Technology is constantly evolving and changing the way we act, function, and see things. From digitalizing almost every aspect of our life to enhancing experiences with the help of various IoT devices, technology has become an integral part of simplifying our lives and make everything available at our fingertips. Apart from simplifying day-to-day lives, technology has also enhanced business user experience by lessening organizations’ burden and complexity, helping them expand their businesses horizontally and vertically – within the region and across borders. Nowadays, a company does not need to have their own office at every location they operate and can still standardize and control the entire operation process. A single office now has the ability to manage multiple locations across the globe.

In short, technology has made process automation possible. This has eased organizations’ daily functioning, but with increasing, operational scale and geographical expansion, the complexity of management and administration has also increased.

One of these administrative tasks that can benefit from automation is payroll management. Organizations with dated manual processes and legacy payroll solutions find it difficult to cope with the competition posed by digitally adapted organizations and their dynamic environment. This is why they are looking to digitalize and update the legacy platform to increase efficiency.

The digital solution – Robotic Process Automation and Machine Learning.

Emerging technology such as Machine Learning (ML) and Robotic Process Automation (RPA) has been increasingly accepted and adopted in various departments.  However, in payroll management, it is in the emerging stage. Organizations are noticing the potential held by ML and RPA to eliminate manual processes and gradually beginning to automate payroll processing.

Global payroll processing deals with collecting, moving, and delivering hefty amounts of sensitive data from varied sources and locations. And manual handling of such sensitive and heavy data can be risky as there are chances of miscalculation of payroll, duplication of data, and other human errors. ML and RPA help to reduce human error through the enhanced security systems.

Payroll processing is not just about the disbursement of payroll to employees. It is a combination of a collection of data, processing it in a standardized format, followed by computation of payroll based on the data and various local and global compliances. Once the completion of all the above steps, deductions are made, and the net compensation is disbursed. This four-step process might look like an easy task, but complications like dynamically evolving regulatory compliances, numerous types of employees [payroll, freelancer, and Employer of Contract (EOR)], varied calculation terms, and other minute yet important aspects make the payroll-cycle processes complex.

Automation eases the payroll process and generates a desirable outcome for organizations by identifying patterns, reducing duplicity, automating redundant processes, and streamlining workflow. This helps to:

  • Increase the speed using the digital process with less human intervention.
  • Minimize costs due to reduction in repetitive processes.
  • Improve efficiency with a more focused and precise output.
  • Reduce data discrepancy with the digitalization of data.
  • Perform nano analysis to provide better insights.

Payroll management automation has gained a lot of traction with increasing geographical expansion, employee diversity, and organizations accepting automation in the payroll-cycle process. It will reduce fines and fees by staying updated with the local regulations and alert management in cases of discrepancies through automated triggers. It is bound to help organizations seamlessly transform from legacy to digital platforms and speed up the scaling process.