How to adapt and implement

Internet of Things - A case study of how Tieto is working with IOT in

the context of digitalization

DENISE THUNSTRÖM

Master of Science Thesis Stockholm, Sweden 2016

Hur företag anpassar sig och

implementerar Sakernas Internet

- En fallstudie av hur Tieto arbetar med Sakernas Internet i samband med digitaliseringen

DENISE THUNSTRÖM

Examensarbete Stockholm, Sverige 2016

How to adapt and implement

Internet of Things

- A case study of how Tieto is working with Internet of Things in the

context of digitalization

DENISE THUNSTRÖM

Master of Science Thesis INDEK 2016:50

KTH Industrial Engineering and Management

Industrial Management

SE-100 44 STOCKHOLM

Hur företag anpassar sig och implementerar Sakernas Internet

- En fallstudie av hur Tieto arbetar med Sakernas Internet i samband med digitaliseringen

DENISE THUNSTRÖM

Examensarbete INDEK 2016:50

KTH Industriell teknik och management

Industriell ekonomi och organisation

SE-100 44 STOCKHOLM

9

Abstract As if today’s society, globalization, digitalization and labor mobility is daily increasing, and individuals are, in one way or another, constantly surrounded by Internet. Technical change, in general, is one of the fundamental engines of economic growth and structural transformation in modern societies. Internet has long been seen as the most disruptive technology of our time, but now new technologies are entering the market, including the concept around Internet of Things (IOT).

New dynamics is being put on the market, and companies are forced to re-think their way of working with innovation. The market for IOT is developing, rapidly, which creates a huge pressure on companies to maintain innovative and relevant in the market. Companies are willing to invest, but due to challenges and questions marks, they end up doing nothing.

The overall purpose of this thesis was to investigate how IT consulting companies can implement and apply the concept of Internet of Things (IOT), and what type of challenges they were facing. In order to achieve this purpose, this study was empirically grounded in a case study at the Finnish-Swedish IT Consultancy Company, Tieto, at division Telecom and Media located in Stockholm, Sweden. The division is partly responsible the internal research on the topic of IOT, and has as a goal of increasing profitability regarding the use of this disruptive technology.

The results indicate that Tieto, as well as other companies, are investigating in the ecosystems of IOT. Companies are also starting to realize the use of partnerships, and that they might be required to join under one, if they want to provide an end-to-end IOT solution. However, the results also indicate that there are several challenges in the progress when adapting and implementing IOT. Some of these challenges were found to be: maturity in the market is slowing down the process; complexities in the partnerships; complexities in the IOT service; the demand of forming new operational models; and the realization of that one cannot be everywhere. Nevertheless, the IOT solutions generate enormous complexitivities, both in the technical aspects and the partner related aspect.

The findings of this study have implication on that even though the market is facing many challenges, the future for IOT is looking promising, and IOT is predicted to contribute with tremendous growth within all industry segments.

Key-words: Internet of Things; IOT; digitalization; ecosystems; challenges; pricing models.

Master of Science Thesis INDEK 2016:50

How to adapt and implement Internet of Things

- A case study of how Tieto is working with Internet of Things in the context of digitalization

Denise Thunström

Approved

2016-06-16

Examiner

Niklas Arvidsson

Supervisor

Vicky Long

Commissioner

Tieto

Contact person

Dick Allansson

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Sammanfattning I dagen samhälle, sker ökning inom globalisering, digitaliseringen och rörlighet i det dagliga arbetet. Individer är, på ett eller annat sätt, ständigt omgivna av Internet. Teknisk förändring, i allmänhet, är en av de grundläggande drivkrafterna för ekonomisk tillväxt och strukturomvandling i det moderna samhället. Internet har länge setts som den mest revolutionerande teknik i vår tid, men nu etablerar sig nya tekniker på marknaden, bland annat konceptet kring Sakernas Internet.

Ny dynamik läggs ut på marknaden, och företagen tvingas ompröva sitt sätt att arbeta med innovation. Marknaden för Sakernas Internet utvecklas snabbt, vilket skapar en enorm press på företag bibehålla innovation, för relevans på marknaden. Företag vill investera, men på grund av aspekter och frågetecken, slutar med att de gör ingenting.

Det övergripande syftet med denna studie var att undersöka hur IT-konsultbolag anpassade och tillämpade sig till konceptet kring Sakernas Internet (IOT), och vilken typ av utmaningar de stod inför. För att uppnå detta syfte, var denna studie empiriskt grundad på i en fallstudie vid den finsk -svenska IT-konsultföretaget Tieto, vid division Telecom och Media i Stockholm, Sverige. Divisionen är delvis ansvariga interna forskning i ämnet av IOT, och har som mål att öka lönsamheten när det gäller användningen av denna revolutionerande teknik.

Resultaten tyder på att Tieto, liksom andra företag, undersöker i ekosystemen kring i IOT. Företagen börjar också inse användningen av partnerskap, och att de skulle kunna verkställas för att det ska kunna erbjuda en end-to-end IOT tjänst. Men resultatet tyder också på att det finns flera utmaningar i utvecklingen när anpassning och genomförande av IOT. Några av dessa utmaningar befanns vara: mognad på marknaden saktar ner processen; komplexiteten i partnerskap; komplexiteten i IOT lösningar; efterfrågan att bilda nya organisationsmodeller; och förverkligandet av att man inte kan vara överallt. Sammanfattningsvis kan man säga att IOT lösningar genererar enorma komplexitiviteter, både i de tekniska aspekterna samt i dem partner relaterade aspekterna.

Resultaten från denna studie har återverkningar på att även om marknaden står inför många utmaningar, så ser framtiden för IOT ser lovande ut, och IOT förväntas bidra med en enorm tillväxt inom alla industrisegment.

Nyckelord: Sakernas Internet; IOT; digitalisering; ekosystem; utmaningar; prissättningsmodeller.

Examensarbete INDEK 2016:50

Hur företag anpassar sig och implementerar Sakernas Internet

- En fallstudie av hur Tieto arbetar med Sakernas Internet i samband med digitaliseringen

Denise Thunström

Godkänt

2016-06-16

Examinator

Niklas Arvidsson

Handledare

Vicky Long

Uppdragsgivare

Tieto

Kontaktperson

Dick Allansson

12

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Foreword and Acknowledgements

This master thesis report is written at the department of Industrial Engineering and Management at KTH, the Royal Institute of Technology, in Stockholm/Sweden, and has been carried out during the period of January 2016 to May 2016.

I would like to thank my supervisor at Tieto, Dick Allansson, for the great support and providing me the opportunity to perform my master thesis at Tieto. During the project, several interviews have been performed, both inside the organization of Tieto, but also with other stakeholders.

I would also like to thanks Sandra Lindman, Partner Manager at TeliaSonera , together with her colleagues that took their time to participate and share their view to the study. I would also like to thank Karin Edström, CEO at Evothings, for sharing her experiences.

I would also like to thank Henrik Blomgren, lecturer at KTH, for sharing his options and challenging me to think broader.

I also would like to thank my supervisor at KTH, Vicky Long, PhD Researcher at the Department of Industrial Engineering and Management, for her advice, support and guidance during the project.

Lastly but not least, I would like to thank all of those who have been interviewed for showing a great commitment, being helpful and for sharing information with me.

A sincere gratitude to all the people involved in the work of my master thesis!

Denise Thunström

Stockholm, June, 2016

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“The Internet of Things has the potential to change the world, just as the Internet did. Maybe even more so.” - Kevin Ashton (2010), who like enough coined the term ‘the Internet of Things’

“A collaborative approach has [a] tremendous opportunity to free up resources and capacity for stretched service providers.” - Don Tapscott (1995), has leading authorities on innovation, media, and the

economic and social impact of technology

“Companies don’t change because they want to. They change because they are forced to by customers, by competition, by advances in science and technology, and by government regulation” -

Vijay Govindarajan (2011), is the author of The Three Box Solution: A Strategy for Leading Innovation

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ABBREVIATIONS AND GLOSSARY OF TERMS

This page presents abbreviations and terms that are used in this thesis.

