Payrollminds
Payrollminds

2 min read

Webinar – How can you identify global payroll risk before a crisis forces the conversation?

Payroll is a critical business function, but many organizations still rely on assumptions that don’t hold up in day‑to‑day operations. As a result, leaders face escalations, surprises in total cost, and a lack of data visibility and control.

On June 2, 2026, in 45 minutes, two specialists from UKG and Payrollminds will debunk three common assumptions about accuracy, data management and local compliance – and share what leading organizations do differently.

Three payroll myths

Myth 1: “Our SLAs prove payroll is accurate and efficient.”

On paper, high SLA scores suggest everything is under control. In reality, they can mask issues that only show up in total cost, internal effort and employee experience.

Myth 2: “Global visibility requires local payroll engines connected to one vendor.”

Many organizations assume vendor consolidation is the only route to data transparency. We will explore why this can create unnecessary risk and delay real insight.

Myth 3: “Owning the local engines guarantees the best compliance.”

Engine ownership sounds like a shortcut to compliance and expertise. We will look at where compliance really sits – and what that means for your future operating model.

Speakers:

•  Michael Jetten – Senior Director Value Advisory EMEA at UKG
•  Kira Rubiano – Partner Payrollminds US

Key insights

In the webinar, you will learn how to:

  • Spot when “green” SLAs hide real payroll issues
  • Gain global visibility and control while staying flexible with providers
  • Test if your operating model still fits your organization
  • Ask sharper questions in your next payroll transformation

This session is designed for leaders and senior specialists in global payroll, HR, shared services and finance. Use this session to stress‑test your current assumptions and set a more realistic, data‑driven direction for your global payroll strategy.

Learn more and register for the webinar here:

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