7 Application Modernization Challenges and How to Avoid Them

79%.

That's how many application modernization efforts fail as per Wakefield Research.

The other 21 percent?

They didn't have better technology. They didn't have bigger budgets or smarter engineers. They had a clearer picture of what goes wrong and they planned around it.

This article will cover the 7 common challenges in application modernization — the application modernization pitfalls that show up repeatedly across industries — why each one derails work, and what you can do before it becomes a problem you're managing in production.

Most of these challenges are symptoms of the same root cause: treating application modernization as a technical execution problem when it's actually a planning and sequencing one.

Key Takeaways

• 79% of application modernization efforts fail. Most failures trace back to planning gaps, not technical ones.
• The hardest challenge isn't the code. It's the undocumented dependencies nobody knew existed until migration started.
• Big-bang modernization almost always fails. Phased delivery with business outcomes per phase is what survives.
• Change management is treated as optional in most projects. It's the reason most finished systems don't get used.
• Scope creep is the silent budget killer. Every challenge on this list can trigger it if it's not caught early.

1. Underestimating Complexity

This is the challenge that gets every team at least once. Application modernization complexity is rarely visible from the outside — the application looks manageable, a few services, a known codebase, a familiar tech stack.

Then migration starts and the real picture emerges. Undocumented dependencies. Services that call each other in ways nobody expected. Third-party integrations that were patched together in 2011 and never reviewed since.

The Red Hat/Konveyor survey of 1,000 IT decision makers found complexity is the top organisational challenge in application modernisation, cited by 48% of respondents, rising to 58% in the early stages when teams are still discovering what they're actually dealing with.

How to avoid it: Run a deep portfolio assessment before committing to any approach. Map every integration, every dependency, every downstream consumer of each service. The assessment takes time. Skipping it costs more. Teams that conduct formal readiness assessments before migrating have 2.4x higher success rates than those that don't.

2. No Clear Business Outcomes

Most modernisation projects start with a technology objective: "We're moving to microservices" or "We're migrating to cloud." Neither of those is a business outcome. They're approaches. And when budget pressure arrives — which it always does — approaches get cut. Outcomes don't.

The challenge shows up at the first steering committee meeting where someone asks: "What are we actually getting from this?" If the answer is technical ("better deployment pipelines," "containerised workloads"), the project is vulnerable. If it's business-language ("50% faster feature delivery," "30% lower infrastructure cost," "zero critical audit findings"), it survives.

This is where the benefits of application modernization conversation needs to happen before the project starts, not after the first phase delivers.

How to avoid it: Define a measurable business outcome for every workstream before work begins. Not a technical milestone. An outcome the business owner can report at a quarterly review. Tie funding decisions to outcome delivery, not task completion.

3. Big-Bang Thinking

The ambition is understandable. The portfolio has fifteen legacy applications, all of them overdue for modernisation, all of them causing pain. The plan: modernise everything in eighteen months, move the whole estate to cloud-native, and emerge transformed.

The outcome: eighteen months later, three of the fifteen applications have been partially migrated, the budget is exhausted, and the team is maintaining two environments simultaneously. Indefinitely.

Big-bang modernisation fails for a predictable reason. It's too large to maintain focus, too long to survive budget cycles, and too complex to deliver a clear win before the programme loses political support. Every challenge on this list compounds across a big-bang programme.

How to avoid it: Phase the work ruthlessly. Each phase should deliver a measurable business outcome in 3 to 6 months, be independently valuable, and be small enough to fit within a single budget cycle. The first phase should be the one most likely to succeed, not the most important one. A proven application modernization strategy sequences work to build momentum, not to tackle the hardest problems first.

4. Data Migration Complexity

The application gets most of the attention. The data underneath it gets underestimated every single time.

Legacy data architectures accumulate complexity across years: schemas that evolved without documentation, transformation pipelines nobody fully understands, downstream consumers that depend on specific field formats and quietly break when those formats change.

Add regulatory constraints on where data can live and how long it must be retained, and data migration becomes the critical path in almost every modernisation project.

How to avoid it: Treat data migration as a separate workstream from application migration, with its own timeline, its own team, and its own risk assessment. Audit the full data lineage (where data comes from, where it goes, what depends on it) before committing to an approach. Budget at least twice as long for data migration as the initial estimate suggests. Then add a contingency on top of that.

