Why Amazon Connect Customer Migrations Stall And How to Fix Them

Amazon Connect Customer migrations stall because of common avoidable pitfalls that push timelines, inflate budgets, and erode stakeholder confidence. Based on our experience supporting dozens of enterprise contact center migrations, we’ve identified the most common reasons migrations stall and what organizations can do differently. This post is for migration program managers, IT leaders, and business stakeholders planning or currently executing an Amazon Connect Customer migration.

1. Lack of organizational alignment on Statement Of Work (SOW) and design documentation
Issue: The SOW and design documentation phase is treated as a formality rather than a critical alignment checkpoint. Business stakeholders are often excluded from sign-off in IT-driven engagements, SOWs contain minimal detail, and design documents move forward with known gaps.

Impact: When the business side of the organization isn’t included in SOW and design sign-off, critical requirements get missed, particularly those which impact the customer experience, agent experience, real time and historical reporting, Interactive Voice Response (IVR) authentication flows, data dips, and integration dependencies. The migration stalls because stakeholders surface missed items after the fact, triggering rework loops. Meanwhile, there’s often no mention of who is building reports, whether they’ll be out of the box or custom, how testing will take place, or how reporting aligns with the legacy experience.

Solution: The SOW and design document require business and IT sign-off on both. Include explicit sections for reporting strategy, IVR/authentication requirements, and integration architecture. Treat design document completion as a gated check point and do not start development until it is signed off by all stakeholders. Do not treat migration just as a technology project rather treat it as a business transformation.

2. Lack of clarity on migration ownership and governance
Issue: Accountability is fragmented across IT, operations, vendors, and AWS teams: with no single migration lead, no clear RACI (Responsible, Accountable, Consulted, Informed) matrix, and no agreed definition of success. IT drives delivery in a vacuum while business stakeholders stay peripheral until late. No one owns the critical path or tracks whether the migration is delivering the transformation that justified the investment and this risks a rebuild of legacy inefficiencies on new infrastructure.

Compounding this, the strategic reasons for choosing Connect Customer (cloud agility, AI, pay-per-use economics, innovation velocity) take a backseat. Without measurable business outcomes defined upfront (cost reduction, Customer Satisfaction Score (CSAT), first-call resolution, self-service deflection), there’s no way to tell if the project is on track or has drifted.

Migration is a chance to modernize processes, workflows, and customer journeys, not just replicate the legacy state. But when modernization goals (omnichannel, AI self-service, real-time analytics, workforce optimization) aren’t defined, teams default to like-for-like rebuilds and miss Connect Customer’s differentiating capabilities.

Requirements come from too few stakeholders. IT architects design the legacy system’s specs rather than engaging contact center leaders, workforce planners, and frontline supervisors on the future state.

Since business-side product owner is not embedded in the team, trade-offs default to technical convenience over customer impact. And when leadership shifts strategy mid-migration (new channels, AI initiatives, outsourcing), those changes don’t reach the delivery team causing rework or unneeded features.

Impact: Without a single owner and shared success criteria, decisions stall, dependencies go untracked, and timelines drift as everyone assumes someone else owns the critical path. IT measures success as “live and stable”; the business measures it by improved Customer Experience (CX), reduced handle times, and cost savings and neither realizes they’re building toward different outcomes until late.

With no defined business outcomes, there’s no early warning when the migration drifts from its strategic intent. Requirement gaps surface during User Acceptance Testing (UAT) or post-go-live, when business stakeholders finally engage and find the build doesn’t reflect how the contact center actually needs to operate. Priority shifts arrive without context, triggering rework the plan never accounted for. The result is a migration that fails to deliver the value that justified the investment and erodes executive confidence, making future innovation harder to fund.

Solution: Appoint a single accountable migration leader with cross-functional decision-making authority. This leader owns the critical path end-to-end, not just the technical delivery. Secure executive sponsorship at the senior leadership level for both the migration lead and the program overall. Publish a RACI that covers IT, business, partner, and AWS responsibilities explicitly.

