21 HR Data Sources for Analytics | AIHR Analytics

A question we commonly hear is “what are data sources that can be used for analytics?” In this article, we will list a number of common data sources in HR and the broader business that will be helpful in your people analytics efforts.

HR data sources can be categorized into three groups.

  • HRIS data. Data from the company’s Human Resources Information System, or HRIS, includes most of the company’s data about its employees. Common examples of HRIS systems include Workday, Oracle, and SAP.
  • Other HR data. Some HR data is essential for data-driven decision making but is not included in the HRIS. This data is often acquired through surveys or other measurement techniques.
  • Business data. Although it is impossible to cover business data exhaustively, it plays an increasingly important role in people analytics. We will touch on the most essential business data used for people analytics.

This is not an exhaustive list. If you feel we’ve missed some, please add them in the comments and we will update the article accordingly!


HRIS Data Sources

The company’s HRIS contains data on the most common HR functions including recruitment, performance management, and talent management. Although the modules in the HRIS differ from company to company, there is often a common group of modules that contain data useful for people analytics.

Recruiting. Recruiting data gathered from the Applicant Tracking System (ATS) is the first common data source in the HRIS. This includes the number of candidates who applied, their CVs and other characteristics, as well as data about the recruitment funnel, recruitment sources, selection, and so on. This system is the most common input for recruiting metrics.

Demographic data. Another key data source is HRIS employee records. This includes the employee ID, name, gender, date of birth, residence, position, department, cost center specifications, termination date, and so on. These demographic data are often included in an analysis as control variables. Also, when data is combined manually, this is often the database that is enriched with data from other systems by matching the employee’s ID as a unique identifier.

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Performance management. The performance management system (PMS) is part of the HRIS and contains information about performance management. This includes employee reviews and performance ratings. For more information, check our full guide on performance management.

Learning management. The learning management system (LMS) is another source of HR information. The LMS contains a course offering and registers employee’s progress through different programs. Not all learning data is stored in the LMS. Often finance holds the information of expenditure on external courses while learning impact and effectiveness is often measured using surveys. For more information, check our full guide on learning & development.

Job architecture. Job architecture, also referred to as global grading or job leveling, is a framework that serves as a foundation for remuneration. Different roles are put into salary scales that have bands and grades with maximum reward levels. Different roles apply to different salary scale levels. The example below shows the salary scales as displayed in the collective labor agreement for Dutch universities. Function scale H2 and H1 are reserved for full university professors meaning that their salaries range from €5582 – €9812. Commercial companies often have these salary scales and job architecture as part of their HRIS.


Compensation & benefits. To keep employees engaged, they are compensated. Compensation and benefits data are also stored in the HRIS. These include remuneration details but also secondary benefits. For more information, check our full guide on compensation and benefits.

Succession planning. Succession planning schemes are also part of the HRIS. The amount of data depends on the maturity of the organization’s succession planning practices. Example data includes leadership development data, managerial bench strength, and data about which people are next in line for positions.

Talent development. Talent development data is a bit of a weird one out. Talent programs often consist of courses and workshops that are often included in the learning management system. However, the broader approach to developing talent is another key piece of information that can be retrieved from the HRIS.

Exit interview. Depending on the organization, exit interview information may also be stored in the HRIS. This provides information on the reasons why employees have left the organization. This data can be used for analyses aimed at reducing employee turnover.

Other HR data

In our categorization, other HR data sources are HR data that are not commonly stored in the HRIS. This is often because data is hard to collect using regular methods.

Learning. Our first example is learning data. Data on learning effectiveness and learning program evaluation is often stored separately from the LMS and is managed by the learning department. Often, this data is stored in excel spreadsheets and survey collection tools. Integrating this data into a broader HR reporting and insights database is an early priority for organizations that are starting to work on learning analytics or try to advance their reporting.


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Travel. Travel data is another source of important data. The number of times someone travels internationally is a potential predictor of employee turnover. However, this kind of data is not stored in the traditional HRIS.

Mentoring. Mentoring is a key practice for high potentials and often forms part of talent and leadership development programs. Mentorship can make mentees more effective, stay longer, and more eligible to advance to a more senior role.

Employee survey data. This is more of a category in itself. A big part of HR data is collected through surveys. This can range from a poll on the quality of food in the cafeteria, a survey by the CEO about his popularity, and the traditional engagement survey. Most companies send out surveys in a decentralized way, leading to survey data being scattered in the organization and survey fatigue. Collecting all this data in one place helps to provide better insight into employee survey data.

Engagement survey. The engagement survey is sometimes part of the employee survey data bank we mentioned before. However, often engagement surveys are collected by a third party to guarantee anonymity. Although this greatly reduces your data capturing potential, it does mean that the engagement survey is a separate data source. For more information, check our full guide on measuring employee engagement.

Absence data. Recorded absence data is another key HR data category. Sick days are usually tracked by managers and recorded in a system. Some organizations also record absence reasons. Similarly, holidays, maternity leave, and lateness data are also captured.

Wellbeing and wellness. Depending on the organization, there may be records available around (participation in) employee wellness programs. This serves as another data source that is not captured in the HRIS.

Social network data. Data on organization social networks also referred to as organizational network analysis (ONA) can be another great source of information. Potential data sources for this are network surveys, email accounts, phone records, or any other system that reports network data.

Business data

The scope of business data is almost endless. A multitude of business data sources can be used for people analytics. We will list some of the most important ones below.

CRM data. The company’s Customer Relationship Management system holds a ton of data on customers. This includes customer contact moments, NPS scores for those touchpoints, lead scoring, and so on. This data can be crucial outcome data to measure the impact of people policies on customer-facing employees.

Financial data. Financial data is another key business data source. This can be for simple analyses on L&D spending, and more complicated analyses on the cost of personnel, ROI calculations for different interventions, and other financial analyses.

Production management data. Another data source can be production management data. Production management systems plan, track, and manage data including scheduling, number of service calls, delivery rate, speed of delivery, and much more. These data can also be used as outcome data to measure the impact of people policies for employees working in the production or service delivery process.

Sales data. Similar to the previous one, sales data is another outcome measurement. Examples include sales per store which can be used as outcome data to measure different HR policies like learning program effectiveness.

Other sources. This last category includes internal business data and external sources. Examples of external sources can be market data, but also flu rates, weather data, and all other factors that can impact people and productivity.

As you can see, many data sources can be leveraged for people analytics. Please keep in mind that every organization has structured their HR and business data differently. Some data may be available, other data may not be. Depending on the business, there may also be other crucial data that is not listed in this article. If you know of such data sources, please comment them below!

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Erik van Vulpen is an expert in connecting HR processes to business results through qualitative and quantitative methods. He is globally recognized as a thought leader in the People Analytics and Digital HR space. Erik is a regular speaker at conferences and trained dozens of HR leadership teams to embed innovative and data-driven HR practices in their organization. He is also an instructor for the AIHR Academy, as well as one of its founders. Contact Erik at erik@aihr.com or connect with him on LinkedIn.