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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.
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.
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through the presentation layer of existing application systems. For this simple emulation of user input and output by software robots, no changes of the systems and architecture is required. However, considering strategic aspects of aligning business and technology on an enterprise level as well as the growing capabilities of RPA driven by artificial intelligence, interrelations between RPA and Enterprise Architecture (EA) become visible and pose new questions. In this paper we discuss the relationship between RPA and EA in terms of perspectives and implications. As workin- progress we focus on identifying new questions and research opportunities related to RPA and EA.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based (bio-) chemical sensor, in which a desired sensing area on the sensor surface can be defined by illumination. Light addressability can be used to visualize the concentration and spatial distribution of the target molecules, e.g., H+ ions. This unique feature has great potential for the label-free imaging of the metabolic activity of living organisms. The cultivation of those organisms needs specially tailored surface properties of the sensor. O2 plasma treatment is an attractive and promising tool for rapid surface engineering. However, the potential impacts of the technique are carefully investigated for the sensors that suffer from plasma-induced damage. Herein, a LAPS with a Ta2O5 pH-sensitive surface is successfully patterned by plasma treatment, and its effects are investigated by contact angle and scanning LAPS measurements. The plasma duration of 30 s (30 W) is found to be the threshold value, where excessive wettability begins. Furthermore, this treatment approach causes moderate plasma-induced damage, which can be reduced by thermal annealing (10 min at 300 °C). These findings provide a useful guideline to support future studies, where the LAPS surface is desired to be more hydrophilic by O2 plasma treatment.
20 years after the successful ground deployment test of a (20 m) 2 solar sail at DLR Cologne, and in the light of the upcoming U.S. NEAscout mission, we provide an overview of the progress made since in our mission and hardware design studies as well as the hardware built in the course of our solar sail technology development. We outline the most likely and most efficient routes to develop solar sails for useful missions in science and applications, based on our developed `now-term' and near-term hardware as well as the many practical and managerial lessons learned from the DLR-ESTEC Gossamer Roadmap. Mission types directly applicable to planetary defense include single and Multiple NEA Rendezvous ((M)NR) for precursor, monitoring and follow-up scenarios as well as sail-propelled head-on retrograde kinetic impactors (RKI) for mitigation. Other mission types such as the Displaced L1 (DL1) space weather advance warning and monitoring or Solar Polar Orbiter (SPO) types demonstrate the capability of near-term solar sails to achieve asteroid rendezvous in any kind of orbit, from Earth-coorbital to extremely inclined and even retrograde orbits. Some of these mission types such as SPO, (M)NR and RKI include separable payloads. For one-way access to the asteroid surface, nanolanders like MASCOT are an ideal match for solar sails in micro-spacecraft format, i.e. in launch configurations compatible with ESPA and ASAP secondary payload platforms. Larger landers similar to the JAXA-DLR study of a Jupiter Trojan asteroid lander for the OKEANOS mission can shuttle from the sail to the asteroids visited and enable multiple NEA sample-return missions. The high impact velocities and re-try capability achieved by the RKI mission type on a final orbit identical to the target asteroid's but retrograde to its motion enables small spacecraft size impactors to carry sufficient kinetic energy for deflection.