HR analytics is a tool for making decisions about the current and future workforce. It can unlock potential at every step of the talent management system while supporting an unbiased future.- BY Sharon Ross
HR analytics is poised to evolve significantly, leveraging advancements in technology and data analytics methodologies to provide deeper insights into various aspects of workforce management. HR analytics are becoming more sophisticated in providing insights into workforce trends, employee sentiment, and performance, ultimately informing recruitment, talent management, and succession planning. In contrast, predictive analytics are used to forecast future workforce trends or talent needs and turnover rates.
HR analytics is more than data analysis. It is an analytical tool that supports informed decision-making in workforce management by collecting, analyzing, and interpreting workforce data to identify trends and corrections. With the right organizational strategy in place, it can deliver insights for developing any strategy concerning the workforce. Analytics also offer insights into employee sentiment and enable employee performance assessments.
The HR function has transformed over the last decade with new technologies. The transformation is not complete because technology continues to advance, becoming more sophisticated in its ability to support HR strategy and management. A good example is the IBM workforce planning analytics program, which uses artificial intelligence (AI) to improve decision-making and implement workforce planning strategies. It does much more than produce analytics because AI and machine learning generate insights and predictions based on analytics and “what-if” scenarios.
For example, the IBM program can assist with planning the mix of in-person and remote work scenarios, using costs, HR drivers and constraints, geographic factors, and talent needs. The system can give visibility into HR metrics and KPIs for the current workforce and assist with staffing metrics and talent gaps, optimizing costs, and reducing turnover rates. It can forecast workforce needs and compensation requirements and identify competencies needed in various work scenarios while enabling the ability to enter assumptions. IBM summarizes the benefits of this workforce planning solution in three ways. First, understanding profitability by turning data into actionable insights, secondly anticipating outcomes through AI capabilities and what-if scenarios, and thirdly, unlocking collaboration through planning and automating workflows, which enhances collaboration.
HR analytics moves beyond traditional demographic segmentation to a more nuanced categorization based on skills, performance, and potential. This segmentation allows for targeted talent management strategies tailored to the specific needs of different employee groups. Advanced analytics will enable HR departments to gain deeper insights into employee performance beyond basic metrics such as sales figures or project completion rates. Organizations can better understand what drives high performance and tailor development programs by analyzing factors like collaboration patterns, learning agility, and adaptability. By analyzing historical performance data and identifying key competencies for different roles, HR analytics can facilitate succession planning, ensuring continuity and minimizing disruptions in leadership transitions.
HR Analytics Become a Strategic Partner in
Decision-Making
The Society for Human Resources (SHRM) identifies key areas where HR analytics can significantly impact talent management. One is through intelligent recruitment. HR analytics can assist with evaluating recruitment channels by delivering data analytics that provides insights into business processes.
For example, data analytics can identify the recruitment channels that led to hiring successful employees. Analytics can extract patterns from data buried in HR processes like performance evaluations, recruitment processes, hiring results, employee sentiment, and more. Predictive analytics are rapidly becoming embedded in HR decision-making. SHRM discusses how predictive analytics coupled with big data can enable building algorithms to predict turnover. Specific company data points are fed into the algorithm, and HR analytics can identify the employees most likely to leave and the signs of disengagement. Big data analytics can assess employee performance, identify areas where employees need more support, and assist with targeted training.
As valuable as HR analytics can be, SHRM emphasizes that HR analytics is not just a matter of running algorithms. “Incorporating HR analytics requires an open conversation with employees, recording their feedback, integrating managers in the loop, involving sundry functions, sharing it with everybody, and committing to it. Business leaders must understand that HR analytics is not just a technology that can be integrated with just a few organizational changes. Instead, they need to prepare the manual workforce to embrace it.” The people using HR analytics must trust them before they are helpful.
One benefit of advanced technology is that it can access unstructured data. Natural Language Processing (NLP) techniques are employed to analyze employee sentiment from various sources. This analysis can provide insights into employee satisfaction, engagement levels, and potential areas of discontent within the organization.
The potential of HR analytics to become a major source of information for HR and talent management decision-making is enormous. However, the potential issue of bias remains. Any AI-driven system is only as good as the data used to produce the analytics. There is always the risk of embedded bias in the data. At the same time, HR analytics using valid and complete data can help HR identify bias in every step of the talent management process, especially implicit bias that people are unaware of but is reflected in decision-making and people trends. Managers may act on learned stereotypes and not realize they are using deeply ingrained learning in their leadership.
The Crystal Ball of HR Analytics
The evolution of HR analytics towards greater sophistication will help organizations make more informed decisions about their workforce, leading to improved performance, higher employee satisfaction, and better alignment between business goals and human capital strategies. However, HR analytics trends signal more than the state of employee performance. HR analytics can assess the many factors related to employee engagement by identifying what motivates and engages employees and people in the multi-generational labor force. They can identify the elements of trends that help HR talent managers develop improved strategies and make critical predictions about the type of talent needed. With these advantages and the ability to identify hidden biases, the possibility of creating an equitable workforce can become a reality.