IN THE FIELD OF TECHNOLOGY DEGREE PROJECT
DESIGN AND PRODUCT REALISATION AND THE MAIN FIELD OF STUDY INDUSTRIAL MANAGEMENT, SECOND CYCLE, 30 CREDITS STOCKHOLM SWEDEN 2018,
The effect of IoT on revenue streams and product features within the mechanical industry
Development of a business model JOHN FRANSSON
MARTIN WÅHLSTRAND
IN
DEGREE PROJECT INDUSTRIAL MANAGEMENT,
SECOND CYCLE, 30 CREDITS STOCKHOLM SWEDEN 2018,
The effect of IoT on revenue streams and product features within the mechanical industry
Development of a business model JOHN FRANSSON
MARTIN WÅHLSTRAND
The effect of IoT on revenue streams and product features within the mechanical industry
Development of a business model
by
John Fransson Martin Wåhlstrand
Master of Science Thesis INDEK: TRITA-ITM-EX 2018:150 KTH Industrial Engineering and Management
Industrial Management
IoT’s effekt på intäktsströmmar och
produktegenskaper inom verkstadsindustrin
Utveckling av en affärsmodell
John Fransson Martin Wåhlstrand
Examensarbete INDEK: TRITA-ITM-EX 2018:150
KTH Industriell teknik och management
Master of Science Thesis INDEK:
TRITA-ITM-EX 2018:150
The effect of IoT on revenue streams and product features within the mechanical industry
Development of a business model
John Fransson Martin Wåhlstrand
Approved
2018-05-30
Examiner
Terrence Brown
Supervisor
Tomas Sörensson
Commissioner Contact person
Abstract
A mechanical industry company’s need for an effective and suitable business model is higher than ever before due to new emerging technologies, especially within digitalization and Industry 4.0.
As the Internet of Things (IoT) trend is emerging, companies need to identify new value propositions and adapt their offerings and revenue models in order to meet the customers’ new demands. The current amount of studies that have been conducted in the area of new business models and product offerings with regards to the IoT technology are limited. Therefore, this study has examined and analyzed how a new business model should be designed and what kind of new product offerings a company in the mechanical industry should offer in the area of IoT and servitization. The literature study contains information about Industry 4.0, Internet of Things and Servitization while the theory study addresses theories regarding the business model canvas together with the KANO model.
The study has been executed by conducting eleven semi-structured interviews, where nine of the interviewees were employees at our commissioner and the remaining two were customers of our commissioner. The internal interviews were held with executives and managers who represented eight different divisions as well as three different nationalities. The customer interviewees represented two different companies with different sizes and ownership structures.
The results of the study indicate that the IoT technology contributes to several new possible product and service offerings, together with new revenue streams, as well as a need for implementing a new servitized business model. Conclusively, offerings such as predictive maintenance, remote assistance, and machine optimization among others, can be offered to the customers with the help of the IoT technology. Furthermore, new payment models such as up- front payments together with a service agreement with monthly payments, are vital parts of a new business model that has to be implemented. In addition, a closer customer relationship is required when moving towards servitization in the area of digitalization and IoT.
Key-words: Internet of Things, IoT, digitalization, servitization, Industry 4.0, Business Model
Examensarbete INDEK:
TRITA-ITM-EX 2018:150
IoT’s effekt på intäktsströmmar och produktegenskaper inom verkstadsindustrin
Utveckling av en affärsmodell
John Fransson Martin Wåhlstrand
Godkänt
2018-05-30
Examinator
Terrence Brown
Handledare
Tomas Sörensson
Uppdragsgivare Kontaktperson
Sammanfattning
För ett bolag inom verkstadsindustrin finns behovet av en effektiv och passande affärsmodell på grund av de nya digitaliseringskoncepten Industri 4.0 och Internet of Things (IoT). Företag måste identifiera nya värdeskapande erbjudanden och anpassa sina affärsmodeller och intäktsströmmar för att möta kundernas nya behov. Antalet studier som genomförts inom området “nya affärsmodeller och produkterbjudanden baserade på IoT-teknik” är begränsat. Därför har denna studie undersökt och analyserat hur en ny affärsmodell bör kunna se ut med hänsyn till vilka typer av nya produkterbjudanden ett bolag inom verkstadsindustrin borde erbjuda inom området för IoT.
I kombination med dessa digitaliseringskoncept, ses konceptet servitization som en möjlig väg för att kunna leverera dessa nya erbjudanden till kunderna. Litteraturstudien innehåller information om Industri 4.0, Internet of Things och servitization medan teoristudien adresserar teorier om business model canvas tillsammans med KANO-modellen.
Vi har genomfört elva semistrukturerade intervjuer, där nio utav de intervjuade var anställda hos rapportens beställare och de resterande två var kunder till samma beställare. De interna intervjuerna hölls med chefer på ledande befattningar som representerade åtta olika affärsdivisioner och tre olika nationaliteter. Kunderna som intervjuades representerade två företag av olika storlek och olika ägarförhållanden.
Studiens resultat visar på att IoT bidrar till ett antal nya produkt- och serviceerbjudanden, tillsammans med nya intäktsströmmar, och det visar även behovet av att implementera en ny serviceinriktad affärsmodell. Slutsatsen visar att erbjudanden som prediktivt underhåll, fjärråtkomst och maskinoptimering med flera, kan erbjudas till kunden med hjälp av IoT-tekniken.
Vidare identifieras nya betalningsmodeller, till exempel direktbetalning för en maskin tillsammans med ett serviceavtal som inkluderar månadsvisa betalningar, som viktiga delar utav den föreslagna affärsmodellen. Slutligen visar studien att starkare kundrelationer måste etableras när ett företag går mot en mer serviceinriktad strategi som en del av digitalisering och IoT.
Nyckelord: Internet of Things, IoT, digitalisering, Industri 4.0, Business Model Canvas, BMC,
affärsmodeller, KANO-modellen.
Foreword
This Master Thesis report was written by John Fransson and Martin Wåhlstrand at the Royal Institute of Technology, Stockholm, Sweden, at the Department of Industrial Engineering and Management. John has a Bachelor of Science in Design & Product Realisation, and Martin has a Bachelor of Science in Engineering. Thus, we have studied different programs, but both have studied Master in Industrial Management and written this report together. This Master Thesis project was conducted during the period of January 2018 - May 2018.
