Smart service

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The term Smart Service (Pl. Smart Services , dt .: Intelligent Service) describes the most advanced level of data-based, digital service offers. They are provided by service providers for customers who use so-called smart products (i.e. technical objects equipped with sensors that can record and pass on data because they are controlled by software and connected to a network, e.g. the Internet).

To illustrate this, a practical example: The weaving machines in a metal weaving mill are equipped with high-performance sensors (see Edge Computing ) by the machine manufacturer, who is also the provider of the Smart Service . Via a broadband connection, the machines can pass on collected or selected data about their status (such as the current operating temperature) to the software platform of the smart service provider. So-called machine knowledge is generated on this platform through the aggregation and networking of many different data, often with the help of processes such as machine learning and the use of artificial intelligence . With the help of this machine knowledge, the Smart Service software can make decisions independently, i. H. it can compare the data with existing data records and, based on this, decide that, for example, preventive maintenance measures are necessary for the machines in the weaving mill. She can then also decide that a service technician needs to be ordered and that certain spare parts are required for the problem identified. By so possible preventive maintenance a failure of the machine can be prevented and the process flow is optimized (see on this subject the so-called preventive maintenance (Engl. Predictive Maintenance) the article on maintenance strategy ). The data obtained from the machines (in this case weaving machines) in the course of this process are processed into so-called smart data through the software-defined analysis, interpretation and linkage with other data sets and thus say something, i.e. H. they are no longer just raw data, but have concrete information content. In this context, there is also talk of refining the data. On the basis of the information now available, smart service providers can not only offer their services, but also identify opportunities for new, data-based services, develop them and also offer them on the market. The smart services can be sold and traded, i.e. monetized , on service platforms such as online marketplaces and app stores .

Meaning of smart services

Smart services are offered in both the public and industrial sectors as well as in the private sector. They are the result of developments in the context of digitization (also known as the digital revolution ): Today's economy is increasingly shaped by the digitization of all products and processes. The spread of new connectable and internet-connected products results in the creation of large amounts of data. On the basis of this data, internet-based services are increasingly being developed and introduced across industries, which means that the spread of digital value-added activities is gaining momentum. In the description of a final report on a project officially funded by the Federal Ministry for Economic Affairs and Energy (topic Smart Services), the so-called Smart Service World working group formed for this project describes the development as follows:

"Our highly networked society already produces gigantic amounts of data. If we use it for innovative products and services, we can conserve resources, create jobs and secure Germany's competitiveness. If we fail to do this, the technological sovereignty of Germany and Europe is at stake. Large Internet companies from the USA and China are penetrating more and more industries with personalized services. "

With this, the editors of the final report Smart Service Welt make clear which role Smart Services play now and in the future. They represent a way of preparing and analyzing data for a specific purpose, e.g. solving a problem or improving a specific activity (see the above practical example, in which a production process ideally runs with fewer machine failures because of the condition of the machine is continuously checked). The innovative services possible through this use of data represent a decisive competitive factor, because: "The performance and innovation capacity of German industry is decisive for economic strength." In the future, added value for customers will primarily be generated through the use of data for digital business models, not exclusively through new physical components of the products. In order to maintain its competitiveness and to design its service portfolio in a customer-oriented manner, the German manufacturing industry must take on this development.

Smart services background

The topic of smart services was scientifically developed primarily in the context of public research projects, e. For example, the project “Smart Service World - Implementation Recommendations for the Project Internet-Based Services for Business”, which was completed in 2015. It was implemented by the aforementioned Smart Service Welt working group and funded by the Federal Ministry for Economic Affairs and Energy - as part of the declared goal of the federal government to actively promote digitization and promote smart services. The project builds on the vision of Industry 4.0 , the implementation of which has also been actively tackled in specific government projects and is part of the government's action plan for the 2020 high-tech strategy .

