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CloudPay: Changing the Performance Mindset with Payroll Efficiency Index

 

This past month, NelsonHall published its annual Next Generation Payroll Services report, which found that buyers and clients of managed payroll services are keenly focused on engaging ‘next generation’ technologies that can enable payroll operating model transformation. Thus, organizations are increasingly seeking out managed payroll services providers that can provide access to these modern technologies and optimized operating models.

New technologies are making a real impact on payroll. Modern cloud platforms, seamlessly connected by advanced APIs enabled with AI, and robust analytic reporting capabilities are collectively transforming the way payroll operates from kickoff to close. And more importantly, they are providing deep insights into some of the richest yet underutilized data sets in the organization. This data is where the real story lies and where the real impact can be made for payroll transformation, assuming the data is reliable and interpreted appropriately.

While managed service providers and the payroll practitioners they support are gaining access to powerful reporting tools and robust data sets, many continue to take a very legacy approach to how they measure payroll, often focusing mostly on timeliness, accuracy, and various other ‘surface level’ metrics alone. 

However, CloudPay, a leading provider of payroll services globally, is aiming to disrupt the way practitioners, and the industry at large, view payroll performance by launching a new Payroll Efficiency Index (PEI).

CloudPay’s Payroll Efficiency Index (PEI)

With the PEI, CloudPay is seeking to help practitioners push much deeper into payroll performance analysis, to truly understand how payroll is performing globally – overall, but more importantly at the macro level, to identify the core failures and opportunities at the source.

The PEI is based on five core Key Performance Indicators (KPIs):

  1. First Time Approvals: % of gross-to-net calculations approved upon initial review
  2. Data Input Issues: % of data errors caused by incorrect or incomplete input of employee data
  3. Issues per 1k Pay-slips: Number of data issues identified for every 1k pay-slips processed
  4. Calendar Length: Number of days required to complete payroll processing (lock to approval)
  5. Supplemental Impact: % of payroll runs completed as supplemental runs.

CloudPay has enabled the PEI benchmarking capability by way of its unified data model and standardized workflows and leverages a rich global payroll data set derived from across ~2.5k global entities and >1m pay-slips processed on the CloudPay platform (all anonymized, of course). The PEI provides benchmarking data against the five KPIs, including country-level performance details for over 130 countries where CloudPay operates and supports its client base. Most importantly, clients can make an “apples to apples” comparison to benchmark within their industry, size, and global footprint to truly benchmark their performance.

CloudPay plans to launch the first iteration of the PEI report as part of global payroll week (week of April 29th) which will provide data derived from calendar year 2018. Moving ahead, the complimentary report will be published each year in Q1 for the prior year. Additionally, CloudPay plans to launch quarterly versions of the report throughout the year, which will focus on deeper dives and analysis into specific geographies and regions.

Clients of CloudPay are already benefiting from the PEI as an embedded methodology within their managed services programs. Every CloudPay client has access to a full suite of analytics tools that help them understand their payroll data – including predictive, descriptive, and diagnostic data combined with the same benchmarking capabilities leveraged to derive the PEI. 

Clients can customize their payroll diagnostic dashboard to include the five KPIs and other metrics, including the ability to drill deeper into each one for valuable insights into the process performance globally. Further, CloudPay is incorporating these same five KPIs into every client contract and engages each client (monthly) to address key opportunities based on the KPIs – a practice CloudPay has seen high client adoption for since the launch of its benchmarking capability in Q1 2019.

Putting CloudPay’s PEI into Context

Historically speaking, payroll has struggled to truly leverage and engage the totality of the data it produces, and at no fault to the practitioners that operate in the space. Too many legacy solutions have been derived from disparate systems that lacked integration, automation, and the advanced reporting capabilities we see today. 

However, despite the payroll services market making massive leaps forward, not all solutions are delivering the transformation desired. NelsonHall’s Payroll Services Client Perspective Report (publishing soon) finds that a leading area of dissatisfaction for payroll services buyers is the lack of overall innovation to drive process improvements from their providers.

CloudPay has addressed this issue by developing a next-generation payroll technology ecosystem (one that incorporates a modern cloud platform, with seamless APIs that move data in and out of payroll), and paired that with standardized workflows, embedded analytics, and processes augmented by RPA, to enable reliable global payroll reporting and KPIs on demand. This technology ecosystem, purpose-built for global payroll, is CloudPay’s differentiator, and its benchmarking capability and the PEI output is a direct derivative of that ecosystem.

CloudPay’s transparency around the PEI report is certainly unusual. While the initial data points are mostly slanted toward client-derived issues, I can’t recall a payroll vendor that has ever released this level of insight into its operations, which I believe demonstrates the confidence CloudPay has in its solution and further validates its effectiveness in delivering payroll transformation to its clients.

Further, I believe the PEI is a step in the right direction to helping the industry begin to think differently about how payroll effectiveness is measured and viewed – helping shift the mindset away from surface level metrics and SLAs and starting to leverage modern technology to question and analyze a deeper set of KPIs that digs further into why payroll performs the way it does, and supplies practitioners with the insights they need to take transformative action. 

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