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Table of Contents
What are the different types of payroll data?
Why is payroll data important?
What are the benefits of leveraging payroll data?
What is payroll data?
Payroll data is the personal information about employees that companies need in order to pay employees compliantly.
What are the different types of payroll data?
When onboarding a new hire, there are key pieces of information needed from employees to ensure accurate and timely payroll. Different types of payroll data include:
- Employee demographics
- Labor hours, overtime, and paid time off
- Salary and compensation figures
- Employee benefits
- Retirement contributions
- Tax withholdings
- Job codes
Why is payroll data important?
Though these details may seem mundane, they’re a crucial part of paying your employees compliantly. Inaccuracies in payroll data can lead to consequences like employee misclassification penalties and hefty fines.
Payroll data can also be a powerful tool when it’s standardized and leveraged strategically. It can show you current trends in your business and help drive future decisions. With the right payroll data tools, you can monitor trends like:
- Hours worked by department
- Distribution of overtime
- Average pay rates by function
- Payroll burden by geography
What are the benefits of leveraging payroll data?
When payroll data is organized and monitored well, it can improve compliance, drive stronger global business decisions, and lead to better recruitment and retention.
Improved compliance
Maintaining compliance is a top concern for many global executives. It’s a common (and sometimes costly) topic clouded in confusion thanks to rules that often change for every country, state, or region.
Oftentimes, compliance issues stem from managing too many payroll providers and separate processes. Through research conducted by Forrester in 2024, we discovered that organizations are using an average of six different tools to manage payroll, and 50% of teams are using a combination of internal and external management.
In the 2025 Forrester Total Economic ImpactTM study, we found consolidating disparate payroll processes contributed to payroll specialists saving 50% of their time previously spent on research, onboarding and offboarding employees, and reporting. Additionally, global payroll managers saved 40% of their time on tasks like training specialists and escalating queries.
With a single, reliable payroll platform, maintaining compliance not only becomes more efficient, but it also becomes more accurate. Consolidating and automating payroll data prevents common problems like off-cycle payments, corrections, and calculation errors when working with different currencies and regulations.
Stronger global business decisions
Access to insights through payroll data helps global leaders make better, faster decisions about business’s strategy without having to crunch numbers in Excel and manually analyze different data sets.
You can use payroll data to inform things like workforce planning decisions and cost-effective opportunities for expansion. Payroll data can also flag potential problems in real-time, allowing your business to identify and correct problems quickly.
For example, let’s say a manufacturer sees a spike in overtime hours at a specific facility. This can trigger an investigation into the root cause with a same-day turnaround. Instead of losing two weeks' worth of productivity, the issue can be discovered and addressed efficiently.
Better recruitment and retention
Talent has always been a subjective area in business. But payroll data provides a new lens through which to understand the dynamics of attracting and retaining employees. Global employers can use payroll data to provide a snapshot of salary, worker demographics, length of employment, benefits, and more to uncover employment trends across the company's global team.
With this data, you can connect talent trends to local cultures, allowing you to make effective decisions regarding pay, benefits, and other offerings that directly feed into talent recruitment and retention in specific locations. For example, payroll data can feed predictive modeling to show you how a small salary increase might affect employee retention in different regions.
Using payroll data to uncover these insights puts time on your side. Your company can proactively work to keep employees happy and engaged or resolve problems in the moment—instead of months after retention rates start to plummet.