People are the heart of any organization. With that in mind, an effective human resources department is the central component of any competitive organization.
Why?
From hiring to onboarding to employee development, HR is a core component of your organization because they are your people-centric department. Optimizing HR's capabilities empowers the people who keep an organization running.
But how do you get peak performance from HR?
Compared to other departments, HR's purview appears to deal with the numbers-averse intangibles of an organization: its people and their relationships. Still, there's plenty of data available to assess key HR metrics you just need to know how to find them.
This article covers the fundamentals of understanding the role of data analytics in HR processes and how to implement it to better prepare for the future.
What are HR analytics?
HR analytics refers to data collection and analysis that assess human capital performance. In other words, it tells you the efficiency of your HR systems alongside key indicators about your workforce.
There are a lot of insights to glean from an organization's workforce. After all, they're the ones driving key metrics like productivity. However, HR analytics seeks to identify the metrics that inform the human assets behind productivity.
HR analytics don't examine employee productivity, per se. Rather, these data-crunching methodologies seek to uncover information about the state of the workforce itself and the forces that affect its performance. In turn, HR utilizes the people-centric data derived from these analytics to reinforce HR initiatives and strategies within an organization.
HR analytics provide insight into your people and their organizational performance; that's the data you need to boost productivity.
The 4 stages of HR analytics
Data collection
HR analytics requires data. The process begins when an organization collects as much data as possible on its workforce and human capital elements. Everything from the total number of employees to employees by department to the time spent with the organization provides helpful insights. The more data collected, the better the results from the final process.
Measurement
With pertinent data, HR professionals have the material to measure their information. Measurements refine the data with analytic tools, compare it to historical data, and create actionable information that is easier to understand and come back to for later analysis.
Analysis
Data analysis is the foundation of HR analytics. Analysts glean key insights, patterns, and trends that affect the organization with synthesized data at the ready.
Application
The most crucial stage is the application, when teams present their findings and build strategies to implement them best. Once HR analytics are applied, teams see results and stand to generate more actionable data with additional predictive analytics.
5 key types of HR analytics for HR managers
HR analytics is a powerful means to boost organizational integrity and workforce performance. However, what do they look for?
Let's examine a few clear HR analytics examples so you know what to expect.
1. Employee churn
Employee retention is a crucial indicator of the state of the workforce; high employee churn means an organization quickly loses employees, contributing to low productivity and costly vacancies. Assessing employee churn with HR analytics helps HR management identify weak points in the organization.
2. Capability
Knowing an organization's potential depends on your knowledge of its capability. Measuring and assessing the capability of your people is a stress test that lets managers know what they can expect. With a better idea about their capability, management is better equipped to lead the organization towards attainable goals.
3. Organizational culture
While epitomizing the intangibility of human capital metrics, organizational culture is very much quantifiable; it's one of the most valuable assessments gleaned from HR analytics. Organizational culture or company culture describes the overall ambiance of a workplace: a tacit system of rules and patterns of behavior. Giving form to an otherwise ambiguous quantity like organizational culture is a massive advantage of HR analytics.
4. Capacity
Capacity measures the operational efficiency of an organization. These analytics assess the latent potential of an organization and aim to improve it. For instance, by delineating the usage of time spent in meetings versus productive hours, management gets a clearer view of how to best structure operations for the best results.
5. Leadership
Organizations depend on the efficacy of their teamwork; teamwork depends on effective leadership. Leadership analytics test the strength of the chain of command. These HR analytics measure communication channels and the leadership abilities linked throughout them. By identifying the virtues in employees who need improvement, organizations empower leadership to steer their reports toward success.
HR analytics vs. people analytics vs. workforce analytics: Are they the same?
HR analytics present a comprehensive group of methodologies to assess the sturdiness of an organization's human capital assets.
Still, that refers to a wide subject matter. Therefore, practices like people analytics or workforce analytics are conflated with HR analytics. While similar, these methodologies differ in the data they collect.
While HR analytics fall into the same category as people analytics and workforce analytics, these methodologies are oriented toward foundational HR functions: employee retention, employee churn, hiring, onboarding, and offboarding.
People analytics commonly known as talent analytics in an HR analytics context focuses on people themselves. These analytics focus on all the people that make up an organization (its employees) and the people who sustain it (its clients and customers).
Alternatively, workforce analytics is a catch-all grouping that assesses the performance of every entity within the workforce, from on-site employees to freelancers, contractors, etc.
Why is HR analytics important? How does it shape organizations?
HR analytics is so important because it provides data on the central-most factors of an effective organization: its people and processes.
Organizations are more than the total of their people, but their people are far and away their most foundational pillar.
Data on employee retention indicates how watertight an organization is: are they churning through employees? Wasting time and money on recruitment? Or are employees happy to stay with an organization in the long term?
HR analytics shape an organization by quantifying the factors that determine organizational success. From consumer reports to on-site talent development processes, collecting and understanding data on consumer behavior helps develop business strategies to impact both consumer and employee experience.
Plus, collected data improves employee performance, maximizing business outcomes in the long term.
Advantages (and challenges of) HR analytics
To give you a closer look at their applications, let's explore the advantages and challenges of implementing HR analytics within an organization.
1. Advantages
Improves decision-making:
Every decision at the management level profoundly impacts an organization and the lives of the people who constitute it. With human resource analytics, HR leaders are equipped with verifiable data to make the right one at every turn.
Bolsters employee retention strategies:
Organizations hemorrhaging talent have less time to be productive; human resource analytics bolster employee retention metrics by providing insights where improvements are most needed.
