As human resource analytics is gaining traction among who’s who of the corporate world and HR managers are gradually shifting towards embracing this change, this tool has been increasingly used to attract and procure talented workforce.

“The biggest payoff in HR analytics comes from monetizing HR functions,” says Paul Seo, global head of HR business intelligence and analytics for Marsh & McLennan.

However, before jumping onto the brand wagon to implement HR analytics, companies need to carefully analyse and critically understand what analytics can do for them. Some of the best practices to evaluate the need for HR data analytics are:

• To implement best HR data analytics you need to have sound infrastructure systems in place that gives you the advantage of scale and speed. Considering there will be huge amounts of data for HR analytics, sound infrastructure gives you the much needed speed to move data faster, synthesize it and push it quicker to meet demands.
• Need for data governance – Since data almost appears to come in from every source available, it is important to imply a governance system in place, such as to make sure that people are using analytics only for purposes intended.
• Analytical capability that will allow people to make the best decisions possible and thus create business value. HR managers need to provide insights to people to help them make the best decisions possible. HR analytics cannot work or function to its optimum if data gathered is not converted to tell intuitive and compelling stories.

To reap maximum advantage and value from HR analytics it has to be carefully integrated into the decision making process. This requires a uniquely tuned approach of using analytics for decision making v/s simply enabling analytics as a part of the HR processes and systems. There is a need for cultural readiness to manage the impact of change and leverage analytics. However, this is one of the major impediments organisations face towards leveraging most out of HR analytics.

See: HR Analytics: Go data crunching and set communication protocol

Integration of HR data analytics with finance holds the key to biggest payoff – monetization of HR functions to gauge and measure investments into hiring and those involved during retiring of an employee. Return on investments sought by HR professionals should include cost of hire, replacement and turnover, or training programs involved etc.

Seo added: “When you quantify everything, you will be evaluated based on not only the improvement itself, but also the degree of improvement. This makes everything very factual; so, less about the relationship and more about the results. That is daunting for many in HR leadership.”

It is required that HR leaders of top organisations see analytics as a value addition to business and not as a means to subtraction. Another emerging trend in HR analytics is use of predictive analytics software tools that help professionals determine the average tenure of an employee with an organisation, their location and helps optimise talent acquisition initiatives.

Analytics helps organisations understand the source from where they find the brightest and best talent to be a part of the team, thus reducing cost of hire and vacancy rate. You can build a pipeline of talent to hire and train as and when a vacancy comes up. HR data analytics is the next game changes in the HR evolution, boosted by technological advancements in the field.

Also read: Predictive HR Metrics: Smart Way to Use Data