HR Analytics

What is HR Analytics?

HR Analytics refers to the use of data to manage and improve HR functions. The common data measured with these analytics include costs incurred on training, the number of employees who engaged & participated in the training programs, and feedback provided by the participants.

Google launched a project called ‘Project Oxygen’ to gauge the importance of HR analytics. The project’s objective was to identify the key behaviors of the best managers. Google collected data from different sources like performance reviews and employee surveys to identify patterns and correlations. Based on these data, ten common key behaviors were identified. This project helped the management modify training programs and the performance evaluation process.

Why HR Analytics is Important?

The objectives of Human Resource Analytics are to give information that can be used in problem-solving, making effective decisions, and improving results. It also measures employee behavior and staff performance levels. People analytics is critical to implement because it gives insight into what is currently being achieved and how it is being achieved.

One of the examples to showcase the importance and objectives of HR analytics is by giving the instance of Nielsen Group. One of Nielsen’s businesses used analytics in HR to understand the high attrition rate in the company. They observed that employees with a change in job responsibilities due to promotion or lateral movement are less likely to leave the organization. It helped the organization’s leadership to provide better career opportunities for employees. They made it easier for employees to pursue jobs internally and build opportunities for at-risk high-performing employees.

What are the main benefits of HR Analytics?

There are many advantages of HR Analytics but the main 6 benefits are:

1. Improved employee trust and work engagement
2. Enhanced workforce productivity
3. Reduced talent turnover and increased retention
4. Optimized and enhanced recruitment process
5. Better workforce planning
6. Refined talent sourcing processes and strategies

What are the HR Analytics Process?

HR analytics process has four broad categories, each offering unique insights. The usage of the workforce analytics process depends on what your needs are and what you have access to. The four processes include:

1. Descriptive Analytics: It focuses on past data but does not discuss future trends.
2. Diagnostic Analytics: It explains the correlation in the data trends.
3. Predictive Analytics: It emphasizes future outcomes.
4. Prescriptive Analytics: It tells the management what to do next.

HR Analytics Trends

Why HR analytics is important, and what are the recent trends in this domain? Let us look at how organizations are taking maximum benefits from HR data analytics. According to Bersin by Deloitte 2017 High Impact People Analytics research, 69% of organizations with 10,000+ employees have a people analytics team.

The recent trends in the HR analytics process are:

• Most organizations depend on descriptive analytics in HR instead of predictive and prescriptive analytics.
• Firms led by analytics are 10x effective at providing insights to leaders. Also, they are 8x more likely to use predictive analytics to make decisions.
• Elements of the HR analytics process are data integration, cleaning, and visualization.
• Some organizations have become good at using workforce analytics processes in the workplace. 29% of organizations claim they are good or very good at making positive changes in the workforce because of HR analytics.

How to Measure HR Analytics?

HR data analytics can be measured with the help of HRMS & surveys, statistical analysis tools, visualization & presentation tools, and specialized tools with AI & ML features. Some of the common tools that can help in analyzing each of these data include:

• HRMS- Payroll data & Employee survey
• Statistical Analysis- SPSS, Excel, R
• Visualization & Presentation- Microsoft PowerPoint, Prezi, Tableau, Keynote
• Specialized Tools- Textio, Visier, Workday Prism Analytics

How Effective is Your HR Analytics Strategy?

The effectiveness of HR data and analytics can be measured in the form of enablers, governance, deliveries, and stakeholder management.

• Enablers: It helps the HR team to gain insights and draw conclusions based on the collected data.
• Governance: It refers to taking care of rules during data collection. It comprises internal and external factors like organizational positioning, reporting structure, delivery channels, and internal team structures.
• Deliveries: It refers to having a clear idea of what results to expect, how they should be presented, and what evidence to include to back them up.
• Stakeholder management: Stakeholder management refers to keeping all stakeholders, like the HR team, top management, analytical teams, and employees on the same page.

Another way to gauge the effectiveness of HR analytics strategy is by measuring the ROI through activity-based and payback costing.

Scope of HR and HR Analytics

The scope of HR data analytics can be extended to the following:

• Hiring- Cost per hire, quality of new hires
• Paying- Cost per available hour
• Developing- Expenses on learning and development
• Engaging- Employee productivity
• Retaining- Turnover rates
• Diversity- Performance evaluation

Frequently Asked Question (FAQs)

Who is responsible for HR Analytics?

The HR managers are responsible for HR analytics/talent analytics in an organization. It comprises a professional team proficient in data analysis, statistics, and HR practices.

What problems does HR Analytics solve?

HR data and analytics can be used to solve problems relating to:

• Employee engagement
• Employee attrition
• Strategic planning
• Hiring process
• Workforce performance analysis

Who needs HR Analytics?

HR managers use HR data analytics to recruit candidates, reduce attrition rates, improve trust and confidence in the workspace, and build a productive workforce.

Is it a skill?

Yes, HR analytics or people analytics is a valuable skill in the HR world. It helps HR managers to make informed decisions. To become proficient in this field, HR professionals require statistical modeling, data analysis, and data visualization knowledge.