Acknowledgements
We would like to thank our supervisor at KTH - Tomas Sörensson, Associate Professor in Industrial Economics and Management. During our Master thesis project, Sörensson has always been available to assist, supervise and coach us with formidable advice during the entire period. At the same time, he consistently allowed this research to be our own work. With Sörensson’s many years of impressive experience within the academic world, he pointed out the right direction whenever we needed it.
We would also like to express our gratitude to our supervisor at the commissioning company. Without him, this thesis would never had been written. Thank you!
Lastly, we would also like to show our thankfulness to the eleven respondents who all agreed to be interviewed, despite the fact that they all were very busy. Even these people are anonymous, but you know who you are.
Thank you everyone for your thoughtful, wise and valuable inputs!
John Fransson & Martin Wåhlstrand Stockholm, Sweden - 2018-05-30
List of Abbreviations
AI – Artificial Intelligence B2B – Business to business CPS – Cyber Physical Systems
CRM – Customer Relationship Management IoT – Internet of Things
KPI – Key Performance Indicator LCA – Life Cycle Analysis M2M – Machine to Machine
PLC – Programmable Logic Controller
Table of contents
1 Introduction ... 1
1.1 Background ...1
1.2 Commissioner ...3
1.3 Problematization ...3
1.4 Pupose & Research Questions ...4
1.5 Contribution ...4
1.6 Delimitations ...4
1.7 Outline of the Thesis ...5
2 Method... 6
2.1 Research Approach ...6
2.2 Research Design ...6
2.3 Research Method ...7
2.3.1 Literature Review & Theory ... 7
2.3.2 Data Colletion & Analysis ... 8
3 Literature & Theory ... 10
3.1 IoT within Industry 4.0 ... 10
3.1.1 The possibilities of the IoT within the Mechanical Industry ... 12
3.1.2 The Architecture Behind IoT ... 13
3.1.3 IoT and the New Value Proposition ... 13
3.1.4 Barriers of the IoT ... 14
3.2 Servitization ... 15
3.2.1 Contribution to Servitization Literature ... 16
3.2.2 Value of Servitization... 17
3.2.3 Servitization & Digitalization ... 17
3.2.4 Servitization Through The IoT Technology ... 18
3.3 Business Models Within Digitalization ... 19
3.4 Business Models Within Servitization ... 21
3.5 Business Model Canvas ... 22
3.6 KANO Model... 25
3.7 Summary of Literature Review ... 27
4 Results ... 28
4.1 Internal Study – Interviews With Employees ... 28
4.2 External Study – Interviews With Customers ... 48
5 Analysis ... 52
5.1 Product Features ... 52
5.1.1 Smart documentation... 53
5.1.2 Real time monitoring ... 53
5.1.3 Predictive maintenance ... 53
5.3 Key Activities ... 54
5.4 Key Resources... 54
5.5 Cost Structure... 55
5.6 Value Proposition ... 55
5.7 Customer Relationships... 56
5.8 Customer Segments ... 57
5.9 Channels ... 57
5.10 Revenue Streams ... 58
5.11 Barriers ... 59
6 Conclusion ... 60
6.1 Answer of Research Question 1 ... 60
6.2 Answer of Research Question 2 ... 61
6.2.1 Key Partners ... 61
6.2.2 Key Activities... 61
6.2.3 Key Resources ... 61
6.2.4 Cost Structure ... 61
6.2.5 Value Proposition ... 62
6.2.6 Customer Relationship ... 62
6.2.7 Channels & Customer Segments ... 62
6.2.8 Revenue Streams ... 62
6.3 Recommendations For Future Research ... 65
7 Discussion ... 66
7.1 Discussion of Method Used ... 66
7.2 Reliability & Validity... 66
7.3 Generalizability ... 68
7.4 Sustainability & Ethical Implications ... 68
8 References ... 70
9 Appendix ... 75
9.1 Appendix 1 – Internal Interview Guideline ... 75
9.2 Appendix 2 – External Interview Guideline ... 76
1 Introduction
In this chapter, a brief background about the research area and Beta are presented, followed by the problematization, purpose & research questions and delimitations.
1.1 Background
Internet of Things (IoT) within the Industry 4.0 is becoming a growing subject of conversations, not only in the workplace, but also outside of it. The concept has the potential to impact how we work and how we live. Today, connectivity is more widespread and broadband has become cheaper and more accessible. Meanwhile, sensors and components are becoming more affordable. An effect of this is that more and more devices are being created with Wi-Fi capabilities and many types of sensors are built into them (Morgan, 2014). According to van der Meulen (2017) at Gartner Inc, the number of connected things worldwide today is 8.4 billion and that this number will be almost tripled in 2020. Other researchers estimate that the number of connected units will reach 46 billion by 2021 (Smith, 2016).
IoT makes it possible for industrial companies to be able to monitor the performance of their machines and in turn, plan for production stops in order to switch spare parts in the machines and help the companies to improve efficiency and reduce waste (Morgan, 2014). According to a director who is responsible for product development at this report’s commissioner, the digitalization, and especially the IoT, will change the market for the machine equipment industry. By knowing more about the products, for example operating time, temperatures, speed of rotation, power, lubrication, abrasion and forces that are subjecting the machine and its components, it will be possible to create more value to the customers in many ways (Morgan, 2014). When a company gets all this kind of information regarding the machines, it can optimize the usage of the machine for a unique environment, prevent accidents from happening and plan for the services and downtime of the machines.
Additional, in parallel with the emergence of IoT, the shift towards servitization is steadily growing in the manufacturing industry. Being able to monitor and receive big data from the customer, open up for the servitization to take place. Servitization is about taking the traditional product offering and deliver it as a service instead. For example, renting the product for a monthly fee including service and maintenance, instead of buying the product up-front and order and pay for the service and maintenance separately (Crozet & Milet, 2015). Bringing the IoT and servitization concepts together (see figure 1.1), opens up for huge possibilities for companies (Rymasewska, et al., 2017).
Therefore, companies are in more need than ever to develop their product offerings.
Now, they have the possibility and the opportunity to additionally add more value to
their product offering making the supply chain smarter, faster and thereby more efficient than ever before (Ibid.).
Figure 1.1 Visual map of the relation between the presented concepts and the mechanical industry.