Abbreviations

B2B Business-to-Business B2C Business-to-Customer IOE Internet of Everything IOT Internet of Things KPI Key Performance Indicator M2M Machine-to-Machine M2P Machine-to-People R&D Research & Development P2M People-to-Machine P2P People-to-People ICT Information and Communications Technology NFC Near Field Communications SLA Service Level Agreement Wi-Fi Wireless Local Area Network WSAN Wireless Sensor and Actuator Networks WISPs Wireless Identification and Sensing Platforms

Glossary of Terms

3G Third-generation mobile telecommunication, providing mobile phone services with transfer rates of up to 2 MB/s for stationary systems and 384 kB/s for mobile systems.

4G Fourth-generation mobile services, providing mobile phone services with transfer rates of up to 1 GB/s for stationary systems and 100 MB/s for mobile systems.

5G Fifth-generation mobile telecommunication. Have not been defined, hence standards will be beyond the 4G.

Cloud Service a.k.a. Cloud Computing, is a kind of Internet-based computing that provides shared processing resources and data to computers and other devices on demand.

RFID Radio-Frequency Identification, uses electromagnetic fields to automatically identify and track tags attached to objects. E.g. opening a door with use of electronically stored information.

ecosystem a.k.a. digital ecosystem, is a combination of all relevant digital touch points, the people that interact with them, and the business processes and technology environment that support both.

proof-of-concept is a realization of a certain method or idea to demonstrate its feasibility.

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TABLE OF CONTENTS

1 INTRODUCTION ......................................................................................................................22

1.1 Background.............................................................................................................................. 22

1.2 Problematization...................................................................................................................... 23

1.3 Purpose .................................................................................................................................... 24

1.4 Research Questions ................................................................................................................ 24

1.5 Expected Contribution ............................................................................................................ 24

1.6 Delimita tions and Limitations ................................................................................................. 25

1.7 Disposition............................................................................................................................... 25

2 INTRODUCTION TO THE INTERNET OF THINGS.........................................................27

2.1 The history of Internet of Things ............................................................................................ 27

2.2 The Interne t of Things: A practical description ..................................................................... 28

2.2.1. Internet of Everything ............................................................................................................ 29

2.2.2. The ecosystem of the Internet of Things: A practical descript ion ............................................ 30

2.2.3. The value chain of IOT: Convert ing data into business ........................................................... 32

2.3 Concluding remarks ................................................................................................................ 33

3 THEORETICAL AND INDUSTRIAL REVIEW ...................................................................34

3.1 Theore tical review ................................................................................................................... 34

3.1.1. Diffusion of Innovations ......................................................................................................... 34

3.1.2. Digital t ransformat ion maturity ............................................................................................... 35

3.1.3. Closed innovation vs. Open innovation .................................................................................. 36

3.1.4. Summation of the theoretical review ...................................................................................... 36

3.2 Industrial review ...................................................................................................................... 36

3.2.1. Digital t ransformat ion maturity ............................................................................................... 37

3.2.2. Business models with relevance for IOT ................................................................................ 38

3.2.3. Summation of the industrial review ........................................................................................ 40

4 METHOD ....................................................................................................................................41

4.1 Research design ...................................................................................................................... 41

4.2 Research approach.................................................................................................................. 42

4.2.1. Case study ............................................................................................................................ 42

4.2.2. Data collection ....................................................................................................................... 43

4.2.3. Interviews .............................................................................................................................. 43

4.2.4. Data analysis ......................................................................................................................... 44

4.2.5. Theoretical review ................................................................................................................. 44

4.3 Reliability and validity ............................................................................................................. 45

4.3.1. Interviews .............................................................................................................................. 45

5 EMPIRICAL SETTING ............................................................................................................46

5.1 Introduction to the case company: Tieto Sweden AB............................................................ 46

5.1.1. Tieto’s Industrial Internet ....................................................................................................... 46

5.1.2. The IOT offerings at Tieto ...................................................................................................... 47

5.2 Introduction to the benchmark companies............................................................................. 48

5.2.1. TeliaSonera ........................................................................................................................... 48

5.2.2. Huawei Technologies ............................................................................................................ 49

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5.2.3. Evothings .............................................................................................................................. 49

6 EMPIRICAL RESULTS...........................................................................................................50

6.1 Introduction to empirical results ............................................................................................ 50

6.2 Focus areas of investiga tion................................................................................................... 50

6.2.1. The ecosystems of the IOT .................................................................................................... 50

6.2.2. Partnership poss ibilities ......................................................................................................... 52

6.2.3. Approaching industries for the IOT......................................................................................... 53

6.3 Main challenges when implementing IOT ............................................................................... 54

6.3.1. The market maturity ............................................................................................................... 54

6.3.2. The partner complex ity .......................................................................................................... 55

6.3.3. The IOT service complex ity ................................................................................................... 56

6.3.4. Internal changes in the ongoing organization ......................................................................... 57

6.3.5. The realization of that one cannot be everywhere .................................................................. 58

6.4 Concluding remarks ................................................................................................................ 59

6.4.1. Main insights ......................................................................................................................... 59

7 ANALYSIS AND DISCUSSION ............................................................................................61

7.1 Introduction to analysis and discussion ................................................................................ 61

7.2 Focus areas of investiga tion................................................................................................... 61

7.2.1. The ecosystem of IOT ........................................................................................................... 61

7.2.2. Partnership poss ibilities ......................................................................................................... 62

7.2.3. Approaching industries for the IOT......................................................................................... 62

7.3 Main challenges when implementing IOT ............................................................................... 63

7.3.1. The market maturity ............................................................................................................... 63

7.3.2. The partner complex ity .......................................................................................................... 64

7.3.3. The IOT service complex ity ................................................................................................... 65

7.3.4. Internal changes in the bus iness models................................................................................ 65

7.3.5. The realization of that one cannot be everywhere .................................................................. 67

7.4 Concluding remarks ................................................................................................................ 67

7.4.1. Main insights ......................................................................................................................... 68

8 CONCLUSIONS AND FUTURE WORK .............................................................................70

8.1 Research questions................................................................................................................. 70

8.1.1. Research Question 1 ............................................................................................................. 70

8.1.2. Research Question 2 ............................................................................................................. 70

8.1.3. Research Question 3 ............................................................................................................. 71

8.1.4. Main research question ......................................................................................................... 71

8.2 Implica tions and concluding remarks .................................................................................... 72

8.2.1. Industrial implications ............................................................................................................ 72

8.2.2. Research implications ............................................................................................................ 73

8.2.3. Sustainability implications ...................................................................................................... 74

8.3 Future work .............................................................................................................................. 74

9 REFERENSES ..........................................................................................................................75

10 APPENDIX.................................................................................................................................79

Appendix 1: Interviewees .................................................................................................................... 79

Appendix 2: Interview questions ........................................................................................................ 80

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TABLE OF FIGURES

Figure 1. The system perspectives (Blomkvist & Hallin, 2015) ............................................................... 25

Figure 2. The technical overview of the Internet of Things (ITU, 2012) .................................................. 28

Figure 3. The ecosystem of Internet of Everything (Cisco, 2013) ........................................................... 29

Figure 4. Internet of Things Ecosystem (IDC, 2014) .............................................................................. 31

Figure 5. The simplified value chain of data (Capgemini, 2015) ............................................................. 32

Figure 6. A simplified version of the IOT’s ecosystem ............................................................................ 33

Figure 7. Diffusion of innovation curve (Rogers, 1962) .......................................................................... 34

Figure 8. A representation of the five stages of the TDWI Maturity Model (TDWI, 2012) ........................ 35

Figure 9. Business Intelligence Maturity Phases (TDWI, 2012) .............................................................. 35

Figure 10. The Closed Innovation Paradigm, to the left (Chesbrough, 2006) ......................................... 36

Figure 11. The Open Innovation Paradigm, to the right (Chesbrough, 2006) .......................................... 36

Figure 12. “The Hype Cycle” (Gartner, 2014) ........................................................................................ 37

Figure 13. The IDC's Digital Transformation Maturity Scape (IDC, 2015) ............................................... 38

