What is HR Analytics: How to Learn and Master this Skill

When it comes to decision-making tasks, some HR purely rely on their intuition, experience, and gut feeling. Sure enough, these factors can sometimes lead to inefficiencies, biases, and missed opportunities. This is where HR analytics comes in to fix the problem. It is the application of data analysis and statistical methods to HR data, such as employee performance, engagement, retention, and turnover. HR analytics can help HR professionals measure the impact of their actions, identify patterns and trends, and optimize their strategies and processes. In this article, we will dive deep into HR analytics, simple steps you can follow to get started, and take a look at HR analytics tools.

3 Key Reasons Why HR Analytics Is Important for Organizations

1. Decisions based on facts

First, it can help your organization make data-driven decisions that are based on evidence rather than intuition or guesswork. How? With HR analytics, you can identify the factors that influence employee turnover, engagement, productivity, and satisfaction. By understanding these factors, you can leverage recruitment analytics to design and implement effective interventions to retain and motivate your talent.

2. Measure the Impact of HR Policies

Second, HR analytics can help measure the impact of HR policies and practices on business outcomes. It can help you evaluate the return on investment (ROI) of learning and development programs, recruitment strategies, performance management systems, and employee benefits.

Ultimately, you’ll be able to quantify the value of HR initiatives, justify your spending, and allocate your company’s resources more efficiently.

3. Anticipating the Trends

The third reason why HR analytics is important is it can help shape the future of work by anticipating and responding to emerging trends and challenges. HR analytics can forecast the demand and supply of skills, assess the readiness and adaptability of the workforce, and optimize the use of technology and automation, which leads to boosted recruitment KPIs.

The foundation of these reasons can come from reliable and detailed HR analytics reports. And since Talent Acquisition is part of HR professionals’ responsibilities, you can get comprehensive HR analytics from a tool like Manatal. Driven by AI, Manatal can provide you with recruitment reports as quickly as a few clicks. You’ll be able to see which part went wrong or went right along the hiring process then forge a stronger strategy for your next campaign.

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Starting HR Analytics in Simple Steps

Step 1: Define Your Objectives

Before diving into HR analytics, your company should first define what specific goals and objectives you want to achieve through the use of HR data. Whether it's improving employee retention, optimizing recruitment processes, or enhancing workforce productivity, having clear objectives will guide your data collection and analysis efforts.

Step 2: Identify Key Metrics

Once you have established your objectives, the next step is to identify the key metrics that will help you measure and track progress toward those goals. This could include metrics such as turnover rate, time-to-fill for job vacancies, employee engagement scores, or training effectiveness.

Step 3: Gather Data

To start with HR analytics, your company will need to gather relevant data from various sources such as HRIS systems, employee surveys, performance evaluations, and recruitment records. Ensure that the data collected is accurate, up-to-date, and consistent to ensure the reliability of your analysis.

Step 4: Analyze Data

Once you have collected the necessary data, the next step is to analyze it to gain valuable insights into your workforce. This may involve using data visualization tools, statistical analysis, and predictive modeling techniques to identify trends, patterns, and correlations within the data.

Step 5: Interpret Findings

After analyzing the data, it's important to interpret the findings in the context of your objectives. Look for actionable insights that can help inform decision-making and drive positive changes within the organization. For example, if the data shows a high turnover rate in a particular department, it may be necessary to investigate the underlying reasons and implement strategies to address this issue.

Step 6: Implement Changes

Based on the insights gained from your HR analytics, your company should then implement changes or initiatives that are informed by the data. This could involve adjusting recruitment strategies, revising training programs, or improving employee engagement initiatives to address identified areas for improvement.

Keep in mind that HR analytics is not a one-time project but a continuous process that requires collaboration, experimentation, and learning. Organizations that embrace HR analytics can benefit from improved decision-making, enhanced performance, and increased agility. It is not only a tool for HR professionals but also a strategic partner for business leaders. This is why HR analytics is important to businesses across industries.

Examples of HR Analytics Tools to Up Your Analytics Skills

There are many HR analytics tools out there. You can get certified with some of those tools to build up your analytics skills. Here are tools worth checking out:

• R: It is a programming language that is widely used for statistical analysis and visualization. It can handle large data sets and has a rich library of packages that enable various types of analyses and visualizations.

