All About HR Data: What It Is, Sources, and How To Collect It
HR data helps you better understand your people, programs, and potential as an organization. Learn about HR data sources and connectors here.
Business success is the sum of many factors. One of the most important ones is your employees. But to truly leverage their power, you must have all the facts. Or in this case, the HR data. Also known as human resource data, this information will help you understand your workforce, market trends, and more. Here’s everything you need to know about it.
What is HR data?
HR data, or human resource data, refers to information and metrics collected by the HR department of an organization. It encompasses data related to your employees, candidates, and other aspects of managing personnel.
HR data is an essential element of HR and people analytics. It helps you make informed decisions about recruitment, compensation, succession planning, and more. You can also use it to understand workforce trends like voluntary turnover or engagement.
Examples of HR data include:
Basic personal information like names and addresses
Leave and attendance
Training and development.
What is HR data management?
HR data management refers to the process of collecting, organizing, storing, and securing HR data. Its main goal is to make data accessible and ensure its accuracy and compliance with laws and regulations.
Data collection is the first step when working with data of any kind. At this stage, HR professionals will need to make sure they’re using a wide variety of sources and that they’re gathering all the necessary data for their goals.
Ensuring data accuracy is the next critical step in HR data management. Without it, you’re at risk of using outdated or incorrect data that will yield less-than-ideal results. This process can involve data validation techniques like cross-referencing figures with other tools, fact-checking with individuals across the organization, identifying and removing duplicate information, and categorizing data appropriately.
Storing and securing data is essential for accuracy, accessibility, and compliance. Ideally, data should be stored in a secure and centralized location that is accessible by all relevant personnel. Don’t forget about backups. You should always have procedures in place to recover data in case of a cyberattack.
Finally, HR data management needs policies and guidelines to ensure consistency and compliance when analyzing and transferring data.
Types of HR data
There are dozens of types of HR data out there. Which ones you collect and analyze will depend on the company’s goals. Plus, it doesn’t have to be the same type of data each time. You can select certain types during one quarter and other types for the next quarter, depending on your goals and strategic priorities. Let’s look at some examples.
Compensation data. This encompasses everything related to a person’s salary, bonuses, overtime pay, and more. It can also include data related to benefits such as retirement plans or healthcare, though some prefer to collect that separately.
Diversity and inclusion data. This is a critical type of HR data for any company that wants to boost its DE&I efforts. It can include data on demographics, gender, race, ethnicity, neurotype, and more.
Turnover data. This includes reasons employees are leaving, how many left voluntarily during a certain period, how many were let go, and more. Analyzing this information will help you create better retention strategies so you can keep your top performers.
Recruitment data. Here we include information about job applicants, hiring decisions, time to hire, and more. You’ll need this data if you want to improve your talent acquisition process.
Employee performance. Included here is data on how well people perform, factors that may have influenced their performance, and more.
What does HR data show?
HR data, especially when used along with HR analytics, can provide valuable insights into your workforce. It can reveal trends, patterns, and correlations that will help you make better business decisions.
Let’s look at a quick example. A company experiences high voluntary turnover rates. They start looking at data related to this issue, such as:
The number of people who left over a certain period
The departments and/or teams they were part of
Their seniority level
Their past performance
The company can then use this data to:
Identify trends. Perhaps turnover rates are higher in one department or one team. Or perhaps it’s the senior employees who are leaving more often than the juniors.
Understand why employees are leaving. Perhaps they were unhappy with their team leader, or they were feeling burnt out. Maybe they feel they’re not compensated fairly for their work or their seniority level. Whatever the reason is, looking at data will help you spot answers.
Create targeted retention strategies. Once you see the trends and understand why people are leaving, you can create targeted retention strategies to improve the areas that were causing issues.
How do companies collect HR data?
There’s no shortage of ways to collect data. Typically, you’ll need a combination of manual and automated tools. The more sources you have, the bigger the need for automated tools and techniques.
The exact tools you’ll use will depend on your systems. But if you have several data silos and store information in cloud storage, data connectors will be your best friends. They can extract data automatically and facilitate the integration and transfer of information between various systems and databases.
Before you can begin collecting data, you’ll need to set your goals. This will help you refine your data pool, selecting only the information that will be most useful. Don’t forget about data privacy and transparency.
Be open with your employees about data collection. To ensure security, limit the number of people who have access to the data. It may feel easier at first to give everyone access. But if people won’t be working directly with that data, their access rights will become a security risk.
3 common HR data sources
HR data comes in many forms. The sources can be just as varied, though we usually work with three categories: HRIS data, business data, and other data. Let’s take a closer look at each data source.
1. HRIS data
HRIS data sources contain the most common types of HR data. A few examples include:
Recruitment data. This is often collected through Applicant Tracking Systems (ATS) and includes the number of job applicants, recruitment funnel and sources, and more. If you want to understand the talent acquisition process, these are the data sources you must look at.
Demographic information. Age, gender, ethnicity, date of birth, and residence are some examples of demographic data. The information will usually be under HRIS employee records and is critical for various processes, especially DE&I goals.
Learning management. Learning management systems (LMS) are an easy way to keep track of what courses or training each employee participated in. This data helps you track progress and is great to use in internal mobility and succession planning programs.
Compensation and benefits. Information regarding compensation and benefits is also part of HRIS data sources. Here we include everything from salary to bonuses and other benefits.
Succession planning. Another essential part of HRIS data, succession planning practices ensure retention and job satisfaction. Here, we can include information on leadership development, managerial bench strength, and people who are in line for succession.
Exit interviews. Nobody likes it when people leave their company. But the exit interviews can be a valuable source of information. They can help you understand turnover, but also other key aspects like engagement and productivity.
2. Business data
Business data sources have the widest variety. They look beyond strict employee data, encompassing information related to clients, budgets, sales, and more. Let’s look at a few examples.
Customer relationship management (CRM) data. There’s a lot of valuable data in CRM systems. Information on customer satisfaction, NPS score, or customer contact moments. This information will be useful in assessing employee performance and more.
Sales data. Sales are an important metric of success for most businesses. You can look at data such as sales per store, per department, or even per person, depending on the specifics of your business.
Financial data. This covers earnings, ROI for learning and development, cost per person, and other related expenses.
3. Other HR data
These sources include data you won’t find in HRIS systems. The data is often harder to collect through classical or even automated means. Here are a few examples.
Mentoring. Mentorship programs are essential in employee engagement, satisfaction, succession planning, and internal mobility. They also help reduce skill gaps and can create strong bonds between employees. Collect information on the mentees and mentors, their challenges, and their outcomes.
Engagement data. You’ll usually gather this information through surveys and things like the NPS score. It has a degree of subjectivity, which is why you won’t usually find it in HRIS systems. Low engagement can often precede turnover, so keeping an eye on engagement metrics can help you anticipate problems in this area.
Wellness data. Some organizations may have data on wellness initiatives. This can help you if you’re working on improving the employees’ work-life balance and preventing burnout.
HR data is essential for any company that wants to leverage the power of its employees and start making data-driven decisions. Along with people analytics or HR analytics, HR data can help you spot trends and patterns and make predictions about future events.
On the Outsmart blog, we write about people analytics and HR technology topics like how bad data can’t stop good people analytics, the benefits of augmented analytics, and everything you need to know about HR data sources and HR data connectors. We also report on trending topics like artificial intelligence, using generative AI in HR, and how skills are rapidly evolving, and advise on people data best practices like how to ingest people data and business data, how to turn source data into insights, and reports vs. analytics. But if you really want to know the bread and butter of Visier, read our post about the benefits of people analytics.