Organizations that adopt a new payroll system know that things can go wrong. In fact, there is rarely a 100 percent match of employee data for gross pay, pretax, voluntary and statutory tax deductions, etc., between the existing system and the new one. The margin of error can be quite large, often with as many as 70 percent of the records not matching. This is not tenable. Therefore organizations need to conduct a comparison of data between the two systems, the old and the new, to ensure and prove that payroll is being calculated accurately.
This makes the role of Parallel Payroll Testing a critical aspect in new payroll implementation.
Parallel Payroll Testing compares the data in the new system with that in the legacy systems and provides assurance that they are nearly the same. It is not necessary that every component of payroll from both systems be identical—but the differences should be known, explainable and within an acceptable and predetermined range. In addition, when variance in an employee’s data is identified, it should be possible to isolate the component (was it bonus, commissions, overtime, child support, dental deduction, etc.?) that is at variance.
Planning delivers perfection (always!)
Achieving this requires planning. In some countries, salary components are straightforward, whereas in others they can be extremely complex. Therefore, the implementation of a new payroll system depends on local regulations and the number of employees.
In USA, for example, tax varies across every state, county, city, school district and locality. It is like dealing with 52 different countries. Which is why planning for Parallel Testing is an important prerequisite.
It has been learnt that the first cycle of comparison generally shows large discrepancies. This is because of a variety of reasons such as conversion issues, payroll calculation customizations, wage basis rules, etc. Hence, it is recommended that organizations plan for a minimum of three Parallel Payroll Testing iterations following seven steps:
- Determine how many iterations/cycles of comparison are needed
- Determine payroll periods for each iteration
- Identify legacy system and new payroll system environment for each comparison cycle
- Define payroll components mapping between legacy system and new payroll system
- Complete data conversion in dev environments of new payroll system
- Identify resources from both the business and the implementation team and their ownerships and roles for Payroll Runs and Results extraction in both systems
- Chart out a payroll comparison strategy
The real challenge of reconciliation – and a tool to simplify it
Many organizations perform payroll comparison using Excel. This can be an uphill task. For example, given the nature of taxation in the USA, you would expect an average 100 rows per employee extracted from both systems. Now imagine doing a comparison for 50,000 employees. Excel would need to compare half a million rows. In such a situation, it is imperative to use a reliable tool.
Wipro has built a Parallel Payroll Testing tool that eliminates manual comparisons. The entire activity of data extraction, transformation and creating comparison reports at summary and granular levels is automated by a comparison engine. The summary level reports show the number of employees that have a mismatch in gross or net salaries; the granular report identifies the salary component(s) in which the mismatch has occurred.
For instance, a global healthcare and diagnostics services provider in USA leveraged during the migration of their payroll to Oracle HCM Cloud. The organization saw significant reduction in time taken for payroll testing. Comparisons for over 50,000 USA employees, that would take 4 months using Excel, had been completed in 2.5 months, delivering an effort saving of 40 percent.
Apart from the savings on time and effort, the tool ensures organizations can be confident that employees will not be impacted and statutory guidelines and conventions will not be violated – assuring a satisfactory migration of their payroll systems.