Month: June 2025

It usually starts with urgency. A missed launch window. A report that doesn’t add up. A customer touchpoint that goes sideways, because the data behind it wasn’t there, wasn’t right, or wasn’t trusted.

From there, the scramble begins. Teams look to the system: maybe it’s outdated, misconfigured, or just not “smart” enough. A new platform feels like the fix. Something faster. Sleeker. More powerful.

But here’s what we’ve seen, again and again: The system might be new. But the struggles are the same.

Manual workarounds. Inconsistent content. Channel delays. Reporting gaps. Why?

Because the real issue wasn’t the platform, it was what you asked that platform to manage.

Bad data doesn’t magically become good data in a new interface. And most systems aren’t designed to be business-ready from the outset.

That’s why the companies seeing real transformation today aren’t just upgrading tech. They’re upgrading their data strategy first.

Data Is Not a Byproduct—It’s the Core

In most companies, data is treated like an output. Something that shows up once the system is in place.

But the reality is the opposite: Data is the input. It’s what drives performance, accuracy, trust, and scale.

You don’t need another dashboard to tell you something’s off. You need to fix what’s underneath it. When your product data is fragmented, incomplete, or out of sync, no amount of interface design will solve the root problem.

You need structure. You need standards. You need a model that actually reflects how the business works. And that doesn’t start with technology. It starts with intent.

Why System-Led Transformation Keeps Falling Short

Most organisations don’t struggle because they chose the wrong tool. They struggle because the tool has become the strategy.

When transformation efforts centre on software decisions, it’s easy to lose sight of what actually drives the business forward: product launches that arrive on time, clean reports that don’t require revision, and content that flows seamlessly from source to shelf without rework.

However, when the focus is purely on implementation, without rethinking the shape, structure, and purpose of the data underlying it, those outcomes remain just out of reach.

The real issue isn’t platform performance. It’s data performance.

Because systems only do what the data allows them to do. If the data is inconsistent, incomplete, or misaligned, even the best tools won’t deliver the value they promised.

So the better question isn’t “Which platform should we invest in?” It’s “What does our data need to deliver, and what’s stopping it today?”

The Shift: From Tools-First to Outcomes-First

Here’s what the new playbook looks like:

1. Start with the outcomes. What do you need to deliver, automate, measure, or improve?
2. Work backwards to the data. What attributes, hierarchies, and relationships power those outcomes?
3. Define the rules. What does “good” data look like for your products, your channels, your buyers?
4. Build systems that support that, not just systems that check the box.

It means prioritising speed to market over technical complexity. It means improving channel confidence by giving partners the right content the first time. It means letting sales and marketing work with data they trust, without calling in the data team every time.

And yes, it means pushing back when someone suggests that buying a new tool is the whole solution.

Business First. Data Led. Automation Driven.

That’s the model. And it’s working.

Instead of racing into the next replatform, more companies are stepping back and asking: Is our data actually fit for purpose?

• Can it support channel-specific syndication?
• Can it scale as we grow into new markets or categories?
• Can it adapt when buyers change how and where they engage?

If the answer is no, then you don’t need a new system. You need a new approach.

One that gets the fundamentals right. One that builds trust from the inside out. One that aligns your data with the goals that actually matter.

Because it’s not about adding another platform to your stack. It’s about making your entire stack work harder, by making the data smarter.

Conclusion: The Real Transformation Starts With the Data

Digital transformation isn’t just about tools. It’s about outcomes.

And outcomes come from data that’s complete, structured, and ready to move, not just stored somewhere new.

So before you greenlight that next system upgrade, take a beat. Ask yourself: Is our data ready to support the future we’re building toward?

If the answer is no, the next best investment isn’t the system. It’s the strategy that gets your data right first.

Because once your foundation is solid, the rest of the transformation doesn’t just get easier. It actually works.

How about we take the first step towards ensuring our data is right for our systems? We at Thoughtspark can do this for you, all we ask is for you to connect with us!

You’re being told it’s time to move.

Your contract is expiring. Your platform version is no longer supported. Maybe your vendor is sunsetting the entire product line. The messaging is loud and clear: it’s time to upgrade, replatform, or rebuild.

And maybe that’s true. But here’s the question no one is asking loudly enough:

Will any of this actually solve the problems you’re dealing with?

Because in most cases, the pain isn’t only the platform. It’s also the data.

It’s Not the Stack—It’s the State of the Data

You’ve felt this already.

The long hours spent fixing the same product data issues on repeat. The Excel workarounds that have somehow become business-critical. The product launches that slip. The listings that stall. The specs that don’t line up across channels.

