Our tailored data analysis reports provide you with in-depth insights specifically aligned with your business requirements. We use advanced statistical methods to turn complex data into clear, actionable insights.

Whether process optimization, quality control, or strategic decision-making, our commissioned analyses provide the basis for data-driven decisions with a lasting impact. Rely on our expertise to make the best use of your data and achieve your business objectives.

The ways in which data is generated in the form of product, process, and lifetime data are virtually countless. In addition, the data to be analyzed is rarely available directly in a form that can be meaningfully evaluated. Experienced and regular “data analysts” are repeatedly confronted with this time-consuming situation. Most of the time invested in a data analysis is charged to data organization. Furthermore, the existing data quality can make a cause-and-effect analysis—e.g., across a complete value chain—difficult in some cases.

Of course, we also see the development of rapidly increasing volumes of information/data. This also increases interest in evaluating the “old” and “new” data together in such a way that clear added value is generated from the data and, not least, at least a return on investment is achieved for the investments made, for example, in data acquisition.
For us, data mining complements the classic statistical methods. Modern methods such as neural networks or machine learning are not always a sensible option when predictive models (e.g., predictive maintenance) are desired.

In projects, we jointly decide which methods can be used effectively, based on the complexity of the available data and the agreed objectives.

Either way, it is highly valuable for at least all areas of a company to understand the relationships between, for example, incoming material, process data, and product quality. This allows products and processes to be designed not only more robustly—reducing scrap and warranty claims—but also keeping costs predictable.