UX Awards

The Premier Awards for Exceptional Digital Experience

Turnover Probability Explorer Powered by ADP DataCloud Details

1-At-a-Glance-and-Top-Factors-1

View Case Study


Turnover Probability Explorer powered by ADP Datacloud applies big data to help HR professionals make smarter decisions.



ADP’s Turnover Probability Explorer uses millions of employee records to compile historical HR data, industry benchmarks, and predictive models for HR professionals. These visualizations provide a comprehensive view of who in the user’s company is most likely to leave and why.

By gathering real employee data across thousands of companies and millions of employees, ADP has not only identified predictors that correlate with higher turnover risk, but we’ve also developed benchmarks to allow companies to understand their own turnover relative to the rest of their specific industry. The product team then designed an interface that helps HR professionals view and understand the data and identify areas where they might want to take action. This knowledge empowers HR professionals to make better and more proactive decisions in their organizations.



Why this project is worthy of a UX Award:

Virtually all companies and their HR teams need to manage employee turnover and retention. Competition for talent pushes companies to identify ways to better anticipate the chance of employees leaving. As technology improves and the pool of available data grows, companies like ADP are uniquely poised to provide deeper insights to HR professionals. To meet this need, ADP created the Turnover Probability Explorer within their Human Capital Management solution. Turnover Probability uses millions of real employee records to compile historical HR data, industry benchmarks, and predictive models to provide HR professionals with a comprehensive view of who in their company is most likely to leave and why. ADP’s data science team has identified key predictors that correlate with higher turnover risk and developed benchmarks to allow companies to understand their own turnover relative to their industry. While the data science team refined the predictive models, the product team designed an interface that helps HR professionals identify problem areas. The module tracks high-level insights about turnover risk to monitor jobs across an entire organization. This includes a ranked list of a company’s highest-impact factors, a table of turnover trends for each job within a company, and information about how these trends compare to ADP Benchmarks. The product also includes analysis of each job, highlighting areas with high turnover risk on a map along with data on the contributing factors that have led to high turnover in the past such as a long commute, below-market compensation, lack of promotions, or desire for a career change. Along with these trends, the product includes a card-based layout that shows which and how many high-risk employees are working under each manager along with how many people under that manager have left in the past. The goal of these views is to augment the knowledge that HR professionals have about their teams, providing data to aid in decision-making.



Submitted By: ADP

3.9/5 (10)

See More 2017 Submissions >>