The importance of data analytics is growing across multiple departments. And this is where the opportunity lies for HR too. HR analytics is a new trend that makes a change in the way teams are built and is widely adopted by those who strive to be more successful in their HR practices.


The problem is that many of those in HR are not very comfortable with analysing data and often make decisions that are based on intuition. In fact, traditional HR's lack the skills and strategies to work with "resources" in a proper way. For them, understanding the importance of HR metrics is vital to make a switch to data-driven HR.

At the same time, HR analytics helps to generate data-driven forecasts and scenarios. HR can thus use the acquired data to create numeric business cases for different candidates. This type of analytics is mostly based on analysing past hiring failures and successes with the final goal of knowing which candidates are the most likely to be productive.

To sum up, while traditional HR practitioners rely mostly on intuition and criteria matching, analytics-based HR's rely heavily on past experiences, statistics, salary ranges and other numeric data that old-school HR's are frightened to take a closer look at.


HR analytics makes it possible for companies to make more informed decisions about their workforce choices and thus enhance their operational efficiency. Thus, the following goals could be achieved:

HR tends to work at various levels of the company and with a wide range of people. It explains why the need for strong analytical skills among HR practitioners has never been stronger. But the challenge is that the utilisation of the required practices cannot be performed through traditional roots. Instead, it can be performed in a few simple ways:


Traditionally, the HR process starts with searching for the specific skills necessary for filling an open position. It is then followed by compensation, plan arrangements and hiring procedures. But the internal analytics is not enough. Broader HR analytics can show you everything that is related to this specific industry. For example, its task will be to analyse how difficult it is to fill the position, who is going to apply for it, who is also offering this position, in which cities this role is also popular, what the salary ranges are, etc. The data acquired are based on real openings rather than just predictions.


Another task of HR analytics is to analyse the behaviours of the candidates. As a rule, they prefer to change their roles when switching between organizations. It requires organizational structure, redesigning and creating new scenarios. With the help of special HR databases, it is possible to analyse massive HR records and plan the scenarios in a form of diagrams that can showcase the most troubleshooting aspects of the HR process and the migration peculiarities.


A workforce planning process shouldn't be performed without analysing all the "What if?" scenarios. How would it affect the budget if the division moves to another city? How would it affect the hiring needs if the business strategy is changed and a company requires a different category of professionals or the ratio of contract employees increases? HR analytics helps to create models that your organization might face and have the solutions ready as soon as it happens.

It's worth repeating again and again that analytics is quickly becoming an inevitable part of HR. Those in HR don't necessarily have to become data scientists to analyse all the relevant information, but they definitely need to switch from data haters to data lovers to be ahead in their hiring practices. HR is currently in need of data-savvy HR specialists with strong analytical skills. This data-driven confidence has already seen luck in assisting workforce planners when identifying strategies for building more productive teams.


Running a modern business is often about bringing the right people together. And this is what HR analytics helps to solve. As a result, the percentage of successful team-building scenarios is much higher in those organizations that implement HR analytics during the hiring processes.

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