Case Study

Technology: Progress through deep and pragmatic know-how

More than just software: how we find the right technological answers to the real problems

Technological progress is more than simply introducing new software. True leadership in this field means asking the right questions, understanding the limits of standard solutions, and developing tailor-made approaches only when needed to create real value. Our independence from software vendors and our deep technical know-how – all the way to our own software development – enable us to do exactly that.

Case 1: The forecasting trap – why the most expensive solution was not the right one

A client faced a classic dilemma: warehouses were full, yet delivery capability was poor. The planned solution seemed obvious: an expensive, highly complex forecasting software that would predict future demand based on statistical models.

But we did what a pure software vendor would not have done: we analyzed the data first. Our evaluation showed that the client’s project-driven sales behavior did not provide a statistically significant basis for a reliable forecast. The planned investment would have been an expensive digital failure.

Instead, we developed a smarter, better-fitting strategy:

The right methodology: we introduced Demand Driven MRP (DDMRP). Instead of trying to predict the distant future, this method focuses on drastically reducing the reaction time to actual demand (time-to-market).
The better process: we optimized the Sales & Operations (S&OP) process and created a bridge between often overly optimistic sales figures and statistical reality.

The result: instead of an ineffective forecast, the client received an agile system that significantly reduced inventory while increasing service levels – at a fraction of the originally planned cost.

Case 2: From data chaos to intelligent automation

Another company struggled with a fundamental challenge: important information was trapped in an unstructured tangle of invoices, order confirmations, delivery notes, and technical data sheets. Manual evaluation was unthinkable.

Standard solutions such as conventional OCR often fail miserably here. They confuse characters such as a capital “O” and zero or a lowercase “l” and a capital “i” and, worse still, they struggle with table structures, which leads to massive errors.

This is where our technological depth came into play. We developed an advanced technology that understands documents and their structures. Without extensive training for every single document type, the AI was able to recognize tables independently, assign data correctly, and turn the information into a clean, usable form. More reliably than humans.

This core technology led, almost as a “by-product,” to our own powerful software. Today it automates the entire workflow for our clients: from reading incoming email attachments to intelligent data extraction and the fully automated matching of purchase order, delivery note, and invoice (three-way match).