Figure 14. The thesis and the interest of the company .......................................................................... 41

Figure 15. A simplified vers ion of Tieto’s organization ........................................................................... 46

Figure 16. “M2M-in-a-Box” .................................................................................................................... 47

Figure 17. The disposition of the empirical results chapter .................................................................... 50

Figure 18. The ecosystem of IOT at Tieto Industrial Internet ................................................................. 51

Figure 19. Key roles in the IOT eco-system at TeliaSonera (TeliaSonera, 2016) .................................. 52

Figure 20. TeliaSonera IOT Partner Program ........................................................................................ 53

Figure 21. Estimation on how each company is working with IOT .......................................................... 60

Figure 22. The disposition of the analysis and discussion chapter ......................................................... 61

Figure 23. Market potential divided by industry segment (IDC, 2014) .................................................... 62

Figure 24. The IDC’s Digital Transformation Maturity Scape Forecast 2015 (IDC, 2015) ....................... 63

Figure 25. The Hype Cyc le for the Internet of Things in year 2015 (Gartner, 2014) ................................ 64

Figure 26. A simplified description of estimating future demand on present data (Kavis, 2016) .............. 66

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TABLE OF TABLES

Table 1. The key differences between Ownership Economy and Membership Economy (Baxter, 2015) . 39

Table 2. Interviewees conducted, organized by company ...................................................................... 43

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1 INTRODUCTION

In the following chapter, the general introduction will be presented. This includes background of the research, problem formulation, purpose and research questions. At the end of the chapter, delimitations and contribution to the research will be presented.

1.1 Background The digital transformation, as some might call it, has long been fascinating the human kind, and for over decade’s professors and journalist has been analyzing the ongoing situation. But looking back at the history of IT, one cannot overlook the information technology bubble, also referred to as the ‘dot-com bubble’.

This started in the late 90s and ended in the beginning of 2000, when the so called bubble reached its climax. Technology promoters asserted that, anyone who would not buy into new technology would be left behind. This triggered the capital spending boom, and lead to that companies started overinvesting in IT. Stock markets within the industry rapidly rose, and dot-coms companies were introduced to the market. Just by adding an “e-” prefix or a “.com” to the company name, many companies managed to increase their stock price. It was also during this time, which Internet gained steady commercial growth.

Meanwhile, Don Tapscott (1995) argued in his book “The Digital Economy”, that the Internet would have a considerable impact on corporations, government, and the overall society. Numerous things triggered the dot-com bubble, but it was probably a combination of rapidly increasing stock prices, companies relying on future profits, and an environment where venture capital was widely available, that gave the market its confidence. The confidence in technological advancements gained such trust that many investors were willing to overlook traditional metrics.

The term “big data” were coined during the information technology bubble in the 2000s. However, there is no rigorous definition of big data. Engineers needed to revamp the tools they used, since the volume of information has grown so big that the quantity being investigated, no longer fit into the memory of the computers used for processing data. In 2005, Internet was becoming known for its important to society and the economics. Just as Tapscott (1995) predicted, it was recognized for its power to change economics, social and cultural systems, both on national level and global level (Byung-Keun, 2005).

As if today, globalization, digitalization and labor mobility is daily increasing, and individuals are, in one way or another, constantly surrounded by Internet. In 2015, it was reported that there were 3.2 billion Internet users, corresponding to 400 million Internet users in 2000 (ITU, 2015). This means that, Internet has changed the way we do business, the way we work, the way we learn, the way we interacts (Tapscott, 2016; Mayer-Schönberger & Cukier, 2013). Just to take an example. What did you do 20 years ago, when you were looking for an answer to a question? Probably ask an older person. What do you do today? Probably search the Internet.

Internet has made it possible to transfer knowledge in way, human kind never thought it were possible. The society is transformed itself into an information society, and the substances of the information society are easy to see. Just imagine a cellphone in every pocket, a computer in every backpack and a large information technology system in each company. Not only is the societies filed with more information than ever before, the information is growing faster than ever before. Right from waking up in the morning, until going to bed at night, persons are now constantly surrounded by things, with information (Mayer-Schönberger & Cukier, 2013). Of course, this amount of data

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comes with countless questions to be answered. But instead of seeing the negative side of it, companies are now investigating how such information can be of great us for them. What kinds of possibilities does this bring to their company? How can it be used in beneficial way? What if we were to connect things to each other, in order to exchange information, what would then happen?

Internet has long been seen as the most disruptive technology of our time (Ashton, 2010; Bajarin, 2015), but now new technologies are entering the market, including the concept of Internet of Things (IOT). The base perception of IOT is enabling things or objects with connectivity. This is be done by providing things with e.g. RFID1-tags (Radio-Frequency Identification tags), sensors, actuators, mobile phones, etc. These microprocessors electronics can later on gather information and perceive their environment, communicate and report on their status, create a situational behavior and help to create smart and attractive services. This means that machinery, vehicles, goods, household appliances, clothes and other things, can be provided with small built -in sensors and computers, enabling new a numerous of advanced services and applications being introduced to the market (Santucci, 2009).

The possibilities of IOT have been well discussed and enlarged. Some even say that that the technology behind IOT has the opportunity to play an important role in solving many of the big social challenges in the increasing urbanization (Vinnova, 2015). In any case, IOT has an important part of the digitalization of our society and our economy, and eventually the entire world will have access through a variety of smart IOT solutions and services (Santucci, 2009).

1.2 Problematization In the 1990s, there were 1 billion PC users connected via the fixed Internet, and 2 billion smartphones users connected via mobile Internet (ITU, 2015). Since then, computers and sensors have been made available for a much lower price, and it is actually getting cheaper and cheaper to connect things to Internet. This means that connectivity is becoming affordable, and sooner rather than later the whole population of the world will have access to Internet.

The number of world Internet users has grown 20-fold in the past decade, leading the number of Internet users approaching about 1.5 billion in 2008. Corresponding to the numbers of computer servers rising from 22.5 million to 489 million (ITU, 2015). According to several forecasts, nearly 26 billion devises within the IOT technology, will be connected by 2020 (ABI Research, 2013; MIT Technology Review, 2014; Gartner, 2013). EU outlines a multi-billion project on IOT (Vinnova, 2015) and a report published in MIT Technology Review (2014) says that “the number of everyday objects, connecting to Internet will exceed PC’s and smartphones by 2020”.

This leads to two main conclusions: the Internet architecture is going to face increasingly complex challenges; and the Internet will continue to go through many transformations (Santucci, 2009). The IOT is seen as the novel paradigm of this decade, and is especially gaining force in the scenario of modern wireless telecommunications (Atzori, et al., 2010). The market for IOT is developing, rapidly, which creates a huge pressure on companies to maintain innovative and relevant in the market.

Many companies understand this, and see that the change is in the horizon. They recognize that they have to act now, to be able to stay market leading and relevant to the market. Leading companies have to ask themselves, how they can develop their processes in able to cherish from IOT. However, the main problem is that they do not know how they should proceed; many IT consulting companies are missing knowledge of applying the concept. There are uncertainties, between the situation today and the forecasts of IOT. How does a company actually adapt and implement a new, likely, complex technology like IOT? Nevertheless, the IOT solutions generates enormous

1 Radio-Frequency Identification, uses electromagnetic fields to automatically identify and track tags attached to

objects. E.g. opening a door with use of electronically stored information.

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complexitivities, therefore it is of interests to investigate in the many challenges that comes with the IOT services, which is the objective for the research.

The future for IOT is looking promising, and the topic shows a great potential for further research. But the dynamics of the complex IOT solution puts up many dilemmas, e.g. security issues, pricing models, support solutions and much more. E.g. no company what to be responsible for lacking sensitive intonation due to an internet attack. Also, companies are not willing to invest in IOT solution unless they are sure that there are great possibilities in the investment. Therefore, knowledge on approaching industries and pricing models are desired.

