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28. – 30.06.2019 | BIELEFELD
The challenge is to transform the Dr. Oetker Back-Club into an online community with various communication and interaction options which is attractive for younger generations as well as existing members and to expand the existing business model in all relevant dimensions.
Since 30 years the „Dr. Oetker Back-Club“ is a big success story and has grown to the leading community for baking enthusiasts in Germany. As the community consist of Dr. Oetker customers who signed up for a paid membership, their members gain diverse benefits such as an exclusive magazine and access to special baking events.
The community has been extremely successful in the offline environment. Still there is huge unused potential in the online world, especially in the lack of interactions between members and with Dr. Oetker. Due to such missing online features the Dr. Oetker Back-Club is not fully addressing the demands of younger generations.
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The variety of nutritional options, full calendars and further factors overwhelm people in the pursuit of healthy nutrition. Due to that the habit of daily cooking „from-scratch“ has declined. Based on this challenging development Miele seeks for solutions, which support the daily cooking process and experience. Thereby the convenience for the customer has to be the focus. The challenge is to create a digital business model within the user journey of daily cooking, which adds value for customers and creates motivation for healthy nutrition.
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Inside a building there are a lot of different components with individual purpose and settings. All of them impact the operation costs, performance and condition of a building. At the same time most components contain of certain data sets which are collected from many data sources. Collecting and combining these diverse data sets would provide a basis to analyze and increase the efficiency of a building overall. It would reduce operating costs, improve the functions of the building and create an opportunity for sufficient monitoring of the building’s condition. The challenge is to create and implement an IoT-platform which enables WAGO to monitor the collected data from connected components and to control the building’s operations to enhance a building’s performance.
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The success of GEA products is based on excellent application and technology knowledge of their employees. A generation change, a rapidly changing market environment and a strong market growth requires new approaches to build and provide expertise worldwide. Thereby it is not sufficient to just focus on existing knowledge (e. g. due to e-Learning). Likewise, the speed of gaining new knowledge is crucial. The challenge is to develop a digital knowledge management approach, which enables a daily interactive and continuous knowledge creation and diffusion without additional bureaucratic effort by the GEA employees.
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Many offices are situated in quite old buildings which originally weren’t meant for that purpose. The layouts of these buildings are often confusing, so that internal staff and external visitors struggle to navigate. Furthermore, due to the structure of the buildings certain industry regulations such as security standards are hard to meet.
Exiting indoor navigation tools lack essential functions for a comprehensive solution. Next to the usual indoor navigation, an applicable solution would need additional benefits like a sufficient access management or mandatory warning notes for visitors.
The challenge is to develop an efficient digital solution, that includes and combines aspects like indoor navigation, security and access management based on the given infrastructure of Dr. Wolff.
One leverage to remain competitive in the market is a continuous optimization of production planning. The basis for production planning is a large amount of master data. This includes, e. g. stored times and process data such as average setup times, lead times, etc. Additionally, actual data for all production processes are recorded.
Currently the comparison of the actual data with the master data and the intelligent and continuous adjustment of the master data often does not take place. To improve production planning sustainably, master data cleansing based on artificial intelligence and cloud systems is required. Existing tools already head in the right direction but the perfect solution is not yet available.
The challenge is to develop a solution and implement a master data cleansing, based on
artificial intelligence, so that production planning can be improved to archive an enormous increase in efficiency.
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