Embed a business product owner in the migration team from day one, someone empowered to make trade-off decisions based on customer and agent impact, not just technical feasibility. Before build begins, align all stakeholders on measurable business outcomes the migration must deliver, the strategic reasons Connect Customer was chosen, and the modernization goals that differentiate this from a like-for-like replacement. Revisit these at every milestone.

Gather requirements from the people who live in the contact center such as supervisors, workforce planners, front line agents and not just the IT team that maintains the legacy platform. When priorities shift mid migration be sure to route changes through the migration lead, who documents the impact assessment and timeline adjustment so there are no surprises.

3. Incomplete discovery process that misses the deeper requirements

Issue: Discovery workshops check the box without diving deep enough. Key areas such as reporting, technology integrations, IVR logic, automation, agent experience nuances, and cross Line of Business (LOB) requirements are skimmed rather than thoroughly mapped.

Impact: Without deep reporting discovery, organizations realize post build that their analytics requirements weren’t captured. Technology integrations go unidentified until development is underway. Conflicting requirements between lines of business surface mid build, forcing prioritization battles. When all stakeholders aren’t included or when IVR deep dives are skipped the design is built on incomplete information that unravels during development and UAT. Additionally, during testing, agent experience gaps are identified that were never surfaced in discovery such as screen pop behavior, workflow sequencing, desktop tooling integration, and call handling nuances that don’t match how agents actually work. These gaps now require additional development cycles to resolve, pushing timelines further when the project can least afford it.

Solution: Structure discovery as multiple focused deep dives: one for IVR/contact flows, one for integrations, one for reporting and analytics, one for agent experience and desktop workflows, and one per LOB. Verify every stakeholder group is represented including frontline agents and supervisors who can validate the day-to-day experience before build begins. Don’t exit discovery until business outcomes and goals are clearly articulated and documented. By capturing agent experience requirements upfront, you avoid late-stage development rework that compounds timeline pressure during testing phases. Build in time post testing for defects, enhancements, and requirements that were missed in discovery so that you have time to address items if the need should arise.

4. Customers attempt to build internally without adequate experience
Issue: Organizations choose internal development over using experienced Amazon Connect Customer Delivery Partners often to save cost or maintain control.

Impact: Without hands-on migration experience, teams underestimate the complexity and hit significant issues such as architectural gaps, misconfigurations, scaling problems. These problems are not surfaced until late in the timeline, often in UAT. By the time they recognize they need expert help, the project is already behind schedule. In addition, recovery may require rework that could have been avoided with proper guidance from the start.

Solution: Engage experienced practitioners early including in an advisory capacity. When using a partner, verify they have the appropriate skill sets and migration experience. Validate that they have delivered successful Connect Customer migrations of similar scale and complexity and not just generic AWS experience. Have both a partner project manager and a customer project manager in place who can work together to drive toward migration success. The cost of course correcting mid-flight far exceeds the cost of getting architecture and approach right from day one.

5. Challenges mapping complex legacy IVR to Connect Customer contact flows
Issue: Legacy Interactive Voice Response (IVR) trees are often built over 10+ years in traditional on-premises contact center platforms and don’t always map 1:1 to Connect Customer contact flows.

Impact: The redesign effort, especially when adding AI capabilities like Amazon Lex bots / Agentic CX Designer, is consistently underestimated. What looks like a “lift and shift” can turn into full re-architecture. Conversational designers are often not included in the process, meaning IVR flows are rebuilt by engineers without the expertise to design intuitive, customer centric voice and chat experiences.

Additionally, future business goals, new self-service use cases, omnichannel expansion, AI-driven personalization are not factored into the design, resulting in flows that need to be rearchitected again within months of go-live. Regulatory requirements (state, country specific compliance), scope creep from missing deep technical requirements, and unrealistic project timelines compound the challenge particularly when customers are misaligned with their partner delivery plan or attempting self-development without adequate support.