• Python: Another programming language that can be used for data analysis. It is easier to learn than R but offers slightly fewer functionalities. It also has a large number of packages that support data analysis.
• Excel: Spreadsheet software that is commonly used for basic data analysis. It can perform calculations, create charts, and apply filters. However, it has limitations in terms of data size, complexity, and automation.

• Power BI: A business intelligence tool that allows users to create interactive dashboards and reports from various data sources. It has a user-friendly interface and supports data visualization, exploration, and sharing.

• Tableau: Another business intelligence tool that specializes in data visualization. It enables users to create stunning charts and graphs from different types of data. It also supports data blending, filtering, and storytelling.

• Visier: A cloud-based HR analytics platform that integrates data from multiple sources and provides ready-made dashboards and reports on various HR topics such as workforce planning, talent acquisition, diversity and inclusion, employee engagement, retention, performance, learning, compensation, etc.

• Crunchr: A cloud-based HR analytics platform that consolidates data from different HR systems into one place. It offers pre-built dashboards as well as customizable ones on various HR topics such as workforce planning, talent management, employee experience, etc.

• Qualtrics: A survey software that helps organizations collect feedback from employees on various aspects such as engagement, satisfaction, well-being, culture, etc. It also provides analytics tools to analyze the survey results and generate insights.

The Importance of HR Analytics Application in the Workplace

HR analytics can be applied to various areas in the workplace to improve HR processes and outcomes. Some of these areas are:

• Hiring: HR analytics can help organizations hire the right talent by using competency acquisition analytics, recruitment channel analytics, and classification analysis. These methods can help identify the skills and attributes that are required for different roles, evaluate the effectiveness of different sources of candidates, and predict the success rate of teams based on their composition.
• Attrition: HR analytics can also help reduce employee turnover by using attrition analysis. This method can help identify the factors that influence employee retention, such as job satisfaction, engagement, performance, compensation, etc. It can also help segment employees into different risk groups and design targeted interventions to retain them.
• Training: With HR analytics, organizations can personalize training programs for employees by using learning analytics. This method can help assess the learning needs and preferences of employees, customize the content and delivery of training courses, and measure the impact of training on employee performance and behavior
• Capacity: Companies can optimize their workforce capacity and utilization by using capacity analytics. They will be able to forecast the demand and supply of labor, allocate resources based on skills and availability, and monitor the utilization and productivity of employees
• Performance: By using performance analytics, organizations can improve employee performance. This can also help set and track performance goals, provide feedback and coaching, and reward and recognize employees based on their achievements
• Anomaly: HR analytics can help businesses detect and prevent anomalies in HR data by using anomaly detection analysis. They can identify outliers, errors, frauds, or irregularities in HR data that may indicate potential problems or risks

Real-Life Examples

There are many real-life examples of successful HR analytics implementations that have delivered business value. Here are some of them:

• Credit Suisse: The global investment bank and financial services firm used an algorithm to predict who might quit the company and why. They also trained special managers to retain high-performing employees who had a high flight risk. This program saved Credit Suisse approximately $70 million a year. [1]
• Best Buy: The famous electronic goods retailer relied on HR analytics to relate employee engagement with store income. They found that a 0.1% increase in engagement resulted in over $100,000 in annual operating income per store. This motivated Best Buy to make employee engagement surveys quarterly rather than annually. [2]
• Experian: The multinational data analytics and credit reporting agency used HR analytics to get ahead of employee attrition. They used a combination of internal and external data to segment employees into different risk groups and design targeted retention strategies. They also created a dashboard to monitor attrition trends and drivers.
• E.ON: The international energy company tackled employee absence with HR analytics. They analyzed the patterns and causes of absence and identified the factors that influenced it, such as workload, stress, health, etc. They also created a predictive model to identify employees who were at risk of long-term absence and intervene early. [3]

Conclusion

HR analytics is a powerful tool that can help organizations improve their HR processes and outcomes. By collecting and analyzing data related to the people in an organization, HR analytics can help make data-driven decisions, measure the impact of HR initiatives, and shape the future of work. These are just some of the key reasons why HR analytics is important. There are many examples of successful HR analytics implementations that have delivered business value in various areas such as hiring, attrition, training, capacity, performance, and anomaly detection.

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Citations:

1. WSJ

2. hbr.org

3. techfunnel