Smart services as a variant of data-based services

Often there is not a sufficient distinction between data-based services and smart services - the two terms cannot be used synonymously. Every smart service is basically a data-based service, but not every data-based service is automatically a smart service. Smart services are to be seen as the highest level of maturity of data-based services. Services as such are generally considered to be data-based if data represent a characteristic part of the resources used for these services - strictly speaking, the said data no longer even need to be available in digital form, and handwritten or printed values ​​and factors are in fact data that are used to provide a service can be. A distinction must also be made between a data-based decision / action and a specific service. To illustrate, a multi-stage example: If the order for the maintenance of a machine is processed in an order management system, the decision made for maintenance is no different from that which was planned with a college block - it is not a data-based service , at most a decision based on data. However, if the service provider also offers a user interface in the form of a dashboard (see Interface ), by means of which the maintenance of the machine park can be tracked in real time, this is a data-based service. A smart service, on the other hand, would exist in this example if the machine equipped with sensors is so intelligent (see paragraph on machine learning and artificial intelligence above) that it independently combines the received raw data into smart data, evaluates it and uses the automatically generated data Data evaluation calls for an action, e.g. maintenance, repair or the like.

Smart Services thus currently represent the highest and market-leading degree of maturity of digital business models in the service sector with the greatest added value for companies. Up until the 2010s, digital business models primarily comprised remote services and condition-based monitoring. The analysis of data and the associated prognostic capability now enable smart services that can be quickly developed through short release cycles and tested directly on the market.

Basic requirements for smart services

So-called smart spaces form the foundation for smart services (see Figure 2). Smart spaces are high-performance technical infrastructures that consist of networked, intelligent and digitally connectable machines and devices as well as IT systems. A comprehensive and high-performance broadband and cellular network with low latency times (5G) enables this networking. The next, also indispensable level for the provision of a smart service are smart products, e.g. B. digitally connectable and intelligent production machines as well as their digital images. They are networked with one another through the layer of the technical infrastructure and thus form a networked physical platform. The data generated here is aggregated and processed on software-defined platforms using complex algorithms. From the raw data, so-called refined data (also called smart data) have been created through data processing. They are available for use by the smart service providers on these platforms. Through this virtualization, e.g. B. the production environment, the service platforms are no longer linked to the physical objects (production machines). The highest level, the service platform with its smart services, is not tied to certain manufacturers of smart products. This makes it a technological integration layer for physical systems and services from heterogeneous sources. The data for the actual smart services are refined on the service platforms and a wide variety of providers and customers are networked to form digital ecosystems. In addition, they form the business integration layer, which provides the necessary framework for automated, legally secure collaboration between actors, the exchange of knowledge and trading in goods, data and services. These ecosystems also require new skills and training for employees. Only they, also referred to as Smart Talents in this context, enable the successful offering of Smart Services.

As part of so-called service engineering , smart data is actively used to continuously develop new service innovations, i. H. the data is refined into smart services and, if necessary, offered on service platforms. These can be app stores or other online marketplaces. Because different providers of data-based services come together on these service platforms and can exchange ideas with one another, they form real digital ecosystems.

Platform economy

The advancing general digitization and the growth of many smart service providers are creating new value creation mechanisms that are primarily handled via platforms (in particular service platforms). This form of economy is constituted by the various actors who are in business and logistical relationships with one another, i.e. who collaborate. Existing industry structures and value creation mechanisms are changing as a result. For example, Uber is the world's most valuable broker of taxi rides without using their own vehicles. In addition, individual platforms sometimes take on tasks from several areas: Amazon is not just a retail company and a sales platform, but also a logistics platform due to its intensive warehouse and shipping activities. These newly emerging platforms open up new opportunities for collaboration, for exchanging data and information and for creating new business models.

Current distribution of smart services

While the developments described in the report on data-based services have already advanced in theory, in practice the industry is still largely in the early stages. So far, existing process chains and procedures are v. a. expanded or improved through the integration of data-based services - smart services as paid value-added offers for end customers are not yet the norm and the corresponding digital business models have so far hardly generated any profits (see).

So far, many Smart Services have failed due to the lack of added value that they offer customers or companies - it is often already clear within a year of its market launch that the Smart Service will not last. Because customers and clients are not sufficiently involved in the development, the services are developed downright bypassing the customer's request, which favors later failure. Smart service approaches, which therefore focus particularly on the interests of customers and clients already in the development phase, are currently very promising approaches for generating long-term success from smart service innovations. One of these approaches is, for example, so-called smart service engineering, which relies on working with prototypes (so-called rapid prototyping ) in order to quickly present the first possible solutions to a problem and to be able to check its effectiveness under real conditions.

