A good welfare policy starts with the right insights. Analysis of Payroll data can lead to important insights on “Human Capital Effectiveness” that not only support HR Management, but also the broader policy of an organization. However, the richest insights come from the combination of Payroll data and other data within the organization, but also and especially from Well-being research data. This combination of data will allow you to move beyond Descriptive HR Analytics (i.e. simply describing efficiency measurements such as turnover rate, degree of absenteeism without trying to explain them) and move towards Predictive HR analytics (i.e. trying to explain e.g. efficiency measurements based on other data within the organisation).
Predictive HR analytics is ideally based on three types of measures, i.e. inefficiency, effectiveness, and outcomes:
Efficiency measurements include HR data such as average number of days to fill in a new position or the costs per hire.
Effectiveness measurements might contain new hire performance ratings, engagement survey results, and exit interview data. In other words, it contains mainly “soft HR data”.
Outcomes measure profitability, productivity, and retention.
With regard to HR Analytics, LISTEN® can guide you with:
- the execution of HR-Analytics on your organisational data
- the implementation of HR-Analytics in an organization (e.g. project-based versus structural, required tools & competences, GDPR);
- the methodology of HR-Analytics: 8 steps from Business demand to Insights to one HR policy