If there’s one thing you can bet on for 2026, it’s this:
So your payroll is performing well, and your metrics back that up – but does that mean that your payroll operation is controlled and efficient?
The 2026 CloudPay Global Payroll Efficiency Index suggests that more and more companies are getting to grips with payroll technology, and joining the dots of their operations from end-to-end. Through analysis of more than 4.7 million payslips processed worldwide during the 2025 calendar year, and by comparing results to previous years, we’ve uncovered that much of the volatility of payroll is being eliminated – with automation and AI-enhancements making it easier to achieve excellent results.
What do the numbers tell us?
The report looks at five payroll performance metrics that go beyond headline SLA figures and benchmark how well payroll is running in reality:
- First-time approvals (FTA): the percentage of all payroll runs approved first time, without any changes being required
- Data input issues (DII): the average number of data-related issues per payslip
- Issues per 1000 payslips (I/1000): the average number of issues (of any kind) per 1000 payslips
- Calendar length (CAL): the average number of days needed to complete an entire payroll cycle from start to finish (including payments where integrated)
- Supplemental impact (SI): the percentage of payroll runs that take place outside of the normal scheduled cycle, out of all payroll runs of any type
Looking at this year’s results in detail, there have been sustained improvements in most metrics, at global level and across all regions, too. FTA has improved by 2.18 percentage points to 74.79% globally, with all three regions (EMEA, APAC and Americas) improving simultaneously for the first time in five years. At the same time, calendar lengths have shortened, and supplementary impact has also reduced.
What does this mean in practice?
In previous years, improvements in one metric have often come at the expense of good performance in another.
For example, a very short calendar length might sound like extremely efficient payroll on paper – but in reality, it might mean that payroll is being rushed because there is less time being spent on validation. In turn, this can lead to more mistakes (and a lower FTA rate), and more remedial work needed to fix those mistakes (and a higher SI rate).
This makes the coordinated improvements across multiple metrics highly significant. With speed improving without sacrificing quality, the results suggest that payroll performance is becoming more controlled and more predictable.
What’s behind this new-found control?
Much of the shift is down to greater understanding of payroll technology, and operating models becoming more mature as a result. With API integrations, automation, AI enhancements and structured data flows becoming more embedded, many repetitive tasks and handovers have been removed from payroll teams’ manual workloads. In turn, this has given them more time to focus on higher-value work such as validation, exception handling and issue prevention.
It also demonstrates that more and more organizations are understanding how to maximize automation, integrations and AI without replacing or marginalizing payroll expertise. Instead of payroll teams chasing files and tasks, their expertise can be put to better use managing exceptions and applying judgement where it is genuinely needed. Ultimately, businesses still need good data discipline, earlier checks and clear understanding of when payroll has been locked, so payroll teams can focus on the ‘edge cases’ while automation improves the standard flow.
How does this control influence payments performance?
Greater control matters beyond payroll, because the PEI analysis shows that many payment issues actually originate far upstream of the payment transaction. Through the PEI report analysis, we found that 57% of payment incidents originate upstream of core payment execution, in areas such as payroll data, approvals, timing, or the handover between payroll and payments.
Bringing payroll and payments closer together – to the point of combining them into a single connected ecosystem – can help resolve these issues. Technology can help create that connected end-to-end flow, integrating data, payroll approvals, funding and payment execution – while reducing the manual handovers and system boundaries where issues can arise.
In summary: delivering maximum pay performance, end-to-end
Payroll doesn’t finish when calculations are approved and payslips are generated – it’s only truly successful when employees and statutory bodies are paid correctly and on time.
And it’s for that reason that payroll efficiency shouldn’t just be measured at the point of approval. Every step on the journey, from HR data input through payroll processing, approval, payment execution and confirmation, is critical. What our PEI report’s results suggest is that more organizations appear to be developing that end-to-end flow, using automation, integrations and AI where appropriate to maximize efficiency without compromising performance.
The end result is a more predictable, joined-up payroll operation, where people, technology, payroll and payments work together to reduce risk, improve visibility and deliver a more reliable employee pay experience.
To read more about how this works in practice, read the next blog in this series on why faster payroll needs stronger validation – and to explore the results and analysis in detail, download the full CloudPay Global Payroll Efficiency Index 2026 here.