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Institute
Remote services are services enabled by information and communication components and therefore do not require the physical presence of a service technician at the service object to provide a task. The impact of remote service on the capital goods industry has been increasingly significant over the recent yeas. Still many companies struggle with developing and implemenling successful business model, for remote service. This leads to a lot of unaccomplished benefits for the customer as well as for the companies themselves. A survey throughout companies in Ihe industrial machine and plant production sector was conducted in order to determine what successful companies do differently from those that cannot efficiently implement remote service business models.
The study presented in this chapter identifies key suceess factors of companies that effectively implemented remote services for their products. In order to identify the successful companies a scale for measuring remote service success was developed. Only by the use of this scale further findings regarding the success factors were possible. Key findings include the fact that successful companies actively market their remotle service to their customers. Generally they try to approach their remote service business from the operating company's perspective.
Kleine und mittlere Unternehmen (KMU) stehen zunehmend vor der Herausforderung, im Wettbewerb immer komplexer und volatiler werdenden Leistungen des After-Sales-Service zu bestehen. Ein Erfolgsfaktor ist die Veränderungsfähigkeit bzw. die stetige Adaption des eigenen Serviceportfolios. Um KMU bei der Identifikation notwendiger Anpassungen ihres Serviceportfolios, bei deren Bündelung, Management und Umsetzung zu unterstützen, wurde das Forschungsprojekt „ReleasePro" gestartet. Im Zuge dieses Vorhabens erfolgt die Entwicklung eines systematischen Service-Release-Managements für KMU.
Industrial Smart Services - Types of Smart Service Business Models in the Digitalized Agriculture
(2018)
Due to lack of experience of companies with digital business models, agricultural machinery manufacturers and agricultural service companies are facing a positioning problem in their ecosystem. Smart services are getting more important for these companies and they have issues to define a matching business model for their newly developed smart services. The lack of a framework for smart service business models makes it even harder for companies to successfully develop new services.
This paper contributes to a better understanding of business models for smart services and establishes a common morphological framework to define different types of business models for smart services. Six types of business models of industrial smart services were identified during the research based, which was based on a literature review and interviews with leading experts in the field of smart services. The validation of the developed types and its practical application was carried out as part of the German research project Smart-Farming-World and its four developed use cases. This paper gives a detailed description of the application of the framework on the use case nPotato.
Smart Services
(2018)
Die Nutzung von Informations- und Kommunikationstechnologien in Wirtschaft und Gesellschaft ist inzwischen zur Selbstverständlichkeit geworden. Deutschen Leitbranchen, wie dem Maschinen- und Anlagenbau, stehen durch die Digitalisierung jedoch noch große Umbrüche vor. Die Erfassung von Daten im laufenden Betrieb der Anlagen bietet die Chance durch die Analyse der Daten wertvolle Informationen zu gewinnen. Diese Informationen lassen sich in datenbasierten Dienstleistungen mehrwertstiftend in der Instandhaltung nutzen. In diesem Beitrag wird das Potenzial von datenbasierten Dienstleistungen in der Instandhaltung erläutert und wie dadurch neue Geschäftsmo-dellen für Unternehmen entstehen können. Der Beitrag schließt ab mit einer Beschrei-bung möglicher Einsatzfelder von datenbasierten Dienstleistungen in der Instandhal-tung am Beispiel des Unternehmens BELFOR DeHaDe GmbH.
Smart Service Engineering
(2018)
Global manufacturing companies currently face an increasingly turbulent economic environment known as the "VUCA-world" (volatility, uncertainty, complexity and ambiguity). After the transformation of many companies from product to solution providers in the last 15-20 years, the focus of many corporate change processes is on digital solutions such as data-driven services. In this context, service development is of particular relevance for industrial services. Companies develop digital strategies and try to maximize the added value for their customers, by offering, for example, smart services. They are based on smart products, which are connected to the internet, interact with their environment and gather environmental data. The collected data sets are combined with other easily accessible information and processed into so-called smart data. Based on this smart data, smart services are designed. They can be defined as individualized combinations of physical and digital services. They generate added value for providers and customers and offer context-related and demand-oriented value via digital platforms. The contribution of this paper to this research field of data-driven services is a service engineering approach for industrial smart services.
Since the 1990s, service engineering has established itself as a systematic process for the development of services. Currently existing service engineering processes are based on engineering science and business model innovation toolsets. However, the increasing digital components in service engineering reveal deficits in the direct application of the classical methods of service engineering to smart services. We suggest that the successful development and implementation of smart services requires a more agile service engineering process. Studies show that companies who develop services successfully (top-performer) act up to six times faster than those with less success (follower). They involve customers in the first running prototype of their digital service to increase customer centricity and focus their development activities on core functionalities of the service to reduce its development time and test it early with customers.