Solution: Invest in discovery and flow mapping early. Treat contact flow design as a dedicated work stream with its own timeline and not a subset of “configuration.” Include conversational designers alongside engineers to verify flows are designed for the customer experience, not just technical functionality. Design with future business goals in mind, build modular, extensible flows that accommodate planned AI, self-service, and omnichannel initiatives rather than optimizing solely for today’s requirements. Account for regulatory complexity and build contingency for scope items that will inevitably surface during development. Establish a minimum self-service target and verify the flows support achieving it for both IVR and Chat. This is critical as containment in these channels directly impacts the contact volumes reaching agents and the financial bottom line of the Contact Center.

6. Lack of effective change management for the workforce
Issue: Agents, supervisors, and operations teams accustomed to legacy tools resist adoption. Without structured training, side-by-sides, and phased rollout, go-live get pushed back due to low readiness scores or stakeholder objections.

Impact: When communication is absent and change management starts too late, the impacted teams aren’t brought along on the journey. By the time training and communications begin, resistance is already entrenched, questions go unanswered, and the organization lacks the buy in needed to execute a smooth transition. Compounding this: no implementation infrastructure plan for various environments (development, test, production), no business communications about the new platform’s expected functional changes, gaps in agent training plans, and insufficient knowledge transfer planning for both IT and business administration teams.

Solution: Start change management on day one and not 30 days before cutover. Identify champions in operations early, run side-by-sides during parallel periods, and communicate the “why” before the “what.” Build a formal change management plan that includes environment infrastructure, business communications cadence, training plans, and knowledge transfer milestones. Verify that your Workforce Management team does extensive testing and is comfortable with how they will be managing schedule creation, real time schedule adherence, achieving Service Level Metrics, short-term planning, and long-term planning.

7. Delays in initiating telephony and number porting requests
Issue: Porting Direct Inward Dialing (DIDs) and Toll-Free Numbers (TFNs) from legacy carriers is subject to third party timelines, carriers, Letter of Authorization (LOAs), regulatory approval. A single rejected port request can delay an entire wave by weeks or more.

Impact: The porting process is often not started early enough in the project timeline. Teams treat it as a late-stage cutover activity rather than a long lead item that should be initiated months in advance.

Customers frequently don’t have proof of ownership readily available, have mismatched information with their carriers, don’t have a complete inventory of their numbers, carrier/provider issues emerge, and the porting timeline itself is undefined, will numbers port before migration day, on the day of, or after? By the time port requests are submitted, carrier response times and rejection cycles consume the buffer that was supposed to protect the go-live date.

Additionally, customer porting concerns often go unaddressed, and some customers feel more comfortable forwarding numbers to Connect Customer rather than porting them outright. These concerns which are often rooted in fear of disruption or lack of confidence in the cutover plan need to be surfaced early because customers who default to forwarding may not fully understand the implications including the potential of doubling usage cost when number forwarding is in place.

Solution: To make certain the customer has all TFNs, and DIDs identified, discuss porting early in the timeline. Submit port requests as early as contractually possible. Verify proof of ownership is on hand. Build a porting tracker with carrier Service Level Agreements (SLAs), rejection contingency plans, and enough buffer for at least two rejection resubmission cycles.

Define the porting timing strategy (pre migration, day of, or post) during planning and not during cutover week. Proactively address customer porting concerns if there’s a preference for forwarding over porting, dig into the “why” and educate on the cost, latency, and operational implications. Forwarding should be a deliberate interim strategy with a defined end date, not a permanent workaround born from unresolved anxiety about the cutover.

8. Underestimation of integration complexity with backend systems
Issue: Connect Customer must integrate with Customer Relationship Management (CRMs), legacy Workforce Management (WFM) tools, custom databases, and screen pop applications. Teams underestimate the Application Programming Interface (API) work, AWS Lambda development, and data mapping required which can stall migrations after the “easy” phases.

