OpsIgnite 2026 in Vancouver brought together operational leaders from the payer ecosystem for several days of sessions, workshops, and excursions focused on how health plans actually operate day to day, not just how they are measured or reported.
One thing that became clear early in the week was how often very different conversations point to the same underlying friction.
Across the caucuses from AI to Membership and Claims to Strategic Execution, the challenges felt familiar and consistent enough to feel connected. It wasn’t isolated to one function or one team. It was showing up across the system in different forms.
In our own session, Kiran Simhadri, Client Relationship Director at Concord, and Jeff Ahlers, Vice President of Finance and Corporate Controller at Blue KC, co-presented on the challenges of Administrative Services Only (ASO) billing. What started as a finance-focused discussion quickly expanded, as billing sits downstream of multiple operational processes. When something is misaligned upstream, it shows up very clearly in billing outcomes.
That made ASO billing a useful way to ground what we see across the broader operating environment.
Most health plans invest heavily in data, analytics, and reporting. That foundation is relatively mature in many organizations and continues to evolve.
The challenge is what happens after insight is created.
Across claims, finance, IT, and care teams, there are still disconnects that make it difficult to move from insight to consistent action. Teams often operate from slightly different interpretations of the same data, or work within systems that are not fully aligned. Insights are generated, but they frequently remain within dashboards or reports rather than translating into changes in how work actually gets done.
When processes span multiple teams, the handoffs introduce additional friction. Context gets lost, timing shifts, and decisions take longer to carry through.
Individually, none of this is unusual. But when it shows up repeatedly across the organization, it becomes a structural issue rather than a series of isolated inefficiencies.
Self-insured arrangements continue to grow as employers look for flexibility, control over plan design, and clearer visibility into costs. However, the operational processes supporting those arrangements have not evolved at the same pace. With the growth of ASO arrangements comes additional complexity and cost.
In many cases, billing still depends on a mix of manual effort, spreadsheets, and delayed reconciliation cycles. Finance teams spend significant time assembling and validating invoices across systems that do not fully align. Payments often require follow-up, and visibility into accounts receivable may only surface issues after they have already developed.
From the outside, these can look like routine operational challenges. Inside the organization, they translate into real cost and effort, whether through increased interest expense, extended settlement cycles, or the operational burden required to keep the process moving.
More importantly, billing often reflects upstream conditions. When data is inconsistent or systems are not well connected, it becomes harder to produce accurate, timely outputs without introducing manual workarounds.
The approach we walked through in our session focuses on reducing those disconnects rather than trying to optimize around them.
Instead of treating billing as a series of separate steps, the model brings together agreement configuration, claims data, invoicing, payments, and reconciliation into a single, connected system on Microsoft Azure. Invoices are generated directly from claims activity, payment status is visible in real time, and exceptions can be identified earlier in the process rather than after the cycle has closed.
Employer groups also have access to their own data, including invoices, payment history, and claims experience, which reduces the need for back-and-forth communication and provides more transparency into how their plans are performing.
The goal is not just to reduce effort. It is to make the process behave like a continuous system, where information moves with the work instead of being reassembled at each step.
AI came up frequently across sessions, and the tone throughout the week was notably pragmatic. There is clear interest and meaningful progress, but most organizations are still working through what it takes to move from experimentation to something that can operate reliably at scale.
What stood out is that many AI efforts are still structured outside of core workflows rather than inside them.
Teams are experimenting with use cases, but those use cases often sit alongside existing systems rather than being embedded into them. That creates fragmentation in how AI is used, governed, and scaled across the enterprise.
We heard examples where AI workflows performed well in early testing, but become harder to manage once they are exposed to real operational conditions. In some cases, changes in underlying models or dependencies introduced variability that existing processes were not designed to absorb. This created additional effort to stabilize outputs or rework how those workflows were integrated into production environments.
At the same time, AI initiatives are often being developed in parallel across teams. That creates momentum, but it also makes it difficult to align priorities, standardize approaches, or build toward shared outcomes.
The opportunity is to design AI use cases so they operate inside existing workflows rather than alongside them.
What stood out most over the course of the week is how similar these challenges look, even when they show up in different areas.
In ASO billing, the issue appears as delays, manual effort, and limited visibility.
In AI, it shows up as scaling challenges, governance complexity, and difficulty embedding into operational workflows.
In both cases, the constraint is not capability. It is how work moves across systems, teams, and processes.
When systems are fragmented, work becomes a series of handoffs. When systems are connected, work behaves like a flow.
The discussion in Vancouver was not necessarily novel, but it felt more urgent.
Healthcare organizations have made real progress in how they collect and analyze data. The next step is ensuring that progress translates into how work actually gets done.
ASO billing makes the gaps visible in finance. AI is surfacing similar gaps in new and evolving ways. Both point to the same underlying reality. The constraint is no longer visibility. It is consistency in how work moves through the organization.
That is where we spend much of our time with healthcare payers.
At Concord, we work with health plans to connect the operational and data layers that sit underneath these challenges, whether that is modernizing billing and finance workflows, improving digital member experiences, or helping teams embed AI into real production environments rather than isolated pilots.
The focus is not on adding more tools. It is on helping existing systems work together more effectively so that decisions, data, and execution are aligned in practice, not just in reporting.
For teams exploring ASO billing specifically, we typically start by grounding the conversation in their current operating reality, including group count, settlement cycle time, and line of credit terms. That alone is often enough to surface where cost and delay are building.
From there, the engagement is straightforward:
01. Discovery call
We map the current billing workflow and identify where breakdowns are occurring across systems and teams.
02. ROI model
We build a financial view using actual group mix, payment behavior, and contract terms to quantify impact in real terms.
03. Live demo
We walk through the platform configured to the organization’s actual structure so teams can see how billing, reconciliation, and visibility would work in practice.
The goal is not to reframe the problem. It is to make the impact visible against the operating reality that already exists. Because in most cases, the challenge is not understanding what is happening. It is making it work consistently at scale.
Are you seeing friction like this in your organization? Whether across ASO billing, AI initiatives, operational workflows, claims settlement, provider incentives, or risk adjustments, we have expertise in building a streamlined operating model.
At Concord, we work with health plans to understand how systems, data, and workflows are operate today, and where the disconnects are creating cost, delay, or inconsistency. Ready to see it against your own numbers? We can model the plan-specific ROI after an initial conversation.
Not sure on your next step? We'd love to hear about your business challenges. No pitch. No strings attached.
