The Next Wave in HR: How AI and Data Analytics Are Redefining the Future

Tuesday, 19 March, 2024

HR analytics involves the methodical identification and measurement of factors related to a company’s workforce that influence organisational outcomes, aiming to improve decision-making processes. A comprehensive grasp of how workforce factors influence the enterprise necessitates timely and integrated insights from the company's HR and operational systems.

HR analytics applications can be diverse, from understanding basic patterns to identifying actionable insights.

1. Descriptive Analytics 
   At a descriptive level, HR analytics can generate reports and dashboards to address inquiries about past events and indicate what has happened.
2. Diagnostic Analytics
   In terms of HR analytics, diagnostic analytics can provide a deeper understanding of the causes behind workforce trends and patterns.
3. Predictive Analytics 
   In predictive analytics, statistical techniques, advanced algorithms, and machine learning can be employed to forecast potential future events and their underlying reasons. 
4. Prescriptive Analytics
   Using prescriptive HR analytics, managers can identify the optimal actions to be taken in response to the analysis conducted. 

For instance, analytics can help in efficient talent management through segmentation and profiling techniques to identify employees with particular skill sets, training requirements, diversity considerations, and more, leading firms to align the most suitable resources with available opportunities.

Another use case could be using predictive models to aid in determining the attrition risk score of high-performing individuals across various units. Managers can leverage this information to pinpoint the primary factors contributing to attrition and take proactive measures to mitigate its occurrence.

Advantages of HR Analytics in a Rapidly Changing Environment

Having understood ‘what’ we can achieve with HR analytics, it is important to grasp the ‘why’ behind its use. The diverse range of data analytics applications, as identified above, will help organisations derive unique insights about their most valuable asset—the human resource—thereby facilitating faster, more accurate, and more effective decision-making about their workforce. 

These insights may include retaining top talent, forecasting recruitment needs, enhancing employee productivity and performance, managing employee attrition, and fostering deeper employee engagement, among others. In turn, these insights will assist organisations in gaining clarity, enhancing preparedness, and becoming more agile, ultimately leading to a higher strategic advantage in a VUCA (volatility, uncertainty, complexity, and ambiguity) environment. 
HR analytics not only furnishes organisations with evidence-based insights but also aids in maximising returns on human capital by understanding the intricate relationships between various factors such as staffing needs, competency levels, compensation structures, and attrition drivers. Humans may not fully comprehend these relationships, especially considering their origins from multifaceted and diverse variables. 

HR analytics serves as a data-driven approach to improving employee performance and organisational efficiency through informed decision-making, enabling HR managers to rely on data-driven or evidence-based models rather than solely relying on gut feelings and past experiences. Hence, HR analytics can undoubtedly enhance the credibility of the HR function, establishing it as a pivotal capability.

Challenges in Adopting HR Analytics

Despite the potential growth afforded by HR analytics in practice, numerous challenges hinder its widespread adoption:

1. First, many organisations struggle to effectively use workforce data, which is often limited to basic reporting and descriptive statistics. 
2. The quality of available data may be compromised, with issues such as incompleteness, outdatedness, or lack of diversity hindering the utilisation of advanced analytics. A fundamental issue underlying these challenges is the lack of analytical competency among HR personnel and decision-makers. There remains a significant competency gap in analytics, as many firms lack skilled staff capable of data gathering, conducting advanced analytics, and deriving actionable insights. 
3. Organisations face strategic hurdles in effectively leveraging HR analytics, as some decision-makers continue to justify their choices based on intuition, outdated information, or personal experiences despite heavy investments in data analytics and AI. This reluctance can be attributed to decision-makers' insufficient analytical skills. 
4. Ethical considerations such as data privacy and security, autonomy, transparency, and algorithm biases pose additional obstacles to the effective use of HR analytics. Given the growing societal demand for responsible and ethical  AI and data analytics practices, organisations must develop the capacity to design and implement analytics systems accordingly.

In summary, there are numerous use cases and advantages associated with implementing analytics and AI in workforce management. Nevertheless, there is a pressing need to equip employees and decision-makers with the skills necessary for the advanced, responsible, and ethical use of analytics and AI in human resource management.

Join Our Upcoming Course: AI-driven Human Resource and Talent Management Analytics, delivered in collaboration with University of Cambridge academics

As we explore the vast potential and challenges of HR analytics in the rapidly evolving business world, it becomes increasingly clear that up-to-date skills and knowledge are essential. To bridge this gap, we are thrilled to offer a unique opportunity: "Human Resource Analytics", delivered in collaboration with University of Cambridge academics.

Led by instructors from both the University of Wollongong in Dubai and the University of Cambridge, you will have the chance to earn an IBM Professional Certificate. This course is not just about learning; it's about applying your knowledge to lead HR transformation initiatives, implement data-driven strategies, and advocate for ethical AI practices.

• Course start date: 18 April 2024
• Course venue: Classroom and lab sessions at UOWD, complemented by virtual instruction from the faculty at the University of Cambridge. 
• Course duration: 11 weeks with 4 hours per week  
• Who should enrol: All postgraduate students in Dubai interested in HR Analytics. No background in statistics, programming, or analytics is required.  
• Educational credits: The course is equivalent to 6 credit points/3 credit hours
• Registration: Contact [email protected] before 15 April 2024

Author

Dr Ruwan J Bandara
Assistant Professor, School of Business
University of Wollongong in Dubai