Service level agreements (SLAs) have long been a highly utilised benchmarking tool for payroll professionals. However, it’s not uncommon for many in the profession to feel dissatisfied with payroll performance, even if their SLAs are fulfilled. The reason behind this is simple: SLAs are a good way to set expectations, but what they fail to do is record the effort and time that’s gone into the process. As a case in point, we found in 2018 that just 0.01% of global payslips (paystubs) had inaccuracies, which on paper sounds great. But how many late nights and supplemental runs were needed to get there? How many resources went into overcoming the many barriers and frustrations that teams are facing?
If we’re to create a truly accurate picture of how efficient global payrolls are in today’s post-COVID-19 environment, we need to look beyond the SLA and analyse the key performance indicators (KPIs) that have the biggest impact on payroll professionals and processes. Essentially, we need to be able to compare the payroll efficiency alongside how difficult the process is. This level of “difficulty” will, of course, be impacted by a range of nuances, including local and international legislation that will impact processes, operational limitation, software maturity, and the scale of payroll resources in the team. This is clearly no easy task, however, at my company, a unique Payroll Efficiency Index (PEI) has been developed which provides this much-needed analysis.
Metrics That Should Be Measured
In our conversations with global payroll teams, we’ve identified five KPIs critical in the modern world of work. These include:
- First-time approvals—This metric is needed to understand both the accuracy and efficacy of your data input processes and your gross-to-net calculations. Obviously, a high first-time approval (FTA) rate suggests little improvements are needed in your input process accuracy or approval workflow, but a low score on this KPI indicates room for improvement. FTAs are already a key metric for many payroll teams, but it’s important to measure this alongside the other KPIs rather than as a standalone KPI.
- Data input issues—Accurate reporting on inefficiencies due to input errors will help pinpoint where data collection or transfer processes may be broken before a serious issue arises.
- Issues per 1,000 payslips—This KPI can provide a more accurate picture than an SLA because it considers the size of the payroll itself, which provides an indication of the number of payslips impacted, rather than a percentage.
- Calendar length—Benchmarking the number of days required to complete payroll processing will help identify where process improvements can aid efficiency, whether it’s subtle changes such as integrating fully automatic data transfer systems, or more impactful developments such as incorporating robotic data validation.
- Supplemental impact—While we’ve certainly seen an increase in supplemental runs during the pandemic as significant changes in headcount drove this need, not all have occurred because of this. Understanding where supplemental runs are needed due to payroll inefficiencies alone is important if payroll teams are to identify where processes may be failing.
Payroll Efficient Regions Performing Well
Using the above metrics, we analysed the efficiency of global payroll processes, and the results revealed several interesting international trends. There were nuances across different countries, which we would expect given the differences in payroll calendars and software maturity across locations, but for each KPI, we unveiled several top performing locations across the globe.
For FTAs, there was an encouraging 1.89% increase in FTAs globally between 2018 and 2020, demonstrating not only the resilience of payroll processes during the initial disruption of the pandemic, but also the impact that investment in technology and software has had on overall efficiency in a remote environment. When we drill down into the regional and country data, Asia-Pacific (APAC) reported the greatest improvement rate (+4.32%), while Brazil was the leading country, reporting a 94.1% FTA rate. Interestingly, China is one of the top five performers, despite its complex and constantly evolving payroll requirements.
While Pakistan was the bottom of the FTA league with a rate of just 48.6%, the country did report the second lowest level of issues per 1,000 payslips, beaten only by India. Luxembourg reported the highest issue rate in this KPI category, though New Zealand’s number of issues per 1,000 payslips did double in the two years leading up to 2020. Encouragingly, though, there was a 24% reduction in this metric globally, suggesting that improvements are being made.
When we look at data input issues, there has been a 4.2% decline in errors caused by incomplete or incorrect data globally, which is another sign that the fast-tracked modernisation of the payroll process caused by the pandemic is having a positive impact on payroll. The Americas region reported the greatest improvement, with issues dropping 6.2% between 2018 and 2020. New Zealand was the top performer across the globe, with just 25.3% of issues reported to be from data input. This is unsurprising given that New Zealand has a straightforward payroll process. This process includes the ability for employers to file hire, change, and leave information in cycles, which subsequently reduces the need for supplemental runs. While those on the bottom of the scale—such as Jersey and Serbia—are likely to have higher data input issue levels due to the smaller payroll footprint in these locations, others such as China, Hong Kong, and Malaysia also reported larger rates of errors.
The country comparisons for calendar length are rather striking in that the top five and the bottom five are each monopolized by one region. All the countries in the top five for the longest calendar length are in the Europe, Middle East, and Africa (EMEA) region (Hungary, Norway, Guernsey, Israel, and Denmark), which posted a 0.2-day increase overall compared to 2018. In comparison, those in the bottom five are from the Americas region (Mexico, Ecuador, United States, Canada, and Brazil). Globally, the number of pays required to complete payroll processing has increased slightly (up by 0.1 days), though this is perhaps unsurprising in the context of the pandemic.
The disruption of COVID-19 also appears to have had a detrimental impact on supplemental runs, which increased 4.2% globally and can be attributed to the number of employees that firms had to lay off at the beginning of the pandemic. We can also see from the data, though, that there is a direct correlation between those countries with a shorter calendar length and higher rate of supplemental runs with countries across South America reporting high percentages for the latter. This suggests that calendar length itself is having a negative impact on payroll efficiency.
When we consider the data mentioned above compares pre-pandemic performance with KPIs during significant disruption, where most payroll teams had to shift to remote processes, the information shows promising signs for the profession. It will be interesting to see how these metrics perform currently, though all indicators are pointing towards a continued improvement in efficiency in a tech-enabled future. The next edition of the CloudPay PEI Report is due for publication in September 2022.