For the customer, the value-adding within servitization is considered to be the integrated and tailor-made product offerings, while for the manufacturers, it is the product innovation and the standardization that comes along with it (Coreynen, et al., 2015). A study conducted by the European Commission, interviewed representatives from 67 different industrial companies within the European Union, showed that companies had two main reasons behind starting to deliver services instead of products (Economist, 2013). Either it was because of differentiating their offerings from their competitors or increasing the customer loyalty (Ibid.). Furthermore, it also found that 28% of the companies got increased customer loyalty, and 16 % got higher sales, and that there is a high correlation between getting higher sales of goods with the combination of starting to sell services (Ibid.).
The Economist (2013) argues that servitization in combination with the digitalization is the future within the mechanical industry. The manufacturing has always been about making the raw material into products, where the physical product has been in the center of the value creation for the customer. However, the servitization, with the help of digitalization, can add additional value to both the customer and the producing company, and thereby generate new revenue streams through other activities besides the physical product (Ibid.). Neely, et al. (2011) point out that in 2007, 24% of British manufacturing companies with more than 100 employees derived value from services, while in 2011 it was as high as 39%.
The globally emerging digitalization creates huge possibilities within servitization (Coreynen, et al., 2016; Crozet & Milet, 2015; Rymasewska, et al., 2017). Although,
2015). Thus, service can be with compliments to the good, or substitutes to it, which makes it into a non-trivial question in order to figure out which one is suitable (Ibid.). It is therefore essential to align it with the strategy of the company, while it must deliver value to both the customer and the company. As the IoT and servitization trends emerges, companies within the manufacturing industry need to consider going from their traditional business model towards a business model that can handle the product as a service (Crozet & Milet, 2015).
1.2 Commissioner
The commissioner of this report is a large European company which hereby is called Beta. It has a turnover of more than € 10 billion and is acting in different kind of business areas, that in some cases are not at all related to each other. Beta is acting worldwide with over 28,000 employees and has more than 320 subsidiaries. It is a leading global supplier within all its business areas and delivers customized turnkey solutions, where it has a strategy to be a machine supplier with quality in first hand. Furthermore, it has partnerships in the whole life-cycle of machines and products.
The products that this study analyzes are machines that process different kinds of material into smaller granulate sizes. The complete process depends on the various type of variables such as humidity, material and temperature. Further, the process strives for as high capacity throughput as possible along with low wearing on the machine parts.
One part of the process is that the input material should not contain too much impurities.
In that case, the wearing life-time will be shortened, and the capacity will go down. With this said, the machines demand a lot of energy (up to 600 kW). It is therefore essential that the process is efficient and optimized so that the customer can save money.
1.3 Problematization
The emergence of IoT within the field of Industry 4.0 brings both challenges and opportunities to established companies in the mechanical industry such as Beta. To play a key role in the digital transition and remain its competitive advantage in the industry, Beta needs to embrace the new product offerings that come along with the IoT technology and evaluate whether it needs to change its business model.
1.4 Pupose & Research Questions
The purpose of this paper is to develop and evaluate a suitable business model in the area of IoT in combination with the concept of servitization. We investigate how the concepts can create more value for both Beta and its customers by identifying new revenue streams and new product features. We study the following research questions:
Research question 1
How can IoT and servitization facilitate new product offerings for a company within the mechanical industry, and thereby create new revenue streams?
Research question 2
What kind of business model should be implemented in order to stay relevant in the mechanical industry?
1.5 Contribution
This paper aims to extend the existing literature in the area of IoT and servitization and to contribute to increased knowledge of business models within the mechanical industry regarding the subjects of IoT and servitization. The aim is also to contribute to how a company within the industry can leverage on it, and what kind of value proposition there is. Furthermore, the thesis contributes to help companies get knowledge about how to construct their business models in the best way when moving towards a servitization based business strategy.
1.6 Delimitations
The study will only investigate a scenario where IoT within Industry 4.0 emerges and will therefore not take into account any other possible future scenarios within the mechanical industry.
From the system perspective, we will analyze market trends from the functional- and industrial perspective. To clarify, we will not analyze how it will affect companies within the mechanical industry on the individual and organizational level, thus how IoT will change it internally and how the individual employees are affected by it. An eventual implementation process of our suggested business model will not be investigated. To increase the reliability of the result, we will only investigate theories and literature connected to IoT that are not older than five years.
1.7 Outline of the Thesis This thesis consists of seven chapters:
1. Introduction - The first chapter is presenting the background of the problem and why it is important and non-trivial. The chapter also presents the purpose of the study, together with the research questions as well as the expected contribution and necessary delimitations.
2. Method - The Methodology is presented in the second chapter. The methodological approach together with the research design that has been used in this project are presented.
3. Literature & Theory - Chapter three contains the literature and theory review. This chapter comprises relevant knowledge with regards to the thesis subject. The chapter addresses literature regarding Industry 4.0, IoT and digitalization and the presented theories are theories regarding the Business Model Canvas and the KANO model.
4. Results - In the fourth chapter, we present our empirical findings. The chapter presents which questions were asked and to whom, as well as the answers to the questions which are presented in a compiled form under each question. The questions asked were derived from the literature and theory review.
5. Analysis - Chapter five presents the analysis of the results found in chapter four. The analysis has been conducted by combining and triangulating our empirical findings with the literature and theory review.
6. Conclusion - The sixth chapter contains a discussion and argumentation of the chosen method. Furthermore, the discussion contains an examination of the reliability, validity, generalizability of the study. Lastly, this chapter presents a discussion regarding sustainability and ethical implications of our study.
7. Discussion - In the last chapter, chapter seven, our conclusions are presented. The answers of the research questions are presented together with recommendations for future work related to the thesis subject.
2 Method
In this chapter, the research approach and design are presented, followed by the research method which explains how the data is gathered and analyzed.
2.1 Research Approach
The background of our thesis established a foundation for the research regarding how to move forward. The literature study will open up the need to define and extend the literature. According to Blomkvist & Hallin (2017) and Goddard & Melville (2004), the research approach can be divided into the three common approaches; deductive, inductive and abductive. In the deductive approach, there already exists a hypothesis about the phenomena that is gathered from the theory which the paper aims to test whether it can be verified or falsified (Ibid.). The inductive approach is where the research has an explorative approach, and the paper aims to further study the phenomena in order to understand it and to develop explanations. The abductive approach is when the paper combines and alters between empirical and theoretical observations throughout the paper in order to analyze which theory should be used in a combination of the findings (Blomkvist & Hallin, 2017; Goddard & Melville, 2004). Since the purpose of this study is to explore how a mechanical industry company can use the IoT technology and servitization, an abductive approach is chosen. This is aligned with what Blomkvist
& Hallin (2017) argue for, namely that the abductive approach is suitable when the paper aims to understand the phenomena rather than to falsify or verify it. Therefore, this approach is highly suitable for our study when answering our proposed research questions. The answers should be forged with the theoretical knowledge applied to the empirical observations (Goddard & Melville, 2004).