To strengthen the successful development pf data-driven services in future industrial service development projects, this paper contributes to a more agile service engineering approach. Smart service engineering combines elements of linear phase models and implements agile and customer-centric findings to decrease the overall development time by focussing on core functionalities that offer a high value for customers. The paper focuses on the service development steps and presents strategic scenarios for smart service engineering. It presents the interaction and interconnection of different elements of smart services based on a case study research. In addition to this, it illustrates the implications of a customer-centric engineering approach and possible strategic decisions based on the customer feedback. The paper focuses on the successful application of the smart service engineering approach and its impact in a German medium-size company in the textile machine industry.
Method for a qualitative cost benefit evaluation of process standardisation for industrial services
(2018)
Industrial service providers deliver complex technical services (e.g. inspection, maintenance, repair, improvement, installation and turnarounds) for a wide range of technical assets in process industries such as the chemical industry. Due to the versatility of assets and industries, there is also a variety of the corresponding service offerings. The demand for a high service quality and the general cost pressure leads to the need of a more efficient and standardized design of the service processes. However, cost-benefit ratio related decisions regarding the questions where and how service processes should be standardized entail great challenges for small and medium-sized enterprises. This is because there is often a lack of understanding of cost savings through process standardization, which is caused by a lack of understanding of the correlations between process characteristics and process target values. Because of this, the goal of this paper is to develop a method for a quantitative evaluation of the cost-benefit ratio of process standardization measures. Within this method, the relevant service performance processes are selected first. Next, the process data will be recorded with the help of questionnaires. These are then analyzed by looking for correlations between the process characteristics and the process target values. Afterwards standardization measures are derived on the basis of these findings in order to improve deficit characteristics and thus target values. Finally, the method´s practical applicability is tested and validated by applying it to an industrial service in the chemical industry.
Digitally connected industrial production promises faster and more efficient processes - in development and production, services, marketing & sales and for adapting entire business models. Agility and the ability to make changes in real time are strategic chracteristics of successful companies in Industrie 4.0. To acquire these features, it is necessary to create a continuously expanding data base. However, a company's organisational structure and culture also play an important part in determining whether this data's potential is leveraged effectively.
This acatech STUDY describes a new tool for helping manufacturing enterprises to forge their own individual path towards becoming a learning, agile company. The acatech Industrie 4.0 Maturity Index is a six-stage maturity model that analyses the capabilities in the area of resources, information systems, culture and organisational structure that are required by companies operating in a digitalised industrial environment. The attainment of each development stage promises concrete additional benefits for manufacturing companies. The model's practical application was validated in a medium-sized company.
Die digital vernetzte industrielle Produktion verspricht schnellere und effizientere Prozesse - in Entwicklung und Produktion wie auch in Service, Marketing und Vertrieb oder bei Anpassung ganzer Geschäftsmodelle. Agil zu handeln und in Echtzeit Veränderungen vorzunehmen, wird in der Industrie 4.0 zur strategischen Erfolgseigenschaft eines Unternehmens. Voraussetzung dafür ist der Aufbau einer immer breiteren Datenbasis. Ob deren Potenzial effektiv genutzt wird, hängt jedoch auch wesentlich von der Organisationsstruktur und Kultur eines Unternehmens ab.
Die vorliegende acatech STUDIE stellt ein neues Instrument vor, mit dem produzierende Unternehmen den Weg zum lernenden, agilen Unternehmen individuell gestalten können. Der acatech Industrie 4.0 Maturity Index ist als sechsstufiges Reifegradmodell aufgebaut und analysiert die in der digitalisierten Industrie benötigten unternehmerischen Fähigkeiten in den Gestaltungsfeldern Ressourcen, Informationssysteme, Kultur und Organisationsstruktur. Jede erreichte Entwicklungsstufe verspricht produzierenden Unternehmen einen konkreten Zuwachs an Nutzen. Das Modell wurde in der praktischen Anwendung in einem mittelständischen Betrieb validiert.
KVD-Service-Studie 2018
(2018)
Digitalisierung ist eine der zentralen Herausforderungen der heutigen Zeit. Aber die Digitalisierung rein technisch zu betrachten, ohne Augenmerk auf die Unternehmenskultur zu legen, wird dazu führen, dass Unternehmen die Potenziale der Digitalisierung nicht vollständig realisieren können. Wer weiterhin wettbewerbsfähig sein will, muss den Wert der Digitalisierung erkennen und sie für sein Unternehmen nutzbar machen. Aber welche Auswirkungen ergeben sich daraus für die Serviceorganisation? Um den aktuellen Stand der digitalen Kultur im Service zu erfassen, die Dimensionen zu verstehen und einen Weg für Unternehmen aufzuzeigen, liegt der Schwerpunkt der diesjährigen Service-Studie, die vom KVD zusammen mit dem FIR durchgeführt wurde, auf dem Themenkomplex Digitale Service-Kultur.
