At LAPP, we are currently thinking intensively about which data is really needed and, above all, why? The "why" is easy to answer: We want to offer our customers specific products and services which in turn enable them to create better ones themselves. In higher quality, in less time or at lower cost. That's why we don't just collect randomly, but question the exact use case and added value for the customer in all the information we gather. If this cannot be answered, there is no reason for us to collect such data at all.
LAPP is running numerous digitization projects at the moment, which also always deal with the correct use of data. In addition to condition monitoring and predictive maintenance, we are also revising our content management system and redesigning our digital product catalogue. We came to the conclusion at an early stage that it is not the quantity of data that is decisive for success, but its quality - better data instead of big data. That's why we don't just collect randomly, but question the exact use case and added value for the customer in all the information we gather. If this cannot be answered, there is no reason for us to collect such data at all. It is particularly important to us that this is done in compliance with data and privacy regulations. I am a fundamental supporter of the GDPR, as it emphasizes the value of personal data. It is demanding in its implementation, that is true, but it also creates clarity for us providers and gives control back to customers regarding their own data. In accordance with GDPR, we are revising our customer relationship management and cleansing the data records. Sounds like a lot of work, but it contributes to the clarity and accuracy of the information and thus to a higher quality in customer relations.
These figures show what a monumental task we are facing: The LAPP catalogue contains around 40,000 products, from cables by the meter to connectors and tools. For each of these products we are checking all product features. These are probably an estimated six million individual values. And then we adjust them, add new ones, pull attributes apart, and even discard some of them. By hand. At present, only a small part of this can be automated. We primarily rely on the many years of experience and expertise of our product management and sales departments to accomplish this.
When we change the attributes, we have to think both about making them readable and usable for humans as before, but also for all kind of systems in the future. Here's an example: Many of our products are designed for a specific temperature range: for example a cable with the attribute "-30°C to +120°C". In the printed catalogue it would also be written in the exact same way and even non-experts would understand the meaning. In the online catalogue, the challenge is somewhat different: A customer may need a cable that can withstand at least +80°C. To do this, he would set a filter such as ">80" for the search. The search software has to understand that this can result in different temperature values for the lower and upper range, and secondly that the upper range is the important one. At the same time, it has to exclude the possibility that an American might not mean ° Fahrenheit. The example demonstrates that it is not simply enough to digitize all information, but that it is also necessary to understand the connections between them. We digitized our analog print catalog years ago, but now it is mainly a matter of adapting our way of thinking and assuming that our customers will primarily use all offers digitally.