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Due to the high number of customer contacts, fault clearances, installations, and product provisioning per year, the automation level of operational processes has a significant impact on financial results, quality, and customer experience. Therefore, the telecommunications operator Deutsche Telekom (DT) has defined a digital strategy with the objectives of zero complexity and zero complaint, one touch, agility in service, and disruptive thinking. In this context, Robotic Process Automation (RPA) was identified as an enabling technology to formulate and realize DT’s digital strategy through automation of rule-based, routine, and predictable tasks in combination with structured and stable data.
Information technologies, such as big data analytics, cloud computing,
cyber physical systems, robotic process automation, and the internet of things, provide a sustainable impetus for the structural development of business sectors as well as the digitalization of markets, enterprises, and processes. Within the consulting industry, the proliferation of these technologies opened up the new segment of digital transformation, which focuses on setting up, controlling, and implementing projects for enterprises from a broad range of sectors. These recent developments raise the question, which requirements evolve for IT consultants as important success factors of those digital transformation projects. Therefore, this empirical contribution provides indications regarding the qualifications and competences necessary for IT consultants in the era of digital transformation from a labor market perspective. On the one hand, this knowledge base is interesting for the academic education of consultants, since it supports a market-oriented design of adequate training measures. On the other hand, insights into the competence requirements for consultants are considered relevant for skill and talent management processes in consulting practice. Assuming that consulting companies pursue a strategic human resource management approach, labor market information may also be useful to discover strategic behavioral patterns.
In der Diskussion über die Digitalisierung der Forschung spielt die Frage nach der optimalen IT-Unterstützung für Forschende eine wichtige Rolle. Forschende können heute an ihren Hochschulen bzw. Wissenschaftseinrichtungen auf ein breites Angebot interner IT-Dienstleistungen zurückgreifen, das auch kooperative IT-Dienste umfasst, die von mehreren Institutionen in Zusammenarbeit bereitgestellt werden. Außerhalb der eigenen Organisation und des weiteren Verbunds hat sich im Internet zudem ein breites externes Angebot an innovativen, häufig kostenlos nutzbaren Onlinediensten entwickelt. Neben horizontalen Onlinediensten, die sich prinzipiell an jeden Internetnutzer richten (bspw. Dropbox, Twitter, WhatsApp), nimmt auch die Zahl von vertikalen Diensten für wissenschaftliche bzw. Forschungszwecke immer weiter zu (bspw. GoogleScholar, ResearchGate, figshare). Für Forschende eröffnen sich damit vielfältige neue Möglichkeiten, ihren individuellen Forschungsprozess durch digitale Werkzeuge zu verbessern. Aufgrund rechtlicher, technischer und personeller Restriktionen können jedoch interne Dienstleister bei der Identifizierung, Auswahl und Nutzung externer Onlinedienste nur wenig Unterstützung leisten. Aus einer serviceorientierten Perspektive stehen Forschende zunehmend vor dem Problem, wie sich heterogene IT-Dienste interner und externer Anbieter in den eigenen Forschungsprozess integrieren lassen. Als Lösungsansatz skizziert das Kapitel das Konzept eines persönlichen Forschungsinformationssystems
nach Gesichtspunkten eines digitalen Servicesystems.
Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.
Einfluss von Künstlicher Intelligenz auf Customer Journeys am Beispiel von intelligentem Parken
(2021)
Im Konsumentenmarkt entstehen vermehrt neue Anwendungen von Künstlicher
Intelligenz (KI). Zunehmend drängen auch Geräte und Dienste in den Markt, die
eigenständig über das Internet kommunizieren. Dadurch können diese Geräte und
Dienste mit neuartigen KI-basierten Diensten verbessert werden. Solche Dienste
können die Art und Weise beeinflussen, wie Kunden kommerzielle Entscheidungen
treffen und somit das Kundenerlebnis maßgeblich verändern. Der Einfluss von KI
auf kommerzielle Interaktionen wurde bisher noch nicht umfassend untersucht.
