Compare your HR Analytics capability with this employee turnover example.

Here is an example of how you could be using data from just one HR metric, employee turnover, at each of the HR Analytics capability levels.

Josh Bersin put forward his 4 level model of HR Analytics maturity in 2012. According to his subsequent reports for Deloitte, in 2014, just 4% of companies were using HR Analytics predictively – i.e. at Level 4. In 2017, this figure was around 9%. For more detail on the levels of HR Analytics maturing, check out our article.

Download a PDF version of the checklist!

Level 1: Operational Reporting

  • Quarterly turnover reports
  • Cost of turnover by department and region
  • Turnover hotspots indicate issues
  • Turnover drop suggests successful recruitment, engagement, etc

Level 2: Advanced Reporting

  • Turnover data in a ‘live’ dashboard
  • Connected with performance and demographic data
  • Clear regrettable and non-regrettable turnover
  • Turnover trends by department, region, or gender

Level 3: Advanced Analytics

  • Integration with psychometric, engagement, and business data
  • Analytics explain and predict turnover
  • Actions customised by department to decrease turnover
  • Evidence-based ROI for retention programs

Level 4: Predictive Analytics

  • Analytics inform recruitment & selection redesign
  • Predictive models identify and map talent risks
  • Anticipation of future turnover trends or hotspots
  • Evidence-based scenario planning for M&A or restructures