2023, Gatziu Grivas, Stella, Imhof, Denis, Gachnang, Phillip, Soffer, Pnina, Ruiz, Marcela

Digital technologies enable new forms of value creation, value proposition, and value capturing for all kinds of organizations in all kinds of industries. Often, companies strive to digital transform and obtain consultancy services due to missing expert knowledge on how to approach the transformation. Interestingly, research shows that the consulting industry itself shows a high potential for a digital transformation, but platform-based consulting models and self-service consulting models are still underdeveloped. With this position paper, the authors propose an own approach on how to integrate human expert knowledge and machine learning in a novel hybrid artificial intelligence and platform-based consulting model, which not only offers the potential to transform the consultancy industry but also supports organizations in their transformation efforts. The authors take the area of digital leadership consulting to illustrate this.

2022, Kech, Benjamin, Schneider, Bettina, Gachnang, Phillip, Azan, Wilfrid

2023, Ehrenthal, Joachim, Hanne, Thomas, Telesko, Rainer, Gachnang, Phillip

Zu wenig Personal und Rollmaterial, kurzfristig angesagte Arbeiten an der Infrastruktur mit den entsprechenden betrieblichen Behinderungen und Einschränkungen sowie kurzfristig auftretende Störungen prägen zurzeit die Berichterstattung über die Entwicklungen im öffentlichen Verkehr der Schweiz. Es ist absehbar, dass sich diese unbefriedigende Situation über eine längere Zeitspanne kaum massgeblich verbessern wird. Umso wichtiger ist es, vorhandene Ressourcen optimal einzusetzen und den zukünftigen Bedarf an Mitarbeitenden und Rollmaterial in den Griff zu kriegen. Die Fachhochschulen der Ostschweiz (OST) und der Nordwestschweiz FHNW entwickelten mit der Südostbahn (SOB), den luxemburgischen Eisenbahnen (CFL) und der Eisenbahn-Softwareherstellerin Qnamic eine zukunftsweisende Software zur Unterstützung der Eisenbahn-Disposition, um in Echtzeit über situationsspezifische Massnahmenpakete zur Störungsbehebung zu verfügen.

2022, Hanne, Thomas, Gachnang, Phillip, Gatziu Grivas, Stella, Kirecci, Ilyas, Schmitter, Paul

In this paper, we discuss the possibility of using machine learning (ML) to specify and validate maturity models, in particular maturity models related to the assessment of digital capabilities of an organization. Over the last decade, a rather large number of maturity models have been suggested for different aspects (such as type of technology or considered processes) and in relation to different industries. Usually, these models are based on a number of assumptions such as the data used for the assessment, the mathematical formulation of the model and various parameters such as weights or importance indicators. Empirical evidence for such assumptions is usually lacking. We investigate the potential of using data from assessments over time and for similar institutions for the ML of respective models. Related concepts are worked out in some details and for some types of maturity assessment models, a possible application of the concept is discussed.

2022, Kech, Benjamin, Schneider, Bettina, Gachnang, Phillip, Azan, Wilfrid

This paper elaborates on the technology of quantum computing. It is aimed at people new to this field and introduces characteristics of quantum computing along with comparisons to classical computing. Furthermore, the paper describes the challenges and opportunities of quantum computing. In addition, applications have been explored where quantum computing could create value for businesses. The findings include three categories. First, quantum computing might make a difference in simulating nature, which was also the initial idea that led to the invention of quantum computing. Second, quantum computing could benefit the category of machine learning. Last, optimization problems will take advantage of quantum computing. It is concluded that quantum computing is still in its early stages and there are many challenges to overcome ‚ in particular the challenge of error correction. To gain in the foreseeable future from the advantages that quantum computing pledges, more advances in research have to be made to have a fault-tolerant system. A fault-tolerant quantum computer is a promising technology that could create significant value for various branches, such as finance.

2021, Pustulka, Elzbieta, Hanne, Thomas, Gachnang, Phillip, Biafora, Pasquale, Arai, Kohei, Kapoor, Supriya, Bhatia, Rahul

Information extraction (IE) from forms remains an unsolved problem, with some exceptions, like bills. Forms are complex and the templates are often unstable, due to the injection of advertising, extra conditions, or document merging. Our scenario deals with insurance forms used by brokers in Switzerland. Here, each combination of insurer, insurance type and language results in a new document layout, leading to a few hundred document types. To help brokers extract data from policies, we developed a new labeling method, called FLIE (form labeling for information extraction). FLIE first assigns a document to a cluster, grouping by language, insurer, and insurance type. It then labels the layout. To produce training data, the user annotates a sample document by hand, adding attribute names, i.e. provides a mapping. FLIE applies machine learning to propagate the mapping and extracts information. Our results are based on 24 Swiss policies in German: UVG (mandatory accident insurance), KTG (sick pay insurance), and UVGZ (optional accident insurance). Our solution has an accuracy of around 84-89%. It is currently being extended to other policy types and languages.