Basierend auf einem Framework, welches einen ersten Überblick über die Effekte
von KI auf kommerzielle Interaktionen gibt, wird in diesem Kapitel der Einfluss von KI auf Customer Journeys am konkreten Anwendungsfall des intelligenten Parkens analysiert. Die daraus gewonnenen Erkenntnisse können in der Praxis als Grundlage
genutzt werden, um das Potenzial von KI zu verstehen und bei der Gestaltung eigener Customer Journeys umzusetzen.
Intelligent autonomous software robots replacing human activities and performing administrative processes are reality in today’s corporate world. This includes, for example, decisions about invoice payments, identification of customers for a marketing campaign, and answering customer complaints. What happens if such a software robot causes a damage? Due to the complete absence of human activities, the question is not trivial. It could even happen that no one is liable for a damage towards a third party, which could create an uncalculatable legal risk for business partners. Furthermore, the implementation and operation of those software robots involves various stakeholders, which result in the unsolvable endeavor of identifying the originator of a damage. Overall it is advisable to all involved parties to carefully consider the legal situation. This chapter discusses the liability of software robots from an interdisciplinary perspective. Based on different technical scenarios the legal aspects of liability are discussed.
The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated
structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.
Robotic process automation (RPA) has attracted increasing attention in research and practice. This chapter positions, structures, and frames the topic as an introduction to this book. RPA is understood as a broad concept that comprises a variety of concrete solutions. From a management perspective RPA offers an innovative approach for realizing automation potentials, whereas from a technical perspective the implementation based on software products and the impact of artificial intelligence (AI) and machine learning (ML) are relevant. RPA is industry-independent and can be used, for example, in finance, telecommunications, and the public sector. With respect to RPA this chapter discusses definitions, related approaches, a structuring framework, a research framework, and an inside as well as outside architectural view. Furthermore, it provides an overview of the book combined with short summaries of each chapter.
Subject of this case is Deutsche Telekom Services Europe (DTSE), a service center for administrative processes. Due to the high volume of repetitive tasks (e.g., 100k manual uploads of offer documents into SAP per year), automation was identified as an important strategic target with a high management attention and commitment. DTSE has to work with various backend application systems without any possibility to change those systems. Furthermore, the complexity of administrative processes differed. When it comes to the transfer of unstructured data (e.g., offer documents) to structured data (e.g., MS Excel files), further cognitive technologies were needed.
Promoting diversity and combatting discrimination in research organizations: a practitioner’s guide
(2022)
The essay is addressed to practitioners in research management and from
academic leadership. It describes which measures can contribute to creating an inclusive climate for research teams and preventing and effectively dealing with discrimination. The practical recommendations consider the policy and organizational levels, as well as the individual perspective of research managers. Following a series of basic recommendations, six lessons learned are formulated, derived from the contributions to the edited collection on “Diversity and Discrimination in Research Organizations.”
Diversity management is seen as a decisive factor for ensuring the development of socially responsible innovations (Beacham and Shambaugh, 2011; Sonntag, 2014; López, 2015; Uebernickel et al., 2015). However, many diversity management approaches fail due to a one-sided consideration of diversity (Thomas and Ely, 2019) and a lacking linkage between the prevailing organizational culture and the perception of diversity in the respective organization. Reflecting the importance of diverse perspectives, research institutions have a special responsibility to actively deal with diversity, as they are publicly funded institutions that drive socially relevant development and educate future generations of developers, leaders and decision-makers. Nevertheless, only a few studies have so far dealt with the influence of the special framework conditions of the science system on diversity management. Focusing on the interdependency of the organizational culture and diversity management especially in a university research environment, this chapter aims in a first step to provide a theoretical perspective on the framework conditions of a complex research organization in Germany in order to understand the system-specific factors influencing diversity management. In a second step, an exploratory cluster analysis is presented, investigating the perception of diversity and possible influencing factors moderating this perception in a scientific organization. Combining both steps, the results show specific mechanisms and structures of the university research environment that have an impact on diversity management and rigidify structural barriers preventing an increase of diversity. The quantitative study also points out that the management level takes on a special role model function in the scientific system and thus has an influence on the perception of diversity. Consequently, when developing diversity management approaches in research organizations, it is necessary to consider the top-down direction of action, the special nature of organizational structures in the university research environment as well as the special role of the professorial level as role model for the scientific staff.
