HR Analytics – the game changers
‘Your employees are one of your company’s greatest assets. What they say about your company, how they act in the workplace, and how happy they are in their roles all impact on your brand, your image, your levels of service and ultimately your customers’ satisfaction. Thus the HR department becomes a key driver of you most important assets.’
HR Departments have a wealth of data across the multiple processes it manages
- Applicant stage :- Personal details (Age, Marital status) , Current and past employer details , Areas of experience and work , Salary (Current and past employer), Feedback on screening process (suitable / unsuitable for job applied and why), Vendor / Consultant / Channel information
Common fields captured at each stage include:-
- Employee data :- Details of induction , Place In the organization framework , Job description , Salary , Employee band / level, Compensation structure
- Training data :- Induction , other specialized skill training , Non specialized skill training, Who nominated the employee for training, Assessment from the trainer
- Job Performance / movement :- Periodic rating / assessment, Areas of interest and growth as per employee and manager, Promotions and movements
- Exit:- Reasons for exit , Next Employer
A lot of automation over the last decade sees HR information stored in HR Management Systems (akin to the ERP systems for business data). However, the HR department often works in silos and integration and interpretation of the data across the whole system is a rare practice. IT does not help that HR is virtually never seen as an equal partner in the success of the business and senior management does not review the performance of this department in any but the most operational sense.
Often the profile and attitude of the people in HR in itself lends it incapable of conducting the data integration to predictive analytics cycle by itself. And who ever hears of HR sharing information with internal analytics setup because of ‘confidentiality’ issues. Masking the data etc. are seen as tedious and as no concrete benefit can be promised upfront , is this really worth the effort? So this becomes a chronic cycle of data and not much information.
However, as business success using analytics is gaining credibility , and awareness on data driven decision making is increasing from college students onwards, we see the shift happening in the HR space. People are investing time and energy to get insights into questions like :-
- Employee Acquisition :-
- Who are my most profitable employees in the 3 years / 5 year’s time horizon?
- Which channels give me ‘my kind of employees’ at an optimal cost?
- Employee Engagement:-
- How do I segment my employee base to identify groups with similar requirement?
- Which engagement is most effective to hold the interest of different groups of employees?
- Employee retention :-
- How can I proactively identify profitable employees who are likely to attrite?
- Create a strategy to retain these employees
- Analytical Infrastructure and Process Efficiency :-
- What is the data infrastructure required for my HR analytics process?
- What are the bottlenecks causing maximum dissatisfaction in my process?
The HR analytics space is hot right now, with a dearth of talent and the hunt is on for people who can handle the data so very specific to this domain . SO we can look out for loads of action in this space in the near future !!