Ten years ago, data was the new gold. Back then People Analytics was a business advantage, today it’s not an option to neglect it. Explore how to move from plain reporting to HR analysis.
Digital HR Insights CommunityWorking in the space between HR, People analytics and HCM systems I see that there is a need for an increased alignment between these groups. So far, the big star of People Analytics has been Storytelling - who doesn't like a nicely packaged story with some cool visualizations? However, there are more important things - such as a reliable data set to base conclusions on. Of course, there won't be any cake no matter which ingredient we claim to be the most important one when baking, but one of the biggest parts in analytics is to make sure the data is clean. So how do we get there? The road to mining the data gold, is to ensure a close collaboration between process owners, system administration teams and analytics specialists.
Below you can find three examples of how a close collaboration between the functional process owners, the HRIS team and the analytics team can better prepare your HR data for analysis. By bringing all perspectives to the table, we will make sure that the data not only meets the requirements of regulations and policies, but also can give those extra insights. These three examples will show how to strengthen the analytics ability in terms of what, how and why.
When configuring a job structure into an HCM system, you build the structure based on individual jobs, as well as cluster them into groups. This job catalog is then used for building compensation processes and talent management. However, these job groups do not always overlap with what is relevant for business analysis and steer cards. For example, the job structure might collect all bus driver job profiles into one job family, while the business side might be interested in analyzing metrics on all jobs of employees driving red vehicles. Instead of manually hard coding jobs groups to be reported on in your BI tool, make sure they are proactively coded when building the job catalog in your HCM. Thay way, you will be able to slice your metrics into relevant dimensions without adding extra work and administrative debts in additional systems.
A challenge not often thought of from an analytics point of view, is the configuration of business processes. Luckily, not only analysts benefit from a balanced business process - so does HR and End Users as well. A good business process is one that will be completed by its users and can provide insights on how internal processes work in terms of timings. For example, it's possible to analyze recruiting processes based on the dates for different stages in the recruiting process. However, too long processes with too many approvals will not be fully used. Except for creating compliance issues, they also leave us without data to analyze or give us corrupt data when system support teams need to finish the processes themselves to remove blockers.
It's no news that turnover is a huge cost to organizations, therefore it is also among the commonly monitored metrics. Understanding the turnover and who the leavers are is important, but so is also understanding why they are leaving. When setting up an HCM system you usually configure the reason why the employee is leaving. However, that is not always done with analysis in mind. Making sure these reasons can lead to actionable insights will add a huge value. For example, the termination reason “left for another company” does not give any actionable insights into how to be preventing this from happening in the future. Instead, try to use specific reasons such as “left for a higher compensation” or combine the data-point on where they went (another company) with another on why (better compensation).
The above case will not solve all your problems, but it is a concrete example of how small adjustments in the system can give a good leverage on gaining important insights. A centralized HCM system with robust reporting abilities provides a great opportunity for making data driven decisions, so make sure to fill it with reliable and actionable data. A first step in doing so, is to include all parties using the system or the output from it in the design or enhancement discussions.
Me and our team can provide you with the needed support – we may help facilitate the stakeholder discussions, propose concrete examples and provide technical solutions to suit your people analytics needs.
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