Industrial production systems are facing radical change in multiple dimensions. This change is caused by technological developments and the digital transformation of production, as well as the call for political and social change to facilitate a transformation toward sustainability. These changes affect both the capabilities of production systems and companies and the design of higher education and educational programs. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these concepts, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the capabilities dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we discuss the benefits of capturing expert knowledge and making it accessible to newcomers, especially in highly specialized industries. The experts argue that in order to cope with the challenges and circumstances of today’s world, students must already during their education at university learn how to work with AI and other technologies. This means that study programs must change and that universities must adapt their structural aspects to meet the needs of the students.
Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030.
Der Themenkomplex urbane Mobilität ist getrieben durch den Verkehrsinfarkt in Ballungszentren, durch Luftverschmutzung und Lärm, sowie den Trend zum Leben in der Stadt in den städteplanerischen Fokus gerückt. Emissionsneutrale Antriebskonzepte in der Luftfahrt führen zu Ansätzen Fluggeräte einzusetzen, die batteriegetrieben vertikal aufsteigen und landen können. Flugphysikalisch und energetisch ist diese Technik nur dann sinnvoll, wenn es zwingende Gründe gibt (z.B. Rettungseinsätze), daher wird der flugphysikalische Hintergrund prinzipiell erläutert. Es werden einige aktuelle Lufttransportkonzepte für eine urbane Personenbeförderung vorgestellt. Sollte es verstärkt zu Lufttransport über Städten kommen, müssen betroffene Lufträume geordnet und überwacht werden. Wie kompatibel Lufttransportsysteme mit den heute bereits relevanten urbanen Beförderungsmitteln sein müssen, wird kritisch diskutiert. Abschließend werden die Aspekte Akzeptanz durch die Kunden und Wirtschaftlichkeit ebenso angerissen, wie die hochproblematische Rohstoffgewinnung, die Entsorgung und das Recycling von Batterien.
Das Ziel des INTERREG-Projektes „SHAREuregio“ (FKZ: 34.EFRE-0300134)
ist es, grenzüberschreitende Mobilität in der Euregio Rhein-Maas-Nord zu
ermöglichen und zu fördern. Dazu soll ein elektromobiles Car- und Bikesharing-
System entwickelt und in der Stadt Mönchengladbach, im Kreis Viersen
sowie in den Gemeinden Roermond und Venlo (beide NL) zusammen mit den
Partnern Wirtschaftsförderung Mönchengladbach, Wirtschaftsförderung für den
Kreis Viersen, NEW AG, Goodmoovs (NL), Greenflux (NL) und der FH Aachen
implementiert werden. Zunächst richtet sich das Angebot, bestehend aus 40
Elektroautos und 40 Elektrofahrrädern, an Unternehmen und wird nach einer
Erprobungsphase, mit einer größeren Anzahl an Fahrzeugen, auch für Privatpersonen
verfügbar gemacht werden. Die Fahrzeuge stehen bei den jeweiligen
Anwendungspartnern in Deutschland und den Niederlanden.
Im Rahmen dieses Projektes hat die FH Aachen „FlexSHARE“ entwickelt
– ein methodisches Framework zur innovativen Gestaltung urbaner Sharing-
Angebote. Das Framework ermöglicht es, anhand von messbaren Kenngrößen,
bedarfsgerechte und auf die Region abgestimmte Sharing-Systeme zu entwickeln.