With advances in technology and cloud computing, numerous data sources are available to drive organizational success. The better you understand the different types of metrics and analytics in HR, the more relevant information you’ll be able to gather from data to help meet business goals. The insights analytics reveals provide a more complete perception of what’s really going on in https://ativanx.com/2015/09/21/latest-ativan-news-5/ the company. Prescriptive analytics goes beyond predictive analytics with a more pre-emptive approach to looking at the future. A general prescriptive analytics definition would be the targeted recommendation for decision options and actions based on the findings of predictive analytics. Prescriptive analytics is the final and most complex stage of the analytics journey that transfers predictive analytics into ideas for what to do next.

Managing HR data isn’t just about collecting information—it’s about ensuring that the data remains accurate, secure, accessible, and useful for making strategic decisions. Whether it’s a change in job role, compensation, or contact information, outdated records compromise operational decisions. HR data includes any information that relates to the people within an organization. These configurations give you a more flexible and secure approach to managing who can access specific data, ensuring privacy while enabling tailored insights. With Visier’s Analytic Model, you can modify existing metrics, create new attributes, or integrate additional data sources to meet unique business challenges. Whether reducing turnover, improving hiring quality, or saving millions through smarter systems, each example shows how people analytics can drive meaningful, measurable business outcomes.

Because talent acquisition can be so expensive, it’s important to make sure your recruitment process is as successful as possible. With engagement scores, tenure, performance trends, and compensation benchmarks, you can predict which employees are at the highest risk of leaving. In this HR data analytics example, you can examine why certain individuals or teams consistently underperform. HR leaders and managers can analyze why certain job postings fail to attract qualified candidates by evaluating job descriptions, sourcing channels, and measuring application conversion rates. Diagnostic HR data analytics examples can illuminate the descriptive analytics you uncovered and show you how best to make improvements. You can also measure the average performance review scores of teams and departments.

Automating HR data workflows

We are developing use case scenarios with built-in guardrails to ensure the team understands the appropriate ways to use AI and other in-house tools. We look at location, leader, department and other data points to understand whether issues are isolated or part of a broader pattern. But deeper insight comes from understanding how employees use those channels. Nearly all organizations provide anonymous reporting tools, use of required investigation processes reached an all-time high in 2025 and purpose-built technology remains the standard approach to manage issues and investigations. Are they appropriate for managing and analysing your HR data? Consider both existing HR data and potential new data sources.

HR Data Analytics Help Spot Risk Early

The payroll feature automates the pay process of an organization’s employees. It serves as a centralized platform for managing various benefits plans and enables employees to easily access and modify their benefits selections. Employee benefits are an essential aspect of compensation and are also managed in this system. Depending on the HRIS provider, the exact functionalities of the system will differ.

• With unified employee data management, all branches, departments, and employees operate on a single, integrated platform.
• Improved transparency across countries and departments, faster responses to local engagement issues, and improved team morale.
• The HRIS also stores compensation and benefits information.
• HR creates a personalised training plan that helps the employee develop those specific skills.
• ContentsWhy you should have an HR data strategyWhat to include in your HR data strategyHow to build an HR data strategyHR data strategy examples from practice

Typical internal sources of HR data include the HRIS, the ATS, the LMS, and data collected from employee surveys. The short answer to the question of which data sources can be used for data analytics in HR is that there are many different data sources. These reports help contextualize internal data and guide strategic planning. These benchmarks help HR stay competitive in pay, understand talent availability, and spot shifts in demand for certain skills. This includes customer contact moments, NPS scores for https://viamrkting.com/seo-for-saas-to-rank-higher-on-google/ those touchpoints, lead scoring, etc. While it requires careful handling due to privacy concerns, ONA can provide valuable insight into how work really gets done beyond org charts.