2.2 Research Design
The research design of this paper is chosen to be a case study due to the high complexity of the problem and its non-trivial solution (Blomkvist & Hallin, 2015). In the beginning of the work, a research purpose was formed together with the commissioner with relevant research questions of the topic. Namely, to find out what kind of product features there are within IoT and to adapt a business model for it. In addition, our research is limited to a single technology, which is described as the main characteristics of a case study according to Bryman & Bell (2015). To identify new value propositions and at the same time adapt a new business model to this, is in nature very complex, and little consensus exists regarding how this should be performed and shaped. A case study captures the complexity of our phenomena in a better way than for example experiments, surveys or multiple case studies (Blomkvist & Hallin, 2017). This is further in line with what Soy (1997) means, namely that case study is the best practice when it comes to a complex problem with a defined focus. It can be argued that a study of a specific case cannot be
approach captures a more realistic picture of the phenomena compared to other types of research design. Further, the case study methodology has been criticized for being primitive and subjective by for example Blomkvist & Hallin (2017). It is thus important to collect empirical data in a systematic way as well as thoroughly elaborate on the analytical method in order to minimize the subjectivity. The methodology will therefore be to conduct eleven semi-structured interviews, where nine of the interviews will be held with current executives at our commissioner’s company. The remaining two interviews will be conducted with customers of our commissioner. The customer interviewees represent two different type of companies of size ownership structure.
2.3 Research Method
The research method, see figure 2.1, explains how we will gather information throughout the work. Firstly, we will conduct a pre-study, which builds the foundation of the report.
This leads us to the literature and theory study, where we will investigate literatures within the areas of Industry 4.0, Internet of Things and servitization. The theory study addresses theories regarding the Business Model Canvas and the KANO model. After that, we will execute the empirical study comprised of eleven semi-structured interviews with people on various position, both within the commissioner company, but also outside of it. Last, we will use the findings from the empirical study and analyze it together with the literature and theoretical models in order to draw thoughtful conclusions. Throughout the whole project, the literature review will be conducted and adapted to our findings.
Figure 2.1. The research process.
2.3.1 Literature Review & Theory
The purpose of the literature review is to have a foundation for the empirical study and to triangulate the answers in the analysis. It is also used to find out what has already been done as regards to the phenomena. We will investigate previous literature within the research area of IoT, Industry 4.0 and Servitization. Different search tools such as the internet, databases, and libraries will be used. The most frequently used tools will be Google Scholar, DiVA, Business Source Premier, LIBRIS, and JSTOR. Furthermore, books, journals and conference papers (both paper and digital) will be evaluated to get an as broad perspective as possible of the subjects. This kind of über reading up will be performed in order to better understand what has to be done within the area to get a good result as possible at the end of this study (Blomkvist & Hallin, 2015). Keywords such as the Internet of Things, IoT, Industry 4.0, servitization, business model, business model
canvas, and its Swedish equivalents will be used in order to search for relevant literature and information.
2.3.2 Data Colletion & Analysis
The case study will gather primary sources through semi-structured interviews and data collection. The qualitative method is chosen due to the complexity of the phenomena, and a quantitative method of this kind would risk to simplify it (Blomkvist & Hallin, 2015). Thus, the literature will give us information about what kind of questions that need to be posed and answered.
According to Greener (2008), a qualitative interview can either be structured, semi- structured or unstructured. The semi-structured interview form is chosen and considered as appropriate for this kind of approach due to the fact that it makes the interviewee talk freely about the phenomena (Blomkvist & Hallin, 2015; Green, 2008). The interviews will be conducted with employees at various positions at Beta and will include both managers and subordinates. As a last step of the empirical study, we will contact and interview two current customers of Beta. This will be done in order to get a better understanding of what the customers want and also if, and how they want to pay for it, in order to identify new possible revenue streams. The two customer interviewees will represent two different companies, which have different size and ownership structures.
Before the interviews, we will provide the interviewee with an explanation about the background and purpose of our study in order to provide the interviewee with a clear picture of what we are doing and why. Declaring the purpose of the study prior to an interview tends to make the interviewee to provide answers that are correlated with the purpose of the research analysis (Collis & Hussey, 2013). In addition to this, we will send the questions we intend to ask beforehand to the interviewees. An unprepared interviewee would have decreased the validity of the study which is the reason for sending the questions on beforehand (Ibid.). Since the interviewee will get the questions before the interview starts, they have a lot of time to think through and prepare their answers. Thus, providing us with thoughtful answers which are not based on guesses or hasty conclusions.
Additionally, the questions will be tested and reviewed on beforehand to secure that the interview is time-efficient and that it will run smoothly throughout the whole interview session. The secondary sources include company statements from Beta’s annual report, internal documentations and presentations. The secondary sources will also be used to cross-check and triangulate the information gathered from the primary sources.
In the data analysis, the theoretical models will be used as the foundation in order to categorize the data from both the literature review and the empirical findings. The
each topic will be triangulated with the literature review and the empirical findings. We will use these two models since it is a request from Beta since it is using the models in its organization today. Since the abductive research design is chosen, the theoretical models will be adapted for our use. Thus, the KANO-model will define the possible product offerings that come along with the concept of IoT. This can then motivate the upcoming value proposition for the Business Model Canvas.
The aim is that the conclusions will help us to provide further academic recommendations and the eventual future work that needs to be done in order to complete the transition towards the new business model and new product and service offerings.
3 Literature & Theory
In this chapter, a brief overview of Industry 4.0 is first presented, followed by a more in- depth explanation of the concept and the technological possibilities of IoT and lastly the barriers for implementation.
