The invisible work of cleaning up duplicate automation in contact centers
Automation has become the rallying cry in modern contact centers. Companies of all sizes are placing heavy bets on orchestration platforms — those solutions that promise to connect channels, systems, and interactions into a single, seamless customer experience.
The idea is simple and appealing: it doesn’t matter if the customer starts with a chatbot, an IVR, or talks directly to a human agent — the context follows the entire journey.
Sounds great on paper.
But what many companies are discovering in practice is something very different. When they get around to implementing orchestration, they find a scenario that has been quietly building over the years: layer upon layer of automation stacked on top of each other, each one solving a specific problem, each one speaking a different language, and almost none of them talking to one another.
The problem isn’t new. It’s just that orchestration shined a light on it.
And here’s the twist: orchestration doesn’t create this chaos — it simply reveals what was already there. 👀
Before thinking about connecting systems, many organizations need to face a more uncomfortable reality: they’ve accumulated duplicate and disconnected systems that fragment the customer experience and make everything harder to operate.
How contact centers piled up overlapping automation
Nobody wakes up one day and decides to create a chaotic automation environment at their company. This scenario forms gradually, almost always with good intentions. A support team needs a chatbot to answer frequently asked questions, so they buy a quick solution and get it running. A few months later, the marketing team wants to automate post-purchase messaging, so another tool comes in. The collections department has an urgent need, and here comes yet another system. Each department solves its immediate problem, and nobody is looking at the big picture.
Oru Mohiuddin, research director at IDC, explains that it’s extremely common for large enterprises to build contact center environments through incremental technology adoption, acquisitions, and channel expansion. The result, according to her, is that IVRs, chatbots, RPA workflows, and AI assistants end up independently handling similar types of interactions.
Alex Levin, co-founder and CEO of Regal, adds to this perspective. He says that most of the time, when each system was implemented, it was solving a critical issue. But nobody planned for all of them to eventually overlap.
Aleks Bass, chief product and technology officer at Typeform, goes further and points out that the pattern reflects how organizations are structured internally. According to Bass, companies build automation the same way they’re organized. Marketing adds tools for lead generation, sales for follow-up, support adds chatbots, operations adds workflow automation. Each decision in isolation is perfectly reasonable on its own.
The result, over two, three, five years, is an environment where multiple tools are doing similar things, storing data in different places, and operating with zero synchronization between them.
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When orchestration exposes hidden problems
The most critical point in this story is that these duplicate systems are rarely identified as a problem until someone tries to do something bigger — like implementing an orchestration platform. As long as each system stays in its own lane, the operation sort of works, even if inefficiently. But the moment you try to put a layer on top that connects everything, the inconsistencies come crashing to the surface.
Customer data that doesn’t match across systems, automation workflows that conflict with each other, business rules that are duplicated and often contradictory. That’s when the company realizes the full extent of the problem it’s been accumulating in silence.
Overlapping automation environments frequently produce inconsistent routing decisions, fragmented journeys, repeated interactions, duplicate tickets, and increased operational complexity. Different systems may solve the same problem in different ways or send customers down conflicting paths.
Bass emphasizes that these issues often stem from a lack of complete context about the customer. When tools overlap without sharing context, each system invents its own version of the customer — and they disagree with each other.
Another factor that contributes heavily to this buildup is vendor switching over time. When a company migrates from one platform to another, what should be a replacement often turns into an addition. The old system keeps running in some part of the operation because there’s a workflow that hasn’t been migrated yet, or because someone still depends on a specific report that the new tool doesn’t deliver yet. So both coexist — sometimes for months, sometimes for years. Multiply that across several switches over time, and the result is a pile of tools that nobody knows exactly what they do, but everyone is afraid to turn off.
The direct impact on customer experience
From the perspective of the person on the outside — the customer — this tangle of systems translates into frustrating experiences that seem inexplicable. Someone reaches out through chat, explains the problem in detail, partially resolves it, and when they need to speak with a human agent, they have to repeat everything from scratch. Or worse, they receive an automated message with information that contradicts what the agent just told them.
This kind of situation doesn’t happen because of carelessness or lack of training. It happens because the systems simply don’t share information with each other, and the customer experience pays the price.
Levin notes that customers rarely distinguish between individual systems when something goes wrong. According to him, the biggest risk is a customer experience that feels completely disconnected. He cites situations where customers resolve an issue through one channel and then receive follow-up communications about the same issue from another system. To the customer, the company just looks disorganized.
Bass uses a spot-on expression to describe this phenomenon: the customer ends up being the integration layer the company never built. In other words, it’s the customer who does the work of connecting information across systems — repeating data, explaining again what they already said, and manually carrying context from one channel to another.
The fragmentation caused by duplicate and disconnected systems creates what we can call broken journeys. The customer starts an interaction on one channel, and that context gets trapped in that specific system. When the conversation needs to continue on another channel, the integration doesn’t exist, and the history is lost. To the customer, it feels like the company simply doesn’t know who they are — even if they’ve interacted dozens of times before.
The silent erosion of trust
Beyond the immediate frustration, there’s a long-term impact that’s even more concerning: the erosion of trust. When a customer realizes that every contact with the company feels like starting over, they begin to question whether that brand is actually capable of taking care of them. The customer experience stops being something isolated and becomes a perception built across every single interaction.
