Here’s how the HR function can be transformed with Data Analytics
Data analytics can be an effective tool to understand employees and their engagement levels in a better way. It has the power and potential to transform the length and breadth of the HR function. It can help reduce hiring bias, find drivers of performance, improve employee relationships and help manage attrition.
A wealth of data is captured through HR processes. Right from initial contact, to long after employees move out of active engagement, the collected data can provide useful insights. And it can turn into a goldmine when supplemented with the right external sources.
Here’s 3 suggestions for a smarter HR Function:
- Get creative with your data sources
A common complaint in organizations is lack of data or curated sources. This is often the reason behind slow progress in making HR more data-driven with people quoting that the entire function is driven by excel sheets. Or how it’s difficult to pull together a single employee view, despite being in the age of digitization.
In every such situation, solutions come out if one gets creative. ORG systems generate numerous data trails. Data from biometrics, CCTV feeds, intranet logs or sensor-enabled smart offices can be harvested without treading on privacy or ethics.
- Make the most of the full Data Science toolbox
When you mention Analytics, you invariably start with AI-driven algorithms. Predicting behaviour comes even before understanding what employees want. Even in the analytics toolbox, there is a parallel to the concept of fortune at the bottom of the pyramid.
It is important to start simple and discover ‘what happened’ and ‘why it happened’ for maximum business impact. One can then analyse what will happen in the future or how it can be influenced. There’s value in employing the full analytics spectrum, bottom-up.
- It’s all about the approach, tools don’t really matter
While starting analytics initiatives, don’t directly dash on to deciding the right tool. The tool is not going to dictate the extent of magic that can be created. The good news is that you don’t need huge investments or fancy tools. The bad news is that the real value of analytics is determined by the quality of approach. So it’s far more people-dependent as well as subjective. Getting the method right can be an enabler, but it also depends on the quality of your team.
The value from HR analytics is all about the solution approach just like any application of Data Science. The algorithms need as much framework as computing power. For example, if you want to build a model to predict employee attrition, you should start with all available factors. Then carefully crop the list by investigating the relevance and relationships.