Want to transform business performance? Tracking these five key metrics is a great place to start.
Despite all the talk about ‘Big Data’, many HR functions still find it difficult to manage ‘Small Data’ and provide their organisations with the operational and strategic data needed. Research by NGA Human Resources found that over three-quarters of CEOs said they would like to receive more data from their HR team. Good data enables new insights – when these insights are acted on, it can lead to improved productivity, lower operating costs and shift the role of HR from a transactional to a strategic business function.
Developing a cohesive management information strategy is the first step towards delivering better insights, yet HR teams often encounter two major challenges when they attempt to improve their use of data.
The research also found that more than a third (34%) of HR departments are spending more than a day each month producing analysis, often more. It’s not that organisations are short of data – organisations accumulate vast quantities of data as a direct result of their internal processes.
The first step is to identify those metrics that will provide the building blocks for meaningful insight. Here are five key areas that organisations should focus on:
Inefficient recruitment processes are not just frustrating for managers who need staff urgently, they can also be hugely expensive. To understand how hiring processes can be improved, HR teams should be monitoring the key recruitment metrics involved. Performance indicators could include the time it takes to fill vacancies as well as the costs involved.
Given the pains of the recruitment process, employers will want to keep attrition rates as low as possible. To evaluate whether the actions to retain staff are making a difference, HR teams should be examining turnover rates. These metrics can be broken down further to analyse whether there is an issue with new hires for example, or if keeping key personnel has become a problem.
When it comes to losing key personnel, you’ll want to ensure you get in front of any potential problems. Satisfaction levels amongst the workforce can prove a good indicator of how likely it is employees could leave the organisation. Looking at how probable it would be for staff to recommend their employer, via a Net Promotor Score, when individuals last had training or whether their last performance review was in-line with other colleagues, are all key metrics to monitor. Predictive analytics based on clever algorithms can now identify potential leavers.
Reviewing revenues generated against staff numbers is a key way to judge the productivity of an organisations’ employees. This can be broken down into organisational departments, and further still by the units within. This will allow managers to evaluate the performance and contribution of their team in the business.
Regulatory requirements, such as gender pay reporting, have increased the importance of maintaining good employee data for analytical purposes. Personal information about the workforce now needs to be tracked against factors such as pay to stay compliant. There have also been calls for this type of reporting to be extended to race, sexuality, religion and disabilities.
Of course, collecting this information isn’t enough. Reporting is step two in the process and this stage requires the data to be up-to-date and easily accessible for analysis. The trouble is this information is often held on disparate systems, with different permission levels and technical expertise required to access the separate data sets.
To make meaningful reporting possible, HR teams need to simplify the challenge and create one single source of truth for their HR data. Bringing all this information together within one system must, therefore, be the goal for all HR teams looking to provide actionable insights that can transform an organisation’s performance.
If you’d like to discover more about ResourceLink or how our people can help you transform your payroll and HR operations, we’d love to talk.Talk to us