BIG DATA IN SERVICE DESIGN: CREATING SERVICE INNOVATION FOR INDUSTRY 4.0 ENVIRONMENT

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BIG DATA IN SERVICE DESIGN: CREATING SERVICE INNOVATION FOR INDUSTRY 4.0 ENVIRONMENT Author: Sruthy Padannappurath, Msc. Product Service System Design, Politecnico di Milano Guided by: Dr. Daniela Sangiorgi, Department of Design, Politecnico di Milano. Tutors: Marta Carrera, Filipe Lima

Keywords: Service Design, Big Data, Big Data Analytics, Service Innovation, Industry 4.0, Industrial Internet

Introduction “For modern industry, data generated by machines and devices, cloud-based solutions, business management, etc., has reached a total volume of more than 1000 Exabytes annually and is expected to increase 20-fold in the next ten years� (Yin and Kaynak, 2015, p.

143). And what are all these data used for? This essay is to understand the usefulness of big data in the field of service design; for creating service innovations in the manufacturing and supply chain sector for industries, especially in the context of the Fourth Industrial Revolution which is called Industry 4.0 or Industrial Internet.

Big Data Analytics is in urgent need for helping manufacturers execute their right strategies with greater precision and efficiency in the present world. It could transform business processes, alter corporate ecosystem and facilitate innovation (Zhou, et al., 2017). The enquiry is based on desk researches done aiming to understand and define the terms used, and to analyse two existing case study examples that have used Big Data Analytics for creating service innovation in industries. The potentialities and challenges in using big data for Industry would vary from sector to sector, but the cases chosen here are to exemplify the benefits of using disruptive technologies like Big Data for designing innovative services for industries in the Industry 4.0 environment.

Background The world is on a threshold of change to a new era for industries, by merging advanced computing, low cost sensing, Internet of Things, Big Data Analytics and other disruptive technologies with the existing industrial system. To put it simply, we are witnessing a union of the digital world with the world of industrial machines, paving the way for the fourth industrial revolution. This phenomenon is called in different names, like Industry 4.0, Industrial Internet of things or just Industrial Internet. According to Hermann, Industry 4.0 is a recent concept that was used for the first time in 2011 in the Hannover Fair, Germany and this concept involves the main technological innovations applied to production processes in the field of automation, control and information technologies. It is a collective term for technologies and concepts of value chain organization (Hermann, et al., 2016). The basic foundation of Industry 4.0 is that through the connection of machines and systems, organizations can create smart grids which enable decentralized decisions and automate 1 SRUTHY PADANNAPPURATH |891976

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processes Within the Industry 4.0 framework, organizations will have the capacity and autonomy to schedule maintenance, predict failures and adapt themselves to new requirements and unplanned changes in the production processes (Jazdi, 2014). On the technological side, there are many disruptive technologies like Artificial Intelligence, Cloud computing, IoT, Big Data etc. that Industry 4.0 makes use of. Here we shall focus only on Big Data as an approach in the Industry 4.0 environment.

Though Big Data has become a buzzword, the definition of Big Data still revolves around much conceptual vagueness. It is a standalone term when referring to those “Information assets characterized by such a high Volume, Velocity and Variety to require specific technology and analytical methods for its transformation into Value” and as an attribute when denoting its peculiar requisites like “Big Data Analytics” (Mauro et al., 2015). Big Data is about new challenging data sources helping to understand business at a more granular level, creating new products or services, and responding to business changes as they occur.

(Davenport et al., 2012) Many companies are using Big Data Analytics to understand their market value. But here we will be exploring the possibilities of Big Data in creating service innovations for Industry 4.0.

“Service innovation is a new service or a renewal of an existing service which is put into practice and which provides benefit to the organization that has developed it; the benefit usually derives from the added value that the renewal provides the customers” (Toivonen and Tuominen, 2009 p. 893). And (Agarwal and Selen, 2011) conceptualize service innovation as an elevated service offering with new client interface/customer encounter; new service delivery system; new organizational structure and marketing; and or improvements in productivity and performance through human resource management. Another key concept in this essay is service design, which facilitates service innovations.

Services are not tangible or standardised goods that can be stored away in an inventory.

Instead, services are created through interaction between a service provider and a customer. It should meet the customer needs and be used frequently and recommended heartily. (Stickdorn and Schneider, 2011, p. 28) Also Mager tries to explain services as systems that involve many different influential factors, so service design takes a holistic approach in order to get an understanding of the system and the different actors within the system. (Mager and Sung, 2011) Now that all the terms used in this essay are introduced, let us explore the possibilities of Big Data in Industry 4.0 for bringing service innovations.

Big Data fuelling the Industry 4.0 to create innovative services “Massive data is produced not only in manufacturing process but also in marketing, sales, maintenance and services. The current challenge consists in converting this Big Data into knowledge and wisdom that produce intelligent manufacturing decisions for creating new products and services” (Zhou et al., 2017, p. 107). In many cases designers have proved to be an integral part in a team for utilizing these data sets for developing innovative services.

