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Case Study

Contact Center Misrouting: How a Health Insurer Saved $1.84M Annually

Using Speech Analytics and Root Cause Analysis to fix Contact Center routing at scale



When Members Can't Find the Right Help, Everyone Pays

Contact center optimization is one of the most underestimated cost levers in health insurance. When a member calls the wrong channel for support (e.g. the insurance division instead of the employee benefits and administration team), the consequences compound quickly; the call gets transferred and the member repeats their issue. When the caller repeats their issue, handle times balloon, and agents on both ends absorb the work. What looks like a member experience problem is also a hidden operational expense.

The challenge is structural. Health insurance contact centers often sit at the intersection of multiple support functions (benefits administration, clinical services, eligibility, claims) and members have no reliable way to know which one handles their issue. Without clear ownership and smart routing logic, even well-staffed contact centers generate unnecessary volume. Understanding why members misroute, and fixing the conditions that cause it, is the difference between managing demand and reducing it. Contact center analytics provide the visibility to tell the difference.

Client Opportunity

Our client is a large health insurance organization serving a substantial commercial membership base. The health insurer had multiple member support channels in place and a contact center operation, but persistent routing issues were creating friction that they couldn’t quite make sense of.

Members were frequently entering the wrong support channel for their issue, most often contacting the insurer directly for matters that should have been directed to their employer's benefits administration team. The Interactive Voice Response (IVR) system wasn't catching the mismatch, and once a misrouted call arrived, agents had limited options beyond transferring the member, which added hold time and required the member to re-explain their situation.

Leadership recognized the problem but lacked objective, call-level data to quantify it or identify where the largest opportunities existed. The Andrew Reise team was engaged to conduct that analysis and translate findings into a prioritized action plan.

The Challenge

Members were regularly entering the wrong support channel, driving up handle times, increasing transfer volume, and creating a fragmented experience that undermined satisfaction and efficiency. The problem was distributed across the contact center and partially hidden by how performance data was being captured.

Insurance agent consulting on computer in customer support

Unclear ownership between support organizations

Members had no reliable way to determine whether their issue belonged with their employer's benefits team or the insurer directly. This ambiguity wasn't addressed before the call was placed, which meant misrouted contacts entered the queue and required human intervention to redirect. Andrew Reise has seen this pattern before in health insurance CX engagements: unclear ownership at the support channel level is one of the most common and most costly experience design gaps in the industry.

IVR routing that couldn't catch the problem

The existing interactive voice response system wasn't designed to screen for organizational ownership issues. Members who selected the wrong path weren't redirected, they were connected, and the misrouting became apparent only once an agent was on the line.

Transfers that extended every interaction

Once a misrouted call was identified, agents were required to transfer the member to the correct organization. Those transfers came with hold time, and members often had to re-explain their issue entirely, extending handle time and compounding frustration on both sides.

Inconsistent call-handling practices

Even within correctly routed calls, variation in how agents handled transfers and complex inquiries contributed to longer call durations. The connection between quality assurance and employee experience is direct: when agents lack consistent protocols and coaching, the impact of upstream process failures gets amplified on every call.

Our Role

Andrew Reise was engaged to conduct a data-driven root cause analysis of contact center misrouting, quantify the operational and experience impact, and deliver a prioritized set of recommendations to reduce avoidable contact volume and improve routing accuracy.

The engagement drew on four of Andrew Reise's core methodology areas:

    • CX (Customer Experience): Analyzed how members navigated support channels and identified where confusion drove misrouting behavior

    • EX (Employee Experience): Evaluated agent tools, processes, and call-handling protocols that contributed to or prolonged transfer activity

    • Contact Center Operations: Assessed routing architecture, IVR logic, and call-level performance data to identify structural inefficiencies

    • DX (Digital Experience): Identified opportunities to improve pre-call member guidance through self-service channels to reduce demand before it entered the queue

1. Discovery and data collection

The engagement began with speech analytics applied to a representative sample of member calls. Call-level operational data was layered in to establish baseline performance metrics, including handle time, transfer rate, and first-contact resolution. This combination gave the team visibility into behaviors that wouldn't appear in aggregate reporting, including how often members verbally indicated they weren't sure where to call and how frequently agents flagged routing issues mid-call. Journey analytics were also applied to understand how routing failures connected to broader member experience patterns.

2. Current state assessment

The team mapped the full routing journey, from how members selected their support channel to how calls were handled once they arrived. IVR logic, transfer protocols, and call-handling practices were each evaluated. The assessment identified where routing decisions were made, where they failed, and what operational requirements (hold time thresholds, transfer procedures) amplified the impact of each misrouted call.

