by Jea Yu
Bonus and overtime pay programs can result in payroll leakage. Here’s how to locate and eradicate these often-unnoticed costs.
While bonus and overtime pay are often expected expenses, they can also be a source of unnoticed payroll leakage that results in mounting revenue and productivity losses. This leakage can come from loose oversight, policy bottlenecks or willful gaming of the system, which is why organizations should consider re-examining their current bonus and overtime pay programs.
Here’s how to integrate people and data analytics to identify payroll leakage risks, enable process and policy solutions and establish an ongoing monitoring system to ensure optimal efficiencies.
Hidden in Plain Sight
Leakage is often embedded right into the structure of payroll processes, making it all but undetectable during audits. In fact, these costs are often so ingrained into processes that they’re assumed to be part of normal operating expenses.
“Payroll leakage can come from various sources — it can result from poor design of policies and procedures as well as lack of enforcement,” says Sushma Tripathi, Vice President of Workforce Strategy and Compliance for ADP. “So, employers need to ask themselves: How are we spending our company’s valuable payroll dollars on our people? Are we efficiently paying people for the jobs they do? Is there consistency in how we pay? Is it based on performance, tenure or for showing up?”
Over time, leaks can add up, and unchecked leakage can lead to corrosion and serious disruptions down the road — especially if it triggers legal, compliance or regulatory complications like fines and investigations.
Payroll leakage is most likely in organizations that have lagged in workforce technology investments and fallen behind on developments that could curtail the problem.
“A good example is employees clocking in a few minutes early for a ‘premium’ night or weekend shift,” says Tripathi. “This generally results in the unintended consequences of overspending with respect to base hours, as well as overtime pay if the employer is rounding time. The dollars may exponentially increase as more employees do this, specifically if they are working in a jurisdiction like California or Nevada or a federally regulated industry in Canada, where there is daily overtime calculation.”
Lacking tools that can quantify the total impact of these costs leaves businesses unprepared to handle the root problem, let alone the symptoms. And leakage vulnerability magnifies as organizations accommodate the modern workforce model that expands beyond just full-time and part-time workers to encompass independent contractors, seasonal employees, and remote and virtual workers with hourly fixed, variable and project-based compensation schedules.
Root Problem vs. Symptoms
Organizations may make the mistake of fixing only symptoms, leaving the root problem untouched. But of course symptoms are merely expressions of the root problem, which is often embedded at a deep structural level. The temptation to judge a patch to be adequate instead of taking on the prohibitive costs of making structural repairs means that it’s prudent to make the effort of performing cost-benefit analyses to gain clearer insight.
Implement Cost-Benefit Analysis
Performing cost-benefit analyses on the effects of overtime and bonuses will help organizations understand whether these premium payments are truly adding to the bottom line. Such analysis will also reveal how tied overtime and bonuses really are to output and efficiency.
“The key question to ask yourself is, ‘Can I differentiate between productive vs. non-productive time?’ Paying for non-productive time can be detrimental for low margin business.”Sushma Tripathi, Vice President of Workforce Strategy and Compliance for ADP
Variable-pay incentive programs can be a boon, but they should be outcomes-based rather than discretionary. Discretionary overtime and bonus policies are especially likely sources of leakage.
Employing People-Data Analytics
Conventional financial analysis and audits fall short when reporting payroll leakage. Data analytics, on the other hand, offer the ability to define, identify and quantify payroll leaks and the context of their occurrence. Running the data through machine-learning algorithms and cognitive-learning technologies can generate predictive analytics that enable companies to anticipate where and when leakage may occur.
As leakage costs are quantified and root problems isolated, companies can integrate labour cost optimization (LCO) programs for layered solutions to fix problems at the source, whether they’re related to processes or policy. Data analytics is not the end but the start of solution implementation.
Labour Cost Optimization Programs
LCO programs are designed to target root problems, in turn eradicating symptoms. They involve deep excavation, potentially involving structural repairs that integrate process and policy changes and continual monitoring on a maintenance schedule to optimize outcomes.
Organizations will have to weigh the cost savings for the investment in LCO programs, but for long-term optimization, the benefits are ultimately likely to outweigh the initial disruption and costs. And byproducts that further optimize efficiency can commonly materialize through the LCO integration.
“So, the key question to ask yourself is, ‘Can I differentiate between productive vs. non-productive time? Paying for non-productive time can be detrimental for low margin business,” says Tripathi. “Also, casually inflating time or over staffing — resulting from lack of tools — can cause payroll leakage and compromise accuracy, efficiency and compliance.”
While organizations constantly adapt to workforce trends and focus on flexibility, it’s just as important to maintain workforce technology investment spending to avoid payroll leakage. Data collection should be interwoven into the organizational ecosystem to keep the connected pipeline flowing with robust data that can be translated into predictive analytics and critical foresight.
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This article originally appeared on SPARK Powered by ADP.