Problems in customer service
Enterprises today face mounting pressure to resolve customer issues quickly, accurately, and empathetically. However, they frequently stumble, providing disjointed support experiences that drive up costs and damage brand loyalty. Solution Designers must look beyond surface symptoms of the contact center to address the structural root causes across the enterprise:
Agent cognitive overload and system fragmentation
- Symptom: Agents experience high average handle time (AHT), burnout, and frequent errors due to "swivel-chair" operations as they manually navigate dozens of disconnected screens.
- Root cause: Legacy desktop environments do not unify core systems, so agents act as the manual integration layer between them.
Broken resolutions and limited process visibility
- Symptom: Slow resolution times, dropped handoffs, and customers who repeatedly call for status updates on complex, multi-step requests.
- Root cause: The organization treats customer service as a front-office interaction only and lacks the end-to-end workflow automation needed to orchestrate fulfillment across the back office.
Reactive service model and ineffective self-service
- Symptom: Overwhelming inbound call volumes for routine queries and a reactive approach that addresses problems only after the customer complains.
- Root cause: Self-service channels operate in isolation from underlying systems, and the organization lacks event-driven intelligence to detect anomalies, automate routine work, and resolve issues before customers experience them.
Persona pain points and the diagnostic translation layer
In customer service, business stakeholders often focus on metrics such as AHT (average handle time), CSAT (customer satisfaction), and cost-to-serve. When they describe their pain points, they are describing symptoms of a broken operating model. The Solution Designer must translate these into structural workflow and integration failures.
1. The contact center leader (VP of Customer Service / Call Center Director)
Focuses on agent productivity, AHT, agent attrition, and operational costs.
| What they say (the symptom) | What it actually means (the root cause) |
|---|---|
| "Our agents take way too long to resolve calls, and new hire training takes months." | Agents act as the manual integration layer and manually navigate more than 10 disconnected legacy systems to find information. |
| "Our agents make too many compliance and process errors." | The system lacks prescriptive, step-by-step AI guidance, so agents must memorize complex, ever-changing procedures. |
| "Our phone lines are jammed with customers just asking for a status update on their request." | The front office (contact center) operates independently of the back office (fulfillment). Agents have no visibility into where work actually sits. |
2. The customer experience (CX) leader (Chief Customer Officer / Head of Digital Service)
Focuses on CSAT, NPS, seamless journeys, and self-service containment.
| What they say (the symptom) | What it actually means (the root cause) |
|---|---|
| "Our self-service portals and chatbots are failing; everyone just escalates to a live agent anyway." | Chatbots and portals function as FAQ search engines only; they do not connect to the underlying workflows needed to execute and complete the work. |
| "Customers hate having to repeat their story when they switch from chat to the phone." | Channels operate in silos. There is no centralized context carrying the customer's state from the digital channel to the human agent. |
| "We are always apologizing for problems instead of preventing them." | The service organization is reactive and lacks the event-driven intelligence needed to notify customers of issues (such as a network outage or claim delay) before they call in. |
3. The operations and fulfillment leader (Head of Ops / Back-Office Director)
Focuses on service-level agreements (SLAs), processing backlogs, automation, and end-to-end efficiency.
| What they say (the symptom) | What it actually means (the root cause) |
|---|---|
| "Work keeps falling into a 'black hole' when it gets passed from the front line to the back office." | Handoffs are manual (emails, spreadsheets, legacy ticketing). There is no end-to-end orchestration (Case Management) to track the work across departments. |
| "We throw more people at the problem, but our backlogs just keep growing." | Workflows contain repetitive, manual tasks that RPA and intelligent routing could automate. |
4. The IT / technology leader (CIO / VP of Service Tech)
Focuses on technical debt, integration, system agility, and total cost of ownership.
| What they say (the symptom) | What it actually means (the root cause) |
|---|---|
| "It takes us six months to update a service process when a new regulation or product launches." | Legacy systems contain hardcoded business logic; the architecture lacks a centralized, low-code layer to make rapid workflow changes. |
By translating these conversations, the Solution Designer shifts the focus from "buying a new chatbot" or "training agents better" to "fixing the underlying workflow and integrating the front and back office."
The "Ask Why" framework to uncover service root causes
In customer service, the most common trap that a Solution Designer can fall into is solving the problem for the interaction (how we talk to the customer) rather than for the resolution (how we finish the work).
To identify a customer service Pega-shaped problem, you must drill down past the "clunky UI" or "high call volume" complaints to find the breakdown in workflow orchestration.
The diagnostic drill-down
When a stakeholder says, "We need to fix our agent desktop because it is too slow," use the five whys to shift the focus from the interface to the workflow orchestration layer:
- The request (the surface): "Our agents need a new, faster desktop UI to lower average handle time (AHT)."
- Why 1 (the performance gap): Why is the current desktop slowing them down?
"Because they have to log into six different systems to process a single address change." - Why 2 (the integration gap): Why aren't those systems connected?
"Because they are legacy databases that don't talk to each other; the agent has to copy-paste data between them." - Why 3 (the logic gap): Why is the agent responsible for moving the data manually?
