Quality of management information
These findings report on known HR data quality issues, limitations of the indicator set in providing insight into HR service performance, and opportunities for improvement. The Context chapter includes common quality of management information findings across all functions that are not repeated in this chapter.
The quality of the data underlying the metrics is of a high standard, and information can be meaningfully compared. Data quality is high for two reasons:
- HR data is collected and stored centrally by agencies, making high-quality data readily available.
- Measurement agencies were aligned to common definitions and data collection practices.
Payroll costs are not included. In this report, the payroll process is included within the Finance function for comparability with international benchmarks. However, operationally, most agencies consider the payroll process to be part of the HR function.
While results are broadly comparable, results need to be understood within the context of each organisation. While agencies have common features, each has their own functions and cost drivers. For example, some agencies may have higher recruitment costs due to the need for more specialised skills or higher training costs due to greater need for technical knowledge. Agencies should use the benchmarking results as a guide to relative performance, and conclusions regarding efficiency and effectiveness should be made in light of each agency's operational context.
There is an opportunity to strengthen the HR MPI. HR practitioners would like to review this indicator and consider introducing different indicators for the maturity of HR management practice for the next benchmarking report.
