Why data is the missing copilot

International mobility is often viewed as an operational support function. This creates valuable data on costs, risks and talent movements along every posting. Professor Stefan Remhof shows how data-driven global mobility creates transparency, reduces risks and becomes a success factor for international mobility.

Global mobility is one of the most data-rich disciplines in HR. At the same time, it is one of the least data-driven HR fields. Every assignment creates a universe of data: visa status, tax risks, cost flows, talent movements, compliance deadlines. And yet for many of us it all ends up in Excel spreadsheets, email chains and isolated tools. That has to change. Not out of technical ambition. But because the costs of our blind flight are simply too high.

The status quo: honest inventory

If we are honest: our level of digital maturity in global mobility rarely delivers what it promises. The most common answer when GM professionals are asked about the status quo? “We’re working on it.” That’s correct. But it’s not nearly enough. “For years, everything was done via Excel and email. We never really knew how much a posting actually costs,” says a GM manager at a German industrial group.

This statement represents a reality that many know but rarely say out loud: manual processes and isolated tools are still the rule, not the exception, in global mobility. This has noticeable consequences for compliance, cost transparency and strategic controllability.

Many of us know the result: we react instead of creating. A compliance problem becomes visible when the deadline has already passed. We only fully record costs in the annual financial statements. And whether a secondment contributed to the success of the business? This question usually remains unanswered. Why? Because we don’t even collect the data for this.

We encounter this pattern regularly in our work at the People Mobility Alliance (PMA). As long as we see global mobility primarily as a compliance function, its full strategic potential remains unused. Moving from reactive management to data-driven, business-integrated mobility strategy is exactly what we are working on with organizations.

This is not a technology problem. It’s our mindset problem. The tools have existed for a long time.

From the operational data grave to the strategic intelligence layer

The decisive leap we need to make in global mobility is not the digitalization of individual processes. It is the networking of our data points to create strategically usable knowledge. Specifically, this means:

• Identify compliance risks early: A well-integrated system automatically flags when someone from the team stays in a country beyond the tax-critical period of stay – before negative consequences arise or even threaten penalties.
• Really understand mobility costs: Not just gross salaries and relocation allowances, but the total cost of assignment – including tax equalization, school and housing allowances, shadowing costs. Only when this number is known can internal negotiations take place.
• Correlating Talent Movements with Business Outcomes: Was the posting successful? This question can only be answered if HR data, performance data and GM data are brought together.
• Use predictive analytics: Which of the posting objectives will become regulatory critical in the future? Which employees are at risk of abandonment? Those who warn early save costs later. A failed assignment costs, on average, two to three times the employee’s annual salary.

The technology landscape: What really helps?

The market for GM technology is growing quickly – and with it our disorientation. Here is an honest assessment:

• HRIS integration as a foundation: Without a clean connection to the central HR system (Workday, SAP SuccessFactors, Oracle HCM), every GM platform is just another data pillar. Integration is a hassle, but it’s not optional.
• Specialized GM platforms: Tools like Equus, Topia or Workflex address the end-to-end process. They offer policy management, cost calculation and compliance tracking in one. The advantage: GM logic is built in. The disadvantage: The integration effort with the existing IT landscape is often underestimated.
• AI-powered compliance tools: In the area of ​​tax and immigration, AI applications are becoming increasingly important – especially for the automatic recognition of shadow payroll obligations, social security risks and visa requirements. There is real added value here, not temporary hype.
• Analytics und Reporting: Self-developed Power BI or Tableau dashboards can be a pragmatic bridge solution. This is especially true for GM teams that don’t have the budget for a complete solution but already have data sitting in various systems.

Attitude decides: From administrator to strategist

Technology is an enabler. But it doesn’t change anything if our attitude doesn’t grow with it. Many of us still act primarily as process facilitators. The crucial question is: What would be possible if we didn’t spend 70% of our time on administration?

The shift requires curiosity and a willingness to learn, not necessarily deep technical know-how. Anyone who understands what questions data answers and what information it can provide becomes a valuable dialogue partner for management and finance. Anyone who rejects this leaves this place to others.

At the same time, we have to learn to deal with ambiguity: no data set is complete. No system solves all of our problems. But we can make good decisions with incomplete information and improve incrementally rather than waiting for the perfect solution.

Five steps to the data-driven GM function

The transformation doesn’t have to start big or expensive. What matters is that we get started.

Step 1: Data Status Audit: Where is our GM data located? In which systems, in what quality? This includes an honest inventory, perhaps even uncomfortable truths.

Step 2: Set priorities: What question would our management most like to see answered? Cost? Compliance risks? Talent retention? We choose a use case that has a quick impact.

Step 3: Start data integration: We connect at least two data sources, e.g. HRIS and GM tool. A simple API connection or automated data export is also a start.

Step 4: Develop Dashboard: We build a simple reporting dashboard, internally with Power BI or Tableau, or via the reporting function of our GM platform. And actively share it with HR leadership and finance.

Step 5: Establish feedback loop: Data is only useful if it leads to decisions. We determine who reviews which key figure and who responds to it. Without clear accountability, every dashboard dies.

What really fails – and how it can still work

GM digitalization projects rarely fail due to technology. They fail because of patterns we all know:

• Our silo mentality: GM, Payroll, Tax and IT are in different departments and don’t talk to each other enough or not at all. Anyone building a GM intelligence system needs allies, especially in finance and IT.
• Fehlendem Executive Buy-in: With GM we are often perceived as an operational support function. We have to actively sell the strategic value of our mobility data, with numbers, not narratives.
• Data protection concerns without a solution: GDPR and international data protection rules are real, but not a killer argument. A clear data governance strategy – who can see what? – is our key.

Conclusion: Earn a seat at the table with data

We in Global Mobility have the potential to be one of the most strategically relevant functions in HR. No other area has a direct influence on talent acquisition, knowledge retention, compliance risk and international growth strategy at the same time.

But we have to continually earn this influence. With data, with transparency, with the courage to make uncomfortable truths visible. Anyone who positions themselves as a pure process service provider will be treated that way. Whoever acts as an intelligence partner gets a different place in the room.

Flying blind is optional. It’s time for us to enter the cockpit.

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