple factors that impact employee retention or flight, and lead users to act.
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 next two pages use the Key Influencers visual to leverage some of Power BI’s AI capabilities, revealing which factors are impacting flight risk and employee retention most. To learn more about the Key Influencers visual, check out this blog post.
Using the knowledge gained from the previous pages to guide them, the final page of the report lets users facilitate their own analysis to attain more detailed insights around flight risk for specific populations. The table on this page breaks the entire employee population down by facility and job detail, of course responding to users’ slicer and filter selections. The charts along the right side of the final page display flight risk distribution for three specific employee populations compared to the overall population. The original distribution for all employees is shown by the dotted line and shaded area, while the distribution for the specific selection is show by the bars. For example, in the topmost chart, Insights revealed that for employees who had not had a performance review recently, the difference in distribution between high and low risk is much smaller. This leads a manager to conclude that conducting regular performance reviews might result in more employees falling into the low-risk category, thus aiding in employee retention.
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Click around and explore the above report! What insights can you discover?