Why contact center execution still lags behind strategic planning

Contact-center maturity depends on execution

A contact center can have a clear transformation strategy and working self-service while still making customers explain the same problem to successive agents. For customer-experience leaders, that is a practical test of maturity. It shows whether the organization can deliver the experience it has planned, because disconnected systems leave customers and agents bearing the cost of the gap between intention and execution.

Closing that gap is becoming more urgent as operational complexity and agent burnout threaten service quality. Customers expect fast, high-quality support across channels, so organizations need to preserve context as an interaction moves between them. That takes connected systems, usable information and a way to assess each interaction.

Strategy and self-service are ahead of operational execution

The Contact Center Maturity Benchmarking survey examines this gap between planning and delivery. CMSWire INSIGHTS, the research arm of CMSWire, partnered with SuccessKPI to ask 400 global contact center leaders about the tools they give agents to improve customer experience. Presented under the title Unpacking the State of Contact Center Maturity, the findings show substantial progress in planning alongside weaker operational capabilities. SuccessKPI has a commercial stake in investment in contact-center technology.

The survey defined maturity as an organization’s ability to use contact-center and customer-experience data to make decisions. It therefore assessed how effectively organizations plan and carry out digital transformation to improve agent performance and customer experience. For leaders, the practical question is how the contact center operates today and whether it can keep analyzing and improving its work.

To assess that ability, CMSWire INSIGHTS and SuccessKPI grouped the questions into seven benchmark pillars. These were Strategy; Customer Experience (CX), Channels and Automation; AI (artificial intelligence), Analytics and Quality Management; Real-Time Intelligence and Agent Assistance; Workforce Management and Operational Agility; Agent Experience (AX); and Reporting, Measurement and Value Realization. Together, they connect an organization’s direction with the capabilities needed to deliver it.

Reading the pillars together reveals gaps between those capabilities. A leadership team may agree on the intended customer experience while agents lack the information to deliver it. An organization may also introduce automation but struggle to assess its effect. The framework examines whether these efforts work together well enough to support ongoing improvement.

Within that framework, strategy was the most mature area, with broad leadership agreement about responsibility for contact-center strategy and customer-experience outcomes. More than 50% of respondents reported executive or cross-functional leadership team ownership. Another 20% said responsibility was shared among a cross-functional leadership team. Many organizations have therefore assigned responsibility and set a direction for transformation.

Progress extended to self-service: more than 90% of contact centers had at least basic self-service operating, and the survey reported some success with those efforts. When customers resolve suitable issues themselves, agents gain capacity for work that needs human attention. This broad availability shows that organizations have put part of their service plans into practice.

Yet the least mature areas were customer-experience channels and automation; real-time intelligence and agent assistance; and reporting, measurement and value realization. These capabilities determine how service moves between channels, how agents receive help during an interaction and how leaders understand the results. Weakness in these areas helps explain why widespread basic self-service can coexist with low automation maturity: customers may have another way to seek help while information still fails to follow them to an agent.

The partnership’s findings also distinguish organizations that lacked the technology to deliver their plans from those that had begun making changes but had yet to see results. Both still have work to do before they can turn their plans into a consistent experience. The next investment should therefore address an identifiable operational gap, with a way to judge whether it has closed.

Connected channels let agents continue the customer’s work

One such gap appears when a customer changes channels and the next agent lacks the context already provided. The survey findings describe organizations with roadmaps for these transitions but limited ability to carry them out automatically. Customers see that gap when they have to explain the problem again.

The technical cause often lies in backend integration, the connections that let separate systems exchange information. Incomplete connections leave customer information divided between tools, causing delays and fragmented service. Each tool may work within its own boundaries while the customer still has to reconstruct the issue for the next agent.

Fixing that handoff requires customer information to move across systems and channels as the interaction develops. The receiving agent needs the issue and its relevant context to continue working toward a resolution. Without that information, transferring the contact leaves the customer doing the work of connecting the service process.

Because several systems and teams take part, integration requires cross-functional implementation. Workflow automation, the automatic execution of connected steps in a process, must support the handoff, while real-time intelligence must provide relevant information and guidance during the interaction. CMSWire INSIGHTS and SuccessKPI identified gaps in both capabilities, alongside difficulty connecting separate systems. Their recommended integration work aims to make customer information usable wherever the issue is being handled.

Automating routine work leaves agents with harder cases

Giving agents that context becomes more important as self-service changes the work reaching them. When customers find answers and resolve suitable problems independently, agents have more capacity for complex requests. Automation therefore changes both the volume of work and the demands of the remaining cases.

As AI takes on routine challenges, human agents are left with the most complicated and emotionally demanding cases. The survey findings place this changing workload alongside existing burnout pressures. Removing routine work from the queue can help operations while leaving agents with a harder mix of interactions.

That harder mix makes real-time assistance more important, because agents need usable context and guidance while resolving difficult issues. Yet the survey found low maturity in this area, pointing to a gap in support for the work that remains with people. Automation planning should therefore include the help agents receive after routine issues have been handled elsewhere, so service improvements also support the people delivering them.

AI deployment requires measurement by caller intent

As the division of work changes, leaders also need to assess how each kind of interaction is handled. A contact center adding AI agents first needs data and technology infrastructure that can supply them with relevant information. Reporting must then show how the resulting service performs, so the organization can evaluate what it has deployed.

That reporting needs to distinguish how human and AI agents handle each caller intent, the reason a customer contacts the organization. Keeping this reason visible helps leaders interpret performance as routine issues increasingly go to AI and difficult cases remain with people. They can then judge whether each kind of request is being handled as intended.

With that view, the organization can assess whether its agents are working as expected and whether the investment is producing a return. Deployment counts show that a capability has been introduced; performance reporting shows how it operates. The survey’s low maturity finding for reporting, measurement and value realization therefore bears directly on decisions about adding AI agents.

CMSWire INSIGHTS and SuccessKPI describe the risk of proceeding without that understanding: at best, additional technology increases technology debt; at worst, it worsens customer experience. Technology debt here means the continuing burden of systems introduced without the means to understand their performance. Their warning makes evaluation part of the deployment decision, with reporting in place to assess how the new capability handles its assigned work.

Key highlights

• Close operational gaps: The survey of 400 contact center leaders found strategy ahead of channel integration, real-time assistance and performance reporting. Contact center executives need to tie each investment to a specific operational gap and define how progress will be measured.
• Preserve context across channels: Disconnected systems force customers to repeat information and agents to reconstruct issues. Technology and operations teams need to connect customer data and workflows so the receiving agent can continue the work already started.
• Support agents handling harder cases: As self-service and AI absorb routine requests, human agents face more complex and emotionally demanding interactions. Contact center managers need to pair automation plans with real-time context and guidance for that changing workload.
• Measure AI performance by customer intent: Reporting needs to show how human and AI agents handle each reason customers make contact. Technology and CX owners need this visibility to assess service quality, evaluate returns and make further deployment decisions.