29 Apr 2026
6 min read
Data and AI transformations don’t fail because of technology. They stall when organizations move too quickly without aligning people, processes, and existing systems.
In a recent TAG Data Talk episode sponsored by Wavicle, Dr. Beverly Wright speaks with Guy Brassard about what it really takes to build the right foundation before starting a transformation.
Here are five key highlights from the conversation on building that foundation the right way.
Speaker details
- Host: Dr. Beverly Wright – Executive in Residence at Institute for Insight, Georgia State University
- Guest speaker: Guy Brassard – Vice President & CIO, Shaw Industries
1. Leadership approval is only the starting point
Executive sponsorship is critical, but it does not move the transformation forward on its own. As Guy explains, approval from leadership is simply the baseline.
“Once the leadership team approve, it’s not the end of it. It’s just—it’s not like, oh okay, it’s all done because the leadership approved. How this transformation, this transformation will affect people is key and eventually what people need to understand is that what’s in it for me? What does that mean to change all this…
“By no mean it’s any easy, but if you just assume and lead with, ‘Hey, you have no choice. I got the CEO support. How long is that going to last?”
Organizations often assume that once leadership signs off, momentum will follow. In reality, the work only begins at that point. What matters next is ensuring that people across the organization understand what the transformation means for them and how it will impact their day-to-day work.
Without that clarity, even well-funded initiatives stall.
2. Start with people, legacy systems, and internal alignment. Not tools
Before selecting platforms, tools, or partners, Guy strongly advocates for internal preparation. That includes listening to teams, understanding existing systems, and acknowledging legacy constraints and technical debt.
“Quickly what we’re going to end up doing is not just talking to people about the changes but also understanding the current state of their legacy application, technical debt but things that will be affected by the transformation
Eventually you get so attached to your legacy system and then just to a point where seeing that changing over two three years when you’ve been using it for twenty‑five, thirty years I think it’s an interesting expectation we have to manage that altogether…
There is no rush, I believe, in signing up a new contract and getting the partners in the house. We need to clean up a little bit before. You don’t need help to do your housekeeping.”
Rushing into technology decisions without this groundwork often increases resistance and creates avoidable complexity later.
3. Change works best when it’s done with people, not to them
Resistance to transformation is rarely about unwillingness to change. Guy stresses the importance of listening, especially to those who push back.
“Make sure you do that with them, not to them. The people who push back usually care. They often have insights you wouldn’t get otherwise if you take the time to listen.”
Instead of forcing change after decisions are made, organizations should involve key stakeholders early. This includes even those who are initially against the transformation.
Listening, asking questions, and repeating back what’s been heard improves clarity and increases the likelihood of adoption. When people feel included, they are far more likely to support the change.
4. Platform decisions matter—but they are not the differentiator
While organizations often spend months comparing technology options, Guy is clear that tools alone do not determine success. Many platforms are capable; what matters most is how they are implemented, governed, and used.
“It’s not about the logo. It’s often about the people you find and whether they understand your business, your culture, and where you’re trying to go.”
What matters more is whether the people involved—internally and externally—understand the organization’s objectives and are aligned with how the transformation will be executed.
He also highlights the importance of balancing enterprise-wide standards with local autonomy. Teams should follow shared governance, but still have the flexibility to move quickly within those boundaries.
“As long as people follow the standard they helped build, they can work locally and move faster. That’s how you scale without creating chaos.”
Without shared standards, fragmentation grows. Without autonomy, speed and adoption suffer.
5. Don’t rush. Sustainable transformation takes time and discipline
A common mistake is moving too quickly into implementation. Guy’s advice is clear: slow down, be curious, and build the right foundation before making major decisions.
“Don’t start too quickly. Make sure you get the people on board. Be curious. Configure your platforms instead of over‑customizing them and let vendors be accountable for the capabilities they provide.”
He also emphasizes configuring platforms rather than over-customizing them, allowing vendors to deliver built-in capabilities—especially as AI features continue to evolve across ERP, CRM, and other systems.
At the same time, transformation does not end at go-live. Organizations must continuously learn, share both successes and challenges, and avoid repeating mistakes.
“It’s just the beginning… it’s going to stay.”
Final takeaway
This conversation reinforces a clear and practical approach to transformation: focus on people, understand your current state, and align the organization before making technology decisions.
When people are aligned and informed, data is reliable, and governance is clear, technology becomes much easier to implement and scale. Without that foundation, even the best tools struggle to deliver value.
Watch the full podcast below:
If your organization is preparing data‐ and AI‑driven transformation and wants to align people and data before making major investments, Wavicle can help you build the right foundation. Connect with us to learn how to move forward with confidence.
Disclaimer: Quotes in this blog are excerpted from a longer conversation and have been edited for length and clarity.