Impact: Clarity gaps on integration requirements are identified too late. Dependencies on legacy middleware, authentication flows, data formats, and API contracts aren’t fully discovered until development is underway, forcing rework cycles and pushing timelines when what seemed like straightforward integrations reveal hidden complexity.

Compounding this, the correct customer technical resources, those with deep knowledge of the integrations are often not included in the project or discovery. These aren’t always the IT team members at the table; they’re the engineers and developers who built and maintain the middleware, APIs, and data flows day-to-day. Consider that this knowledge may be distributed across multiple resources who have shared responsibility over time, or that different lines of business may have entirely different technical owners for their integrations. Without getting the right people in the room, discovery produces an incomplete picture that doesn’t surface until the build is underway.

Solution: Before the build begins, run a dedicated integration discovery sprint. Document every API contact, authentication mechanism, and data transformation. Prototype high risk integrations first. Critically, identify and engage the correct technical resources beyond the IT leadership team such as the people who actually built and maintain the integrations. Map out ownership per LOB and per system, recognizing that institutional knowledge may be spread across multiple individuals.

If ownership has changed hands over time, bring in both current and former owners to verify nothing is lost in translation. Include business users in integration testing, they are best positioned to validate that the tool supports actual customer workflows.

9. Inadequate testing and validation
Issue: Organizations rush to cutover without sufficient validation across multiple dimensions and when validation checkpoints do exist (like sprint demos), they fail to surface problems because the right people aren’t in the room and the right scenarios aren’t being shown.

Testing is treated as a side activity rather than a formal work stream with its own resources, timeline, and leadership. Without a dedicated test lead and structured test plan, gaps cascade into every area: UAT coverage is thin, reporting discrepancies go unnoticed, agent experience issues compound at scale, and sprint demos become rubber stamp ceremonies that don’t reflect real world workflows.

Business stakeholders and supervisors don’t validate routing logic, queue behavior, and edge cases until too late, surfacing defects post go-live that should have been caught weeks earlier. Short testing windows, insufficient testing resources, lack of testing scripts, and missing testing accounts all contribute to inadequate coverage. Meanwhile, business users aren’t in attendance or aren’t engaged during sprint demos. Customer specific use cases aren’t demoed instead; teams show generic functionality that doesn’t reflect how the contact center actually operates. When multiple migration phases require a longer timeline, compressed demo cycles don’t allow sufficient feedback loops between sprints. By the time business stakeholders finally see the build in a meaningful way, it doesn’t match their expectations, and rework is required causing delays.

Historical and real time reporting in Connect Customer doesn’t always match legacy platform metrics {Average Handle Time (AHT), Average Speed of Answer (ASA), Abandon Rates}. Discrepancies in dashboards and custom reports erode leadership confidence and force rollbacks. There is often no dedicated business performance reporting testing work stream. IT teams do not seek input, testing, or sign-off from business analytics teams who actually consume the data. It is assumed that out of the box reporting is sufficient, without considering that formulas for common metrics (abandon rate, service level, AHT) may have variances in how they’re calculated between the legacy platform and Connect Customer. These differences go unvalidated until leadership sees numbers that don’t reconcile with what they’ve reported historically.

Amazon Connect Customer Contact Control Panel (CCP) or Agent Workspace latency, missing screen pops, unfamiliar User Interface (UI), broken whisper/barge, or degraded audio quality during parallel run periods frustrate agents and drive escalations. Without dedicated agent experience testing side by side, call quality audits, workflow simulations; issues compound at scale. No deep agent platform testing means these issues aren’t caught until real agents are handling real calls.

Impact: The absence of a dedicated testing work stream means there’s no single owner accountable for validation quality across UAT, reporting, agent experience, and demo effectiveness.

Each gap reinforces the others: demos don’t surface issues because the wrong people attend and generic scenarios are shown; UAT doesn’t catch what demos missed because coverage is thin and time boxed; reporting discrepancies aren’t flagged because analytic teams aren’t involved; and agent experience problems aren’t identified because no one tested the end-to-end workflow under realistic conditions until go-live.

