How Insurers Can Diagnose Claims Workflow Friction Before Redesigning the Process

Claims workflow friction is rarely caused by one broken step.

When claims slow down, the visible symptoms are easy to recognise. Customers wait longer for updates. Brokers chase for progress. Claims handlers spend more time moving between systems, escalating blockers or finding the right internal contact. Service teams see more requests and incidents linked to claims platforms, access, integrations or handoffs.

The harder question is what is really causing the friction.

A claims workflow may look like a process problem when the root cause sits in service ownership. It may look like a technology problem when the real issue is unclear routing. It may look like a resourcing issue when the data points to repeated rework, weak knowledge or avoidable contact. It may look like a claims operations issue when release-related incidents are disrupting the services claims teams depend on.

That is why insurance claims workflow management should start with diagnosis before redesign.

Insurance claims workflow management is the structured management of the services, handoffs, data, controls and performance measures that support claims operations. It helps insurers understand how claims work moves through the organisation, where friction is being introduced and which improvements should be prioritised.

At Fusion GBS, we help insurers build this evidence baseline through Service Management Scorecards, AI Talos analysis and Value Adoption Services. The goal is not to redesign the claims process from assumption. The goal is to identify where insurance service management is slowing claims down, then target the improvements that will make the biggest measurable difference.

 

What is claims workflow friction?

Claims workflow friction is anything that slows, disrupts or obscures the movement of claims work from intake to resolution.

It can appear when claims are captured, categorised or routed. It can appear during assessment, when internal teams, suppliers or third parties need to provide input. It can appear during customer or broker communication, when status visibility is weak. It can also appear after platform change, when a release affects a claims system, integration or service dependency.

The important point is that friction is not always visible as a single failure. It often appears as extra effort. A claims handler checks multiple systems instead of one. A broker follows up because progress is unclear. A service team reassigns the same request type repeatedly. A platform team resolves an incident, but the same disruption returns after the next release.

Over time, this friction becomes part of the operating model. Teams work around it. Manual steps become normal. Escalation depends on individual relationships. The claims workflow still moves, but it moves with avoidable cost, delay and risk.

 

Why claims workflow friction is hard to diagnose

Claims workflows are difficult to diagnose because they cross many teams, systems and ownership boundaries.

A single claims journey may involve claims handlers, customer service, brokers, policy administration, finance, legal, fraud, suppliers, loss adjusters, platform teams and service management teams. Each team may see only one part of the journey. Each system may hold only part of the evidence. Each function may measure success in a different way.

That makes it easy to mistake a symptom for the root cause.

A claims backlog may be treated as a staffing issue when the underlying problem is unclear triage. A spike in broker contact may be treated as a communication issue when the real cause is poor claims status visibility. A long resolution time may be treated as a claims process issue when the delay is caused by supplier handoffs or weak escalation routes.

This is why insurers need more than anecdotal evidence.

They need a connected view of claims operations, service management and change activity.

Insurance service management provides that wider view. It connects service operations, change and performance across claims, broker, policy and billing workflows, helping insurers improve stability, reduce operational risk and support evidence-led improvement.

 

Why redesign should not be the first assumption

When claims friction is visible, the instinct is often to redesign the process.

That can be the right answer, but it should not be the first assumption. A redesigned process may still underperform if the supporting service environment remains weak. New workflow steps will not solve unclear ownership. Automation will not fix poor data quality. A portal will not reduce contact if brokers still cannot see meaningful progress. A new operating model will not create stability if release activity continues to disrupt claims services.

Before redesigning the process, insurers should understand what type of friction they are dealing with.

Some friction is caused by routing. Claims-related work may enter through different channels and arrive in the wrong queue. Some friction is caused by ownership. Teams may be unclear about who is accountable for resolving a blocker. Some friction is caused by visibility. Claims handlers, brokers or service teams may not be able to see status, dependency or next action clearly enough. Some friction is caused by change. Releases may affect claims systems or integrations without enough operational readiness.

Each cause needs a different response.

That is why diagnosis matters.

 

How service data reveals the real cause

Service data can show patterns that are difficult to see from process mapping alone.

A process map might show the intended claims journey. Service data can show how work actually moves, where it waits, where it repeats, where it is reassigned and where it fails. It can show whether claims-related requests are concentrated around particular services, teams, channels, platforms or release windows.

If claims handlers frequently raise the same support request, the issue may be knowledge, access or system usability. If claims-related tickets are repeatedly reassigned, the issue may be unclear ownership or catalogue design. If broker follow-up increases after a platform release, the issue may be release readiness or post-release validation. If cycle time increases at the same point in the journey, the issue may be a supplier handoff or fulfilment bottleneck.