Technical change, in general, is one of the fundamental engines of economic growth and structural transformation in modern societies (Dosi, 1984). Companies want to invest, but due of these aspects and questions marks, they end up there doing nothing. It is therefore a huge opportunity to look at this area from an academic view and investigate how it can help companies, organizations, and even societies. This provides the study with a strong argument for further research, and a clear goal for further investigation in this matter.

1.3 Purpose Against this background, the overall purpose of this thesis is to investigate how companies, within the IT consulting industry, adapt and implement Internet of Things, and what type of challenges they are facing.

Therefore, the study aims to provide a better understanding of what IT consulting companies are investigating in when implementing and adopting to IOT, as well as deepen the knowledge about external requirements.

The study also aims to deepen the knowledge on how to adapt to these requirements and suggest a way of how to generate value through the concept. The objective with the investigation is to provide the reader with an understanding of how IOT can be implemented and applied for IT consulting companies and the effects of applying the concept.

In order to achieve this purpose, this study is empirically grounded in a in a case study at the Finnish-Swedish IT consultancy company, Tieto, at division Telecom and Media located in Stockholm, Sweden. The division is partly responsible the internal research on the topic of IOT, and has as a goal of increasing profitability regarding the use of this disruptive technology.

1.4 Research Questions In order to achieve the purpose of this study and the intended investigation, the following main research question has been formulated:

How do companies, within the IT consulting industry, adapt and implement Internet of Things?

In order to answer the main question a subset of questions will be answered:

What are the main aspects that companies, within the IT consulting industry, are investigating, when it comes to IOT?

How have companies, within the IT consulting industry, changed their way of working, when it comes to IOT?

What are the main challenges in the process, when adapting and implementing IOT?

1.5 Expected Contribution The problem can be approached according to three perspectives: the individual and organizational level; the functional level; and the industrial level, also referred to as the system perspectives (Blomkvist & Hallin, 2015). See Figure 1. This means that the problem can be approached from several different

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viewpoints, and therefore provide different contribution. The individual and organizational level focused on seeing the problem from the perspective of management and co-workers. The functional level focused on seeing the problem from a process and production perspective. And lastly, the industrial level sees the problem from a wider industry perspective (Blomkvist & Hallin, 2015).

The study aims to provide further research at an individual and organizational level and at a functional level. This means that the study aims to provide use for manages and co-workers, especially at the case company, but also for other IT consulting companies working with IOT. The study also aims to contribute with a deeper understanding for how the concept can be utilized. Something that today is lacking.

Also, provide further research for at a functional level means that the study aim to provide deeper understanding for the process, when adapting and implementing IOT. The study aims to clarify many of the confusions in the progress and aims to provide guidance with in the area. This is directly connected to the main question of the study, and from initial investigation, further knowledge within this matter is highly appreciated.

1.6 Delimitations and Limitations For this study, the investigation is delimited to studying the phenomenon at an individual and organizational level and at a functional level (Blomkvist & Hallin, 2015); see previous section for a clarification of the terms. This delimitations means that, even though the industry perspective will be discussed, the study does not aim to solve specific industry related issues.

Furthermore, the study has been delimitated to investigate the Business-to-Business (B2B) perspective. This delimiting has been done, since the case company’s client or customer is other companies, and not the consumer. Therefore, the Business-to-Customer (B2B) perspective will not be investigated.

Another limitation that most probably will affect the investigation is the timeframe. This brings limitations in many areas. On examples on this, is the fact that the case company is located in several cities in Sweden, with main office is located in Finland.

Due to this limitation, a delimitation will be to only investigate the case company in Stockholm, Sweden, as well as the organization at selected benchmark companies. Optionally this might be lead to that the study will not be able to present the full situation of the case company. This since empirical data only can be collect under a specific timeframe, and the strategic decision will be to focus on Stockholm.

Nevertheless, accessing information within the case company might also be a limitation. This is partly since the information might be widely spread, and difficulties in finding the right information or informant may occur. But also since due to confidentiality reasons, meaning that sensitive information or information that can be used for competitive advantage, may not be shared. The result of this might lead to that the study will gain a narrowed perspective.

1.7 Disposition The introductory chapter has presented the research together with its purpose and scope, the research questions and the delimitations and limitations. The rest of the report will first cover the theory behind IOT, a theoretical and industrial review and frameworks used as foundations for the study. The following chapters describe the methods used for addressing the research questions, and

Industrial lev el

Functional lev el

Indiv idual and Organizational

lev el

Figure 1. The system perspectives (Blomkvist & Hallin, 2015)

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the results and analysis of the empirical research. The results and analysis are thereafter discussed, and the concluding chapter presents the key findings, conclusions drawn during the research process, and recommendations on future work.

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2 INTRODUCTION TO THE INTERNET OF THINGS This chapter gives an introduction to the concept of Internet of Things, including its history, how is may be used and categorized, as well as highlights components that is important to consider. The purpose with this chapter is to give the reader an understanding of Internet of Things, what it is and how it can be useful for an organization.

The base perception of Internet of Things (IOT) is enabling things or objects with connectivity. This is be done by providing things with e.g. RFID-tags, sensors, actuators, mobile phones, etc. These microprocessors electronics can later on gather information and perceive their environment, communicate and report on their status, create a situational behavior and help to create smart and attractive services (Santucci, 2009).

2.1 The history of Internet of Things The term “Internet of Things” is said to be first coined by Kevin Ashton, who used it in a presentation at the Procter & Gamble Company, in the spring of 1998 (Ashton, 2010). However, one might argue that the history of IOT started much sooner then so. Since that very foundation of the term, IOT has been a vision of everyday items. Over a time or period, the term “Internet of Things” was recognized and found it use at the research center Massachusetts Institute of Technology (MIT). In November 2005, the International Telecommunication Union (ITU) published their report on the Internet of Things (Santucci, 2009), and 16 months later the European Commission adopted a Communication on RFID (Commission Communication, 2007), which trigged a thorough reflection process.

During 2008, many developers and visionary persons recognized the use of IOT, this lead to further investigation within the area. These events have been essential for IOT, both to verify its continued development but also to gain its official recognition ion the market. Some of the most interesting event throughout the history has been summaries in the following list:

• 1974: ATMs went online (Intel, 2016)

• 1949: The bar code is conceived by Norman Joseph Woodland, a IBM engineer (Forbes,

2014)

• 1994: Steve Mann develops a wearable wireless webcam, considered the first example of life logging (Forbes, 2014).

• 1999: The Auto-ID (for Automatic Identification) Center is established at MIT, and researcher such as Sanjay Sarma, David Brock and Kevin Ashton manage to turn RFID into a networking technology, and thereby linking objects to the Internet through the RFID tags (Forbes, 2014).

• 11 October, 2006: NASA Research Park founds the Machine-to-Machine Intelligence (M2Mi) Corporation, with the aim to provide an essential platform for the M2M and Internet of Things economy (NASA, 2006).

• 5 April, 2008: Vinton Cerf, one of the founders of the Internet, declared that “… billions of Internet enabled devices with communication capabilities would emerge in the Internet of Things.”

• 16 September, 2008: The IP for Smart Objects (IPSO) Alliance is founded by Cisco, Atmel, the Swedish Institute of Computer Science (SICS) and other leading technology vendors.

• 25 September, 2008: Vinton Cerf declared that “the Internet of the future will be suffused with software, information, data archives, and populated with devices, appliances, and people who are interacting with and through this rich fabric”.

• 27 November, 2008: The Council of the European Union, in its conclusions on Future

Networks and the Internet acknowledges and endorses the work of the European Commission (Santucci, 2009)

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• November 2008: The U.S. National Intelligence Council, has in their Report on global Trend 2025 has identified the Internet of Things as one of six Disruptive Technologies that may have an invaluable impact on U.S. national power, i.e. economic development and military capability.

• Late 2008: TIME magazine announced Internet of Things is as one of 50 Best Inventions of 2008 (TIME , 2008)

• 22th of June, 2009: Kevin Ashton writes an article in RFID Journal, stating that he probably coined the term “The Internet of Things”.

The history differs depending on where one draws the line. Today, the term “Internet of Things” is recognized by governments, academia and the global industry (Santucci, 2009), and since the start, the concept has made extraordinary progress (Atzori, et al., 2010).

