The Chicken or the Egg: Investing in Data for a System That Will Soon Be Replaced?

You know you can use data to improve your organization. You see the possibilities, you understand the value. But you also know that your organization is constantly changing—and you’ll probably replace one or more systems within the next year or two.

Should you invest in data now, or wait until after the new system is implemented?

This is the classic “chicken or the egg” problem many organizations struggle with. In my 15 years of experience with BI implementations, I’ve seen this dilemma countless times. The answer isn’t simple, but there is a practical approach that works.

The Dilemma

Most organizations fall into one of two traps:

Trap 1: Wait for the new system — “Why would we invest now if we’ll have to redo everything in a year anyway?” This sounds logical, but it means you’re flying blind for a year without the insights you need to steer your organization.

Trap 2: Invest now and start over later — “Let’s just start, we’ll see what happens.” This leads to frustration when you indeed have to rebuild everything after the system replacement, and to the feeling that you’ve wasted time and money.

Both approaches are flawed because they ignore the value that data investment now can have for the system selection itself.

The Solution: Data as a Guide for System Selection

My experience has taught me that the question isn’t “should we invest now or wait?” but “how can we invest in a way that delivers value, even if there’s rework?”

The answer: use the data exercise to discover what you really need from your new system. Not just the features it has or doesn’t have, but especially: what do you need to calculate your KPIs and steer your organization?

In my experience, this is the most valuable input for system selection—and you only get it by working with data now.

The Practical Approach

I always use this approach when clients face this dilemma. Imagine: you’re replacing your ERP system within 12-18 months. You know you need data to steer your organization, but you wonder if it makes sense to invest now.

Step 1: Start with your KPIs, not your system Which KPIs do you use to steer your organization? Not “what can the system do?”, but “what do you need to know if you’re on track?” I’ve seen organizations that skip this step choose systems based on features instead of what they really need.

Step 2: Work with what you have Use your current system to calculate these KPIs. It won’t be perfect—that’s okay. The goal isn’t perfection, the goal is to discover which data you need and how you combine it. In my experience, you learn more from this than from vendor demos.

Step 3: Document what you discover During this exercise, you discover things you wouldn’t have known otherwise. Which fields are really important? Which calculations are crucial? Which data combinations do you need? This becomes your requirements document for the new system—not based on what vendors say you need, but on what you actually use.

Step 4: Use this for system selection Now you know exactly what you need from your new system to calculate your KPIs. Separate from the features it has or doesn’t have. This changes your selection process—you no longer ask “does it have this feature?” but “can I calculate my KPIs with this the way I calculate them now?”

I’ve helped clients who made better system choices this way because they knew what they really needed, not just what vendors said they needed.

Why This Works

This approach works because it accepts the rework but extracts value from it. You know upfront that there will be rework—but that rework isn’t waste, it’s investment in knowledge.

By working with data now, you learn what you really need. When you then select the new system, you don’t do it blindly. You know exactly which functionality is crucial for your organization, separate from what vendors say is important.

In my A-to-Z implementations, I always use this approach when system replacement is on the agenda. We don’t build for eternity—we build to learn. And that knowledge makes system selection better.

The Trap of “Perfect Timing”

The danger lies in waiting for perfect timing. “We can’t start until the new system is here.” Or: “Why would we invest now if we’ll have to redo it anyway?”

Perfect timing doesn’t exist. Organizations are always changing—there’s always a system being replaced, a process changing, a new challenge. If you wait for perfect timing, you never start.

I’ve seen more projects fail by waiting for the “right moment” than by starting with imperfect circumstances. An imperfect data solution that helps you make decisions now and informs your system selection is more valuable than perfect timing that never comes.

The Philosophical Depth

This problem has deeper philosophical roots. It’s about change and uncertainty—how do you make decisions in a world that’s constantly changing?

The solution doesn’t lie in avoiding change, but in accepting that change is constant. You don’t wait until everything stands still—you work with what you have and use that knowledge to make better decisions about what’s coming.

In data, this means: you don’t start with perfect circumstances. You start with what you have, and you use that experience to make better choices for the future. The rework isn’t waste—it’s investment in knowledge you wouldn’t have had otherwise.

Conclusion

The “chicken or the egg” problem with system replacement isn’t something you solve by waiting—it’s something you solve by accepting that rework is part of the process, but that rework can have value if you approach it right.

Don’t start by waiting for the perfect moment. Start by working with what you have, discover what you really need for your KPIs, and use that knowledge to make better system choices. The rework that comes isn’t waste—it’s investment in knowledge that informs your system selection.

This is exactly why I always start with strategic alignment in my Vision-to-Growth Framework before we look at tools or systems. We first identify the KPIs that matter, then how you calculate them with what you have, and only then what you need from new systems to keep calculating those KPIs.

Waiting for perfect timing is a trap I help prevent in my advisory work. It leads to missed opportunities and poor system choices because you don’t know what you really need. Start now, learn what you need, and use that knowledge for better decisions.

Are you facing the choice to invest in data now or wait for system replacement? Get in touch for a consultation call, or read more about my philosophical approach to data.