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Service Engineering Models
(2019)
Since the field of service engineering emerged in the late 20th century, the service industry has undergone drastic changes. Among the reasons for these changes is the increasing digitalization, which has made it difficult for companies to successfully develop new service offerings. While numerous service engineering models are available to provide guidance during the design of new services, many of them cannot keep up with the requirements of today’s economic environment. The present paper examines the requirements that service engineering models need to meet in order to be suitable guidelines for the digital age. To this end, the introduction illustrates how digitalization has changed the service industry. Afterwards, selected service engineering models and related norms are presented. Finally, a set of requirements for modern service engineering models derived from best practices from recent years is introduced.
Smart Service Engineering
(2019)
In our digitalized economy, many traditional service engineering models lack flexibility, efficiency and adaptability. As today’s market differs significantly from the market of the late 20th century, service engineering models must meet different requirements today than they had to meet in the past. The present paper starts off by providing an overview of the requirements that modern service engineering models need to fulfill in order to succeed in today’s economic environment. Afterwards, three promising models that meet several of these requirements will be introduced.
Monetizing Industry 4.0: Design Principles for Subscription Business in the Manufacturing Industry
(2019)
Subscription business models have a major role for monetizing products and services for manufacturing companies in the age of Industry 4.0. As the manufacturing industry has difficulties generating revenues through digitalization, the implementation of innovative business models are essential to remain successful. Physical assets are often capital-intensive and require a more complex manufacturing process than subscription business models. Moreover, subscription models can focus on the individual customer benefit and a consistent service transformation, constituting a unique selling proposition and a competitive advantage. Hence, the following paper provides a management model that enables manufacturing companies to successfully realize the transformation towards a subscription business model. The management model presents four major fields of action, each matched with one design principle that must be considered when dealing with subscription models in the manufacturing industry. These principles were determined by an in-depth case study analysis among various manufacturing companies. Opportunities, challenges and recommendations for action were then systematically derived and integrated into the management model.
Many industrial companies face their digital transformation. In addition to an existing portfolio of products and services, new digital services are being developed to offer a portfolio of smart product service systems (Smart PSS). While the development of new digital services is rarely a problem for the companies, the organization of sales and distribution of Smart PSS in particular is a key issue. The sales of Smart PSS differs considerably from the sales of only products or services and must therefore be designed differently in order to meet customer requirements and successfully commercialize the developed Smart PSS. This paper therefore describes how the sales organization of Smart PSS should be designed successfully in various forms. The network thinking methodology is used in combination with a case study research approach to describe the connection between the offered portfolio, the customer requirements and the different elements of a sales organization. Furthermore, four different types of a sales organization for Smart PSS are described. This paper gives a recommendation for companies on a design of their sales organizations on which practical implications may be developed.
Ziel des Forschungsvorhabens CSS 2.0 war es, kleine und mittlere Unternehmen (KMU) dabei zu unterstützen, die Effizienz und Effektivität ihres Kundenservices durch den Einsatz von Social Media zu verbessern. Hierfür wurde ein Self-Assessment-Tool zur Bewertung und Prognose des Nutzenbeitrags des Social-Media-Einsatzes im Kundenservice entwickelt. Der Fokus des Forschungsvorhabens lag auf der Betrachtung des externen Social-Media-Einsatzes an der Schnittstelle zwischen Unternehmen und Kunden.
Industrie 4.0 ist in den Bilanzen deutscher Industrieunternehmen aktuell noch nicht angekommen. Seit der Einführung des Begriffs „Industrie 4.0“, als Bezeichnung für die massenhafte Verbindung von Informations- und Kommunikationstechnologien mit der industriellen Produktion, wird das Thema national wie international in Wirtschaft und Forschung in zahlreichen Initiativen und Projekten behandelt. Enorme wirtschaftliche Potenziale wurden und werden in diversen Studien beziffert, um den revolutionären Charakter dieser Entwicklung zu unterstreichen.
Über die Hälfte der KMU des Maschinenbaus passen ihre am Markt angebotenen AS-DL nicht oder unstrukturiert an, indem sie ad hoc auf Kundenanliegen reagieren (KAMPKER 2015). Es existiert kein standardisiertes Vorgehen zur systematischen Identifikation und Umsetzung notwendiger Änderungen von AS-DL. Hierbei entstehen Ineffizienzen in der Nutzung vorhandener Ressourcen (z.B. Personalkapazität). Dies ist insbesondere ein Problem in der Kleinserienfertigung des Maschinenbaus, da grundsätzlich eine hohe Variantenvielfalt und Kundenindividualisierung besteht. Dies erhöht massiv die Komplexität der Dienstleistungserbringung, da sich Maschinen aber auch Kundenwünsche viel häufiger ändern als in der Großserienfertigung. Ein Service-Release-Management trägt dazu bei, die Effizienz der Ressourcen im Bereich AS-DL zu steigern.
Aus wissenschaftlich-technischer Sicht fehlt ein Vorgehen, um notwendige Änderungen von AS-DL systematisch zu identifizieren und effizient in ein Service-Release umzusetzen. Hierfür ist ein spezifisches Service-Release-Management notwendig. Dieses soll es KMU ermöglichen, notwendige Änderungen an AS-DL systematisch zu identifizieren, Service-Releases zu gestalten, deren Durchführbarkeit und Wirtschaftlichkeit zu bewerten sowie Service-Releases umzusetzen (RANA ET AL. 2014). Die Forschungsfrage des Vorhabens lautet:
Wie ist ein Service-Release-Management zu gestalten, damit KMU in der Kleinserienfertigung des Maschinenbaus notwendige Änderungen an ihren AS-DL systematisch identifizieren, daraus Service-Releases gestalten und diese Service-Releases effizient umsetzen können?
- Wie können Auslöser identifiziert werden, die dazu führen, dass eine AS-DL geändert werden muss?
- Wie ist ein Service-Release in Abhängigkeit der Auslöser zu gestalten?
- Wie können Service-Releases (unter Berücksichtigung der Strategie des AS-DLGeschäfts) hinsichtlich ihrer technischen, rechtlichen und kompetenzbasierten Durchführbarkeit geprüft werden?
- Wie können Service-Releases hinsichtlich ihrer Wirtschaftlichkeit bewertet werden?
- Wie wird ein Service-Release erfolgreich eingeführt?
Today, maintenance exceeds this definition, it is significantly more.
In many companies, it plays the role of an incubator for development
and drives digital transformation forward. The very essence of
Industrie 4.0 is the optimisation of the flow of information within as
well as outside of a company to accelerate the adjustment of company
organisations in the context of increasing competitive pressure.
Because of the variety of interfaces, information and data that
is available as well as its service character, maintenance lends itself easily as the area of choice for a company to make Industrie 4.0 real. Whilst doing so, the aim is not to equip employees with the
latest “gimmick“ for order processment or to be the company with
the highest number of lighthouse projects. Instead, maintenance
ensures reliable and cost-efficient production and, consequently,
the primary creation of added value of the manufacturing company.
Those who were identified as top performers during the “Smart
Maintenance“ consortium benchmarking by FIR at RWTH Aachen
University gain particular useful ideas twice as often as other follower companies directly from staff, thus releasing the right potential.
Information and data help to reach these goals and transfer the
vision of smart maintenance into actual pratice. But what is smart
maintenance exactly and how far along are you in the development
of your individual smart maintenance concept?
Smart-Farming-Welt
(2019)
Smart-Farming-Welt
(2019)