2.2 The Internet of Things: A practical description Looking at a more theoretical picture, one can say that things are objects of the physical world, and information is capable of being identified and integrated into communication networks. All things have associated information, which can be both static and dynamic. Physical things are capable of being sensed, actuated and connected, while virtual things are things capable of being stored, processes and accessed (Holler, et al., 2014; ITU, 2012). See Figure 2 below.

This means that devices communicate with other devices. This in normally done via a communication network via a gateway (case a in the figure), via communication network without a gateway (case b in the figure) or directly, that is without using the communication network (case c in the figure). The IOT services include numerous kinds of applications (ITU, 2012), e.g. “connected car”, “smart homes”, “smart building”, “e-health” etc.

Figure 2. The technical overview of the Internet of Things (ITU, 2012)

The applications can be based on proprietary application platforms, but can also be built upon common service/application support platform(s) providing generic enabling capabilities, such as authentication, device management, charging and accounting (Holler, et al., 2014; ITU, 2012).

The simplified way of doing this is connect one machine to another and let them exchange information. This is already integrated and can be seen all across the manufacturing industry, and is the technology many refer to as Machine-to-Machine or M2M (ITU, 2012). When objects can both sense the environment and communicate, they become tools for understanding complexity and responding to it swiftly (Chui, et al., 2010).

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To get a broader understanding, the theory and definition of Internet of Everything, will be described in the following section.

2.2.1. Internet of Everything

Internet of Everything (IOE) brings together: people, process, data, and things, through networked connection. IOT is a single technology conversion, while IoE comprises many technology conversions, including IOT. The main different between IOT and IOE is that IoE connect everything, while IOT connect things. Since IOE combines everything, the future connections will likely include People-to-People (P2P), Machine-to-People (M2P), and Machine-to-Machine (M2M).

The vision about IOE is to “connects the unconnected”. But still, it is estimated that 99.4 % of physical items that may one day be part of the IOE are still unconnected (Cisco, 2013). To get a clear understanding of Internet of Everything, and how it is connected to other known technologies Figure 3 has been provided. In the following sub-sections the technologies Internet of Everything (IOE), People-to-people (P2P); Machine-to-machine (M2M); and People-to-machine (P2M), will briefly be described.

Figure 3. The ecosystem of Internet of Everything (Cisco, 2013)

People-to-people, P2P – This service and application is about connecting people in more relevant, valuable ways. The service involves video collaboration; mobile plant-floor collaboration; connected learning. These services lead to that innovation can be done faster. Cost within companies can also be lowered, as well as increasing the employee productivity (Cisco, 2013). For e.g. co-workers can have a video conference instead of travelling, which saves travelling costs.

Machine-to-machine, M2M – Machine to machine is the direct communication between devices using a communication channel. This is most common in industrial environments where the data received and sent is very structural. The M2M concept includes industrial instrumentation, e.g. enabling a sensor or meter to communicate the data it records to an application software that can use it. With this data the machine is able to adjust an industrial process. Such communication was originally accomplished by having a remote network of machines relay information back to a central hub for analysis, which would then be rerouted into a system like a personal computer (Watson, et al., 2004).

People-to-machine, P2M – Refers to the common use of machines, for e.g. a person using a computer in able to create something of value (Watson, et al., 2004). This can include services such

Process Delivering the right information to the right person (or machine) at the

right time

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valuable w ays, e.g. People-to-People

(P2P)

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devices and objects connected to the Internet and each other for intelligent decision making

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)

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as Wi-Fi badges; gesture recognition; fleet and transportation monitoring; product sensors; connected cameras and analytics; and much more. This all is likely to lead to operational efficiencies; end-user insight; and increased revenue (Cisco, 2013).

2.2.2. The ecosystem of the Internet of Things: A practical description

IOT technology provides a complex ecosystem with multiple layers and with hundreds of players. In a way to organize this, the industry has identified the so called ecosystem of the Internet of Things. The ecosystem of IOT refers to collection of component needed to develop an IOT service (IDC, 2014).

This is everything from the devices, to the connectivity, to the storage and support, and may be referred to as the “key stones” when building an IOT service. The main components of the ecosystem can be identified as: modules; connectivity; platform; and application, and are therefore located in the center of the ecosystem (IDC, 2014). To get a full understanding of the ecosystem, the Figure 4 has been provided. In the following sub-section a clarification of each segment will be provided.

Modules and Devices – The main idea behind IOT is based on the devices (or the things). They are more or less essential for IOT’s persistence. Once can consider things as very small and simple items, e.g. Radio-Frequency IDentification (RFID) tags. NFC2 and WSAN3 together with these RFIDs are recognized as ‘‘the atomic components that will link the real world with the digital world”. These devices should be connected to each other in one or another way, referring to connectivity. This is the easy part of IOT, where you more or less verify that the devices are capable of receiving and sending information. (Atzori, et al., 2010)

Connectivity – Without connectivity the devices are more or less useless. This can be either via a Wi-Fi or a home network. This verifies that the devices have the connectivity needed in able to send and receive data (IDC, 2014). However, it is essential to understand that combining a device with connectivity is more than just adding a cable. Connectivity can be organized under two main categories, Hardwired broadband access and Wireless broadband access (Atzori, et al., 2010).

The difference between the two is of course the type of connectivity. When looking at the IOT case, the possibility of being wireless might seems like the obvious solution. But now when IOT is everywhere, everywhere might just as well be home. The nowadays, traditional, broadband enables higher reliability, and lower mobile data traffic, creating endless possibilities of products or application. (Atzori, et al., 2010)

Platforms – When it comes to big companies and operations, platforms are a great tool when overviewing the collected data. But also imagine having 100 devices installed everywhere, in different areas or different countries. This might as well read of different kinds of information. Therefore, a platform where information is exchanged is needed (IDC, 2014). WISPs4 are powered and read by the standard RFID readers, harvesting the power from the reader’s querying signal. WISPs have been used to measure quantities in a certain environment, such as light, temperature, acceleration, strain, and liquid level (Atzori, et al., 2010), and visualizing it. This is normally located in some type of “Cloud Service”, which enables mobile access (IDC, 2014).

Applications – The application refers to the many different types of IOT services located in the market. This can be covered by thousands of applications and solution, maybe even millions. This is where the actual IOT ideas come to life (Atzori, et al., 2010). E.g. services can be providing people waiting for the bus with real-time data when the bus arrives. This solution is based on that the bus station is “communicating” (in other words, exchanging information) with the bus. By sharing its GPS location, the bus “calculates” the estimated time to arrival.

2 Near Field Communications 3 Wireless Sensor and Actuator Networks 4 Wireless Identification and Sensing Platforms

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Analytics – After final development of the applications, the “Analytics” tools can be connected. This means that companies and researchers access collected information and data from the devices, and analyzes the information (Atzori, et al., 2010). E.g. if the bus (from the previous example) always is late during a specific time frame, action can be taken in able to minimize this delays.

Security – Since information is located in a cloud service it is quite easily accessed, the risk of threat is quite big. Therefor a safety net has to be added to ecosystem, to prevent the information from theft or leak out in other ways. Therefor “security” has to be added. When this is all in order, it is ready to be packaged under the title “Professional Services” (IDC, 2014).

Professional Services – By adding analytics and security to the IOT services or solutions, the service can be packages as a “Professional Services”. This means advanced solutions, which looks at the whole value chain. From receiving the data, to sending out a service technician to the actual device. After validation of this, the professional services can later on be sold and packaged under tentatively three main categories: Consumer; Government; and Enterprise (IDC, 2014). Examples on Professional Services can be found in Figure 4.

2.2.3. The value chain of IOT: Converting data into business

One way of clarifying the understanding for IOT is to present a value chain for how the information is transmitted. As mentioned before, IOT is dependent of devices. These devices collect data from their environment and surroundings, and performance and usage data is acquired and transmitted (every x seconds). Data from many connected devices is aggregated and stored. This data is later on sent to a database, most likely a Cloud Service (Capgemini, 2015).

