Digitalisierung

Employees, machines and products get connected: the 4th Industrial Revolution has begun [1]. This is a central statement on the homepage of the German „Plattform Industrie 4.0“. Meanwhile the basic ideas started to move from the shopfloor level to the level of business processes and business models. In consequence it was detected pretty early, that digitization will affect the employees and their qualification and tasks in the companies; the term Work 4.0 evolved. The following contribution emphasizes the systematization of qualifications. A new model will be displayed, that helps to bring transparency to the distribution of qualification in companies. The useability of the model is verified in two case studies. The model is a practicable instrument for companies to gain a realistic view to the upcoming challenges of the shift of qualification due to digitization.

In the digital transformation, managers are facing changed requirements. They are important actors in the design process of the digital transformation, for which they must change their leadership behavior and acquire the corresponding competencies. In corporate practice, it is necessary to address these issues systematically in leadership training. However, such a qualification is a major challenge for companies. The article shows demands on leadership in the digital transformation and presents an innovative procedure for the competence development of managers at a provider of professional training.

Digitalization and the possibility to use big data give companies the opportunity to establish hybrid business models. This enables them to offer customers smart services in addition to their physical products, create more value and strengthen their competitiveness. The hybridization goes along with new competence requirements, which need to be shaped. In the AnGeWaNt project, hybrid business models were developed and implemented in three companies. This article describes the approach to analyze new competence requirements and how to build up new skills for a successful hybridization

Initiated by the digitalization, the organization of production and employees are subject to change. Innovative and digitized formats should be integrated into existing training programs. Therefore, suitable and target group-specific teaching/learning formats are needed that support participative methods and digital collaboration. For this purpose, a digital teaching and learning format for the application area of automotive engineering in SMEs was designed. This prototypical teaching/learning format was created and evaluated in an iterative process through the participation of the potential. The results show that the test subjects mainly refer to the usability criteria of DIN ISO 9241-110. Recommendations for the creation of future digital teaching and learning formats for SMEs are derived from these findings.

Despite a strong media presence and proven potential benefits, Industrie 4.0 is not yet established in many companies. Industry 4.0 projects often remain in a prototype status and do not deliver long-term added value. The solution is an integrated digital system landscape consisting of a connected, digital infrastructure and a business organization oriented towards Industrie 4.0. Through a four-step approach, this paper presents the foundations that need to be created to enable scalable solutions and realize long-term benefits.

Artificial intelligence (AI) is the next stage in the digitalization of the economy. The technology also offers great potential for small and mediusized enterprises (SMEs). However, many SMEs are still reluctant to introduce AI and are only at the beginning of digitization: only around one fifth of all SMEs in Germany have thoroughly digitized their own processes and departments. What does this mean for the use of AI in companies? What steps should businesses take now to take advantage of the opportunities AI offers? And what stumbling blocks should be avoided? This article presents practical implementation concepts for companies with different levels of digital maturity and AI deployment capabilities and shows the range of potential benefits of AI applications in different industries and with different value creation architectures in medium-sized companies.