literature

  • Christian Fabry: Smart Services - Potentials and challenges of internet-based services for the economy . PhD lecture, FIR e. V. at RWTH Aachen, August 22, 2014 (available in FIR library and RWTH library: http://publications.rwth-aachen.de/record/443173 ).
  • Marco Husmann, Christian Fabry, Gerhard Gudergan: Smart Services - New Opportunity for Services 'Made in Europe'. Facts and trends in service. KVD Service Study 2014. Ed .: Günther Schuh; Gerhard Gudergan; Marcus Schröder; Volker Stich. FIR at RWTH Aachen 2014.
  • Henning Kagermann, Frank Riemensperger (ed.): Smart Service World. Implementation recommendations for the future project 'Internet-based services for the economy' . Berlin, March 2014. http://www.acatech.de/fileadmin/user_upload/Baumstruktur_nach_Website/Acatech/root/de/Projekte/Laufende_Projekte/Smart_Service_Welt/Smart_Service_Welt_2015/BerichtSmartService2015_D_lang_bf.pdf (last accessed: April 15, 2016)
  • Ralf Kreutzer, Karl-Heinz Land: Digital Darwinism. The silent attack on your business model and your brand. Springer Gabler, Wiesbaden 2013.
  • Günther Schuh, Christian Fabry: Digitization of Services - Potentials and Challenges. In: Service in the digital society. Contributions to the service conference of the BMBF in the Science Year 2014. Ed .: A. Boes. Campus, Frankfurt / Main 2014, pp. 50–59.
  • Günther Schuh: Smart Services New business models for medium-sized companies . Lecture at the 18th Aachen Service Forum in the Logistics Cluster on the RWTH Aachen Campus, March 25 - 26, 2015 (available in the FIR library).
  • Volker Stich: “Digitization of the service. Massive changes in the professional environment. ”[Lead article by Volker Stich, Managing Director of FIR e. V. at RWTH Aachen University, on the subject of 'Service goes digital - processes are changing'] Service Today 29 (2014) 1, p. 9f.

Documents

Individual evidence

  1. ↑ Günther Schuh: Smart Services New business models for medium-sized companies . Lecture at the 18th Aachen Service Forum in the Logistics Cluster on the RWTH Aachen Campus, March 25-26, 2015 (available in the FIR library)
  2. ↑ Timothy Kaufmann: Business Models in Industry 4.0 and the Internet of Things. Springer Fachmedien, Wiesbaden 2015, ISBN 978-3-658-10271-5 , pp. 6 .
  3. ^ Daniel Liebhart: Renaissance of the data processing. (PDF) 2012, accessed April 30, 2018 .
  4. ^ Günther Schuh, Christian Fabry: Digitization of Services - Potentials and Challenges. In: Service in the digital society. Contributions to the service conference of the BMBF in the Science Year 2014. Ed .: A. Boes. Campus, Frankfurt / Main 2014, pp. 50–59
  5. ↑ Smart Service Welt working group: Brief description. Retrieved December 14, 2017 .
  6. ↑ a b Henning Kagermann, Frank Riemensperger (ed.): Smart Service World. Implementation recommendations for the future project 'Internet-based services for the economy' . Berlin, March 2015. Acatech final report (PDF; 6.78 MB), last accessed: April 15, 2016, p. 174.
  7. ↑ a b c Henning Kagermann, Frank Riemensperger (ed.): Smart Service World. Implementation recommendations for the future project 'Internet-based services for the economy' . Berlin, March 2015. Acatech final report (PDF; 6.78 MB), last accessed: April 15, 2016
  8. ↑ Promotion group communication of the research union economy - science: Securing Germany's future as a production location. Recommendations for implementation of the future project Industry 4.0. Final report of the Industry 4.0 working group. (PDF) Promoter Group Communication of the Research Union Industry - Science, April 2013, SS 81 , accessed on December 14, 2017 .
  9. ↑ Reinhard Ematinger: From Industry 4.0 to Business Model 4.0. Springer Fachmedien, 2018, ISBN 978-3-658-19473-4 , pp. 10 .
  10. ↑ August Ortmeyer: Fiber optic expansion: The most politically sensitive area is yet to come! (=  Wirtschaftsdienst . No. 97 (01) ). 2017, p. 60 , doi : 10.1007 / s10273-017-2084-7 .