After the data is received, the data can be analyzed. Data is analyzed in real -time to identify issues. This is done either manually by an individual, or by a smart mainframe, which bases its analysis on threshold values. E.g. temperature should not drop below x point, humidity is not to rise above x point etc. Data indicates an issue that can cause problem or opportunity. (Capgemini, 2015)

Based on which alarm is set of, a case is created and a service is notified. This service can for example be: Customer Care, which provides the operator with tips and instructions; Sales & Marketing could proactively send the customer offers an order; and/or; Technical Services are dispatched to perform maintenance or repair; System sends messages to the machine directly. (Capgemini, 2015)

After action has been taken, an evaluation of the process can be made and the resolution is recorded. All to verify that accidents are prevented, sales are captures, and customer dis -satisfaction is prevented (Capgemini, 2015). The value chain is simplified, and presented in its fullest, in Figure 5 below.

Figure 5. The simplified value chain of data (Capgemini, 2015)

1. Data is aquired and transmitted

2. Collection

of data

3. Data analyzation

4. Data alarm

5. Action is taken

6. Evaluation

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The value chain and it use is of great importance; since it allows companies to visualize the value chain, and helps them analyze in which step they can contribute. However, it is of great importance to understand that this way of describing the process is just one of many processes, and that each IOT solution provides its unique value chain.

2.3 Concluding remarks The theories presented in this chapter provides the reader with the theoretical knowledge needed, in able to understand the following analysis. The background of IOT provides the reader with the understanding of IOT. That even if IOT is new to market, the concept behind IOT has been known for years. The term “Internet of Things” is just a new way of naming a concept that has more or less been known for years. And it is also essential to understand that the technique behind IOT is well developed. The biggest change today compared to accent time is that the Internet is entering even small devices and applications. When it comes to Internet of Everything’s, it is essential to understand the core differences compared to IOT. This means that IOE compared to IOT connects “everything”, while IOT only connects the devices. Even if this is not further discussed, the importance of understanding the difference is necessary. Worth highlighting is the importance of understanding the ecosystem of the IOT. This is essential for understanding the later on arguments in the study. In Figure 6, the ecosystem of the IOT has been simplified, in order to simplify the later on analysis.

Figure 6. A simplified version of the IOT’s ecosystem

The components in the ecosystem can be summarized as: Security; Analytics; Modules / Devices; Connectivity; Platforms; Applications, where the following four are the components of most importance: Modules / Devices; Connectivity; Platforms; Applications. Understanding the value chain of the IOT system is of use, but might not be essential for understanding the further analysis in the study.

IOT Services

Security Analytics Modules / Devices

Connectivity Platforms Applications

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3 THEORETICAL AND INDUSTRIAL REVIEW

In this section is the main theories and industrial theory, used in the study, is presented and revised. How previous research relates to the research and how it will complement the found literature, is explained in each selected investigation area.

3.1 Theoretical review To get and understanding for the IOT concept, the researcher has searched several different sources. The collection of the literature has been chosen based on reliability and what the researcher assess to contribute with to the study. The researcher has used exploration where previous findings have been reported, for example Watson et al. (2004), Rogers (1962), Kevin Ashton (2010), Chesbrough (2006) and many more.

These authors’ knowledge in the field was in these cases considered to be important to assure that the material was reliable. The information that has been collected in the reports has been compared with information found in other reports to confirm that their reliability. The literature covers the theory of: ‘Diffusion of Innovation’; the ecosystem of IOT the value chain of IOT; business models with relevance for IOT; and closed and open innovation. The literature in the following section provides a stable base for continued investigation in the area of IOT.

3.1.1. Diffusion of Innovations

One can argue that the future of IOT is based on innovation, and this is partly true. But innovation is highly dependent on more than juts smart ideas. When it comes to companies one can analyze companies “adoption rate of innovation”. Also, open vs. closed innovation is a theory worth discussing. Diffusion of innovations, or “adoption rate of innovation”, is a theory that seeks to explain how, why, and at what rate new ideas and technology spread through cultures.

Rogers (1962) argues that diffusion is the process by which an innovation is communicated through certain channels over time among the participants in a social system. There are four main elements that influence the spread of a new idea: the innovation itself, communication channels, time, and a social system. However, one can not to forget that this process relies heavily on human capital. This means that the innovation has to be widely adopted in order to self-sustain, and happened when the innovation reaches critical mass. The five categories of adopters are: innovators, early adopters, early majority, late majority, and laggards, and are illustrated in Figure 7 below (Rogers, 1962).

Figure 7. Diffusion of innovation curve (Rogers, 1962)

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In the figure we can see the innovators on the left side and the laggards on the right side. As mention earlier, there are five types of adopters. The rate of adoption is defined as the relative speed at which participants adopt an innovation. This means that innovators require a much shorter adoption period (adoption process) when compared to late adopters (Rogers, 1962).

3.1.2. Digital transformation maturity

Maturity models were first introduced in the quality management (Chiesa, et al., 1996). The concept of maturity models implies an evolutionary progress, were the aim is transforming from an initial point to a desired target or naturally existing end stage (Marx, et al., 2012; Gastaldi, et al., 2014). The basic around this way of categorizing progress, contains in the stages of growth that possess a way of transformation. This is done through a number of intermediate stages of growth towards reaching higher maturity levels (Sen, et al., 2012). Maturity is regarded as “a measure to evaluate the capabilities of an organization”, when it comes to the information system discipline (Rosemann & De Bruin, 2005). These models can later on be design in a top-down or bottom-up approach (van Steenbergen, et al., 2010). In the following section, TDWI’s Maturity Model will briefly be presented. This model is similar to the ‘Diffusion of innovation curve’ presented in previous section, and the researcher aims to provide a broader perspective of the different maturity models found in the field of research.

TDWI’s Maturity Model

‘TDWI Maturity Model’ helps companies investigate the internal maturity and establish a process improvement roadmap. The idea with this kind of way of categorizing business is to develop an organization from where they are today to where they want to be. Figure 8 illustrates the five different stages in the model: (1) Nonexistent, (2) Preliminary, (3) Repeatable, (4) Managed, and (5) Optimized.

Figure 8. A representation of the five stages of the TDWI Maturity Model (TDWI, 2012)

There are also two major obstacles: the Gulf and the Chasm. The Gulf occurs between the Nonexistent and Preliminary stages, while the Chasm occurs between the Repeatable and Managed stages. The first level covers question like “Is it happening”, the second lever covers question like “What happened?”, the third level covers question like “What will happen?”, the fourth level covers question like “What is happening?”, and the fifth level covers question like “What can we do to make it happen?”. See Figure 9 below.

Figure 9. Business Intelligence Maturity Phases (TDWI, 2012)

This way of categorizing a process is useful when transforming the business intelligence. This means that the framework provides companies with good guidelines, to be able to fasten the development

Level 0: Operate

• Is it happening?

Level 1: Understand

• What happend?

Level 2: Change

• Why didi it happen?

Level 3: Grow

• What will happen?

Level 4: Compete

• What is happening?

Level 5: Lead

• What can we do to make it happen?

GULF CHASM

1 Nonexistent 2 Preliminary 3 Repeatable 4 Managed 5 Optimized

Business Value Sematic Integration

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phase when it comes to business intelligence. This framework will later on in the report be further discussed.

3.1.3. Closed innovation vs. Open innovation

The traditional way of working with innovation is to do it under quite closed circumstances, and develop the technology completely internal. This process is referred to as closed innovation (Chesbrough, 2006; Tidd & Bessant, 2013). Companies change their way of working with other companies, by networking and searching both outwards and inwards, for solutions to business issues (Jolly, 2008). This includes investigate the matter of open innovation. This, in able to provide IOT solution and services together. Here Figure 10 and Figure 11 below have been provided to clarify the difference between close and open innovation. Here one can see how the closed innovation, see Figure 10, completely is developed internally, while open innovation, see Figure 11, opens the company’s organizational boundaries (Chesbrough, 2006).

