The HR Crystal Ball is here!
For long, HR has been dogged by data which is not really useful. While there is a huge of amount of data collected across systems and people, they are mainly hoarded in silos. With multitude of opportunities offered by predictive analytics, HR could not only use it for fact-based decision making but also in enhancing its operational efficiency. The ultimate beneficiary is the organization, at large.
Traditionally, HR has been using excel spread sheets and dashboards to mine data. This is really the issue – the lack of relational, contextual analysis reduced the depth of analysis derived from rich data. Advanced analytics algorithms with predictive capabilities empower decision makers with real-time data and actionable insights that accelerates business decision making and the accuracy therein.
Flight risk: Today, most organizations are grappling with ever increasing attrition rates. They spend millions of dollars in retaining existing staff and hiring new staff for vacant positions. This can be greatly minimized by predicting attrition risk of staff and taking appropriate steps to avoid it. By co-relating reasons for attrition to employee engagement, performance and other data, HR could predict the likelihood of the staff leaving the organization. This is especially helpful in case of critical and high potential staff.
Demand Forecasting: Demand forecasting whether it is for manufacturing, sales or HR, it would reduce revenue loss by a significant margin – a key business health metric. A robust demand forecasting model encompassing business plans, pipeline, resource pool, productivity, attrition would improve resource management, optimization and utilization.
Change Management: By using sentiment analysis tools, HR could determine the impact of any major change, business or organizational, on employee behavior and performance. HR Leaders could compute the sentiment using NLP, machine and deep learning methods to extract, identify and characterize the sentiment of staff against a particular change or as a regular exercise either to enhance the existing tempo where positive and taking corrective measures where it is negative.
Lifetime value: Businesses, today, are fully convinced that employees are organization assets, their competitive advantage. However, how many actually measure the value generated by each employee? Hardly! Some do in terms of revenue per employee but it is an averaged out number and not specific to each employee. Here, employee lifetime value comes into play. It is really the long-term financial contribution of an employee, the dollar value directly attributable to an employee’s performance. Though some contributions are difficult to measure, the model would calculate lifetime value based on past performance, employee related investments, monetizing value derived. This way, organizations could use ELTV determine future investments based on past performance, time investments, maximize performance and use at as a measure of performance as well. When utilized appropriately, it has been seen that cost of investment per employee comes down as employees are more engaged.
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