7 Benefits of Predictive Retention Modeling (HR analytics)
Instead of using descriptive analysis (tables, reports, ratio’s, metrics, etc), predictive analytics will enable organizations to analyze the past and look forward to spot trends in key factors related to voluntary termination, absences and other sources of risk. Unfortunately, most organizations lack a consistent and holistic view of the work force and the needed HR analytics to perform workforce optimization.
Predictive retention modeling allows organizations to identify high-risk employees, build profiles of those most likely to leave or stay, and understand how risk is distributed throughout the organization. Several innovative large organizations have started building these kind of HR analytics with great success in the past years (e.g. Google, HP,…). Next to the traditional HRIS dashboard with descriptive turnover information, we see more and more companies adding these predictive turnover information to their standard reporting. An overview of the 7 benefits, thanks to SAS for this information:
- Recognize the strengths and vulnerabilities of the workforce and predict vacancies and leadership needs.
- Track and analyze critical skills, and predict which skills will be lost and when by predicting turnover.
- Measure turnover, understand its causes and design programs to control it to reduce vacancy costs – both financial and productivity – to avoid their devastating effects on business performance.
- Assess risk on an organization-wide level by integrating workforce and relevant business and third-party data for comprehensive risk analysis.
- Build weighted risk factors into strategic human capital management plans and reduce risk by understanding workforce supply-and-demand patterns.
- Understand and mitigate risk linked to seasonal absences, resignation trends or length of employment to prevent being blindsided by loss of critical workers, skills or leadership.
- Measure, monitor and predict the effect of risk factors over time and prevent organizational risk by devising contingency plans based on insight and foresight.
Interested in using predictive retention modeling as a key component in your HR analytics strategy? We can provide you with more details. Contact us at [email protected] for more information.
Luk Smeyers, iNostix, May 2013