The digitalization of the economy and society continues unabated. Generative artificial intelligence, especially ChatGPT, has triggered a new wave of digitalization since its availability in November 2022. In addition to new technologies such as generative AI, companies and their IT function are still busy with the transformation of applications and IT infrastructure into the cloud, the expansion of capabilities in data analytics, the agilization of application development, new regulatory requirements, the increase in IT security and the shortage of skilled workers. Furthermore, many companies are developing new digital business models that place new demands on the IT function. Social developments, such as sustainability and diversity, are also leading to new challenges for the IT function. The pace of change in companies is also accelerating. The complexity that IT management must deal with has grown in recent years and continues to grow at a rapid pace. Traditional ITmanagement models and IT operating models, such as ITIL or COBIT, are not able to cope with these challenges. Against this backdrop, this contribution discusses whether and how systems thinking can be an integral part of future IT management models and IT operating models and can help deal with the increased complexity brought about by digitalization.

In recent years, process mining has emerged as the leading Big Data technology for business process analysis. By extracting knowledge from event logs readily available in information systems, process mining provides new ways to discover, monitor, and improve processes while being agnostic to the source system. Despite its undisputed practical relevance, we have a limited understanding of how organizations realize value potentials from applying process mining in different organizational contexts. Addressing this gap, we conduct an assessing literature review by analyzing 58 papers from the literature on process mining to synthesize the existing knowledge on business value realization from process mining. Our analysis is guided by adopting the perspective of process mining embedded within its organizational context. By analyzing the dimensions of the nomological net around process mining, we contribute to the broader research field of Big Data value realization twofold. First, we uncover which benefits organizations gain by applying process mining. Second, we analyze the organizational capabilities and practices that influence how organizations use and implement process mining. In addition, we reveal how process mining leads to business value realization. Based on these results, we suggest directions for future research on process mining in the organizational context.

Although German companies have a strong innovative tradition, they must use intellectual property creatively if they are to be successful in meeting the economic challenges of the 21st century.