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Data represents an important source of information for businesses, since data-driven decision-making is a real game changer when it comes to business success. That’s why business functions that generate large sets of data are becoming increasingly important, one of them being payroll.
Payroll data holds an incredible value for organizations of any size, since it provides detailed insights into one of the major cost centers of a business’s cash flow and other critical aspects regarding the workforce.
In order to leverage the strategic potential of payroll, businesses need to know how to properly analyze the data sets generated during the payroll process. That’s where payroll analytics come into play.
In this blog post, we will explore what insights businesses can gain from payroll analytics and how they can leverage these insights to improve their global operations. But first of all, let’s have a look at what payroll data analytics actually means.
Payroll analytics describes the use of data analytics tools to analyze payroll data in order to:
Uncover trends and patterns regarding a business’s workforce
Gain deeper insights into payroll costs
Better understand the impact and effects of the business’s overall operational strategy
Make informed business decisions based on the analytics results
In other words, payroll data analytics is the tool that transforms raw sets of payroll data into detailed insights into various business processes and operations. The aim of conducting a thorough analysis of the organization’s payroll data is to end up with clean global payroll reporting.
So, now that we know what payroll analytics is, the next question is what organizations can gain from scrutinizing their payroll data. Payroll analytics can provide businesses with a large number of insights, including:
Which business functions, units and business locations have too many or not enough employees
Which employees should receive a raise
How high the organization’s total payroll costs are
What the total cost of payroll processing is
How payroll costs are distributed (basic salary, payroll taxes, employee benefits, and more)
What the average pay for a certain position is across the organization
How high the month-to-month changes in payroll are
Workforce diversity, inclusion and pay equity
Total employment cost per geography, entity, department and more
Even the most precise definition of payroll analytics will leave most businesses wondering how to analyze their payroll data. After all, there are many different angles under which the generated data sets can be evaluated and interpreted. Here are some payroll analytics examples to give you a better idea of what metrics to track and what kind of payroll reports to generate in order to get the full picture:
Percentage of payroll runs that don’t need amendments
Number of off-cycle payments and reasons that lead to off-cycle payments
Cost per payslip / cost per employee when using managed payroll services
Time needed to complete a payroll run
Attendance and absence rates within the organization
Distribution and total amount of overtime
Comparison of revenue and cost of compensation
Employee turnover rate (both total and specific to locations, departments and more)
Comparison of budgeted and actual payroll costs
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In order to leverage the full potential of payroll data analytics, organizations first have to know which departments and roles actually benefit from gaining detailed insights into the business’s payroll data. There are three different functions within the organization that can create value from payroll data analysis, i. e. Finance, HR, and the executive leadership team.
That Finance and HR can use payroll data insights to draw conclusions for their own purposes is no surprise. After all, the payroll function is typically part of either the HR or the Finance department. The Finance team needs to exercise financial control over the business’s operations, which includes knowing exactly how much is spent on payroll.
The HR department, on the other hand, can use the different analytics and metrics in payroll to enhance the employee experience and check if important employment regulations are respected. But the use of payroll data analytics is not just limited to the responsibilities of CFOs and CHROs. Instead, the data insights from payroll can benefit the entire upper management.
Payroll analytics can benefit multinational businesses in many different ways. The potential of global payroll analytics ranges from enhancing financial control to enabling strategic business decisions. But a detailed payroll data analysis can offer many more benefits than that.
Payroll is a substantial expense for businesses, which means that knowing exactly how much is spent on employee compensation is crucial for budgeting correctly and mitigating financial risks. Payroll analytics can not only help businesses decide how much money they can dedicate to new business ventures and projects, but they also support companies when it comes to budgeting for new hires.
Having access to detailed data on overtime, employee absences and other workforce metrics can be a huge advantage when it comes to a business’s hiring and recruiting practices. Seeing which departments are constantly putting in additional hours helps managers decide where new hires are most needed. At the same time, an in-depth payroll data analysis can also show whether the business needs to focus more on diversity in its hiring strategy.
Another HR area which is closely linked to hiring and which payroll analytics can have an impact on is talent acquisition and retention. When brought together with employee satisfaction surveys and turnover rates, payroll data analytics focusing on salary level, length of service and benefits package can be used to create better incentives for employees to remain with the company.
What’s more, if businesses have a clear view of their internal compensation structures, they can use pay benchmarking to ensure they offer adequate compensation to make employees stay.
Relying on good business sense, experience and intuition when making business decisions can quickly go wrong, which is why organizations should instead rely on data to inform business decisions. And since payroll generates large sets of data, it is a valuable source for gaining a deeper understanding of the business’s overall situation and assessing the potential impact of decisions and operational changes.
For instance, global payroll analytics can help companies decide where to expand next based on the local cost of compensation. Similarly, payroll data analytics can be used to compare generated revenue against payroll expenses to see if it is worth continuing operations in a certain location.
Payroll and compliance are closely interlinked. Not only because payroll is highly regulated and therefore poses various compliance risks, but also because payroll analytics can be used by HR teams to gain valuable compliance insights. For example, having a clear view of the amount of overtime employees put in allows HR to verify that overtime is within legal limits. Similarly, data insights from payroll can point out employees who have yet to use their annual leave.
With the help of payroll analytics, businesses can spot recurring problems in the payroll process and work towards finding a solution. Since payroll errors often have negative repercussions on the employees who end up getting paid late or incorrectly, taking the necessary steps to prevent payroll errors from happening significantly helps improve the overall employee experience. Plus, it saves the business a lot of time, money and resources, since spotting and correcting errors in payroll is a long and tedious process.
Before they can start using payroll analytics, organizations first have to bring all their payroll data together. While this might not be much of a challenge when operating in one country only, the task becomes much more difficult when running a multi-country payroll.
In a global payroll set-up, payroll data is typically generated by a multitude of different payroll providers who all use different data formats and file types, and list different pay elements. Before any data analytics tools can be used to analyze such incoherent and distributed data, it is first necessary to standardize and consolidate all data sets in one central system. This is where global payroll solutions like Lano come into play.
Lano’s Payroll Consolidation Platform allows you to unify your global payroll infrastructure and centralize employee and payroll data for all of your entities in one single platform. Obtain detailed reports on your global employee data by country, cost center, employment type and more, and use the rich reporting features to gain a deeper understanding of your global workforce costs. Book a demo with one of our experts to find out how Lano can help you leverage the strategic potential of global payroll analytics.
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