- Tension: Organizations rush toward digital transformation while treating the foundation of that transformation as an afterthought.
- Noise: Quick-fix migration solutions and “lift-and-shift” promises obscure the complex reality of moving business-critical data safely.
- Direct Message: Data migration succeeds when organizations treat it as a strategic transformation, not a technical checkbox.
To learn more about our editorial approach, explore The Direct Message methodology.
Here’s a number that should give every business leader pause: close to 85% of businesses run into a significant problem during data migration. Not minor hiccups. Significant problems. The kind that delay launches, inflate budgets, and sometimes corrupt the very information companies depend on to operate.
During my time working with tech companies in the Bay Area, I watched a promising startup lose three months of momentum because their migration team assumed moving customer data would be straightforward. It wasn’t. Their legacy system had years of inconsistent formatting, duplicate entries, and fields that meant different things to different departments. What they estimated as a two-week project became a quarter-long crisis.
The irony is striking. We live in an era obsessed with data. Companies invest millions in analytics platforms, hire data scientists, and build entire strategies around customer insights. Yet when it comes time to actually move that data somewhere useful, preparation often falls to the bottom of the priority list.
This disconnect reveals something important about how organizations think about digital transformation. There’s a gap between the vision of what new systems can accomplish and the unglamorous work required to get there. Understanding this gap is the first step toward closing it.
The Uncomfortable Truth About Transformation Timelines
Every organization tells itself the same story when planning a migration. The narrative goes something like this: We’ll select the new platform, the vendor will help us move our data over, and within a few months we’ll be operating with improved efficiency. It sounds reasonable. It almost never happens that way.
The tension lies in what organizations want migration to be versus what it actually requires. Leaders want a clean break from old systems. They envision a fresh start with better tools. What they get instead is a mirror reflecting every shortcut, workaround, and inconsistency their teams have accumulated over years of daily operations.
Shiv Kaushik, Chairman and CEO of ICCG, puts it directly: “When organizations embark on an enterprise resource planning transformation, data migration often becomes the silent disruptor. Despite its critical role, data migration is routinely undervalued. This can lead to project delays, unplanned costs and unreliable insights post-deployment.”
That phrase “silent disruptor” captures something essential. Migration problems don’t announce themselves upfront. They emerge gradually, often after significant resources have already been committed. A field that worked fine in the old system doesn’t map to the new one. Customer records that seemed complete turn out to have critical gaps. Security protocols that were sufficient before don’t meet new compliance requirements.
What I’ve found analyzing consumer behavior data over the years is that the same psychological patterns affecting individual decisions also affect organizational ones. We underestimate complexity. We overweight short-term convenience. We assume the future will be more forgiving than the present. These cognitive shortcuts serve us well in daily life but become liabilities when applied to technical projects with cascading dependencies.
The companies that struggle most are often those with the longest histories. They’ve accumulated data across multiple systems, through acquisitions, through departmental silos that developed their own conventions. Each layer adds complexity that simple migration tools can’t automatically resolve.
Why the Easy Path Creates Harder Problems
The technology industry has a talent for packaging complicated processes into simple-sounding solutions. “Lift-and-shift” is perhaps the most seductive of these packages. The concept promises exactly what stressed executives want to hear: take everything you have now, move it to the new system, and start benefiting immediately.
Kevin Campbell, CEO at Syniti, part of Capgemini, challenges this assumption head-on: “While that seems like a quick and cost-effective solution, I’m here to tell you that it creates more problems than it solves.”
The appeal of lift-and-shift is understandable. Organizations are already stretching budgets and timelines to adopt new platforms. The idea of adding extensive data preparation work feels like scope creep. But this thinking confuses activity with progress. Moving bad data faster doesn’t make it good data. It just relocates the problem while adding new technical debt.
A survey by Softek found that 83% of data migrations experience problems, with unexpected downtime being the leading issue, followed by technical compatibility issues, data corruption, application performance issues, and data loss. These aren’t edge cases. They’re the norm.
The conventional wisdom in enterprise software circles often emphasizes speed to deployment. Vendors have incentives to show quick wins. Internal champions need to demonstrate momentum to maintain organizational support. This pressure creates an environment where thorough preparation feels like unnecessary caution.
But speed without foundation is fragile. I learned this the hard way during my years in growth strategy. Data without empathy creates products nobody wants. Similarly, migrations without preparation create systems nobody can trust. When employees don’t trust the data in their new platform, they create workarounds. They maintain shadow spreadsheets. They make decisions based on intuition rather than insight. The promised benefits of the new system evaporate.
Seeing Migration as Strategic Investment
Data migration succeeds when treated as a strategic transformation opportunity rather than a technical necessity to endure. The process itself becomes valuable when organizations use it to understand, clean, and improve their most critical asset.
This reframe changes everything about how migration projects unfold. Instead of viewing preparation time as delay, organizations can recognize it as investment. Instead of seeing data cleaning as tedious overhead, teams can approach it as the foundation for every analytical capability they hope to build.
Kaushik offers an important perspective: “Data migration doesn’t have to be a risk. With the right strategy, leadership focus and execution, it can become a powerful enabler of ERP success and long-term business value.”
The difference between organizations that struggle and those that succeed often comes down to this mental shift.
Building Migration Readiness Into Organizational Culture
A report by PwC highlights that low-quality or siloed data can compromise analytics, decisions, and regulatory reporting, steering transformation programs off course. The report emphasizes data readiness as essential to mitigating transformation risks.
Data readiness isn’t a one-time project. It’s an ongoing organizational capability. Companies that maintain clean, well-documented data as standard practice find migrations significantly less disruptive. Those that treat data hygiene as someone else’s problem accumulate technical debt that compounds over time.
The practical implications are straightforward, even if implementation requires discipline. Understanding your data before migrating means knowing what you have, how clean it is, and what security protocols apply. Testing and validating throughout the process catches problems while they’re still manageable. Backing up everything acknowledges that technology fails and recovery options matter.
When I consult for startups on behavioral pricing and conversion strategy, I always ask about their data infrastructure first. The answers reveal more about an organization’s maturity than any pitch deck. Companies that know their data intimately make better decisions. Those that treat it as an abstraction stumble when reality intervenes.
The California tech ecosystem has produced countless tools promising to make data work easier. Some of them deliver real value. But no tool can substitute for organizational commitment to data quality as a continuous priority rather than a periodic cleanup.
For leaders preparing for migration, the essential questions aren’t technical. They’re strategic. Do we understand what our data actually contains? Have we invested in cleaning it before we try to move it? Are we giving this process the time and resources it genuinely requires?
The organizations that answer these questions honestly position themselves to join the minority that migrates successfully. The rest discover that moving unprepared is worse than not moving at all.
91% of companies will attempt data migration. The question isn’t whether your organization will face this challenge. It’s whether you’ll approach it as a strategic opportunity or an inconvenient obstacle. That choice, more than any technology selection, determines the outcome.
