Imagine you are heading to a high stakes meeting with a potential big client to further expand your business outside of your small country of Curacao. Your phone buzzes—the client asks if they can get different breakdown of customers base linked by age group which you never had before, including the expected forecast sales and YOY growth.
In many local offices, this triggers a “Panic Search”: frantic WhatsApp voice notes to colleagues, waiting for manual CSV exports, and spending precious time cleaning data in Excel. You walk into the meeting with a report that is already less relevant to the potentials. You have the data, but you can’t see what it’s telling you. You’re flying blind with a cockpit full of instruments.
Now, imagine a different reality. Your warehouse logs and sales transactions are already linked in a secure, unified cloud environment. You aren’t “running a report”; you are querying a reality. You enter that room with certainty, not just spreadsheets. This isn’t about an “easy button”—it’s about building a house where you finally know where the keys are.
The Mirror: Diagnosing the “Dead Curve”
Why are we stuck in the Panic Search? It isn’t a lack of talent; it’s that change is scary and staying put feels safer—even when “staying put” means working harder for smaller gains.
We blame old computers, but the real problem is that our systems don’t talk to our strategy. We’re solving the wrong problem.
Think of it this way: every technology has a limit—an S-curve.¹, a rate of how much productivity we can get out of tool. In Curaçao, many of us are exhausting ourselves trying to squeeze the last drops of efficiency out of the “Manual Excel” that have been with decades now. We’re polishing a machine that has already stopped working.
The “Leapfrog” isn’t about climbing that old adoption curve faster; it’s about jumping to a new one (cloud-native tools, AI-assisted analytics) where the potential is vertical again. By perfecting 2015-era processes, you’re optimizing yesterday’s solutions for tomorrow’s problems.
So the question becomes: do you keep optimizing the curve, or do you accept the discomfort of jumping to a new one? If you choose the leap, here’s what to expect.
The Strategy: The “Awkward Middle” (Biting the Bullet)
Here’s the uncomfortable truth: it gets messy before it gets better.² You dismantle the old manual ways before you’ve fully mastered the new automated ones. Your team will complain that “the old way was faster.” Dashboards sit unused because people don’t trust data they didn’t create themselves.
This awkward middle? It’s not failure, it’s the process. Every organization that makes this leap goes through it. That local beverage distributor manager, who’s is fixed fixture at your big family gathering, who linked warehouse to sales? Their first insight was painful: two years of overstocking the wrong products. But they finally knew. And knowing, even when it stings, beats guessing.
The instinct during this phase is to retreat back to what’s familiar. Biting the bullet means pushing through that discomfort long enough for the new way to become the normal way. So what does that actually look like in practice?
The Tactic: Moving Knowledge from “Juni’s Desktop” to the System
Too many local firms rely on “Hero IT”—systems that only work because one specific person (let’s call him Juni) remembers the manual logic. This is a massive liability. If the knowledge that makes your reporting work lives only in Juni’s head, your company is one resignation away from a blackout.
The Leapfrog way of approaching reality of business & IT moves knowledge from the person to the system.³ Here’s how:
Relative Advantage: Don’t just buy Azure or Fabric because it sounds modern. Use it to solve a specific boardroom pain—like real-time inventory visibility or sales forecasting that doesn’t require three days of manual work.
Observability: Start with a pilot project. When other managers see the result—when they watch someone pull a real-time report in 30 seconds that used to take half a day, the fear of change vanishes.
Information Independence: Leadership succeeds when you can access the insights you need without waiting on a manual chain of command. It’s not about becoming a technical expert; it’s about not being held hostage by the one person who knows where the data lives.
And here’s why this matters in dollars and cents: How many hours does your team spend monthly hunting down information that should be automatic? A local wholesaler calculated 15 hours just reconciling inventory—$4,500 yearly per person. Multiply across departments. The cost isn’t hypothetical; it’s already labeled “normal operations.”
Where This Goes Sideways (And How to Avoid It)
Let’s be honest about where this fails:
Mistake 1: Buying technology before knowing your question. It’s like buying a hammer because hammers are useful, then realizing you don’t actually have any nails. The tool sits there. Everyone feels guilty. Nothing changes.
The fix: Start with the question. “What decision would I make differently if I had better information?” Then find the tool that answers that.
Mistake 2: Migrating messy data without cleaning it first. Garbage in, garbage out—but now it’s expensive, cloud-based garbage. You’ve just automated the mess.
The fix: Accept that the first phase is often manual and boring: standardizing how you record customer names, product codes, dates. It’s not glamorous. But you can’t build a house on sand, even if the house design is beautiful.
Conclusion: Calculated Boldness
Curaçao has a unique advantage: We are small enough to be agile. While global giants are stuck untangling 30 years of “Technical Debt,” we can skip those legacy steps entirely.
Here’s the truth about Curaçao: specialized talent is scarce and expensive. Physical infrastructure in this climate is a liability. That’s precisely why tools like Azure, AWS, and Fabric matter—they give us access to capabilities we cannot build or maintain locally.
The real risk isn’t investing in modern platforms. The real risk is staying dependent on systems that only work because one person remembers how. When they leave—and they will—the knowledge walks out with them.
Start with one question you can’t answer today but wish you could. Build that answer. Then ask the next. That’s not timidity—that’s building confidence before you ask the board to bet bigger.
The “old way” feels safer because it’s familiar. But in a small market with scarce talent and global competition, familiarity is the riskiest bet you can make.
Are you ready to stop polishing a dead curve and start querying your reality?
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¹ Christensen, C. M. (1995). “Disruptive Technologies: Catching the Wave.” Harvard Business Review. The foundation of the S-Curve and leapfrog strategy.
² Besson, P., & Rowe, F. (2012). “Strategizing IS-Enabled Organizational Transformation.” MIS Quarterly. Defines the “Uprooting Phase” of transformation.
³ Rogers, E. M. (2003). Diffusion of Innovations. Free Press. Frameworks for Relative Advantage, Compatibility, and Observability in technology adoption.
