HR analytics
HR Analytics: A Guide to Data-Driven HR
In this post, we’ll talk about HR analytics and how it helps companies make better, data-driven decisions regarding their employees. We’ll look at what HR analytics is, how it works, why it’s important for aligning HR strategy with business goals, and how it affects employee engagement, turnover, and productivity.
Let’s look at each section in detail:
What Is HR Analytics?
Types of HR analytics
Data analysis methods help discover HR trends and insights, allowing for more effective planning and decision-making. Here’s a summary of the four forms of HR analytics:
- Descriptive HR Analytics: Looks at previous data to figure out what happened. Example: Tracking yearly employee turnover.
- Diagnostic HR Analytics: Analyse data to determine the causes of prior events. Example: Reviewing absence records to identify causes of absenteeism.
- Predictive HR Analytics: Predicts future events or behaviours using present and historical data. Example:Analysing recruitment data to predict the qualities of top candidates.
- Prescriptive HR Analytics: Actions are suggested based on predicted future scenarios. Example: Designing an onboarding plan based on a new hire’s experience and skills.
The Importance of HR Analytics
- Make better data-driven decisions for people and the organisation.
- Identify and address inefficiencies to increase productivity and lower costs.
- Build a strong case for HR initiatives
- Measure the success of HR strategies and policies.
- Analyse and improve DEIB (Diversity, Equity, Inclusion, and Belonging) efforts.
- Prepare for change and manage interruptions effectively.
What is the business impact of HR analytics?
People-related issues can harm a company’s performance if practical tools are not in place to understand what is happening. Here’s how HR analytics may help:
1.Turnover
High employee turnover is costly, with replacement costs ranging from 50% to 200% of a person’s annual income. HR analytics helps uncover the causes of turnover, allowing you to create and measure effective retention measures.
2.Employee Engagement
- 17% higher productivity
- 10% better customer satisfaction
- 20% increase in sales
- 41% reduction in absenteeism
- 9% reduction in turnover
3.Goal Setting
Companies can use HR analytics to define measurable objectives that drive business performance.This entails identifying priority areas, collecting data, analysing it, and working on the results to improve.
4.Developing Top Talent
HR analytics assists in the retention and development of top talent by utilising data from performance reviews to solve engagement issues, identify training needs, and support career growth, thereby motivating high-performing employees to stay and grow within the organisation.
5.Reducing Bias
Compliance with labour laws requires non-discriminatory practices. HR analytics promotes fair hiring and evaluation processes, supporting DEI (Diversity, Equity, and Inclusion) initiatives by reducing bias through data-driven, standardised practices.
6.Building Collaborative Teams
A sense of belonging helps improve team performance and retention. HR analytics promotes collaborative, productive teams by informing hiring, tracking performance, and early spotting team difficulties, resulting in a strong, harmonious work environment.
Incorporating HR analytics allows companies to make data-driven decisions that improve employee experience, engagement, and productivity.
What data does an HR analytics tool need?
Data for an HR analytics solution is typically divided into two categories: internal and external data. A fundamental problem in data collection is ensuring that the data is both relevant and of good quality.
1.Internal Data
- Employee tenure
- Compensation details
- Training records
- Performance appraisals
- Reporting structures
- Information on high-potential employees
- Records of any disciplinary actions
2. External Data
- Financial Data: Financial data from the entire organisation is used to calculate measures such as revenue per employee and hiring costs.
- Organisation-Specific Data: Different data can help improve HR analytics depending on the industry. A global retailer, for example, may use data on store income, costs, and customer experience, whereas a construction company may concentrate on health, safety, and labour cost information.
- Passive Employee Data: Employees supply data on a continuous basis, beginning with their hiring and continuing with sources such as social media posts, surveys, and ongoing feedback.
- Historical Data: Major global events, such as the 2008 crisis, impact workforce behaviour and reveal trends, allowing HR to predict how employees will react to comparable events in the future.
Key HR Analytics Metrics
1.Revenue per Employee
This metric shows how much revenue the company generates for each employee. It helps measure how efficiently the business uses its workforce to drive profits. To calculate it, divide the company’s total revenue by the number of employees.
Example: If a company earns ₹10 crore in revenue and has 100 employees, the revenue per employee is ₹10 lakh.
2.Time to Fill
This measures how long it takes to fill an open job position. It’s calculated by counting the days between when a job is posted and when an offer is accepted. This helps understand how efficient the hiring process is.
Example: If a company posts a job on 1st March and the position is filled by 20th April, the time to fill is 51 days.
3.Voluntary and Involuntary Turnover Rates
These rates track employee exits. Voluntary turnover shows the percentage of employees who choose to leave, while involuntary turnover shows the percentage who are let go. Both metrics indicate how well the company is retaining and managing employees.
Example: If 10 out of 100 employees leave due to being fired, the involuntary turnover rate is 10%.
4.Offer Acceptance Rate
This metric helps measure how successful the company is at convincing candidates to join after making a job offer. A high rate suggests that candidates are interested in the company, while a low rate may indicate a need to improve the hiring process.
Example: If a company extends 20 offers and 10 candidates accept, the offer acceptance rate is 50%.
5.Retention Rate
6.Absence Rate
The absence rate tracks how many days an employee is absent from work, excluding approved leave like vacation. It is important to track in sectors like retail, where absenteeism can affect operations.
Example: If there are 20 workdays in a month and an employee works 14 days, with 3 days off for vacation, the absence rate would be 18%.
We have reached the end of this post. Please post your questions in the comments section below.
FAQS
1. How are HR analytics used?
Ans: HR analytics are used by businesses to understand how well they hire, manage, and retain people. They can discover failures in employee-related procedures throughout the firm and identify solutions to save money on items like hiring.
2. What are a few examples of human resource analytics?
Ans: Most small organisations’ main HR KPIs include revenue per employee, time to hire, voluntary and involuntary turnover rates, offer acceptance rate, retention rate, and absence rate.
