change management

Originally developed in the software industry, a method inspired by the mindset of designers has proven to be a broadly applicable approach to solving complex problems. Design thinking holds the potential to contribute positively to social and economic change. A look at its development offers valuable insights for a deeper understanding.

Change is necessary for companies to maintain their competitive edge—both digital and ecological change. But while external support is at hand, the drive for change must come from companies themselves. In this issue of Industry 4.0 Science, experts of the Academic Society for Work and Industrial Organization discuss how the real-world application of innovative technologies lead to resource-efficient manufacturing.

Transformative forces present companies with enormous challenges. At the same time, new forms of collaboration and new roles and responsibilities are emerging. Due to the risks associated with change, many employees hold on to old habits and work processes, which can slow down positive developments. The challenge for managers is to recognize this resistance, prevent it and turn it into acceptance or even proactive support.

Digital transformation processes have a high tendency for delay, exceeding costs, and failure. This poses a significant risk in competitive global markets and shifting business models of entire industries. Successful companies have a different approach to new technologies than more traditional incumbents. Including the workforce in the transformation via change leadership in a digital transformation coaching process can reduce fear and resistance and can lead to a paradigm shift of approaching the digital transformation itself: as an agility driven, infinite game with high potential gain.

Artificial intelligence (AI) is already an important part of business models and processes of many companies. In the future, AI systems will pro- foundly change our working environment. AI systems can develop completely new potential for companies in a wide variety of sectors and domains - especially in industry. Existing busi- ness models can be optimized along the value chain by optimizing production flows and processes or avoiding production downtimes with predictive maintenance. At the same time, AI systems can enable completely new business models and thus radically change existing mar- ket structures through new players. The AI economy of tomorrow will be more individual, more precise and more sustainable: Competitive value creation without AI will not be possible in many areas of industry.

Companies are increasingly acquiring new technologies that enable higher quality and efficiency. Every technology adoption is also a change process which affects the employees and their work and thus needs to be managed in an optimal way. This article is focused on the importance of goal definition during a change process. To facilitate this process, a checklist with 81 goals is presented. The checklist was developed based on scientific literature and practice-oriented tools and can be used by project teams to focus their activities on a holistic change process and track the goal progress.

With targeted measures, in-house staff can make a valuable contribution to sales. First, we need a new self-image in the affected departments, as well as the provision of key competences. Following the right track, technology companies can make a leap forward in customer orientation and more sales.