3.1 IoT within Industry 4.0
During the past time, we have faced three big industrial revolutions, see figure 3.1. It started back in 1760 where hand production methods were replaced by machines and mechanical tools. The second revolution emerged during the 1870s when Henry Ford started to mass produce cars. The third revolution occurred recently in 1980 when the automatization with help of computers started to play a big role within the manufacturing industry (Roser, 2017). Today, we are facing a new revolution called Industry 4.0, which is centered around digitalization, smart products, connected products and connected machines (Zawra, et al., 2017). The concept of Industry 4.0, initially known as Industrie 4.0, was first presented by the German government at the Hannover fair in 2011 and has then been reviewed to present the final concept in 2013 (Marr, 2016). It is one of the ten strategic goals that Germany has settled in order to remain its position as one of the leading supplier of products (Ibid.).
Figure 3.1. The Industry 4.0 (Roser, 2017).
Moreover, Industry 4.0 brings numerous technologies together which includes the well- known technologies as: Internet of Things (IoT), Cyber-physical systems (CPS), communication machine-to-machine (M2M), cloud computing, big data, smart factory, cognitive computing, mobility, artificial intelligence (AI), autonomous vehicles, 3D- printing and a lot more (Roser, 2017; Lins, et al., 2016; Zawra, et al., 2017). The mentioned technologies are needed in some way in the Industry 4.0 and are therefore included under the umbrella of it. According to Zawra, et al., (2017) and Rymasewska, et al., (2017), the continuous development of these technologies, will result in more sensors, data acquisitions systems, and the learning to apply high-tech solutions will tend to result in higher availability for it. The falling cost for the technologies such as internet,
optimization and value creation for both processes and products. As a result, it will generate an enormous amount of data that can be analyzed, also known as the mentioned big data (Zawra, et al., 2017; Rymasewska, et al., 2017).
According to Lins, et al. (2016), when trying to concretize the Industry 4.0, it becomes quite vague. they further argues that overall it tries to make a passive object to an active object, where it aims to self-monitor all processes in order to alter flows and optimize the production . However, the three main technologies that are often mentioned are CPS (1), smart factory (2) and IoT (3), which will scientifically help the implementation of the Industry 4.0 (Strandhagen, et al., 2017; Zawra, et al., 2017; Lins, et al., 2016).
The first mentioned (1), is an automated system that mainly focuses on networking several devices instead of a stand-alone device by monitoring and controlling physical processes as a communication infrastructure (Zawra, et al., 2017). The concept was first coined back in 2006 by selected experts from the European Union and the United States.
The main focus of the CPS is to integrate the computation with the physical processes (Ibid.). An example of a CPS-system is a smart power grid, which communicates between each component in order to self-heal, and make sure that each component of the system has power (Strandhagen, et al., 2017; Zawra, et al., 2017).
The second mentioned is the smart factory (2), which takes the initial lean and other efficient processes one step further. By getting, monitoring and calculating information, the concept of smart factory will predict demands and make the supply chain smarter, faster and better by computer control and high level of adaptability the concept is quite broad, because manufacturing overall touches a lot of different areas, but it is supposed to help refine the complicated processes (Lins, et al., 2016). By connecting each machine to suppliers of raw material, original equipment manufacturer (OEM), all parties can have a greater understanding from each other and thereby the flow of material and manufacturing will run smoother (Strandhagen, et al., 2017).
The third technology is IoT (3), which is the most mentioned technology when the Industry 4.0 is discussed. The first time IoT was presented was by Kevin Ashton of Procter and Gamble in 1999. The "Things" in IoT refer to smart and intelligent objects that can have seamless connections and can share information through the internet which can thereby react and work proactive (Zawra, et al., 2017).
These three technologies; CPS, smart factory and the IoT, go hand-in-hand in Industry 4.0 since IoT needs the CPS, and the smart factory needs booth CPS and IoT technology and vice-versa (Strandhagen, et al., 2017). The strict line between each technology within Industry 4.0 is hard to draw because it is interpreted differently by different persons (Zawra, et al., 2017).
3.1.1 The possibilities of the IoT within the Mechanical Industry
According to Cedeño, et al., (2018), the Industry 4.0 is an emerging digitalization of the industry by utilizing smart devices through IoT as a main component. See figure 3.2 for an illustrative picture of the Industry 4.0. The connection enables the most optimal predictions and actions when getting big data that can be analyzed and thereby give valuable input to the product processes. To concretize IoT further within the industry, the IoT will provide smart meters (1),wear-out sensing (2) and manufacturing control (3) (Lins, et al., 2016; Labib M. Zawra, 2017).
Figure 3.2. Illustrative picture of the Internet of Things (Indo Sateki, 2018).
The smart meters (1) enables two-way communication between the meter and the central system, monitoring it can reduce load, disconnect entirely, and reconnect when needed (Lins, et al., 2016). It can thereby optimize consumption, analyze and alter behavior (Ibid.). For example, the smart meter can measure daily consumption at people’s home, and thus switch off, or reducing electricity when it is not needed (Zawra, et al., 2017).
By remote monitoring, the IoT will enable wear-out sensing (2); thus, involvement with a third-party interaction and thereby enable monitoring and operating the maintenance of factories with new services (Lins, et al., 2016). The big data that will be gathered from the third party will deliver proactive maintenance to it and will be enabled by the system monitoring it (Zawra, et al., 2017). This will lead to a deeper understanding of possible breakdown and failure, which will lead to initiate self-maintenance processes and more precise scheduled production activates (Ibid.).
Regarding the manufacturing control (also called; smart systems) (3) through the IoT technology, it is possible to track deliveries to the machines, and thereby send signals including information about demands to other suppliers before it has happened (Zawra, et al., 2017). It can attach sensors to monitor complete systems as conveyor systems,
e.g., sawmill production, and thereby collect relevant data in order to better work proactive and prevent failures in the system (Ibid.).
3.1.2 The Architecture Behind IoT
Beside the application to the IoT, the function of it can be broken down into three different layers, also is called the ecosystem of the IoT, see figure 3.3 (Rymasewska, et al., 2017; Karacay & Aydin, 2018). Frontend Layer: the end devices, the things that can measure and take in the physical information and make it digital. Connectivity:
propagator codes that can ensure to receive the data from the end devices and transport it through gateways. Backend Layer: the storage, or the integrator functions, which then take in the information - big data - and analyses it and determines a course of action.
Figure 3.3. The ecosystem behind IoT (Karacay & Aydin, 2018).
