Article

The Hidden Cost of Lift-and-Shifts: Why Cloud Migrations Fail CTO Expectations

July 17, 2026
employees in a meeting looking at key risk indicators on a screen

Key Takeaways

  • Moving legacy systems without redesign carries technical debt into a consumption-based environment, increasing cost, risk, and performance issues.
  • Refactoring code, cleaning data, and modernizing integrations are critical to achieving scalability, real-time insight, and cost efficiency.
  • The most successful leaders align cloud decisions to financial outcomes, operational performance, and long-term growth.

By 2027, 90% of organizations are expected to adopt hybrid cloud strategies, according to Gartner. And while a strategic cloud strategy is vital for growth and resilience, moving a broken or heavily customized on-premise ERP or financial system to the cloud can be disastrous.

A move to the cloud only works if your systems are scalable, regularly updated, and integrative. True cloud optimization requires re-engineering the application and data layers before migration to ensure scalability, accurate data delivery, and risk mitigation.


Infographic on cloud ERP strategy showing that 80% of IT budgets are spent on cloud services, 75% of cloud migrations exceed budget, and 38% take longer than planned, underscoring the need for effective cloud migration planning and digital transformation strategy.

Don’t Treat Migration as a Lift-and-Shift

Lift and shift migrations move broken processes into new systems without redesign, essentially moving legacy technical debt to an environment where you pay for it by the minute.

Instead, use migration as a chance to redesign processes for automation, visibility, and security.

Data Flow & Integration

Legacy data often contains duplicates, errors, and outdated records. Migrating “bad data” simply creates “bad data in the cloud.”

In an on-premises environment, a poorly written, highly nested SQL query or standard batch job might just run slowly overnight on a fixed-cost server. In the cloud, that same unoptimized process creates massive data bottlenecks, delays real-time financial reporting, and drives up computing costs exponentially.

Optimizing system and data reliability means moving from slow, batch-processed financial data to real-time, event-driven visibility that gives leadership immediate insight. After all, rapid data growth, especially given AI-driven models, has made data governance critical.

Ask Yourself: Are our systems giving leaders the data they need, when they need it?

Next steps include:

  • Optimize the database schema and refactor legacy code before migrating.
  • Transition heavy financial processing out of the core transactional layer and into modern cloud data architectures.
  • Formalize data ownership and lifecycle policies.
  • Build in a robust data cleansing and validation process before migration begins.

Process, Governance, and Change Management

Even the most seamless migration fails if end users don’t adopt the new system. Optimization is not about making bad processes faster; it is about eliminating process debt so that your automation investments target actual strategic growth.

Companies often use expensive cloud integrations to automate manual, broken workarounds that only exist because the original on-premises system was poorly configured. Automating a broken process just generates errors at cloud speed.

Ask Yourself: Are our technology investments solving real problems, or are we automating processes that need to be fixed first?

Next steps include:

  • Conduct a rigid process-and-code audit before any data touches the cloud.
  • Deprecate redundant customization scripts that were built to bypass old software limitations.
  • Align the workflows with native cloud ERP capabilities instead.
  • Invest in early communication, hands-on training, and role-specific onboarding.

Scalability and Risk

On-premises architecture is built for predictable, static limits. When lifted directly to a multi-cloud or hybrid environment, brittle point-to-point integrations and rigid database locks fail under sudden spikes in transactional volume, introducing serious compliance and data-loss risks.

A genuinely optimized platform leverages cloud elasticity safely, absorbing transaction surges and scaling operations effortlessly without introducing security or stability risks.

Ask Yourself: Can our platforms and integrations handle more volume, more users, and more data without creating new risk?

Next steps include:

  • Refactor monolithic financial engines into modern, decoupled architectures using APIs and event buses.
  • Ensure that integrations between Salesforce, NetSuite, and Microsoft platforms handle API rate limits and data validation at the architectural level.
  • Build layered security controls, train users, and test incident response.
  • Use ERP insights and secure data to drive growth and strategic decision-making.

Align Systems to Strategy

Technology leaders are often stuck in maintenance mode. However, the strongest way to prepare for system integration and optimization is with a proactive approach.

Frame migration not as an IT infrastructure project, but as a financial systems optimization initiative.

Ask Yourself: What technical debt or system limitations are blocking the projects leadership is counting on?

Not every application warrants the same migration strategy. Some can move quickly to the cloud to reduce infrastructure dependence, while others are better aligned to managed services or container-based architectures.