5. Skill Gaps

Teams often choose a modernisation approach based on what the architecture needs, not what the team can deliver. The right answer for the application is re-architecture to microservices. The team has never run a microservices estate in production. The gap between those two facts is where projects die.

Skill gaps show up in three forms: missing technical capability (nobody has done this before), missing operational capability (the team can build it but not run it), and missing domain knowledge (the engineers don't understand the business logic well enough to safely refactor it).

Legacy system modernization is where this challenge hits hardest. Legacy codebases are often the least-documented and most-coupled systems in the estate, and the engineers who originally built them have long since moved on.

How to avoid it: Assess team capability as part of the portfolio assessment, not as an afterthought. Match the chosen approach to what the team can actually deliver: replatforming when the team isn't ready to refactor, rehosting when replatforming is a stretch. Build in training, embed senior specialists, or bring in external partners for approaches the internal team hasn't executed before.

6. Change Management

This is the challenge that technical teams most reliably underestimate, and the one that most reliably kills finished projects.

Modernisation delivers a new system. That new system forces new workflows. The people who use it, support it, and depend on it need to change how they work. When that change isn't planned for (training, communication, process redesign, a deliberate productivity-dip allowance in the first thirty days) the new system gets rejected. Users build shadow processes on top of it. IT teams revert to the old system. The modernisation investment sits unused.

Employee resistance is behind 39% of organisational change initiative failures, according to McKinsey. Modernisation projects are not exempt from this.

How to avoid it: Treat change management as a delivery requirement, not an optional add-on. Assign a named change lead for every workstream. Build training plans, communication schedules, and feedback loops into the project plan from week one. The productivity dip is real and temporary — the goal is to plan for it, not be surprised by it.

7. Scope Creep

Every project has a scope creep story. Application modernization scope creep is particularly dangerous because the technical debt exposed during migration is real and genuinely needs addressing.

What starts as "migrate the customer portal to cloud" becomes "migrate the customer portal, refactor the authentication service, replace the legacy CRM integration, and also update the reporting stack because it's right there."

Six months later, the team is managing a programme three times the original size with the same budget and deadline.

The temptation to fix everything at once is understandable. But every scope expansion increases timeline, adds risk, and dilutes the team's focus. One scope expansion rarely kills a project. Three will.

How to avoid it: Define scope boundaries in writing before work starts and get explicit sign-off. When new scope is identified (and it will be), log it in a separate backlog and treat it as a future phase. Every scope change should require a formal decision: accept it now (and adjust timeline and budget), defer it to the next phase, or reject it entirely. Never absorb scope silently.

How These Challenges Connect

None of these seven challenges operates in isolation. Underestimating complexity (challenge 1) leads to missed business outcomes (challenge 2) because the technical work expands beyond what was planned.

Big-bang thinking (challenge 3) makes every other challenge worse. Data migration complexity (challenge 4) triggers scope creep (challenge 7) when the team discovers problems mid-flight. Skill gaps (challenge 5) create quality issues that compound the change management problem (challenge 6).

The common thread running through all seven is the same gap that causes most project failures: work that's planned at the surface and then surprised by what's underneath. The teams that avoid these challenges don't have more luck. They do more discovery before they commit.

That discovery work is what a serious application modernization strategy is built on: portfolio assessment, business outcome definition, phase sequencing, skill mapping, and change planning. These are the upstream decisions that determine whether a modernisation programme succeeds or becomes the next Wakefield statistic.

Managing technical debt proactively helps too. Most of these challenges are more acute in estates where debt has been allowed to accumulate unchecked — undocumented systems, brittle integrations, skill dependencies on individuals who understand the old code. The earlier debt gets addressed, the less complexity the modernisation team inherits.

The Part Most Teams Skip

Every one of the seven challenges above is avoidable. Not easily — but avoidable. Knowing how to avoid application modernization failures means doing more discovery and planning before writing a line of migration code than most teams spend on the entire first phase.

That discovery work is unglamorous. It doesn't produce visible output. It's hard to schedule a steering committee update around it. But it's the work that determines whether modernisation finishes or becomes the latest expensive lesson in the 79%.

Classic Informatics has helped mid-to-large enterprises unstick modernisation work at every stage, from an assessment that missed the complexity to a scope that got away from the team. Let’s have a conversation if you are encountering these challenges.