3.1.3 IoT and the New Value Proposition
As mentioned above, the development of these technologies will increase the amount of available information from the whole supply chain. When getting more valuable information about both the products and its processes, it can be linked to the context of the servitization (Rymasewska, et al., 2017). According to Karacay & Aydin (2018), the value creation that will be triggered by the IoT, will not only create value by all the sensors, or the machine intelligence, IoT are the tools that will give personal, social and economic return. Getting valuable data from the end-customer, the whole value chain and every industry will gradually be disrupted by the IoT technology and will contribute to new applications, hardware, services which will fundamentally change the process of production. By utilizing the big data, thus psychical information by making it digital, the Backend Layer will analyze it and predict trends that will enable companies and governments to make predictions about the market and thereby create more value for businesses and overall world-wide economy (Karacay & Aydin, 2018). Therefore, the value creation from the IoT is not limited to one or two Industries; it enables value
creation for all various application in real life. The value creation that can be created from IoT must be adapted to the specific sector that it will be acting in because it is shaped by the specific dynamics. Within the IoT, it is all about catching the right sort of data in order to deliver value to the right receiver (Rymasewska, et al., 2017).
3.1.4 Barriers of the IoT
Talking about the technological possibilities and the emergence of the IoT technology, this phenomenon however comes with barriers such as privatecy, security and standardization (Karacay & Aydin, 2018). Manyika, et al., (2015) argue that these barriers are slowing down the implementation of IoT in the industry and thus, the possibility to create value for the stakeholders. In order for the IoT to fully reach its potential, some conditions need to be assessed and barriers need to be counteracted (Manyika, et al., 2015). The four most outspoken complex areas that need to be taken into account are the current standards (1) and technologies (2) that are on the market, the (3) security of sharing information with each other, and the private concerns (4) (Karacay
& Aydin, 2018; Manyika, et al., 2015).
The complete standardization (1) of IoT is not yet settled. Due to the new concept, the significant number of different devices and the possibilities of connecting them to each other is still being developed (Karacay & Aydin, 2018). Additionally, manufacturers can deliver complete systems of them, and they are not difficult to connect to each other, so there is not a great need for a comprehensive standardization regarding the devices.
Manyika, et al., (2015) state that the low-cost and the low energy consumption for the sensors are essential for the IoT technology (2) to continue. Further, they states that the technology for the sensors need to continue to be developed. The users of the IoT need to be able to gather the right information from the real world (Ibid.) However, the most important is that the manufacturers of IoT technologies agree about standards regarding the security (3), which they have. The mission is stated to: “secure the IoT, in order to aid its adoption and maximize its benefits.” (Karacay & Aydin, 2018). The privacy (4) of information has always been a huge barrier when it comes to sharing it with each other and the IoT is not an exception (Manyika, et al., 2015). For private persons, it can be related to smart home technologies, for example which have access to the monitor that is connected to the camera. What happens if some information comes into the wrong hands (Karacay & Aydin, 2018). For Business to Business, it is important that the competitors cannot get access to sensitive information if they are sharing the same open platform for instance (Manyika, et al., 2015). The examples are many and the conclusion is that the users of the technology must feel secure regarding who is getting what kind of information, and to get the right guarantees for it.
3.2 Servitization
Servitization is a term coined 30 years ago by Rada & Vandermerwe (1988), who argued that manufacturing companies needed to differentiate themselves from their competitors, in order to increase their customer base. Servitization is a transformation journey in essence where manufacturing companies are developing the capabilities they need in order to supplement their traditional product offering with services (Fitzgerald, et al., 2017). Baines et al., (2009) define servitization as; “Servitization is the innovation of an organization's capabilities and processes to better create mutual value through a shift from selling product to selling PSS”, where PSS stands for product-service system.
However, the concept of servitization can be identified as early as back in the 1960s where the British aero engine manufacturer Bristol Siddeley, which later was acquired by Rolls Royce, provided “power by the hour”, which was a servitization plan for its engines (Smith, 2013). Rolls Royce started to sell power by the hour instead of selling aircraft engines, and today it contracts many of its customers for the same concept (Rolls- Royce, 2017). The idea is that the customer pays for the delivered power from the aero engine while Rolls Royce takes care of everything else including providing of the support and maintenance to ensure the quality of the engine. Also, to make sure that the engines can continue to deliver power in a safe way (Ibid.). This kind of business model includes mutual interests for the stakeholders, meaning that both the clients and the providers are satisfied as long as the engines deliver power. Before Rolls Royce started providing power by the hour, the company made its money on time and materials i.e. in repairing engines (Neely, 2008). The worse the engine were, the more money Rolls Royce made, since more maintenance were required. This was of course not aligned with what the customers and air travelers wanted. Everyone wants reliable products that allow planes to fly safely, and Rolls Royce realized that early and focused on producing engines of high quality. Later, the IoT concept enabled the company to, in real-time, monitor and measure every single aspect of the engines in order to prevent engine failures and breakdowns, and thereby adding more value to its customers (Choudhury & Mortleman, 2018).
Neely (2008) states that a lot of different industries are adapting to this trend, focusing on selling solutions rather than products. In the healthcare industry, many pharmaceutical firms are under pressure due to increased development costs and new competition that arise when a drug is coming off patent. As a consequence, the pharmaceutical companies need to consider changing their business models and start to define themselves as health care solution providers (Neely, 2008). As an example, a patient does not want the drugs that the firms are providing. The patient does not want to get ill in the first place, which means that if someone can provide a solution that reduces the likelihood of illness, the interests between the clients and the providers are more closely aligned.
To make the transformation towards selling services rather than products, traditional manufacturers need to do significant changes. They need to see the product as a platform to deliver the services and they have to build solutions that deliver the values and outcomes their customers are demanding. According to Sawhney (2016), these solutions are often captured in product-service systems which are combinations of products and services. The realized value for the customer within these systems arise when they receive the service.
3.2.1 Contribution to Servitization Literature
Rada & Vandermerwe (1988) were pioneers within the literature field of Servitization.
They based their research on interviews with senior executives at both manufacturing and service companies. In their article, they tried to express the importance of service incorporated in corporate strategy. They showed this with support from their illustrations of the competitive advantages as well as competitive impacts of such change in the companies’ core strategies. Their main argument is that a company should not remain fixed to either a core service or a core product approach to meet their customer’s needs.
They rather argue that the basis for the offering is the customer’s needs, meaning that the offering can include products as well as services. It can also include other elements that normally are not part of the company’s core business activities (Rada &
Vandermerwe, 1988).
