Of all the departments in an organization, the Human Resource (HR) department may have the least popular reputation.
This has two reasons. First of all, the HR department is like a doctor: you’d rather never need one.
Picture your role from the other side – when you ask an employee to come by your office, it’s likely that something bad is about to happen. You may need to reprimand, put on notice, or even fire your colleague. Good news, like getting a promotion, tends to come from an employee’s direct manager. Not HR.
Secondly, many regard HR as soft. Fluffy-duddy. Old-fashioned. A lot of the work in HR is based on ‘gut feeling’. We’re doing things a certain way because we’ve always done it that way. HR doesn’t have a reputation of bringing in the big bucks or playing a numbers game like sales. HR also struggles to quantify and measure its success, as marketing and finance do.
HR data analytics changes all of this. A lot of the challenges we just described can be resolved by becoming more data-driven and savvy about HR and analytics.
Example questions include:
- How high is your annual employee turnover?
- How much of your employee turnover consists of regretted loss?
- Do you know which employees will be the most likely to leave your company within a year?
These questions can only be answered using HR data. Most HR professionals can easily answer the first question. However, answering the second question is harder.
To answer this second question, you would need to combine two different data sources: your Human Resources Information System (HRIS) and your Performance Management System.
To answer the third question, you would need even more HR data and extensively analyze it as well.
As a HR professional, you collect vast amounts of data. Unfortunately, this data often remains unused. Once you start to analyze human resource challenges by using this data, you are engaged in HR data analytics.