Your HR Analytics Maturity: How to Take it to the Next Level

What Level of HR Analytics Capability Are You?

The Data

Josh Bersin put forward his 4 level model of HR Analytics maturity in 2012. In 2014, just 4% of companies were using HR Analytics predictively – i.e. at Level 4.

The Four Levels of HR Analytics Maturity

When our team talks about HR analytics, we mean using data to make evidenced-based predictions and decisions. However, organisations vary widely in their approach to HR analytics and the depth at which they use their people data. Four levels of HR analytics ‘maturity’ are usually differentiated based on the model by Josh Bersin:

1. Operational reporting: is usually descriptive reporting reflecting the current situation on a range of HR measures. Usually considered a must-have for HR ‘hygiene’; people take it for granted and you won’t get much credit for it. But the opposite is not true – if this basic HR reporting is messy or not available then this has an adverse effect on HR’s credibility. Operational reporting usually uses HR data only and typical examples include: FTE, employee turnover, salary, training and recruitment costs etc. This is current information at best and usually historical reporting. It is of relatively low value to the organisation overall and is ideally fully automated and highly efficient to produce.
2. Advanced reporting: is more detailed descriptive reporting that often uses the same data as operational reporting but with the addition of tracking trends or the progress towards goals. This reporting usually still reflects only the current or historical situation for various HR measures of interest. It might provide insights useful for benchmarking and decision-making and be delivered in static or interactive digital dashboards. This is also ‘must-have’ reporting for most organisations, so, again, it’s important that the data is prepared efficiently and displayed.
   
3. Advanced analytics: is when data starts to be used to solve problems and make complex decisions. Using the data from levels 1 and 2 plus more besides, statistical analysis can identify patterns, trends, successes, and failures that can inform solutions to business problems. HR analytics at this maturity level adds tangible value to the organisation by proactively identifying HR issues and suggesting evidence-based solutions.
4. Predictive analytics: uses data from the lower levels in predictive models and machine learning algorithms to simulate different scenarios and find optimal solutions. Multiple data sources from HR and the business are used at this maturity level and the aim of predictive HR is to anticipate and satisfy strategic business needs with data-driven decisions. Leaders can be more fully informed about the range of possible scenarios and potential risks when planning for their business and their workforce.

Predictive analytics is more within reach than many HR Managers think. To progress to the next level of maturity, you’ll likely need to: integrate and organise your data differently, add to your tools and capabilities, and engage with the business in new and richer ways. We can help you deliver results at each level of maturity and provide you with structures, tools, and skills to move to the next level sooner.