AI Doesn’t Fail Because of the Algorithm. It Fails Because of the Weights.
Not metaphorically. Literally.
The Wake-Up Call
A few years ago. Major automotive supplier, Stuttgart region. We implemented a Transport Management System—technically robust, operationally sound.
Then came the reality check: The system couldn’t calculate optimized routes. Not because the algorithm was flawed. Because no one knew how much the parts weighed. Or how big they were.
Weights and dimensions—the most basic master data in logistics—were missing. Or wrong. Or buried in an Excel spreadsheet no one had updated in years.
We had to completely redefine the project scope.
This wasn’t an isolated incident. In 30 years, I’ve seen it again and again—in SAP rollouts, digitalization projects, and now with AI.
The algorithm is never the problem. The problem sits upstream: in processes, in data, in the organization.
Why I Call Myself “The Industrial Translator”
Not because I explain AI. But because I know the gap between technology and operational reality.
And because I’ve learned:
- Ignore the gap? Burn budget.
- Close the gap? Create real value.
Next Steps
Planning to deploy AI in your company? Let’s verify if your master data can deliver what it promises.
E-Mail: sven.vollmer@business-quotient.com
Sven Vollmer is “The Industrial Translator.” He bridges the gap between industrial operational reality (SAP, supply chain) and the possibilities of generative AI. His focus is on value-creating applications—beyond the hype.
Transparency Note: This article was created with editorial support from AI (Gemini/Claude). The ideas, technical validation, use case selection, and adult supervision were 100% authored by Sven Vollmer.
LinkedIn: www.linkedin.com/in/sven-vollmer-bq