The cumulative effect is that the organization reaches cutover believing the system is validated when the validation was shallow across every dimension.

Solution: Testing needs to be a first-class work stream with its own lead, plan, and entry/exit criteria. Include reporting validation and agent experience testing alongside functional UAT not as an afterthought. The testing strategy needs to be discussed and planned at the start of the project with the project team and partners and not defined mid build when timelines are already compressed.

Verify test cases are well documented with scripts, testing accounts are created, adequate time windows exist to test, and dedicated resources are in place before testing begins. Plan for regression testing as needed and do not allow development updates made after testing to go without a dedicated retest period. Any code change, configuration update, or flow modification introduced post UAT must go through a regression cycle before cutover. Make demo attendance mandatory for business stakeholders.

Demo real customer use cases with actual customer data, not out of the box features. Align demo cadence with the actual number of migration phases, and build time between sprints for feedback incorporation. When stakeholders see their workflows validated iteratively throughout the build, late-stage rework is dramatically reduced, and business stakeholder buy in is earned.

10. Security and compliance related delays
Issue: Information Security (InfoSec), compliance, and data governance teams are brought into the migration too late, often after architecture decisions have already been made and development is underway. In regulated industries (financial services, healthcare, government), these teams operate on their own review cadences with non-negotiable approval gates. Organizations treat security sign-off as a formality near the end of the project rather than a foundational input that shapes architecture from day one.

Compounding this, Disaster Recovery (DR) and Business Continuity planning are frequently deferred until post go-live, treated as a “Phase 2” initiative rather than a core requirement that security and compliance teams may demand before approving production readiness.

Impact: Security and compliance reviews surface requirements that should have been addressed in design such as encryption of call recordings, Payment Card Industry Data Security Standard ( PCI DSS) scope for payment IVRs, Health Insurance Portability and Accountability Act Business Associate Agreement (HIPAA BAA) coverage for healthcare data, data residency constraints that dictate which AWS Region the instance must reside in, and access control models that don’t align with how Connect Customer’s security profiles were configured.

A single compliance finding can block go-live for weeks while the team rearchitects. Meanwhile, when DR planning is absent, security teams flag the lack of a failover strategy as a risk that prevents production approval, particularly in industries where regulatory bodies require documented continuity plans. Connect Customer’s regional architecture means DR isn’t automatic; multi region failover, data replication, and routing redundancy require deliberate design.

Organizations that don’t account for this upfront find themselves stuck between a compliance team that won’t approve go-live without a DR plan and a project timeline that never allocated time to build one. Additionally, audit logging, data retention policies, and agent access controls may not meet compliance requirements as initially configured, triggering rework.

All the AWS Applications that are needed may also need to be approved by Security to be used in the customer environment. This vetting process can also take significant time depending on the customer’s internal approval process.

Solution: Plan to engage InfoSec, compliance, and data governance teams during discovery and not during pre-production review. Include them in design sign-off so their requirements are baked into architecture decisions rather than retrofitted after the build. Conduct a compliance requirements workshop early in the project that maps regulatory obligations (PCI DSS, HIPAA, General Data Protection Regulation (GDPR), Telephone Consumer Protection Act (TCPA), System and Organization Controls 2 (SOC 2), state/country specific regulations) to specific Connect Customer configuration decisions.

The Connect Customer configuration decisions include recording storage, encryption, data residency, access controls, and audit logging. Define the DR strategy (multi region, active passive, pilot light) during design, get security team sign-off on the approach, and build it into the implementation timeline. Establish a clear compliance approval gate in the project plan with defined criteria, responsible reviewers, and enough calendar buffer. Don’t assume a single review pass will result in approval, plan for findings and the time needed to address them.

11. Migration plan gaps and cutover risks
Issue: The migration plan itself such as the sequencing, governance, and logistics of cutting over is underdeveloped or lacks critical stakeholder alignment.