And if most of those interactions are marked by repetition, contradiction, and lack of context, the perception that forms is negative — regardless of how much the company invests in team training or relationship campaigns. The problem is in the technology foundation, and without fixing that, all other efforts have limited impact.
The checklist before jumping into orchestration
Successful orchestration efforts typically start with a detailed examination of existing customer journeys — not with a review of technology platforms. This reversal of priorities is essential.
Bass recommends starting with the journey, not the tech stack. He suggests mapping the complete customer experience — from acquisition and onboarding through support, retention, and expansion. Organizations should identify where customers are asked to provide the same information multiple times, where workflows overlap, and where context disappears between systems.
Data analysis is equally important. Companies should examine transfer patterns, escalation points, repeat contacts, and situations where multiple systems are handling the same customer intent. Frontline employees can provide additional insights into workarounds and inefficiencies that may not be visible through reporting tools alone.
Levin recommends focusing on the interactions that customers encounter most frequently. According to him, by tracking these interactions from start to finish, you’ll almost certainly find points where multiple systems are competing for the same customer at the same time. This process often reveals redundancies and conflicts that were hiding under years of technology deployments.
Why integration alone doesn’t solve it
A common response when companies identify this chaos is to launch an integration project. The logic seems sound: if the systems don’t talk to each other, let’s build bridges between them. And then begins a new cycle of projects — often long, expensive, and complex — to connect tools that were built with completely different architectures, at different times, for different purposes.
Sometimes this effort partially works, but it rarely eliminates the actual problem, because the root cause isn’t the lack of connection. It’s the existence of redundant systems that shouldn’t coexist in the first place.
Integrating duplicate systems is like trying to organize a messy drawer by putting little boxes inside it. In the short term it looks neater, but the volume of unnecessary stuff is still there — it’s just hidden behind a structure that gives the appearance of organization. Each new integration created to connect systems that do similar things adds another layer of complexity to the operation, another point of failure, another dependency that will need to be maintained and updated.
Bass is blunt about the most common mistake he sees: treating orchestration as a way to manage complexity instead of reducing it. Adding another layer on top of fragmented systems only hides the mess — it doesn’t eliminate it.
Consolidate, retire, or modernize existing systems
Once organizations identify overlapping workflows, the next step is determining which systems are still delivering real value.
According to Mohiuddin, organizations should evaluate their automation assets based on business value, performance, functional overlap, integration capability, maintenance requirements, and long-term scalability. She notes that some technologies may justify modernization, while others may be candidates for consolidation or retirement.
Many organizations are tempted to preserve existing systems and rely on orchestration to coordinate them. But doing so can perpetuate exactly the complexity that orchestration was supposed to solve.
What modern orchestration calls for is different: before integrating, you need to map, understand, and when necessary, consolidate. That means having the courage to look at duplicate systems and make decisions about what truly needs to exist, what can be deactivated, and what should be replaced by something that’s built from the ground up to communicate within a unified architecture.
This process is more work upfront, but it’s the only path that leads to a truly cohesive operation — one where the customer experience is consistent from end to end, regardless of how the customer chooses to reach out.
What separates successful orchestration from attempts that fail
Technology alone doesn’t compensate for fragmented workflows and disconnected customer data. Successful organizations start by rationalizing workflows, eliminating duplication, establishing unified data layers, centralizing routing decisions, and aligning automation around a shared customer intent.
These efforts improve both the customer experience and the employee experience, while building a stronger foundation for orchestration. Skipping these steps often preserves existing fragmentation and just adds another layer of complexity to the mix.
Bass sums it up well: AI doesn’t create a better experience on its own — it exposes the experience you already have.
Before introducing new orchestration layers, companies first need to understand the automation environment they already have, identify where systems overlap, and determine which workflows genuinely contribute to the customer outcomes they’re aiming for.
What changes when automation is designed as a unified whole
When a company decides to tackle the problem at its root and build an automation architecture designed as a unified whole, the gains show up across multiple levels at once. The most visible one is in the customer experience: journeys gain real continuity, context travels along with the interaction, and customers no longer need to reintroduce themselves with every new contact. This reduces customer effort, which is one of the top indicators of satisfaction and loyalty in the contact center world.
On the operational side, the simplification is also significant. Fewer systems to maintain means lower licensing costs, less fragmented training for teams, fewer points of failure, and less rework when something needs to be updated. Orchestration actually works when it has a clean foundation to operate on — where each tool has a clear role and there’s no unnecessary redundancy competing for data and workflows. In that kind of environment, it’s much easier to measure what’s working, identify bottlenecks, and make adjustments with precision.
The deepest transformation, however, is cultural. When a company goes through the process of mapping and consolidating its automation architecture, it inevitably creates a clearer vision of how it wants to serve its customers going forward. Decisions about which systems to keep, which to integrate, and which to deactivate force important conversations between departments that previously operated in silos.
And those conversations, when handled well, create alignment that goes beyond technology — shaping how the entire organization thinks about the customer experience as a strategic asset, not just a support metric.
As Bass puts it directly: the strongest companies are the ones willing to simplify. Fewer handoffs, fewer redundant workflows, a smaller set of connected systems that work exceptionally well together. 🚀