3. Analysis and synthesis

Findings were organized by root cause category. The analysis distinguished between calls that misrouted because of unclear member guidance (a CX issue), calls that misrouted because of IVR logic gaps (a technology issue), and calls that became unnecessarily long because of how transfers were handled (a process and EX issue). Each category had a different fix profile and different cost implications. This is the same methodology Andrew Reise used to uncover $2.3 million in annual savings for a separate insurance client by using speech analytics to identify digital friction driving unnecessary call volume.

4. Recommendation development

Andrew Reise consolidated findings into a prioritized roadmap spanning CX, EX, DX, and contact center operations. Recommendations addressed IVR routing logic, pre-call member guidance improvements, transfer protocol standardization, and agent coaching opportunities. AI-supported tools for agent performance coaching were identified as near-term enablement opportunities, consistent with the approach outlined in Andrew Reise's guide to AI-powered coaching programs.

5. Enablement output

The client received a practical roadmap with recommendations organized by effort level and estimated impact. The engagement also established a repeatable framework for ongoing optimization, giving the organization the internal capability to continue monitoring and reducing avoidable contact volume without requiring a new external engagement each cycle. 

 

Industry
Health Insurance

Case Study Attribute
Contact center optimization, customer experience 

Results

  • The engagement generated an estimated $1.84 million in annual benefit
  • Transfer-related inefficiencies were measurably reduced, shortening average call duration and freeing agent capacity
  • Members became significantly more likely to reach the correct support resource on the first attempt
  • The organization gained structured visibility into the operational drivers behind unnecessary contact volume
  • A repeatable optimization framework was established

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How Much Is Contact Center Misrouting Costing You?

If your organization is seeing high transfer rates, rising handle times, or avoidable contact volume that you can't fully explain through existing reporting, the answer is usually structural, and it's usually findable. Book a discovery call to talk through where the friction is.

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Frequently Asked Questions

What is contact center misrouting and why does it cost so much?

Contact center misrouting happens when a member calls the wrong support channel for their issue, such as contacting a health insurer directly for a matter their employer's benefits administration team should handle. The cost compounds quickly: the call gets transferred, the member re-explains their issue, handle times balloon, and agents on both ends absorb the extra work. What looks like a member experience problem is also a hidden operational expense, and in this engagement, fixing the conditions that caused it generated an estimated $1.84 million in annual benefit.

Why does misrouting happen in health insurance contact centers?

Misrouting happens because health insurance contact centers sit at the intersection of multiple support functions (benefits administration, clinical services, eligibility, claims) and members often have no reliable way to know which one handles their issue. In this case, three causes compounded: unclear ownership between the insurer and the employer's benefits team, an IVR system that wasn't designed to catch the mismatch and simply connected misrouted callers, and transfer procedures that added hold time and forced members to re-explain themselves. Each cause had a different fix, which is why diagnosing them separately mattered.

How does speech analytics help fix contact center routing problems?

Speech analytics helps by revealing behaviors that never show up in aggregate reporting, such as how often members verbally indicated they weren't sure where to call and how frequently agents flagged routing issues mid-call. In this engagement, speech analytics was applied to a representative sample of member calls, then layered with call-level operational data on handle time, transfer rate, and first-contact resolution to establish a baseline. That combination made it possible to separate calls that misrouted because of unclear member guidance from those that misrouted because of IVR logic gaps, and to size each opportunity before recommending a fix.

What's the difference between managing call demand and reducing it?

Managing demand means staffing and handling the calls that come in; reducing it means eliminating the conditions that generate avoidable calls in the first place. The distinction matters because even well-staffed contact centers produce unnecessary volume when routing logic and channel ownership are unclear. In this engagement, understanding why members misrouted (rather than just handling the misrouted calls faster) is what surfaced the structural fixes across IVR routing, pre-call guidance, transfer protocols, and agent coaching that reduced the volume at its source.

How do you reduce transfer volume without adding new technology?

You reduce transfer volume by fixing the upstream conditions that create misrouted calls and by standardizing how agents handle the transfers that remain, rather than adding a new platform. In this case, the recommendations addressed IVR routing logic, pre-call member guidance through self-service channels, transfer protocol standardization, and targeted agent coaching, all organized into a roadmap prioritized by effort and estimated impact. The engagement also left the organization with a repeatable framework to keep monitoring and reducing avoidable contact volume on its own, without a new external engagement each cycle.

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