The circles in emphasizes how firms acquire external sources as valuable resources and allow their internal generated knowledge to flow outwards, while now welcoming externally generated knowledge into the business. This cannot be found closed innovation. (Tidd & Bessant, 2013)

3.1.4. Summation of the theoretical review The theories presented in this chapter provides the reader with the theoretical knowledge needed, in able to understand the following analysis. The theory behind the rate of innovation, the maturity models and open innovation theory help the reader understand the importance of innovation and the companies’ maturity in this field.

3.2 Industrial review In the following section, a presentation of some of the industrial findings will be presented. Since the topic of investigation is affecting several industries and fields, greatly investigation from companies working within the field of investigation has been made. In this section of the report, the researcher has used exploration where previous findings have been reported from the industry, for example MIT (2014), Cisco (2013), Gartner (2014), IDC (2014), Capgemini (2015) and many more. In the following section, some of the most influenced and well-known frameworks from the industry will be presented. The collected industrial findings will provide a stable base for further investigation within the areas of IOT.

Figure 10. The Closed Innovation

Paradigm, to the left (Chesbrough, 2006)

Figure 11. The Open Innovation

Paradigm, to the right (Chesbrough, 2006)

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3.2.1. Digital transformation maturity

There are many ways of categorizing an emerging technology, and looking across the market search oriented companies, such as Gartner, Capgemini and IDC, are all presenting their ideas of assessing the degree of maturity on the IOT. In the following section, some of these models of frameworks will be presented.

Gartner’s Hype Cycle

To get an understanding and knowledge about an approaching technology, Gartner have developed their so called Hype Cycle. The Hype Cycles provide a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities (Gartner, 2014), see Figure 12.

The methodology from the Hype Curve gives the reader a view of how a technology or application will evolve over time, providing a sound source of insight to manage its deployment within the context of your specific business goals (Gartner, 2014).

Companies that are willing on taking on risks and investments are categorized as “early adopters”. Executives who are more moderate understand the argument for an early investment, but will also insist on a sound cost/benefit analysis when new ways of doing things are not yet fully proven (Gartner, 2014). Each Hype Cycle involves five key phases of a technology’s life cycle. Each one of these phases is described below:

1) Technology Trigger: Early proof-of-concept5 stories and media interest trigger significant publicity.

2) Peak of Inflated Expectations: Early publicity produces a number of success stories —some companies take action.

3) Trough of Disillusionment: Interest wanes as experiments and implementations fail to deliver.

4) Slope of Enlightenment: More instances of how the technology can benefit the enterprise start to crystallize and become more widely understood.

5) Plateau of Productivity: Mainstream adoption starts to take off. The technology's broad market applicability and relevance are clearly paying off.

Gartner’s Hype Cycle for emerging technologies is developed each year, and gives companies an understanding of were Gartner believes the technology to be. The framework will later on be used, when analyzing the future potential of IOT (Gartner, 2014).

5 is a realization of a certain method or idea to demonstrate its feasibility.

Figure 12. “The Hype Cycle” (Gartner, 2014)

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IDC’s Digital Transformation Maturity Scape

Another framework worth mentioning is IDC’s Digital Transformation Maturity Scape. The approach, by which enterprises drive change in their business models and ecosystems, by leveraging digital competencies, can be defined as digital transformation. IDC’s framework identifies stages, dimensions, outcomes, and actions, which is required by a business, when they are investigating in digitally transforming their operations, organizations, products and services.

The framework also helps business identify areas in need of improvement, for business to successfully transform their business from one phase to another (IDC, 2015). The framework can be found in Figure 13.

Figure 13. The IDC's Digital Transformation Maturity Scape (IDC, 2015)

Each phase involves five key behaviors seen in companies. Each one of these phases is described below:

1) Digital Resister: Business is a laggard, providing weak customers experiences and using digital technology only to counter treats.

2) Digital Explorer: Digital enabled customer experiences and products are inconsistent and poorly integrated.

3) Digital Player: Business provides consistent, but not truly innovative products, services and experiences.

4) Digital Transformer: Business leader in its market, providing world-class digital products, services and experiences.

5) Digital Disruptor: Business remakes existing market and creates new ones to its own advantages and is a fast-moving target for competition.

The framework can later on be used when analyzing the current stage of the case company, as well as the other companies interviewed.

3.2.2. Business models with relevance for IOT

There are several interesting revenue models and pricing models approaching when it comes to IOT. This since the complexity of IOT opens up fort new opportunities, when it comes to offer a product as service, instead of just a product (Celaya, 2016). The IOT services are still very complex. But now when initial techniques are arriving to the market, so are also new pricing models. Traditional pricing is based on the average cost to service customers, which means that e.g. washing our car can be done at a price that covers the cost of materials, while the company also earns little (Baxter, 2015). If this company were to start offering this “as a service”, meaning a fixed fee and the customer could use the service as much as they like e.g. Netflix, Spotify, they would be applying the so called “Membership Economy” concept to their business. (Baxter, 2015)

This concept means that a customer that uses a product/service one time pays the same as a customer that uses the product 10 times as much. The model is quite new to many organizations, but can be easily found if one just enters a “membership” at a gym. This way of pricing is starting to

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become common in many industries. However, most companies and industries are more known of using the so called The Ownership Economy. (Baxter, 2015)

In able to understand the difference between “The Ownership Economy” and “The Membership Economy”, Table 1 has been formulated.

The Ownership Economy The Membership Economy

Key Metrics Conversion, transaction size,

manufacturing economies of scale Lifetime costumer vale/retention

Customer Value Path Cross-sell to increase revenues Tiers of value and add-ons

Personalization Customization Configuration

Sampling Free trial or sample Free trial and freemium add-ons

Key Organizational Objective Control Flexibility

Network Effect Minimal Critical

Pricing Cost-based Value-based

Product Innovation Periodic big reveals and new product launches

Customers expects ongoing innovation

Relationship Ends at transaction Forever

Table 1. The key differences between Ownership Economy and Membership Economy (Baxter, 2015)

The IOT opens up the opportunity to starts selling products as a more than just a product. So it is essential to understand that, while IOT is entering the market, so is also new pricing models. To explore this area deeper, different pricing models have been investigated. A selection of pricing models has been made, and the one of most interest has been gathered in the list below.

Most interest revenue models with importance to IOT:

Micropayments – Micropayments are usually defined as small-quantity transactions. This kind of transaction is used to access certain types of contents, and examples on which could be an article on a webpage, a song, or the next level in a video game (Celaya, 2016).

Pay-Per-Use – This business models first appeared in the television sector, and get the

name Per-per-view. This model later on got developed and can now outside of the audiovisual industry. As its name inclines, it is a payment system which allows users to pay only for what they use (Celaya, 2016).

The Subscription Model – This business model is client based and ties the client to the company for a specific timeframe (a week, a month, a year etc.). This model generates a constant flow of revenue, since subscribers pay up front (Celaya, 2016).

The Membership Model – This business model is quite similar to “The Subscription Model”, however, member means belonging to a group. Therefore, a person could be a member of e.g. a fan club, a book club, a golf club. To in order to be includes to the group, or even society, the member must first pay a subscription. E.g. annual, quarterly, or monthly (Celaya, 2016).

Freemium/Premium – The idea behind this model is to offer a product or content for free

while reserving additional content for paid users. Therefore, the model separates the paying users from the non-paying users, and calling the paying users for Premium users. At times, the Freemium content includes embedded advertising or marketing (Celaya, 2016).

Open Access – Also known as open source, is this business model no subscription or payment is necessary, and the user is accessed with an open access/open source material. It is often an educational, scientific, and academic material, but it might as well be loans in digital libraries.

Peer-to-peer (P2P) – The origin of this model can be found in P2P networks, in which computers are directly linked to each other. This is referred to a quick an effective way of sharing documents at work, but have now become so popular that the whole world now is sharing all sorts of files. This way of sharing is however not that safe, and unfortunately many seem to forget this (Celaya, 2016).

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As one might understand, there are many way of offering a service, especially now when IOT is opening up the possibilities for more. This way of pricing IOT, will later on in the report be discussed.