Furthermore, Rada & Vandermerwe (1988) argue that “Corporations are increasingly offering full market packages or ‘bundles’ of customer-focussed combinations of goods, services, support, self-service and knowledge. But services are beginning to dominate”.
According to Alvizos & Angelis (2010), there are two points of interests in this quote.
Primarily, it is about that servitization is connected with the bundling process of different components of a market proposition to be able to create a more complete market package.
Secondly, by accepting the dominance of services in this more complete market package, Rada & Vandermerwe (1988) propose that services are different from knowledge, support, goods and self-service. Also, that services seem to dominate the more complete market package creation process, at least in the end of the 80s (Alvizos & Angelis, 2010).
Rada & Vandermerwe (1988) are discussing definitions and no-definitions of services and servitization. They identify the existence of several various definitions of the word services and finally state the view of services as something that are intangible and performed, while goods are produced and tangible. They also state that there are a substantial relationship between products and services, i.e. one of them may be substituted by the other. Examples of this is an electric razor replacing a barber service, an ATM machine replacing a bank clerk, as well as a terminal service substituting a PC (Alvizos & Angelis, 2010). Furthermore, Rada & Vandermerwe (1988) argue that there is “total complementary” between services and products. They also mean that almost all
Vandermerwe, 1988). In order to concretize the services process and the incorporation of services in products, they mention the example of future artificial intelligence (AI).
With the help of AI, firms can be able to anticipate failure and breakdowns, and repair the damage before it escalates and also before the customer knows that anything is wrong (Ibid.).
3.2.2 Value of Servitization
Firms are becoming more aware of the value that servitization of their products brings to them and their customers, thus marketing the capability that their products can deliver (Slack, et al., 2004). With the context of business-to-business (B2B) service provision, Åhlström & Nordin (2006) refer to servitization as an attempt of a manufacturing company that tries to deliver product services through established service supply relationships, in order to strengthen their physical products. As a result, this will differentiate them from their competitors since they are offering services at a higher degree compared to the competition. When looking at a specific company’s goals in the pursuit of becoming servitized, Nordin (2006) includes the offering of full maintenance contracts, business solutions and management of the customers’ operations as key objectives regarding the servitization strategies. At the same time, he considers services as product support, repair, installation, system integration and product-oriented training as secondary services.
When identifying patterns in the buying process of complex services, Lindberg & Nordin (2008) use a broad and disseminated picture of servitization where they believe it to be a trend where companies move from manufacturing products to offering services or integrating services and products to functions and solutions (Lindberg & Nordin, 2008).
Andy Neely (2008) has conducted a study of the financial consequences of servitization within manufacturing companies. He means that manufacturing companies are moving beyond just manufacturing, and instead offer services and solutions not seldom delivered through the goods, or in association with the goods (Neely, 2008). Another possible definition of servitization according to Neely, is mentioned as “the innovation of an organization’s capabilities and processes so that it can better create mutual value through a shift from selling products to selling Product-Service Systems”.
3.2.3 Servitization & Digitalization
Digitalization can be considered as the concept of increased usage of digital technologies in order to connect systems, people, products, services and companies (Hsu & Hsu, 2007). This kind of trend offers a lot of opportunities for companies within the manufacturing industry. Digitalization has the potential to radically improve the industrial companies’ performance and also to increase the companies’ reach and offering (Coreynen, et al., 2015). For the concept of servitization, the use of digitalization and its methods may promote different innovation types. The manufacturers are handling problems regarding the cross-functionality within the company when managing solution-
oriented business. These problems can be viewed from two operational perspectives:
commercial and industrial (Storbacka, 2011). Each perspective can be supported by digital applications by offering additional services through these applications.
Firstly, from the industrial, or back-end perspective, the providers try to effectively improve their ability to create solutions (Storbacka, 2011). The operational performance, especially through automation, will be enhanced by the emerging digital technologies in the companies’ back-end operations. The technologies will also help to increase the transparency to better be able to make decisions, such as resource allocation, grounded on as much information as possible (Coreynen, et al., 2015). The digital methods will change general assumptions regarding cost of manufacturing and will possibly break the trade-off between effectiveness and efficiency which may help companies to reverse offshoring (McKinsey & Company, 2014). This knowledge can be leveraged by the manufacturers to improve their own processes, and also to improve the clients’
processes. This will be done through providing the customers with advice and training services among other things. The next step for the manufacturers is to further integrate into the customer’s process, by taking over production activities and also certain design processes (Tukker, 2004).
Secondly, from the commercial-, or front-end perspective, the customer’s value creating process is in focus, and it is up to the provider to aim to better understand it and help them to reach their goals (Storbacka, 2011). This kind of front-end digitalization opens up for new kinds of customer interaction through for example creation of self-service offerings such as digital personal assistants (Coreynen, et al., 2015). Furthermore, it leads to a deeper understanding of the customer’s preferences, since the possibilities of sharing in-depth information enables (Ibid.). Today, manufacturers are implementing digital methods to improve their back- and front-end operations and also to disrupt the provider-customer relations through creating digitally-enabled offerings (Ibid.). This kind of digitalization can provide both digital and physical offerings. For example, a certain product or machine can be sold, and in addition to this, a complementing software can be provided in order to help the customer to monitor and control the product through an online interface (Porter & Heppelman, 2014). Such kind of combined offerings create opportunities for the manufacturers to provide better services and products to their customers regarding the areas of maintenance, reparation and field operations. Thus, new business opportunities will arise by adding digital products that complement or substitute the traditional physical products (MIT Center for Digital Business and Capgemini Consulting, 2011; Coreynen, et al., 2015).
3.2.4 Servitization Through The IoT Technology
When connecting IoT and Servitization together, it has become known as Smart Service
oriented approach, where the development of the data-driven service by the IoT has a central role of it (Ibid). The role of how a company can deliver value to the customer will be changed by creating an ecosystem where multiple participants from the value chain can act and share information with each other (Ibid.). According to Kagermann, (2015) the core product offerings will be replaced by tailor-made offerings that will include of product, service and support services where the total focus will be on the customer.