And the trust, between teams, with customers, with partners, that starts to erode, little by little, with every delay and discrepancy. You can rebuild the tech stack. But if the data is still fragmented, inconsistent, or incomplete, you’ll just be managing bad data in a fancier interface.

That’s the reality no replatform pitch deck wants to talk about.

Because most MDM and PIM systems were never designed to prepare your data. They’re designed to govern it after it’s clean. Which means the real heavy lifting, profiling, standardizing, validating, and syndicating, still gets kicked downstream to overworked teams who already know how this plays out.

The Hidden Cost: Replatforming Alone Won’t Break the Cycle

Let’s be honest: there’s a playbook here.

Step 1: Get pushed into an upgrade or migration.
Step 2: Spend months (or years) configuring and customizing.
Step 3: Migrate all your legacy data into the new system.
Step 4: Realize that all the old issues came with it.
Step 5: Start patching, fixing, and firefighting all over again.

Sound familiar?

We’ve seen this cycle play out across industries, from manufacturing to retail to distribution. The common denominator isn’t the platform. It’s the core, the data!

When the data isn’t ready, replatforming just turns a data problem into an integration problem. Or a delay problem. Or a user adoption problem. And you wind up stuck in the same reactive loop, just with a prettier dashboard and a bigger invoice.

Ask Better Questions Before You Sign That Upgrade Contract

So before you lock yourself into another five-year cycle, ask a different set of questions:

• Is your product data really serving the business?
• Can it support faster product launches and omnichannel syndication?
• Can your teams trust it enough to power automation and self-service?
• Can your partners rely on it to drive listings, content, and conversions?
• And most importantly, can it adapt to what your buyers expect next?

If the answer is no, or even “not really”, then your strategy may be faulty.

Because replatforming isn’t a tech decision alone. Readiness? That’s a business decision.

It’s the difference between “what software do we use?” and “what outcomes are we trying to deliver?”

Where Are You on Your Data Readiness Scale?

Before you think about platforms, think about readiness. Ask yourself: where are you in your data journey?

• Is your product data consistent across systems?
• Do your teams still rely heavily on manual Excel workflows?
• Can you launch a new SKU in under 3 days?
• Is your data aligned to the requirements of each selling channel?

If these questions feel uncomfortable, you’re not alone. But that discomfort is also a sign: Your data isn’t ready yet.

Checklist: Are You Data Ready?

Give yourself a quick self-assessment:

Is your product data consistent across 3+ systems?
Can you launch a new SKU in less than 3 days?
Are manual Excel steps less than 10% of your product data flow?
Can your content be syndicated across marketplaces without manual intervention?
Is your data enriched with the context your buyers expect—across every touchpoint?

If you answered “no” to more than one of these, replatforming might just magnify the cracks.

What Good Data Looks Like

• Clean: No duplicates, errors, or misaligned values.
• Normalized: Aligned to taxonomy and attribute standards.
• Enriched: With marketing copy, visuals, specs, and certifications.
• Channel-ready: Structured for each endpoint—retailers, D2C, mobile, etc.
• Trusted: Validated by both systems and subject-matter experts.

This is what unlocks better launches, smoother syndication, and faster time to market, not just the next new tool.

Rethinking the Migration Approach: Data-First, Platform-Last

Here’s the shift that makes everything work better:

• Begin with a data audit. Know what you have, what’s broken, and what’s working.
• Fix the core first: clean and normalize your top 20% most-used product data.
• Align your content with the channels that drive 80% of your revenue.
• Then, and only then, bring in the technology that supports the clean foundation.

This is the model that turns replatforming into transformation. Everything else is just a cosmetic upgrade.

Replatform If You Must—But Rethink the Model First

We’re not saying don’t upgrade. There are real cases where it makes sense.

But if you’re going to invest that much time, money, and effort, make sure you’re not just recreating the same problems in a shinier environment. Make sure your data strategy evolves along with the system, because one without the other just leads to déjà vu.

A new platform with the same messy data is like putting new tires on a car with a cracked engine block. It might look better, it might run a little smoother, but the real problem’s still under the hood.

So replatform if you must. But rethink the model first. Because if your data still isn’t ready, neither is your business.

Conclusion: Fix the Data, Not Just the Platform

You’re under pressure to move fast. To modernize. To upgrade.

But don’t confuse motion with progress.

The system might be due for a refresh. But the foundation, your data, needs to be ready first.

Without that, every new platform is just another layer on top of the same old mess.

If you’re spending more time cleaning, fixing, and reconciling than delivering, maybe the answer isn’t just replatforming. Maybe it’s time to rethink how you get your data ready in the first place.

Because the problem was never the stack. It was the state of the data. And that’s the part you actually can fix, for good. Fix this part with Thoughtspark today!