3 Practical Ways Validation Rules Improve Data Integrity & Outcomes in Payroll
Nov 10, 2016 | Tag: Analytics
As an extremely high-volume business function, global payroll is an area of the enterprise where delays, corrections, and reprocessing incidents are all too common. The typical source of most processing problems: incorrect, incomplete, or mismanaged payroll data.
The fact that data issues lead to payroll errors is no revelation: Payroll managers review their post-process payroll exception reports regularly in order to understand where any problems in the pay cycle are stemming from. Yet by looking backwards, payroll teams rarely resolve the root cause of their troubles.
Payroll exception reports deliver error information after the initial processing of a pay run – notifying managers and their teams of any overpayments, underpayments, or miscalculated withholding totals, or of any payees whose payments are undeliverable due to missing or incorrect information.
While valuable, payroll exception reports work exclusively retroactively. Once armed with the intel the exception reports provide, managers and their teams still waste hours (or days) on correcting their data errors and reprocessing affected payrolls.
Pre-process data validation allows payroll managers to be more proactive: By checking supplied payroll data in an automated and flexible manner, and notifying relevant constituencies of issues prior to the pay run, validation can enable global payroll teams to catch and fix errors before they occur – that is, before they lead to re-runs, added costs and processing delays.
For multinational companies that utilize technologically sophisticated, cloud-based global payroll software and managed services, the time saved with pre-process validation is just one of many benefits. With a smart software solution and a more standardized approach to payroll data, organizations can use automated pre-process validation to achieve targeted improvements in three key ways.
CUSTOM VALIDATION SCHEMES
Create greater specificity and accuracy, especially in regional or country-specific payroll.
The top cloud-based global payroll solutions on the market come pre-loaded with default data validation schemes designed to catch common data errors experienced by clients: missing fields, incorrect or unsupplied codes, negative values, and more. Under these default schemes, common errors are prioritized according to their perceived level of severity for the client – for example, as blocker, major, or minor.
But since every customer has their own needs, concerns, and issues in global payroll, pre-loaded default schemes can’t go far enough. In the best-equipped cloud payroll solutions, clients can build unique data validation schemes around their business rules and apply them at the appropriate level – region-, country-, or payroll-specific.
That functionality allows data validation to go beyond just pre-process error notification to providing pre-process payroll intelligence. Take salary limits, for example: If a multinational company wants to be notified of any non-executive salaries that cross a certain threshold, they can create a validation scheme to flag all payments above a certain amount; from there, they could leave that validation rule off of any payroll that goes exclusively to directors and their superiors. Custom validation schemes can also simplify post-process reporting – for example, by flagging any bonuses that must be reported to country-specific regulatory bodies.
Achieve greater control of payroll & visibility into problems.
As mentioned before, pre-built validation schemes are tagged according to priority. But that doesn’t make them static: Global payroll customers can reorient which validations are categorized as blocker, major, or minor in order to match them to their significance to their business – escalating an error’s importance if the payroll manager deems it worthy of stopping an employee’s pay from being processed, or downgrading it if he or she would rather just retroactively review how often it occurs.
The same kind of prioritization adjustments can be applied to multinational companies’ custom validation schemes, as well. So when utilized at a global scale, priority-driven validation functionality creates untold benefits and opportunities over time: Managers can alter error categories over time based on the frequency of an issue, then monitor their global payroll analytics for trends to determine the source of the problem.
If a specific payroll in a given country is regularly submitted with incorrect codes, for example, the payroll manager can conduct an audit to determine which team member or business function is creating the issue. Priority-based validation thus allows for stronger intelligence when team leads filter from a role-based perspective: Managers can view, monitor, address issues in a tactical and defined way based on the user group responsible – client, provider, or approver.
BETTER POST-PROCESS INTELLIGENCE
Boost accountability & drives targeted improvement across the entire payroll ecosystem.
Especially when reviewed in tandem with payroll analytics – ideally through a payroll solution that integrates data from a multinational company’s third-party systems (such as its HCM and ERP technologies) – payroll exception reports still deliver immense value. It’s vital for payroll managers to understand the outputs and results of their payrolls; with a dashboard view into their global payroll processing outcomes, payroll teams can drill down into their data to gain better business intelligence at both the broad and granular levels.
Partnering post-process analytics with smarter pre-process validations essentially boosts the business value of both, because it means no data issues ‘slip through the cracks’ unnoticed: If withholding issues that should have been corrected pre-process shows up in the exception report, payroll managers and their teams have the intelligence to pinpoint where and why they were missed. That can drive greater accountability across the entire payroll team – client and vendor – since it delivers full transparency into both sides of the process.
From there, pre-process and post-process intelligence can be leveraged for long-term workflow optimization and improvement. Managers can compare results for a given period against another period to see how their data validation, error flagging, and audits improve overall payroll performance (by lowering processing timelines or lessening the needs for re-runs) then change their custom validation schemes to drive better outcomes long-term.
Best of all, the benefits of data validation happen automatically. Beyond the effort involved in prioritizing validations or establishing custom rules, data validation involves no manual processes whatsoever – it’s simply integrated with an organization’s existing payroll workflow. All pre-process validations are triggered automatically when locking payroll, and all post-process validations are triggered automatically with processing payroll.
Given the massive volume of global payroll operations for multinational companies, the ultimate end-game is simple: To make delays, corrections, and reprocessing incidents far less common by ensuring end-to-end data integrity.