Consider these steps:

1. Conduct optimization assessments to prioritize fixes.

The strongest organizations know that laying the groundwork will lead to a better technology investment outcome. List every core platform in use, when it was last reviewed, and who owns it. Then, identify three systems that haven’t been assessed in the last few years. These are often ripe for low-effort improvements — like automation, integration, or user enablement — that can deliver outsized business value.

2. Plan for platform integration based on defined use cases.

Talk with users about friction points between systems. What are they re-entering, emailing, or exporting constantly? Turn those into integration use cases with measurable benefits — like fewer errors, faster processing, or better real-time data. The most business-critical platforms often require deeper redesign to improve scalability, resilience, and long-term value.

3. Audit and standardize key platforms.

Choose one enterprise platform and assess how it’s used across teams. Look for inconsistent permissions, naming conventions, and training gaps that create friction or weaken trust. Standardizing configuration and usage improve adoption, efficiency, and platform reliability.

Before cutover, test performance, availability, recovery, and rollback readiness to protect the user experience. Then ensure teams are ready to operate in the cloud, with clear service ownership, monitoring, and deployment practices. That is what turns migration from a one-time event into long-term ROI.


Financial technology transformation framework illustrating a four-stage digital transformation journey for finance organizations: assess current systems, integrate and optimize technology, innovate and future-proof operations, and establish continuous improvement processes.

USE CASE: Skin Script

Skin Script was using a patchwork of QuickBooks and manual processes for sales, inventory, and accounting. They could process only 250–300 orders per day, and closing the books took two full days.

We implemented a modern cloud ERP environment using NetSuite and RF-SMART solutions for warehouse management. The systems were integrated to streamline order entry, inventory tracking, and financial operations — all on a unified platform.

The Results:

  • 3× increase in shipping capacity, managing up to 1,100 orders daily.
  • $25,000 annually saved through reduced payment processing and improved efficiency.
  • Improved operational visibility, cost tracking, and demand forecasting, enabling stronger planning and scalable growth.

Intelligent Automation at Work in Healthcare

One managed care provider modernized claims submission with intelligent automation built on more accessible data and fewer system silos, enabling faster information flow across platforms. The result was a more scalable, reliable billing operation that reduced manual effort, improved data accuracy, and accelerated reimbursements.

What’s Next for Technology Leaders

Optimizing IT operations is imperative for efficient, innovative, and competitive modern businesses. Research shows that only 44% of organizations report a high level of IT agility, yet organizations with high IT agility are more flexible, responsive, adaptable, collaborative, scalable, innovative, and fast.

High-performing CTOs prioritize the following pre-cloud migration:

  • Refactor systems, even if it delays migration timelines
  • Conduct rigorous code and architecture audits
  • Modernize the data layer for real-time visibility
  • Tie cloud spend to business KPIs and cost per transaction
  • Eliminate process debt before scaling automation

This ensures that when the switch is flipped, the business inherits an agile engine built for the next decade of growth.

Frequently Asked Questions

Why do lift-and-shift cloud migrations fail?

Lift-and-shift migrations fail because they move inefficient code, poor data structures, and broken processes into a consumption-based environment, amplifying cost, performance issues, and risk instead of resolving them.

What is the difference between cloud migration and cloud optimization?

Cloud migration moves systems to the cloud, while cloud optimization redesigns architecture, data flows, and processes to improve performance, scalability, and cost efficiency.

When should you refactor before moving to the cloud?

You should refactor before migration if your systems rely on legacy customizations, batch processing, or inefficient queries that will perform poorly or increase costs in a cloud environment.

How does poor data quality affect cloud performance?

Poor data quality leads to inaccurate reporting, increased processing time, higher compute costs, and reduced trust in real-time insights.

What role does API architecture play in cloud scalability?

API-driven and event-based architectures enable systems to scale dynamically, handle higher transaction volumes, and reduce dependency on rigid, point-to-point integrations.

What is technical debt in cloud environments?

Technical debt refers to legacy code, inefficient processes, and outdated architecture that increase costs, reduce performance, and limit scalability in cloud systems.

How do cloud migrations impact financial performance?

Cloud migrations can increase or decrease costs depending on optimization. Poorly planned migrations often increase operating expenses, while optimized systems improve efficiency, reduce waste, and support growth.

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About the Author(s)

Trina Michels
Trina Michels
Director
Trina works with potential clients to help them understand the value of NetSuite implementation.
Shelley Earsley
Shelley L. Earsley, CPA, PMP
Partner/Technology Consulting Practice Leader
Shelley provides leadership for organizations working through their digital transformations, business and technology initiatives, strategic planning, organizational design assessments and implementation projects. She leads a group of talented professionals focused on providing solutions to business challenges.