"Because there is no automated workflow that spans those systems; the 'process' only lives in the agent's head or a PDF manual." - Why 4 (the structural root cause): Why does this process remain manual?
Root cause: You are treating this as a desktop UI problem rather than a workflow orchestration problem. Agents serve as the manual integration layer.
Core diagnostic questions for Solution Designers
Use these probing whys during discovery sessions to expose the need for Case Management and intelligent automation:
| Structural gap | Diagnostic question |
|---|---|
| Swivel-Chairing | "If we gave the agent a beautiful new screen but they still had to manually update three underlying databases, would the problem actually go away?" |
| Limited process visibility | "When an agent clicks Submit on a request, why do they lose all visibility into whether the back office actually finished the work?" |
| Broken Self-service | "Why can a customer start a request on our website but must call an agent to complete it?" |
| Reactive approach | "Why are we waiting for the customer to call us about a service outage or a claim delay that our underlying systems already knew about two hours ago?" |
The so what? test
Once you think you've found a root cause, apply the Solution Designer's critical thinking lens to the service request:
Is this a "talk" problem or a "work" problem?
- If the goal is to have a better conversation, it is a "talk" problem. If the goal is to complete the work across the enterprise, it is a use case suited to Pega Customer Service.
Are we automating the status check, or are we automating the resolution?
- Pega Customer Service solutions focus on automating the resolution. When you automate the resolution, the status check becomes unnecessary.
How Pega Customer Service addresses root causes
Once the Solution Designer strips away the noise and identifies the true architectural failures (disconnected systems, manual handoffs, and broken self-service), Pega Customer Service™ becomes the natural solution.
Pega Customer Service is not another agent desktop tool; it provides an orchestration engine to get the work done.
Here is how a Solution Designer maps root causes to Pega Customer Service capabilities:
1. The system fragmentation problem versus the intelligent unified desktop
- Root cause: Legacy systems do not connect to each other, so agents manually navigate disconnected screens to find data and execute tasks, which increases average handle time (AHT) and error rates.
- Solution: Intelligent unified desktop. Pega integrates with legacy systems through APIs or robotic process automation (RPA) and brings the relevant data into a single workspace. It also uses AI to guide the agent through each step of the interaction.
- Outcome: Agents stop searching for information and focus on the customer. Training time decreases because the system guides agents through each step to ensure compliance and reduce average handle time.
2. The process visibility problem versus end-to-end Case Management
- Root cause: Front-office interactions do not connect to the back-office systems and staff who fulfill the work. Handoffs are manual, which causes lost requests and repeated follow-up calls.
- Solution: End-to-end Case Management (Microjourneys). Pega wraps the entire process in a Case (a digital folder) that tracks the work from the initial customer request through back-office fulfillment, and applies service-level agreements (SLAs), routing logic, and escalations automatically.
- Outcome: Work no longer disappears between the front and back offices. The agent, the back-office worker, and the customer all have complete visibility into where the work is and who owns the next step.
3. The broken self-service problem versus Center-out® architecture
- Root cause: Chatbots and web portals operate as isolated channels. They can answer FAQs but have no integration with underlying systems to execute transactions or resolve complex issues.
- Solution: Center-out® business logic. Pega builds the workflow logic (the Case) once in the center and extends the same logic to all channels. The chatbot does not search an FAQ; it executes the same underlying process an agent uses.
- Outcome: Customers can start a complex process (such as disputing a charge or filing a claim) on their phone and complete it without escalating to a human agent.
4. The reactive service problem versus proactive service
- Root cause: The contact center takes a reactive approach and waits for customers to experience an issue and call in to report it.
- Solution: Event-driven architecture. Pega continuously listens to enterprise data streams (for example, IoT devices in manufacturing, telematics in insurance, and network monitors in telecommunications). When it detects an anomaly, it triggers a Case automatically.
- Outcome: The enterprise shifts from reactive to preemptive service. Pega notifies customers about an upcoming flight delay, a suspected fraudulent transaction, or an imminent equipment failure before the customer realizes there is an issue, which eliminates the inbound call.
By mapping problems this way, a Solution Designer proves that lowering contact center costs isn't about rushing the agent off the phone. It is about automating work, connecting the front and back offices, and solving problems before the customer even has to call.
Elevance improves customer service with a unified agent experience
See how Elevance simplified complex service workflows by bringing systems, data, and guidance into a single, unified experience for customer service representatives.
- Business issue: Customer service advocates experienced cognitive overload. They had to navigate dozens of disparate legacy healthcare systems to resolve complex member inquiries, which resulted in long hold times and high training costs.
- Solution: Elevance deployed the Pega Unified Desktop to abstract legacy complexity. The system connects front-end interactions with back-office data and provides advocates with step-by-step guidance for each inquiry.
- Results: Elevance reduced agent training time and average handle time (AHT). By removing the need to navigate disconnected systems, advocates can focus on member empathy.
For more information, see Elevance Health delivers personalized customer experiences with Pega.
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