Why nobody can see mobility costs: the fragmentation problem
Global mobility is one of the few corporate functions where spending six figures per employee per year on an activity is normal, and where not knowing the reconciled total is also normal. The cause is not negligence. It is an industry structure that fragments every assignment's data across more vendors than any mid-sized program can integrate. This page lays out the measured state of mobility data in 2026, why the fragmentation persists, and what a fix has to look like.
The stack: six to nine vendors per program
A mid-market program (50 to 500 assignees) typically runs across payroll providers in home and host countries, a tax firm, immigration counsel, a relocation management company, a cost-of-living data subscription, housing and schooling providers, insurance, and an HRIS. Six to nine vendors is what mobility and finance leaders consistently describe in our buyer conversations; we present that as field observation rather than a survey statistic, because no survey publishes it. What the surveys do publish is the consequence.
The measured state: spreadsheets and distrust
KPMG's 2025 Global Mobility Benchmarking Report, covering 456 multinationals across 29 jurisdictions, found 72% of organizations describe their mobility reporting and analytics as largely spreadsheet-driven, versus 16% using analytics engines such as Power BI or Tableau. The named obstacles are structural, not skills-based: data spread across multiple systems (55%), cost constraints (44%) and lack of data integrity (43%). Demonstrating ROI has become the number one challenge for 31% of mobility leaders, displacing cost reduction itself.
EY's 2026 Mobility Reimagined Survey (1,038 respondents) quantifies the trust side: only 51% of employers say their mobility data is accurate, just 47% say their technology platforms are reliable, and 62% of mobility team time goes to reactive ad hoc requests. EY also measures what trust is worth: the minority of functions qualifying as high-trust move talent more than twice as fast. And it names the 2026 paradox: 72% of mobility functions are scaling GenAI and agentic AI, on data only half of them trust.
Why it persists: variety, not volume
Assignment volumes are stable to growing (Mercer's 2025 policy survey finds 34% of organizations expect mobility activity to increase), but the shape of activity is what multiplies the data problem. KPMG finds 70% of organizations now use short-term assignments, 52% offer workations under 30 days, 29% allow arrangements under 90 days and 23% permit permanent cross-border remote work. Five assignment types across twenty corridors generate more reconciliation surface than a hundred identical long-term moves: each type touches a different subset of vendors, on different billing rhythms, with different tax treatment. Every new flexibility policy is, operationally, a new data shape that nobody owns end to end.
Why more software has not fixed it
The software that could integrate this exists, but it was priced and distributed for the top of the market: Deloitte runs a formal alliance reselling Equus-based mobility management, and Mercer's cost estimates are produced with the same AssignmentPro platform under license. Large enterprises absorb 65% of relocation-software spend. Meanwhile Deloitte's 2024 survey found organizations planning to optimize existing technology rather than add more tools: understandable, when each added tool is another unreconciled feed. The mid-market's rational response has been Excel, which at least holds everything, badly.
What a fix has to look like
The fix is not another system of record asking eight vendors to change how they work. It is a semantic layer over the stack you already run: ingest every feed as it is, infer what columns mean and which records refer to the same assignee or assignment across systems, have a human confirm each join once, and compute deterministically from then on. Joins are the crux: a figure that silently crossed a wrong join is worse than no figure. That is why Ask & Chart's key magnet proposes matches with evidence and confidence, warns where a join would fan out or double-count, and never accepts an ambiguous match without a human. Once the model is confirmed, the questions that used to take weeks (fully loaded cost by corridor, actuals versus estimate, variance to budget) become deterministic queries with provenance attached, and the discrepancy scorecard turns reconciliation from an annual archaeology project into a weekly routine.
Frequently asked questions
How many companies still run mobility reporting on spreadsheets?
72%, per KPMG's 2025 benchmarking of 456 multinationals; only 16% use analytics engines.
Do we have to replace our vendors to fix this?
No. The fragmentation problem is the joins between vendor outputs, not the vendors. A semantic layer ingests the feeds you already receive; your payroll, tax and relocation relationships stay as they are.
What is a human-confirmed join?
A proposed match between records in different systems (the same assignee in payroll and in the RMC file) that a person reviews and approves once, with evidence shown. Every figure computed afterwards inherits that confirmation instead of an invisible assumption.