„Garbage in, garbage out ?!“

www.cmsattler.com - Garbage in, Garbage out!

There are two points of view onto reality in digital transformation.

  1. The physically tangible reality: The people, machines, tools, workpieces and the processes.
  2. The data that people, machines, tools and workpieces generate during a process and represent the digital twin.

What did Prof. Dr. Karl Schmedders mean in his lecture last weekend at the IMD Business School International Institute for Management Development (IMD), in Lausanne, in Switzerland, when he spoke about data and „garbage in, garbage out!“?

Here is an example from my lecture at the International Institute for Management Development (IMD) in Lausanne, Switzerland, last weekend: „A company asked me to use the data volume of the last 40 years (170 TB) to determine the dependencies of a production process on macroclimate and microclimate. These findings have to flow into forecast models for future product developments.“ What does „Garbage in, garbage out!“ mean in this context? Here are three examples:

  1. The production data determined by the programmable logic controllers (PLC) could be exported. For example, the PLCs provided us with the raw data for a switchable valve, date, time and switching direction (open or close). Statistical analyzes and stochastic forecasts for this task could not be calculated with this raw data. We needed the time between two switching operations. These had to be calculated first.
  2. We also needed macroclimate data from the region and microclimate data from the production buildings. We were able to purchase the macroclimate data from a provider of weather data. The microclimate data were available in encrypted form on data loggers. There was no export software for the encrypted data and the data logger manufacturer refused to develop it. There were only cumulative daily values ​​printed out on thermal paper. The microclimate data were de facto not available in usable digital format.
  3. The employees of the R&D department and production had agreed on a format for the documentation so that the data can be compared with one another. The problem was that this data format was extended or shortened individually by the employees. It was not possible to automatically read in the 1.4 million files and evaluate the measured values.

How to resolve this type of data garbage, I describe in my book „Simply think data differently! – Companies‘ undiscovered gold!“, which will released in Q1.2022 in German and in Q2.2022 in English, and in the online events of „Mittelstand GOES Digital 4.0“.