Turning Plan Consolidation into a Self-Funding Decision

Story Overview

A multi-entity technology manufacturing company had recently consolidated the benefits programs of six acquired businesses into one unified offering. With that work complete, leadership wanted to evaluate whether moving from a fully insured model to a self‑funded arrangement could lower costs without creating administrative strain for the HR and finance teams.

Challenge

The client was not reacting to an immediate crisis, but the decision carried real financial and operational weight. Once the company had a unified data set, the question became whether self-funding would produce savings and the organization was ready to manage the added complexity of budgeting, claims funding, and day-to-day administration. The status quo of staying fully insured was simpler, but the data suggested it might no longer be the most cost-effective path.

The move to self-funding delivered meaningful early savings while positioning the organization for greater long-term control over healthcare costs.

IMA’s Strategy and Actions

IMA’s employee benefits and people analytics team support the client by:

• Gathering the client’s unified plan and claims information to build a decision-ready financial baseline.
• Modeling fully insured versus self-funded scenarios to show possible savings and the probability of those outcomes.
• Using people analytics tools to translate raw data into a clear side-by-side funding comparison.
• Educating the client on what self-funding would require operationally, including billing, budgeting, and plan administration.
• Coordinating across analytics, consulting, and client leadership to turn the recommendation into a practical implementation plan.

Why It Worked

IMA combined modeling, education, and crossfunctional coordination. The client did not just need a savings estimate. It needed confidence that the projections were grounded in its own data and that the team would support the operational shift that comes with taking on more ownership of the plan.

Key Takeaways

IMA helped the client evaluate self-funding with more clarity than AI or a generic market benchmark could provide. By grounding the recommendation in the client’s own data and pairing that analysis with implementation support, IMA made a less traditional funding approach easier to assess and act on.