This article is part of the How Do YOU CM2? blog series in collaboration with the Institute for Process Excellence (IpX). Although I receive compensation for writing this series, I stand behind its content. I will continue to create and publish high-quality articles that I can fully endorse. Enjoy this new series, and please share your thoughts!
What is the quality level of the product data in your organization?
- 🤥100%? — You’re lying to yourself.
- ✅99%? — Hard to believe.
- 🆗95%? — Impressive, but not enough.
- ❌Less than 95%? — That’s the reality for most organizations.
I encountered a company where 70% of spare part data had at least one incorrect attribute value. They didn’t even know which ones, not without a deep investigation.
How valuable is that data?
👉 Exactly. Not at all.
Poor-quality data multiplies. Every time it’s reused, copied into another system, referenced in a design, or used to train an AI model, the errors compound. And when those flawed data sets fuel your “AI-driven product innovation,” you’re not accelerating insight… you’re accelerating inaccuracy.
And let’s not forget confirmation bias.
People want to believe that AI, automation, and “digital transformation” are working, but data often tells another story. In one study, experienced open-source developers completed 246 tasks to measure AI-assisted performance.
📈Economic and ML Experts predicted about 40% efficiency gains.
📈Developers, both during and after the study, predicted about 20% efficiency gains.
📉The observed results? A 20% efficiency loss.
You cannot blindly trust that AI is going to solve all your problems. You have to be smart about it and make data-driven decisions, based on high-quality data. And that’s where Enterprise Configuration Management (CM2) comes in.
CM2 isn’t about managing your data; it’s about curating it.
It establishes the framework to ensure every piece of product information, from requirements to test results, is identified, linked, owned, validated, and released. Resulting in complete, correct, current, and compliant data every single time.
Without that foundation, your digital twin becomes a digital hallucination; a model that looks right but behaves wrong. Is your digital transformation actually working for you, making your day-to-day business efficient and effective, or is it something only for leadership to perceive as progress? Do your metrics tell you the truth?
So, ask yourself:
🔹 How much of your data can you truly trust?
🔹 How much of your AI output is based on assumptions, not accuracy?
🔹 And how do you CM2?
Let’s talk about it.👇
Check out the other How Do YOU CM2? posts.
Copyrights by the Institute for Process Excellence.