Human Resources Analytics

What is human resources analytics?

Human Resources Analytics (HRA) is the process of using data and analytical techniques to inform and improve HR decision-making. It involves collecting, analyzing and interpreting data from various HR-related sources such as employee surveys, performance evaluations, and turnover data. The goal of HRA is to provide insights that can help organizations make informed decisions about their workforce and improve overall HR performance. This can include identifying trends in employee engagement and satisfaction, forecasting workforce needs, and measuring the effectiveness of HR programs and policies. HRA can also be used to support recruitment and selection, performance management, and employee retention efforts.

Why is it important for organizations to utilize HR analytics?

There are several reasons why organizations should utilize HR analytics:

• HR analytics uses data collected by HR software to inform decision-making in various HR aspects
• It provides insights into the return on investments in different HR factors
• Helps strengthen an organization’s decision-making and improve outcomes.
• By automating data collection and analysis, HR analytics can help HR professionals save time and focus on more strategic tasks.
• HR analytics can help organizations stay compliant with employment laws and regulations by providing data-driven insights into areas such as discrimination, fair pay, and diversity.

What are the common measures of HR analytics?

There are several common measures of HR analytics that organizations use to track and evaluate their human resource performance. Some of the most common include: HBR’s people analytics research

1. Turnover rate: This measures the rate at which employees are leaving the organization. High turnover can indicate a lack of employee engagement or a poor work environment.
2. Time-to-fill: This measures the time it takes to fill an open position. A long time-to-fill can indicate a lack of qualified candidates or an ineffective recruitment process.
3. Absenteeism: This measures the number of days employees are absent from work. High absenteeism can indicate a lack of employee engagement or poor working conditions.
4. Recruitment cost per hire: This measures the cost of recruiting and hiring a new employee. High recruitment costs can indicate an inefficient recruitment process.
5. Employee engagement: This measures how engaged employees are with their work and the organization. High engagement can indicate a positive work environment and motivated workforce.
6. Diversity & Inclusion: This measures how well an organization is doing in terms of fostering an inclusive and diverse workplace.
7. Return on investment (ROI) of Training: This measures the return on investment of employee training programs, which helps in identifying the most effective training methods.
8. Employee Net Promoter Score (eNPS): This measures the employee’s likelihood to recommend their workplace to others.

These are some examples of common HR metrics that organizations use to evaluate the performance of their human resource management. Depending on the organization’s specific goals and objectives, other metrics may also be used. SHRM’s HR analytics guidance.

Drawbacks of people analytics

Alongside its benefits, HR analytics comes with real limitations worth planning around:

1. Data privacy concerns: Collecting and analyzing large amounts of employee data raises legitimate privacy concerns that must be managed with clear policies and consent.
2. Limited data quality: Analytics is only as good as the underlying data, poor-quality or incomplete data leads to inaccurate or misleading insights.
3. Limited scope: Analytics typically focuses on quantitative data and may not capture important qualitative factors like employee experience, culture, and behavior.
4. Limited insights: Analytics can only answer questions the available data supports, so it may not address every question an organization has.
5. Limited skills and resources: Effective people analytics requires specialized skills and resources, data scientists, analysts, and technology, that not every organization has in-house.

HR analytics transforms workforce data into the insights that power better hiring decisions and stronger talent retention. Organizations using pre-employment assessments ensure every hire is grounded in verified skills. A data-driven hiring plan reduces mis-hire risk, while strong talent acquisition practices focused on skills-based hiring help organizations attract and retain top talent.

Frequently asked questions