These days, many companies struggle with issues such as employee productivity, retention and attrition, recruiting, and risk management. Usually, finding strategic ways to overcome these familiar challenges falls onto Human Resources teams —and HR professionals play an undoubtedly vital role in helping businesses run more efficiently, productively, and profitably.
Still, even the most experienced human resources professionals can use a little help from time to time. Enter HR analytics, a set of tools that's quite literally transforming the way human resources teams interpret data and make important decisions.
Whether you're already working in human resources or are considering a career in this field, you'll want to be aware of what HR data analytics are, how they can be applied in a human resource setting, and some best practices for using big data to make the right decisions.
What Is HR Data Analytics?
HR data analytics (also commonly referred to as people analytics or talent analytics) refers to the processes and tools used to gather, analyze, interpret, and report copious amounts of human resources data within an organization.
With HR data analytics, human resources professionals and other decision-makers can rely on concrete information to help them set HR policies and make other key decisions that impact the health of the company.
In recent years, predictive analytics, data processing, and even machine learning have made it increasingly possible for companies to gather and interpret large amounts of information about their employees, job applicants, productivity levels, and other metrics. Today, rather than relying on human resource professionals to notice trends and potential issues, HR analytics make it possible to see trends as they emerge.
The Importance of Data in HR
What does all this mean for the world of human resources decision-making? Essentially, it means that businesses and HR professionals can make more data-driven decisions rather than relying on their instincts or something they've anecdotally noticed on the job.
At the end of the day, data is crucial in human resources. It is integral to making sound decisions and even implementing policies. By being able to automate some of the data collection, reporting, and interpretation, businesses can make more sound decisions and be able to answer critical questions about their company at any time.
Data Analytics Best Practices for HR
Of course, because data analytics are still relatively new to the human resources field, it is vital to ensure that everybody is on the same page and knows how to get the most out of the application of big data in HR function. With this in mind, here are some key best practices to remember.
For starters, businesses should find the right tools to do the work for them. This means carefully selecting the right data collection and reporting tools so human resources professionals gain the most valuable and useful insights. Remember that no two businesses will get the same thing out of the same tools; this part may require a little trial and error to find that proverbial sweet spot.
Likewise, human resources teams can't expect to get far with their HR data analytics if they don't have leadership on-board and informed. Ensure that management and leadership have bought into the concept of using HR data analytics and are prepared to make the initial investments needed for implementation. Meanwhile, HR teams should also be prepared to accept feedback and make changes to their data analytics approach—especially in the first few months after it has been enacted. Changes will likely need to be made to ensure that the organization is getting the most out of the chosen tools.
Data-Driven Decision Making
It's important for human resources professionals, management, and other key leaders to implement data-based decision making within the organization and make it a requirement. Otherwise, there is really no use in spending the money on HR data analytics software. Everyone within the company with access to the data needs to be on the same page; moving forward, decisions will be made based on data and its interpretations.
Ways to Use Data Analytics and Big Data in HR
With all this in mind, what are some of the ways in which data analytics and big data can be used in human resources? From recruitment and hiring to training and development (and just about everywhere in between), there are very few areas of HR that cannot be improved with the right data analytics tools and algorithms.
Recruitment and Hiring
These days, many businesses are beginning to use data analytics and big data to help with their recruitment and hiring processes. This is especially true in industries suffering from talent shortages or a shrinking talent pool. In these cases, using data analytics to track recruitment and hiring metrics (such as time-to-fill and cost-per-hire) can help HR professionals better understand what needs to be done to improve recruiting and streamline hiring processes.
Training and Development
Data analytics and big data can also be useful for human resources professionals looking to optimize the training and development of current employees. All too often, these HR teams are left wondering whether their training programs are effective with no real way to measure success.
With data analytics and data processing tools, however, it is possible to gain some real insights into how well these programs are working and to identify areas for improvement. From there, teams can even use data to create training materials for employees that are custom-tailored to their unique learning styles and professional development needs.
Attrition and Retention
Turnover and retention are common challenges for human resources professionals across industries. Unfortunately, when turnover is high, pinpointing the source(s) of the problem is not always easy. This is where data analytics can really prove useful by collecting information from departing employees (in the form of exit surveys). From there, that information can be collected, interpreted, and reported to highlight common causes of turnover. This information can then be used to make data-driven decisions to increase retention.
Benefits and Compensation
Human resources professionals also play a vital role in providing and explaining compensation and benefits packages to employees. At the same time, when faced with inflation and other challenges within today's economy, this aspect of an HR professional's job has become more difficult than ever.
Data analytics information can help with compensation and benefits planning. Specifically, this type of data analytics tool can help HR professionals compare salary ranges from similar positions in other businesses, using this data to create more competitive benefits and compensation packages moving forward.
This type of application relies heavily on contextual data. What is contextual data in HR? Specifically, this refers to the use of supplemental information that provides additional and useful data about a given topic.
Employee productivity is a hot topic in the world of HR because businesses are always looking for ways to maximize productivity while avoiding common issues (such as time theft) that can impact the company's bottom line. Data analytics can be beneficial by helping HR teams determine how efficiently talent, time, and resources are being used.
Human resources professionals also play an essential role in risk management and mitigation within an organization. Specifically, this refers to the responsibility of assessing potential risks that are common within the industry or workforce—then looking for ways to mitigate or reduce these risks. In HR, common risks to mitigate may be related to employee behavior, employee management, or even turnover and attrition.
Regardless, data collection and analytics can be instrumental in pinpointing common sources and contributors to risk within the business. From there, HR professionals may be in a better position to create strategies to mitigate these risks.
Finally, data analytics and big data can be useful tools for forecasting in human resources. Typically, these responsibilities involve predicting (or forecasting) a company's changing staffing needs based on metrics such as growth and projected sales.
With so much data coming into play, having a reliable data analytics tool in place can make spotting trends much easier. Likewise, these tools can be used to project future staffing needs, so businesses aren't caught off-guard when they need more help. Instead, the company can seamlessly grow and scale over time with as few growing pains as possible.
Interested in a Career in HR?
Though there will always be a need for skilled and knowledgeable human resources professionals, the reality is that there are more tools available than ever to help streamline processes and give businesses a competitive advantage. The use of data analytics in HR is just one of many examples of how data integration and collection can be used to improve human resources functions.
Interested in pursuing a degree in human resources or a related field? Lindenwood University Online offers a number of in-demand degree options, including a bachelor's in human resource management and a Master of Arts in Human Resource Management. Learn more about these programs by requesting information, or start your online application today.