Increases employee engagement:
Flagging employee engagement leads to decreases in productivity. Through HR analytics that assesses the employee experience, organizations take action to create a more fulfilling work environment.
Supports recruitment and hiring:
Hiring managers must know who to look for to find the right person for an open position. HR analytics identify top candidates, cross-reference them with the defining qualities of the job, and generally assist with the hiring process.
Boosts productivity:
HR analytics target the factors that drive productivity: the people. There are vast applications HR analytics yield for productivity boosts, from employee engagement measurements to task automation programs that make delegation easy.
2. Potential challenges
Lack of qualified staff in statistical and analytical skills:
HR analytics are effective, but they aren't easy without on-site experts in that field. The lack of specialists on your staff is a significant hurdle to seeing results from HR analytics.
Multiple data analysis resources can be counterproductive:
HR analytics pull in a wide range of data from various organizational elements. Conflicting, redundant, or irrelevant methodologies operating simultaneously make an HR analytics program counterproductive.
Limited access to quality data:
Not all data is alike. HR analytics is only as strong as the data that drive them; without quality data, the applications of your analytics will be limited.
Limited access to quality analytical tools:
Just as an effective HR analytics program needs quality data, they also need quality tools to make sense of them. Lack of quality analytical tools hinders the results of your program.
Ethical issues of data collection:
Data collection presents organizations with a wealth of information about their people, processes, and audience. However, collecting these data sometimes invites ethical quandaries; abusing peoples' privacy should never be the cost of effective HR analytics.
HR analytics process: How does it work?
The scope of an HR analytics program is vast, but how does the process work on a step-by-step basis?
Here's a quick overview of each step of the HR analytics process that feeds into the next.
1. Collect relevant data
The analytic process begins with data. Collect relevant, quality HR data on the subjects you want to analyze.
2. Monitor and measure your data
Your HR data must be synthesized before it is properly analyzed. Monitor and measure your data to ensure they are prepared for later analysis.
3. Analyze data
Analysis reveals the actionable insights from the collected data. Properly measured data allow analysts to identify the organizational trends and patterns they need to know.
4. Draw and implement conclusions from analytics
With a fully analyzed dataset, HR professionals draw conclusions for managers and help them implement corrective initiatives; the HR data have been synthesized, analyzed, and prepared for final applications.
What does HR analytics measure? 7 example HR metrics
The ins and outs of HR data analytics are intriguing. But how does their mission translate to real value for organizations?
What do HR analytics measure that's so important for performance management?
Your people, their potential, and their talent; HR analytics measure the folks who make your organization work. Let's explore seven clear examples of how these HR metrics create actionable, valuable information about the state of your people and your organization.
1. Revenue generation per employee
HR analytics give you a close look at the performance output of your workforce on an employee-to-employee basis. Cost analyses like these help talent management develop a workforce planning structure to produce better business outcomes and a better bottom line.
2. Training cost per employee
With a clear idea of the training costs per employee, organizations establish the basis of their investment in their new hires. From there, human resource management adapt training protocols to be more efficient and cost-effective.
3. Employee voluntary turnover rate
The employee turnover rate tells organizations when and where they lose talent. With that information, HR teams prevent employee churn, mitigate burnout, and keep the workforce watertight.
4. Time to recruit new employees
Open positions sometimes hinder productivity. Analyzing the time to hire new employees helps organizations bring people on faster and mitigate the effects vacancies have on productivity.
5. Job acceptance rate
Organizations assess how attractive open positions are to new talent by measuring the job acceptance rate. That information helps HR make job postings more alluring to top talent and fill vacancies faster. Additionally, demographic analyses in acceptance rates help organizations improve their workplace diversity initiatives.
6. Absenteeism
By assessing absenteeism rates, management prepare by scheduling and hiring accordingly.
7. Human capital risk
Measuring human capital risks with predictive HR analytics is a stress test on a workforce's capability and capacity. Organizations learn whether they're properly equipped with sufficient talent and adjust if necessary.
6 steps to start using HR analytics
Below, discover the steps to adopt a data-driven approach and use HR analytics for effective workforce planning and management.
1. Identify your goals
There's plenty to examine with HR analytics. To find where to start, identify the organization's goals to get the most use out of the information the analytics generated.
2. Create a collective mindset
HR analytics make organization-wide assessments. Make sure everyone is on the same page with your goals, and the aims of HR analytics guarantee you're collecting quality data that yield actionable results.
3. Bring in data scientists
With a clear, collective objective for your HR analytics program established, turn to folks best equipped to generate results: data scientists.
4. Start small
Implementing an HR analytics program is overwhelming initially because there's so much to measure. Start small, understand how the process works, then evolve your program from there.
5. Choose an HR analytics solution
A functional HR analytics program allows you to choose solutions: address faltering metrics, bolster weak areas of the workforce, and create a more effective HR department and workforce.
6. Gather data from various sources
With a firm basis of your HR analytics program established, you are able to confidently move forward to new data sources; tactically including new sources adds dimension to your program.
The future of HR analytics
HR analytics generate datasets that were once difficult to crack. Organizations get a deep understanding of their workforce, client base, and human assets that were impossible just a decade ago.
Big data is a powerful tool that transforms how organizations interface with their people.
But HR analytics must be used responsibly. Data collection from HR analytics programs must be grounded by strong ethical conduct. When datasets overlap with people's privacy, you must take every precaution to ensure that privacy is respected.
When carried out responsibly, the data-driven decisions gleaned from HR analytics boost an organization's performance and is one way to establish its trustworthiness with its workforce and its consumer base.
To learn more about HR analytics and how Payscale can help you make your people management more efficient, check out this article on hire forecasting!