Impact: A single-phase approach for large customers creates unnecessary large scope of impact. Migration plans lack full business and IT stakeholder sign-off. It’s unclear who manages migration issues, who owns the escalation process, or what the rollback plan looks like and critically, who has the authority to make the rollback decision. Resource planning (remote vs. onsite, AWS vs. partner vs. customer) is vague. There’s no command center structure for go-live support.

Solution: Phase migrations into manageable waves with clear success criteria between each. Get explicit business and IT sign-off on the plan. Define the escalation path, rollback triggers, rollback decision authority, and command center structure before going live and not during it.

Confirm resource requirements (who, where, when) weeks in advance. Develop a detailed line of business migration sequence and identify the lowest risk LOB to migrate first. Ask critical questions such as: How do we avoid customer and agent interruption or negative impact? What’s the scope of impact if something goes wrong with this wave? Which LOB has the simplest flows, fewest integrations, and most flexible SLAs to serve as a proving ground? Use early waves to validate the migration playbook, build organizational confidence, and refine the process before tackling high volume or high complexity lines of business.

12. Delay in Connect Customer service quota requests and operational readiness gaps
Issue: AWS service quotas and operational infrastructure (AWS Cost Explorer, billing, Well Architected Framework Review (WAFR) follow ups) are treated as administrative afterthoughts rather than critical path items.

Impact: The service quota process is started too late or only partially completed. Analytics aren’t shared or reviewed with AWS, creating blind spots. Process knowledge gaps mean teams don’t know what quotas to request or how to validate them pre-go-live. When WAFR follow ups require both business and IT attendance, scheduling delays push the operational readiness confirmation into the critical path. Worse still, the WAFR is either not performed at all or performed too late with the wrong resources in the room.

When this happens, the WAFR – whose intention is to proactively identify architectural risks, operational gaps, and best practice alignment before going live – is not fully adopted by the project team. The WAFR exercise loses its value entirely. It becomes a checkbox rather than the risk mitigation tool it was designed to be.

Solution: It is important to initiate service quota requests during Month 1 alongside environment setup. Complete the WAFR early with both business and IT stakeholders present. Confirm AWS Cost Explorer, billing, and operational tooling access well before UAT begins. Share analytics with AWS proactively so quota recommendations are data-driven.

Establish a recurring service quota meeting with the proper resources such as AWS, the delivery partner, and customer technical leads to track progress, review pending requests, and verify there are no gaps at go-live.

The customer will need to develop a process to monitor service quotas post migration as service quotas aren’t a onetime submission; they require ongoing validation as the build evolves and call volumes are better understood with peaks and valleys throughout the year.

Conclusion
These twelve pitfalls share a root cause: Treating a migration as a technology project rather than a business transformation. The organizations that succeed treat their Connect Customer migration as an opportunity to modernize with the right expertise, governance, and alignment from the start.

Every one of these risks is mitigable with early planning, experienced guidance, and intentional cross functional engagement. These pitfalls surface on nearly every migration – preparation is what separates a successful migration from a stalled one.

Author Bio(s)

Soham Tillu is a Senior Customer Solutions Manager at Amazon Web Services. Soham engages with executives to address their transformation challenges, providing domain expertise for cloud adoption, and achievement of key business objectives.

Felix Avila is a Senior Customer Success Specialist at Amazon Web Services. Felix specializes in Amazon Connect Customer and the contact center space. With 30+ years of experience working in contact centers across a variety of industries — managing both lines of business and technology — he works with customer stakeholders and technology teams at all stages of contact center migrations, business optimization, technical delivery, growth, and solutioning to ensure customers achieve their goals.

Chris Egleston is a Senior Customer Solutions Manager at Amazon Web Services and has spent 30+ years in the Contact Center Industry working for several Business Process Outsourcing organizations, financial institutions, and technology organizations. Chris has an Electrical Engineering degree and is passionate about Contact Centers, has led many large-scale technology migrations, and is customer obsessed with helping customers succeed while deepening their relationship with AWS