Mobility Operating Diagnostic
Assess policy, suppliers, workflows, controls, data, cost, and experience—then convert findings into a prioritized roadmap.
I help medium and large organizations turn fragmented mobility programs into compliant, scalable, employee-centered operating models—with sharper policy, stronger suppliers, cleaner workflows, better data, and responsible use of AI.
Most organizations do not need another generic recommendation deck. They need a practical operating model that aligns policy, suppliers, systems, controls, and the employee journey.
Engagements can begin with a diagnostic, a defined project, or fractional leadership—then scale only when the business case is clear.
Assess policy, suppliers, workflows, controls, data, cost, and experience—then convert findings into a prioritized roadmap.
Modernize tiers, eligibility, benefits, exceptions, documentation, and governance for consistency and scalability.
Design and manage RFI/RFP processes, score suppliers, negotiate value, and establish performance accountability.
Map end-to-end mobility workflows and improve the flow of data across HRIS, payroll, vendors, and reporting.
Diagnose underperforming regions or suppliers, identify root causes, and build a focused turnaround plan.
Identify useful AI opportunities while protecting employee data, decision quality, human oversight, and auditability.
Understand the current state, stakeholder needs, root causes, risks, and available data.
Build the policy, workflow, supplier, technology, or governance solution around real constraints.
Translate recommendations into owners, milestones, decisions, communications, and measurable progress.
Establish reporting, decision rights, controls, and feedback loops that keep the program healthy.
That means independent advice across policy, suppliers, systems, service delivery, cost, compliance, and employee experience—with an operator’s understanding of what can actually be implemented.
“The best mobility programs make complex cross-border decisions feel clear, controlled, and human.”Christopher Lagerman, Founder & Principal Advisor
A practical framework covering operating model, service, technology, implementation, governance, pricing, and risk.
Read the guide →Start with business and talent objectives, then redesign tiers, governance, exceptions, data, and communications.
Read the guide →Use AI to reduce friction and surface risk without giving up privacy, human judgment, or accountability.
Read the guide →Review the policy when exceptions are rising, business models have changed, benefits are inconsistent, costs are difficult to explain, or the policy no longer supports current talent and workforce strategy.
Evaluate operating model, service quality, geographic capability, technology, data, compliance controls, implementation, pricing, governance, employee experience, and the supplier’s ability to improve over time.
Responsible AI can support policy guidance, cost estimates, case summarization, exception detection, workflow routing, reporting, and early risk identification when privacy, data controls, human review, and accountability are built in.
It is a structured review of policy, workflows, suppliers, data, governance, compliance, cost, and employee experience that identifies root causes and produces a practical, prioritized improvement roadmap.
A focused conversation can clarify the issue, the stakeholders, and the fastest path to a durable solution.