Cedeño, et al. (2018) argues that the increased amount of inputs regarding product features, competition, costs, real time monitoring, that will come from IoT, organizations will be able to utilize services that are more product-related. Thereby, changing their offering from solid products to products that have tailor-made product and service- oriented offerings. Furthermore, the information will give valuable input for the product development to optimize the product and the service-oriented offering, also known as Product-Service System. Additionally, the information will enable to be more flexible by the input of the changed demand from the market. Moreover, Cedeño, et al. (2018) state that the information needs from the IoT technology, can be found by analyzing the voice of the customer, and thereby concretize the customer need.
According to Rymasewska, et al., (2017), IoT within the emerging digitalization trend, together with the concept of servitization opens up for a whole new kind of value proposition. However, going into new areas brings both opportunities and challenges, and when going into the servitization area, there is a risk for the service paradox. That is, when the revenues from the service increase, but the profit from it becomes less as a result of having little input about how much service that was needed from the beginning (Ibid.). With the IoT, it comes with the possibility to better predict the service, and the needs for it. Therefore, the risk for service paradox will be lesser when servitization and IoT are combined (Ibid.). Additionally, there are two main challenges when wanting to offer services; the services must be closely related to the customers operation, and; the service should differentiate from competitors and thereby create competitive advantage (Rymasewska, et al., 2017). With the emerging IoT technology, organizations have today the possibility to overcome these challenges (Ibid.).
3.3 Business Models Within Digitalization
A business model describes what value or values a company is offering. The success factors of a company are significantly impacted by the business model. Digitalized products that are using sensors in order to make them connected and smart, are changing the ground pillars of the traditional business models and businesses (Cevik Onar &
Ustundag, 2018). With the emergence of IoT, the growing number of connected and smart things released into the market, change the way of competition. With a service- driven business model, the companies are reshaping the mechanical industry and creating completely new offerings (Porter & Heppelman, 2014). The product capabilities within
the area of smart and connected products can be divided into four different groups (PTC, 2014):
Monitor – The sensors and connectivity of the products enable monitoring of the product’s operation, condition to generate alerts and intelligence.
Control – The hardware combined with software, often based on artificial intelligence, enable to control and personalize on a remotely basis.
Optimize – The monitor and control attribute combined with software algorithms enhance product performance and may enable to perform remote services and repairs.
Automate – A combination of monitor, control and optimization together with sophisticated software algorithms allow the product to perform completely autonomously.
As earlier mentioned, the core business models within the industry are in a transformational phase due to the smart and connected product technologies. They are not only creating new revenue streams, but also cost reduction. The four different types of value propositions regarding smart and connected product businesses are classified as follows (Guo, 2017):
Novelty
IoT applications are enabling companies to create new innovations, services and markets. It is not only the IoT solution that creates new business models. The IoT platform itself can be considered as a new business model. As an example, the Watson IoT platform facilitates manufacturers to establish custom made and personalized robots that are adaptive. Also, AT&T provides cars that are connected. This turns the vehicle into a mobile Wi-Fi hot spot. This allows the users to read news, stream videos, TV- shows and music and a lot more through the network of the car.
Efficiency
The most common asset desired within the IoT business. One primary goal of a customer’s business can for example be to increase the efficiency of its transactions. The efficiency is improved when the transaction is made faster, simpler and by increasing the transparency and dependability. As an example, Intel has developed an IoT vibration sensor embedded in bridges that can track vibration and its patterns and in turn provide data that can be used for maintenance planning. This will also increase the reliability of the constructions. Nest Labs has developed a smart sensor called Nest Thermostat that tracks the user behavior of the household heating. The product is decreasing the heating and cooling costs by adjusting the temperature before the user is coming home and
leaving the house. Furthermore, the product helps the energy companies to forecast the energy demand and optimize the production level.
Lock-in
When a customer has started to use a company’s smart and connected products, it allows the firm to increase transaction volume for existing customers and also increase the loyalty. The customers can be provided with virtual communities and affiliate real-time monitoring programs that enhance the repeat usage, customer retention, customization, transaction safety and reliability. Amazon has a product called Dash Button. This product is Wi-Fi based and it reorders items with just a press of the button, perfect for lean industries that works with Kanban. The buttons are paired with pre-defined items and pushing the button is enough for a re-order. The repeat usage is enabled thanks to this product and the customer is locked with buying Amazon’s items.
Complementary
An IoT business model that is based on complementary ideas, is providing additional services and products that provides more value together, as a package. Amazon has a product based on a replenishment service, which enables reordering of ink cartridges or toners for printers and laundry detergent for washing machines. The integrated replenishment services execute orders automatically before the last load is consumed.
The complementing element in this case is that the user has to utilize Amazon’s customer service system including its payment and authentication systems.
3.4 Business Models Within Servitization
When considering changing the approach to a more service-oriented approach as PSS, an organization needs to consider which kind of service strategy that suits them the best (Cedeño, et al., 2018). According to Örtqvist, et al., (2014) there are three main approaches, or business models, when want to apply a service strategy. It can either be;
product-oriented (1), use-oriented (2) or result-oriented (3), see figure 3.4.
Figure 3.4. The different value creations for the three business models (Örtqvist, et al., 2014).
In the product-oriented (1) strategy, the offering is based on supplying the physical product with complementing service as maintenance, installation or support (Örtqvist, et al., 2014). While it uses the product as the foundation of the value creation, but the
service can be more or less executed from the customer itself (Ibid.). The use-oriented (2) is when the offering is using leasing as a financial incentive for the customer and thereby can rent the usage of the physical product and service (Ibid.). The result-oriented (3) is when the provider is responsible for the result of the product, and thus the costs for the product that is based on what the product can deliver for the customer (Ibid.). The offering is therefore not any physical product or service, instead it can include these two in the offering by providing result to the customer (Ibid.).
3.5 Business Model Canvas
The business model canvas was first proposed by Alexander Osterwalder in 2008. The model enables both existing and new actors to focus on strategic and operational management and marketing plans in order to develop their businesses (Osterwalder, et al., 2010). The business model canvas consists of nine basic elements of a business model which are; partners, activities, value propositions, customer relationships, customer segments, resources, channels, costs and revenue streams. Instead of just mentioning the elements, one and one, they are put on a canvas to provide simplicity and visualization of the different issues’ relation (Ching & Fauvel, 2013). That helps the strategist to map, design, discuss and invent new types of business model and business strategies. The model can preferably be divided in the market on the right side, and the product on the left, see figure 3.5. The value proposition element is divided in half since it contains all the products and services that create value for the customer (Ibid.).
