The predictive recruitment analytics have been around for some time now but the growing volumes of data, cheaper and faster computers, cheap storage facilities and above all fast and competitive environment has made organizations turn their attention to it now in a big way. It analyses candidate data from sourcing channels, social media, ATS Tracking Software, and assists recruiters optimize their hiring strategies and improve future talent pool.
The predictive analytics tool reduces the recruitment lifecycle by automating the initial redundant and long-drawn process of attracting talent (posting ads), sourcing and Automated Resume Screening. The reduction in time to hire generates a far higher response rate and helps in better candidate experience.
The predictive analytics is used to qualify the leads and ascertain the effectiveness of the marketing campaigns. This would provide a clear picture of the resource allocation requirement based on the lead’s response.
So many corporate stories of a bad hire are bandied about nowadays. Apart from the monetary loss, productivity lags due to a bad hire rub the wrong way on the remaining employees, resulting in demotivation and lack of commitment towards the company’s goal and vision. Machine learning and AI are changing the way “BIG DATA” is now dealt with, with the single aim of providing a glimpse into the future. Predictive recruitment analytics can reduce attrition rates and bad hire scenario by matching the job description to the candidates’ profile to the “T”, churning out a fit index which showcases how to fit the candidate is on every level.
Learning and Development arm of the HR is also enjoying the benefits of the predictive analytics capabilities of algorithms to customize the training activities in sync with the demand for the latest technologies, making the employees relevant and ready for future projects. This forges a long-lasting customer engagement and maximizes the return on investment.
Predictive analytics has the power to provide insight into the future, based on factual data sets. It optimizes operations and increases value, positioning a company at a vantage point in a competitive landscape. The usual caveat to using the predictive recruitment tools is the manner in which it’s used, as drowning in meaningless data will result in convoluted data sets and patterns.
Importance of HR analytics
Due to the influx of “BIG DATA,” it has become imperative to incorporate data analytics and AI tools into business operations, to make sense of the humongous data overload. For instance, AI-powered predictive analytics capabilities are being utilized in every domain to determine customer responses and their purchasing decisions based on data models created using historical data. HR Analytics provides an opportunity for HR to predict the likely outcome instead of just describing it.
HR analytics metrics
The HR analytics provides metrics on staff performance, turnover, processes, and strategies, based on which the organization can channel their time and money on critical initiatives. Like any other line of business, HR personnel’s have certain KPI’s like time to hire, retention numbers achieved, candidate engagement to name the few, on which they are measured. Advanced analytics enhances the HR personnel likelihood to make an informed and decisive decision based on data sets and patterns derived from real-time information.
Running machine learning algorithms on churn data can unravel churn patterns, which when processed by HR analytics tool provide actionable insights into retention strategies and allows the HR personnel to manage churn proactively.
Resume Screening Tool area such as performance analytics, strategic workforce analytics, and people management analytics. As the name suggests they deal with hiring the right people, training the workforce with skills required in the present and the future and promoting the right people within the organization.
Conclusion
HR analytics has added relevancy in the existence of the HR processes as it uses both people data, compiled by HR systems (payroll) and business systems (performance data) to gain insights into their workforce, HR policies and practices for evidence-based decision making. The only caveat, HR analytics is an ongoing activity which constantly needs finetuning.
