17. November 2017
The German federal state of North Rhine-Westphalia is home to many high-tech companies, among them GKD. We all offer good or even very good products, but find ourselves in the midst of dramatic change. In the past we all had proven business models in order to react to market demands flexibly, quickly and effectively. These models were oriented on adding value as well as on functions and performance. Our ERP systems detected deviations and planned reactively based on this. However, in view of the enormous increase in the complexity of processes and structures as well as customer and quality requirements, this is no longer sufficient. If we want to hold on to our lead on the global marketplace, from now on we need to anticipate developments rather than merely reacting to them. We have long been doing this with our smartphones: before traveling into the city center we check the traffic, the weather forecast, recommended restaurants and events. The smartphone utilizes big data for this purpose, thus giving us the opportunity to navigate perfectly during our trip. We cannot yet do this in our companies due to the heterogeneity of existing data. We can however process, save and transfer great quantities of data more quickly than ever before – and these capacities are multiplying rapidly.
The challenge for entrepreneurs is therefore to master our increasingly complex processes and mechanisms so that we can control them in the same way as our journey into the city. But this process must not slow us down – on the contrary, it should help speed things up considerably. We can simply no longer afford to waste our resources in the form of existent but unused production data by searching and waiting for the required information. When it comes to increasing the efficiency of development and production, there is no alternative to big data. Like our smartphones in our day-to-day lives, it should also be possible to use all information regarding our manufacturing and value creation processes in our companies at any time and interpret and apply it in real time. As such, big data also opens up entirely new development mechanisms. GKD is already putting these into practice for the automotive industry in the field of filters for exhaust gas recirculation. We no longer build a complete prototype, but instead manufacture tools using 3D printing while at the same time simulating the flow behavior. Before making the real filtration product, our development department builds a digital twin, allowing us to make fewer sample weaves. The validation and optimization processes are then performed together with the customer. The findings from the real prototypes are automatically digitized and are immediately put to use in the development process. Using this procedure our filters reach series maturity much more quickly than in the past. After each development process – regardless of whether this is for a product or an organization change – we analyze the entire process and identify potential for improvement in order to use the new findings for future processes. We thus create a self-optimizing loop by implementing the lessons learned.
Nevertheless, the objective of a self-learning factory of this type remains theoretical until a company puts the digital transformation into practice. Data previously gathered using checklists, SPC cards, Excel spreadsheets etc. cannot be networked. However, without a homogenized data landscape in the companies, the existing information cannot be used in the desired form. Indeed, our smartphones are based on data integrity – restaurant guides, weather forecast apps and navigation systems work together. But the digital transformation means we have to give up old ways and allow transparency – although this can prove difficult for some and is not always wanted. In particular medium-sized, family-run enterprises that see their future in the digital transformation must transform their production processes through new approaches, which also entails significant investments in software and hardware. Only by following this path can they rethink and – if necessary – rearrange organizational and procedural business models. It is not enough to simply talk about digitalization if the company’s production processes have not progressed beyond Taylorism. The goal of the digital transformation is to identify the right data from the ocean of information currently available and to derive objectives from this – or in other words, to become proactive instead of reactive.
However, companies in North Rhine-Westphalia and all over Germany can only do this as well as the federal state and local authorities permit them to. This begins with data transmission speeds in public networks and ends with excessive bureaucracy. Public administrations, planning and approval authorities that do not accept the challenges and opportunities of digitalization in the same way as industry waste industrial resources. The companies of tomorrow must be able to do what Amazon can do already, as otherwise they won’t stand a chance. But our public administrations are still firmly in the analog age.
The digital transformation is both a training program and a requirement for continued success in globalized markets. Like German industry as a whole, GKD has positioned itself globally. That’s why we shouldn’t see digitalization as a risk, but as an opportunity. Medium-sized companies such as ourselves are already ahead of others in many areas, and digitalization gives us the opportunity to strengthen this lead. After all, in the future the speed at which a company learns and its ability to draw conclusions quickly and use them to develop products that are ready for series production will decide the scope of its innovative capacity and whether it can compete on the global market. Ultimately, nothing demonstrates this better than the development of the smartphone.
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