04:05 GLOBAL
But here’s what made the difference: she didn’t just know her numbers were bad. She now knew exactly how bad, across which dimensions, and what good looked like. The performance data gave her a road map. Armed with comparative performance data, she pitched a nine-month initiative targeting her specific gaps: automate and establish data governance of upstream inputs to eliminate exception volume, automate processes to improve efficiency where she lagged behind peers, and streamline workflows to match the cycle times that top performers achieved. Finance approved it in one meeting. Eighteen months later, her cost per payslip was in the top quartile. Exception handling dropped to six hours weekly. Processing cycle time matched peer benchmarks. Her team’s engagement scores jumped 40 points.
“The benchmarking didn’t just help me get budget approval,” she reflected. “It completely changed how leadership saw my team. We went from ‘the people who handle paychecks’ to ‘the people who optimized a multi-million-dollar operation.’ But I couldn’t have done that with internal data alone. I needed to know what excellent looked like.” Why Knowing Your Numbers Isn’t Enough The trap most payroll teams fall into when they start measuring performance: they track metrics in isolation, without context. For example: You discover your cost per payslip is $9.20. Is that good? Bad? Average? You’re processing 50,000 payments monthly with a team of 12, but are you overstaffed or understaffed compared to peer organizations?
The trap most payroll teams fall into when they start measuring performance: they track metrics in isolation, without context.
Your employee satisfaction score is 72. However, you have no idea if that’s competitive or if you’re lagging significantly behind industry norms.
One global payroll leader put it this way: “We’d been tracking
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GLOBAL PAYROLL MAGAZINE ISSUE 21
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