How Slovenian companies successful take on the challenges of digitalisation in their production processes

Based on the data acquired from the European commission there have been 15 propositions proposed for digitalisation of the industry in the last years and 7 are still in the preparation phase. However, statistics show that European SMEs are lacking in the level of digitalisation compared to big companies that are relatively well digitalized.

Iskratel is one of the many companies that is mentioned in the article as an example of a relatively well-digitalized company. Iskratel group was with the use of different informational system able to digitalize most of their production and business processes. However, they believe that digitalisation alone is not enough to attain the complete digital transformation. Because of that, they decided to propose a project of digital optimization with the goal to increase productivity, optimisation of operational costs as well as improve user experience. Janez Öri, the director of the sector for strategic development, innovation and digitalisation in Iskratel added that these are the main steps they need to take if they want to attain their strategy of digital transformation with which they are aiming to develop and support new business model as well as create new revenue streams. On the other hand, we have Metro that is focusing on solutions to support production processes. They believe that their solutions can usefully leverage a large amount of data coming from different devices and provide users with content that can improve the quality of their products, increase productivity and improve competitiveness.

Digitalisation also plays a big role in one of the biggest pharmaceutical company in Slovenia named Krka whose business and production processes have implemented all of the elements that are nowadays understood as industry 4.0. Elements that are most commonly used in their production processes are automatization, digitalization, artificial intelligence, robots and big data for decision analysis and process optimization as well as for predicting future events.