We have two cases here; the first case is about developing a Big Data service from scratch for Volvo Used Trucks section. Many companies and organizations collect vast amounts of data to analyse and assess their market values. But in this particular case study, a practical service design approach was used to create service innovation from Big Data analysis. This case elaborates the role played by the designer in understanding and utilizing the Big Data 2 SRUTHY PADANNAPPURATH |891976

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technology. The other case is from General Electric (GE), a giant corporation which use cloud based database system to allow its industrial customers to move their data to the cloud and GE does the Big Data analysis for them. Also GE facilitates machines to machine communications using Big Data, thereby improving their service. Both these cases are innovative service offerings in the Industry 4.0 environment.

Case 1: Innovative service through Big Data for Volvo Used Trucks EMEA Volvo Used Trucks EMEA is a Volvo entity that manages the purchase and sale of used Volvo trucks in the Europe, Middle East, and Asia regions. Interaction design, Chalmers University of Technology was involved in designing this specific service. The aim of the project was to use big data approach to explore the potential of integrating data from a number of pre-existing sources, iteratively exploring the opportunities offered by the new big data set. After collecting and segregating the required data sets, a user-centred design approach was used to match the new insights with domain knowledge, creating a new service.

The Used Trucks division was particularly interested in the initial results derived from the data sets and thus they became the target user group. The first step was to meet the users and conduct focus group sessions to understand the context and users better. The key insight from this was that the managers mostly use intuition and work experience to categorise the quality of used vehicles, meaning much of their work expertise was not quantifiable and thus impossible to relate to databases. Also the physical truck inspections required long hours per vehicle, and mostly managers resort to random sampling to assess the vehicles on time. This is where the potential of Big Data was hidden.

The hardest situation was to manage needs of the Used Trucks business managers to the contents of a vast data set. And it was tackled by a user centric design approach. Several workshops where conducted involving the stakeholders to develop the prototype and several iterations where done before finalizing the service. Finally a fully functional service was made to evaluate the value of used trucks faster using a Big Data server (Wołniak, et al., 2015). The project resulted in building a Big Data service supporting the used trucks business, and managing the risk associated with buying and reselling heavy-duty trucks.

Case 2: Service innovation with Big Data Analytics by GE General Electric (GE) is a literal powerhouse of a corporation as a major manufacturer of systems in aviation, rail, mining, energy, healthcare, and more. Hence GE customers include big oil and natural gas production companies, major U.S. municipalities, global consumer goods manufacturer etc. GE is forefront in digital innovations and the Industry 4.0 which they call Industrial Internet. GE realised their customers are looking for a solution to manage their data across the enterprise and run analytical queries that provide immediate tangible insights to operations and improve business metrics. Identifying this need is the base of their service innovation. GE thought about managing this massive industry sized Big Data from their customers on a cloud based common platform using Predix, the operating system GE developed for the Industry 4.0. They collaborated with a software lab to develop this “data lake�. According to GE, their data lakes have the ability to analyse data 2000 times faster than previous Industrial Internet methods. Also, it would help major industrial corporations 3 SRUTHY PADANNAPPURATH |891976

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spend less money and time on supervising rigorous processes for storing and analysing their data, but focus more on turning data into actionable insight for increasing productivity of operations and optimization of assets. And GE provides them with the service of massive Big Data Analytics (Patel et al., 2017).

GE sells equipment and follows up with maintenance services to their corporate customers.

Another use of Big Data by GE is to improve the efficiency of their service offering. Data collected by sensors installed in machinery, for example in aviation, is used to schedule maintenance and repair automatically by facilitating machine to machine communication.

With their existing resources and also by establishing a new analytics operation centre in San Francisco, GE increased their facilities to establish this innovative service using Big Data Analytics (Marr, 2017).

GE has shown that data combined with analytics is the best way to bring innovative services to the Industry 4.0 environment. Also it is essential for a service designer to understand the potentials that new technologies like Big Data holds to create innovative services for now and future like this case from GE. Analysis from the cases Many organizations in the manufacturing sector are shifting to service offerings from product offerings and these services are already data and technology enabled. But organizations have to understand the potential Big Data holds in improving their service and try to integrate these technologies into their practice as early as possible. The case from Volvo was about facilitating discussion among users to identify the need of the service, making users correct the designer’s mistakes and then to explore the data set in order to bring innovative solutions to the problem in hand. The second case from GE is on a more gigantic level than the previous case. GE developed a service for solving the problem caused by the massive amount of data itself, generated by their customers. GE was quick to embrace the new digital technologies like Big Data early on and that has given them an edge from their competitors. Service designers play a crucial role in creating innovative services for industries and hence they have to be forefront in understanding the potential of technologies like Big Data for service design. These cases solidify the argument that Big Data can bring service innovations for Industry 4.0.

Conclusions Unprocessed data in itself is not useful, and using Big Data has a lot of challenges in data collection, transformation, integration, storage, security, analytics etc. But service designers have to be aware of the immense potential Big Data holds, and take a user centric approach to understand the problems which could be solved by data analytics. This essay confirms that Big Data plays a crucial role in bringing service innovation to Industry 4.0 environment by showing cases from the manufacturing and supply chain sector; but have not discussed about the usefulness of Big Data in other sectors of Industry 4.0. This study can be further developed by including the overall picture of all sectors in the Industry 4.0 and understanding how Big Data approach taken by designers is facilitating service innovations for industries.

Also the study could be elaborated on the role played by a service designer for the future of service innovation through these disruptive technologies.

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