As multinational organizations seek increasingly comprehensive solutions for managing the needs of global business, they invariably turn to technology to help them optimize processes and improve outcomes. One of the main areas of development being discussed and debated at the moment is automation, a topic that can include everything from calculation tools to artificial intelligence.
When it comes to processing payroll, however, most of the discussion centers around robotic process automation, or RPA. This technology is applied to high-frequency, high-volume, repetitive tasks that don’t require human involvement to save time and improve accuracy. Outside of payroll, common RPA applications include vending machines and ATMs.
Yet, as comfortable as we are trusting machines to handle our money and food, the idea of adopting RPA into our work makes many people hesitate. There are valid reasons for this, including concerns over the availability of resources or perceived costs, and some less-valid reasons, like worries about automation replacing jobs despite evidence to the contrary. For some companies, their current payroll or HR solution may not support automated workflows or make it cost-prohibitive.
Whatever the reason, the outcome is that many payroll organizations stick with the status quo, even as the potential benefits of automation begin looking less like nice-to-haves and more like necessities. Sitting at the top of that essentials list is Robotic Data Validation (RDV), the time-saving, compliance-boosting robot that has quickly become an indispensable tool for global payroll. Here’s why.
RDV delivers greater accuracy throughout processing.
The most common data validation process used in payroll today involves a stack of variance reports and a list of 40 or more “checkpoints” that the practitioner has to check off by hand. Based on the volume of data and processing requirements, a threshold is determined for acceptable variance. For example, if an employee salary is more than $250 above the previous cycle, it may fall outside the acceptable variance amount and trigger a manual review.
This means any data discrepancy that falls within the acceptable level of variance is not necessarily validated, unless the practitioner happens to notice it and decide to check it. Another method is to check every fifth or tenth or twentieth line of data and hope there are no major issues in the rest of the file. Practitioners also get to hope that no errors are introduced by hand as they scroll through Excel spreadsheets.
Robotic Data Validation, on the other hand, checks 100% of your payroll source data against customizable validation criteria that can be set specifically for every payroll. In CloudPay, RDV runs automatically both before and after gross-to-net, and categorizes all errors as minor, major, and critical. So in an instant, everyone with visibility of the payroll can see the status of all data, issues, and actions required. And once corrections are made, you can re-run RDV to quickly determine whether any errors remain.
RDV saves significant time and frees up resources.
Currently, data validation is one of the most time-consuming steps in the payroll process, compounded by however many rounds of corrections and rechecks are required. Depending on the headcount, country, and volume of information required to run a payroll, teams could spend days manually validating data.
Robotic Data Validation reduces those days to minutes. Instead of manually scrolling through templates, checking Excel tables, referencing maximum values and data validation rules, identifying invalid data, researching the cause of errors, and every other tedious step involved in checking payroll data by hand, your payroll specialist locks the data entry, and RDV does it all in an instant.
According to the framework published by McKinsey & Company for evaluating the potential of automation across professions, as much as 40% of the time spent on payroll activities could be automated. That is a significant amount of payroll professionals’ time that can be reclaimed and applied to higher-value activities or even more strategic areas of the business. RDV kickstarts that possibility by enabling payroll teams to cut days off their current processing cycles.
RDV enables ongoing process optimization.
With time-consuming manual data validation, the goal is to get through the user input, find the errors, make the corrections, tick the checkboxes, move on. When that’s all done automatically, the possibilities open up.
Suddenly, there’s time to compare errors and data validation lists with previous cycles to look for repeating issues. There’s the opportunity to investigate errors that persist across payrolls to see where the problem starts. Teams can set new goals around data quality and compliance, and configure more precise data validation settings to support those goals.
Rather than thinking of automation as an emerging technology (when it’s actually been part of our daily lives for decades), future-thinking business leaders are seeing it as an invaluable data tool that helps teams clear all the repetitive, time-consuming tasks that slow them down and present unnecessary hurdles.