This is where claims workflow diagnosis becomes more useful than opinion-led improvement. The insurer is no longer asking, “Where do we think the problem is?” It is asking, “What does the evidence show?”

 

How AI Talos supports claims workflow diagnosis

AI Talos helps insurers interpret complex service management data and identify patterns that support better prioritisation.

Claims workflow friction rarely sits in one clean dataset. Evidence may appear in service requests, incident descriptions, assignment history, change records, knowledge usage, availability data, operational notes and free-text comments. Some of that data is structured. Much of it is not.

In a claims context, AI Talos can help identify where the service management signals point. It may show repeated routing problems, clusters of claims-related incidents, recurring knowledge gaps, change patterns linked to disruption or fulfilment paths that create delay.

The output should not be a vague recommendation to “improve the claims process.” It should help the insurer understand which friction points matter most and where targeted action is likely to create measurable value.

 

What insurers should measure

The right measures depend on the insurer’s operating model, but they should connect claims performance with service management performance.

Claims cycle time is important because it shows the overall movement of work. Time to resolution helps show how quickly claims-related service issues are being handled. First contact resolution can indicate whether broker, customer or internal service requests are being resolved at the earliest appropriate point. Repeat contact can show where status visibility or communication is weak. Reassignment rates can reveal unclear ownership. Escalation volume can show where normal service paths are not working.

Service availability and release-related incidents are also important. Claims operations depend on stable platforms and integrations. If change activity causes disruption, the claims workflow will feel the impact even when the claims team is not the source of the problem.

The goal is not to build a large metrics catalogue.

The goal is to build a scorecard that shows where friction is affecting claims performance and what should be improved first.

 

From diagnosis to claims workflow orchestration

A Service Management Scorecard helps insurers move from scattered evidence to prioritised action.

Without a scorecard, teams may focus on whichever issue is most visible. One team improves a form. Another updates a workflow. Another investigates a platform issue. Each action may help, but the insurer may still lack a connected view of which improvements will create the greatest impact.

Once the baseline is clear, the roadmap can follow the evidence.

• If the biggest issue is misrouting, the priority may be service catalogue redesign and assignment logic.
• If the issue is repeated broker contact, the priority may be status visibility and communication workflows.
• If the issue is release-related disruption, the priority may be change governance uplift.
• If the issue is repeated manual work, the priority may be workflow orchestration or knowledge improvement.

This makes claims workflow orchestration more effective because it is applied to the right problem. The insurer is not automating or redesigning from assumption. It is improving the areas where service data shows the greatest friction.

Making claims workflow improvement evidence-led

Claims workflow friction will not disappear through process redesign alone.

Insurers need to understand how claims work moves through the organisation, where service management is adding delay, where ownership is unclear and where change activity is creating instability. Once those patterns are visible, improvement becomes more targeted.

Insurance claims workflow management gives insurers the structure to do that. It connects claims operations with service data, workflow orchestration, change governance and measurable outcomes.

Our Service Management Scorecards, AI Talos analysis and Value Adoption Services help insurers turn claims workflow friction into a focused improvement roadmap.

Request your insurance service management scorecard to identify where claims workflow friction is slowing service performance across your insurance operations.

 

FAQ

What is claims workflow friction?

Claims workflow friction is any delay, handoff, rework, visibility gap or service issue that slows the movement of claims work from intake to resolution. It can be caused by routing, ownership, supplier handoffs, platform instability, knowledge gaps or change activity.

What is insurance claims workflow management?

Insurance claims workflow management is the structured management of the services, handoffs, data, controls and performance measures that support claims operations. It helps insurers understand where claims workflows are slowing down and which improvements should be prioritised.

 

Why should insurers diagnose claims friction before redesigning the process?

Insurers should diagnose claims friction before redesigning the process because the visible problem may not be the root cause. A claims delay may be caused by unclear ownership, poor routing, supplier dependency, weak service visibility or release-related disruption rather than the claims process itself.

 

What metrics help diagnose claims workflow friction?

Useful metrics include claims cycle time, time to resolution, first contact resolution, repeat contact, reassignment rates, escalation volume, claims-related incidents, service availability and release-related incidents.

 

How do we help insurers diagnose claims workflow friction?

At Fusion GBS, we help insurers diagnose claims workflow friction through Service Management Scorecards, AI Talos analysis and Value Adoption Services. This creates an evidence baseline that helps prioritise claims workflow orchestration, service improvement and change governance uplift.