HR Data Analytics: A Comprehensive Guide to Driving Business Success

HR analytics measures how well a company’s workforce performs. It relies on real-time data that helps determine how well employees perform, whether the organization can retain the best talent, the overall employee experience, and much more. Instead of relying on assumptions, HR analytics provide accurate numbers to make data-backed decisions. 

In this post, we will learn about HR analytics best practices, the role of data science, advanced techniques to consider, the challenges it faces, and what the future beckons.

HR analytics and reporting best practices

Following HR analytics and reporting best practices can help effectively manage the workforce. Here are some of the most crucial aspects of HR analytics and reporting.

Key metrics and KPIs for HR analytics and reporting

Data-driven decision-making is the need of the hour across all industries, and Human Resources is no exception. Determining and monitoring critical metrics and Key Performance Indicators (KPIs) that align with organizational objectives is crucial. Here are some essential metrics to consider.

Turnover rate: Calculated by finding out the number of employees who left the organization voluntarily or involuntarily and dividing it by the total number of employees employed at that time. Comparing this rate with industry standards can help determine retention efforts.

Time-to-fill: Refers to the average time taken to fill a position in an organization. It indicates how efficient the hiring process in an organization is.

Employee engagement: Surveys and feedback play a massive role in determining employee engagement. Employee Net Promoter or eNPS scores are the most crucial measure of employee engagement. eNPS surveys and pulse surveys are integral parts of employee engagement metrics. inFeedo’s AI-powered Amber offers customized surveys that are based on organizational requirements and feedback received from employees. Amber also detects insights from these surveys that play a crucial role in retaining high-potential employees and attracting industry talent.

Response rate: The response rate is the number of people who completed the survey divided by the number of people in the sample. People science experts recommend 70% for engagement and 50% for pulse surveys.

Mood score: Mood score is determined from a mood survey where employees safely share their feelings and thoughts. This score gauges the workforce's mood to identify anxiety, tension, depression, or fatigue. These factors disrupt productivity and overall employee performance. Amber can 

Cost per hire: In this metric, the total cost of hiring is divided by the number of employees hired. It determines the effectiveness of the organization’s recruitment process.

Performance metrics: Performance review metrics indicate both individual and team performance. It also measures productivity and professional development as determined by your industry.

Tools and technologies for effective data collection, analysis, and visualization

The right tools and technologies can revolutionize your HR dashboard. 

• A powerful and advanced Human Resource Information System (HRIS) like inFeedo’s Amber can boost the productivity of the HR department.
• Analytics platforms like Tableau, Power BI, and Amber. Open-source tools like R and Python enable better data analysis and powerful visualization to facilitate decision-making. Amber’s reporting and analytics is a robust tool that translates data to actionable strategies empowering the HR department.
• Artificial Intelligence (AI) and Machine Learning (ML) can empower HRBPs with data-backed decisions and powerful predictive analysis platforms. Amber is an AI-ML-powered conversational chatbot that uses NLP to ask the right follow-up questions when speaking to employees.

Developing actionable insights from HR Data

Collecting data is an essential aspect of HR analytics. However, the real power of HR data analytics lies in its ability to develop actionable steps that will give actual results.

The first step is to set goals that align with the overall organizational objectives. Next, use analytics to understand patterns like turnover reasons or skill gaps. Now, devise strategies to combat these trends or patterns. For instance, training programs to address skill gaps. Regularly monitor progress and adjust plans to drive positive change within the organization. Finally, track and progress these strategies and adapt them when needed to ensure positive changes across the organization.

Data science in HR: Revolutionizing talent management

The use of data science in HR has modernized talent management. It helps in every stage of the employee lifecycle, as explained below.

Redefining recruitment

Predictive analysis helps in finding the right talent for specific roles. Machine learning algorithms analyze past recruitment data, candidates’ resumes, and interview results to predict the suitable candidates for the job. It streamlines the hiring process to ensure top talent recruitment.

Talent development

Even after the hiring process, data science plays a significant role in improving employee skills and performance. ML and AI help determine their strengths and areas that need work and suggest learning and development programs based on that. It enhances employee performance and helps them develop as the organization grows.

Talent retention

Predictive analysis plays a massive role in retaining top talent. Data points like job satisfaction surveys, performance evaluations, and historical retention patterns, when analyzed, can help organizations find employees at risk of leaving and address the issues to rectify the situation.

Amber is an end-to-end solution for HR tech that provides support from hiring to employee exits. Regular check-ins after onboarding, providing mentorship and support to enhance employee skills, finding employees at risk of leaving through predictive analysis, and continuous listening for all employees make Amber the right platform for all your HR woes.

Advanced HR analytics techniques

Two emerging techniques in the realm of HR analytics are text mining and sentiment analysis. They enhance the process of employee feedback and engagement and also identify employees with mentorship capabilities.

Text mining and sentiment analysis

Sentiment analysis in text mining refers to scouring through unstructured data in employee surveys, comments, feedback, and reviews to gauge subjective information like employee opinions and feelings. This data helps organizations determine areas of concern and strategize accordingly. The data-driven method ensures employee satisfaction and a thriving atmosphere at work. 

Amber’s Sentiment Analysis feature helps HRBPs track employee performance, sentiment, and engagement.

Network analysis

Network analysis is another advanced HR analytics technique. It identifies communication patterns, collaborations, and employee relationships to enable  HR professionals to find critical employees who play a crucial role in knowledge-sharing and mentorship. These employees can be valuable assets for the company, enhancing employee engagement and productivity.

AI action planning using GPT-3

Amber uses the GPT-3 language model to create intelligent and relevant performance and talent management strategies. It helps HRBPs develop excellent actionable plans to enhance overall productivity. 

Implementing HR data analytics: Challenges and considerations

HR data analytics has incredible potential and can boost your entire HR department, but its execution comes with a few challenges.

• Bringing data from different departments and analyzing them can be challenging for HR departments. Moreover, SMBs often do not have the infrastructure to use the analytical programs required to analyze these raw data.
•  Resisting change can be another problem when implementing HR analytics. The common perception is using too much analytics will take the human out of human resources and let the computer do the decision-making. But that is not the case. Tools and techniques empower HR managers and streamline processes to make them faster and more efficient.
•  Data privacy must be topnotch since these data might contain sensitive information regarding employee health, gender orientation, etc. HR has to balance developing insights from the data and safeguarding them simultaneously.

Thankfully, inFeedo’s Amber can be the right solution that solves all these problems. Amber has automated data collection. All data can be found in the HR dashboard. It takes utmost care to protect sensitive data. Finally, it is a tool that can make your HRBPs more productive and efficient in what they do. Amber helps both employees and organizations win.

Future trends in HR data analytics

The future belongs to AI and automation. The earlier organizations can get accustomed to them, the better. AI-driven chatbots like Amber offer personalized employee support, boosting engagement and satisfaction, and its predictive analysis platform can forecast trends. India Infoline faced difficulty connecting with its 19,000+ employees spread across 1,000 locations. Also, they saw a disconnect in their employees regarding business understanding and the constructive feedback shared with them. 

When they implemented Amber, they could easily connect with all their employees. Employees without email IDs could also chat with Amber using FB Workplace. Amber also analyzed data and sent it to HRBPs every day, through which they could identify high-potential employees and their sentiment to take timely actions.

The future of HR analytics is here. Choose Amber today to empower your HR team with a people-science-backed platform that helps you build a thriving workforce.