3.2.3. Summation of the industrial review The following industrial theories and frameworks provides the reader with the industrial knowledge needed, in able to understand the following analysis. The understanding for “value chain of IOT” is essential for understanding the later on arguments in the study, in combination with understanding the different pricing models. The “Gartner’s Hype Cycle” (2014) and the “IDC's Digital Transformation Maturity Scape” (2015) provides the reader with the understanding of how the market for IOT is today, and the importance of internal maturity within companies. In the following chapter, the empirical findings will be presented.

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4 METHOD

In the following chapter, the research approach is presented, how the case study will be conducted is explained and it is described how data will be collected and analyzed. A case study at Tieto’s business unit Telecom & Media has been chosen as the main research method, in combination with both employees at Teito and other companies. Initially, the choice of research approach is presented. Further, the research design with its underlying methods is presented. And finally, the validity and reliability of each research method is discussed.

4.1 Research design The research was highly dependent on four main areas: the researcher; the paradigm; the design; and the purpose. For this report, the chosen paradigm was interpretivism, which focuses on exploring the complexity of social phenomena with a view of gaining interpretive understanding (Collis & Hussey, 2014). The research objective for this thesis is to explore how IT consulting companies are working with IOT adoption and implementation in the context of digitalization. When the boundaries between phenomenon and context are not clearly evident, a case study is a suitable research approach. Therefore, this research is done through a case study. A case study is an empirical study that allows the researcher to analyze and investigate a present phenomenon within some real-life context (Collis & Hussey, 2014). The characteristics of a case study give the impression to fit the purpose and objective of this research. The method contains collecting data on the topic of the thesis, mainly collected at the case company. The selection of a case company is out of great importance, since an improper choice can lead to a problematic situation. See Figure 14 below. The blue circle (marked with an A) in Figure 14 stands for the researcher’s vision of the study, while the red circle (marked with a B) is the case company’s vision. The ideal situation, when choosing a company, is that the case company shares the same vision as the researcher. But in most common situation the researcher and the case company have similar, but not equal view of the research.

Figure 14. The thesis and the interest of the company

At the case company, the impression given was that the research and the case company shared the same vision. This was also validated throughout the process. In order to obtain in-depth knowledge, a qualitative method including semi-structured interviews was chosen. The background and problem formulation was created after discussion with the supervisor and from the conducted preliminary investigations. This provided the research with the basics of knowledge with in the field and provided the research with an overview of existing research and theory. This also provided the researcher with a better understanding of the knowledge gap. The highly structured research design executes restrains on the result. This means that other relevant finding was discounted (Collis & Hussey, 2014). To validate the findings a triangulation method was used. Triangulation is the use of several sources of data, different research approaches and/or more than one researcher to explore the area of matter (Collis & Hussey, 2014). Here it was appropriate to use the so called “data triangulation” method. This means that data was collected at different times or from different sources in the investigation (Collis & Hussey, 2014). Also, since the investigation also looked at the

Ideal situation Most common situation Potentially problematic situation

A B A B A B

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process for implementing IOT, the so called “methodological triangulation” method was used. This means that more than one method was collected and analyzed.

4.2 Research approach Since the area if investigating was rarely researched, an inductive approach was chosen. This includes collecting data, without having any expectations when doing it, and thereafter analyze and formulate theories based on the findings. This kind of approach allowed the researcher to separate suitable theoretical explanations from individual observation to proclamations of general patterns or laws, thus moving from the specific to the general (Collis & Hussey, 2014). To assure that the problem formulation, purpose and research questions were in line with the research, an iterative approach was used during the study and new information were added to the sections (Blomkvist & Hallin, 2015). The first step of a case study is to select a suitable case (Collis & Hussey, 2009). The case study for this research was conducted at the department Telecom & Media at Tieto in Stockholm, Sweden.

The selected department was involved in investigating within the area of IOT, and from the researcher’s opinion, this give the impression suitable for the case study. The chosen company also appeared suitable since they hold a strong position in the IT market. These circumstances also applies that the case company is facing increased pressure both from customers and competition around the market. By using small samples of data, the chosen research approach aimed to produce rich subjective, qualitative data. This allowed the findings to be generalized, from one setting to another similar setting (Collis & Hussey, 2014). The collected data was then gathered to develop theories regarding this thesis. This was done in parallel with collecting empiric data, which resulted in a frequent increase of the study’s understanding. The findings were derived from qualitative methods of analysis, which leaded to that the research provided a broad conclusion. In the following section a detailed description of each component in the research approach will be described.

4.2.1. Case study The chosen research type for this thesis was a case study. This involved collecting sufficient amount of information regarding the chosen topic (Blomkvist & Hallin, 2015). A case study was chosen since it enables and generates detail-rich empirics, where complexity of reality also is captured. It also allows discovery of new dimensions, which often leads to a new theory, or further development within the area. For this study an illustrative case study was chosen, since the researcher aim was to illustrate new and possibly innovative practices adopted by particular companies (Collis & Hussey, 2014). To gain brief knowledge and becoming familiar with the context of investigation (Collis & Hussey, 2014), preliminary investigations has been conducted. This was done in the beginning of the process, and involved semi-structured interviews with employees at the case company. This was done in order to gain a better understanding of what should be studied. Empirical data gathered from several interviews gave further information about the internal IOT initiative at all levels of involvement.

The case study supports investigate, explain, or describe the phenomenon of this thesis (Blomkvist & Hallin, 2015). This also allows the study to research, explain, describe and answer questions that starts with how and why (Blomkvist & Hallin, 2015), which is line with the research questions. The data collected and analyzed was gathered in numerous ways: interviews, observations, research reports within the company, web pages analysis of existing data and recordings from interviews. The case study provided the research with empirical data, which enabled the study to achieve a result applicable directly to the industry. The case study might be described as an opportunist case study, since the opportunity to explore the phenomenon emerged due to the researcher’s access to specific industry related information (Collis & Hussey, 2014), as well gave opportunity to interviews with definite individuals involved in the field.

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4.2.2. Data collection

When planning from a data collection, one must know where and when to collect data, and the data collection may be qualitative (e.g. words), quantitative (e.g. numbers) or both (Collis & Hussey, 2014). For this study the collection of data with was based on qualitative findings. Meaning that the primary data for this study was partly collected from smaller amount of interviews, with well selected interviewees. The primary data was also collected through observations and experiences, which researcher’s gains during the study. When it comes to the secondary data. It will mainly be collected from publications and data bases, but also from internal records.

4.2.3. Interviews

In total, 18 interviews were conducted. All of the interviews were designed semi-structured with open-ended questions. This was done in order to validate that the interviews answered their own personal thoughts, instead of company specific valuations. To validate the findings an increase the reliability, all interviews were both recorded and transcribed and keynotes were taken, which made it possible to analyze the data more closely. Semi-structured interviews allow the researcher to ask supplementary questions to explore new matters or when more detailed information is desirable (Collis & Hussey, 2014). Since structured interviews often provides answers with a limit and restriction in clarifications of concepts (Collis & Hussey, 2014), it did not seen like an appropriate approach. The interviews were structured with the help of a set of semi-structured questions that formed a guide. The interviewees were informed in advance about the topics covered and all interviewees participated on a voluntary basis. In order to get at understanding for how they are company is working with IOT, it were essential to interview employees at case company that is, in one way or another, were connected to the IOT initiative. Employees suitable in this matter were invited to an interview, and interviews between 45 minutes to 1 hour and 30 minutes were performed. The length of the interviews is based partly on the time that was set from the beginning, but also on the selected individual’s ability to continue after this time had passed. Later on in the process, to gain a broader perspective of the results and finding in the study, a combination of different interviewees was organized. This included interviewees from three different companies and the technical university in Stockholm, Sweden. Partner companies and employees suitable at these were invited to participate in an interview. The interviews were also between 45 minutes to 1 hour and 30 minutes, and varied based on each person’s ability to continue the interview. On total, 14 interviewees from four companies and one university were interviewed, and Table 2 presents the final summation of the interviews.

Company Description / Job title Department No of interviews

Tieto

A1 Sales Director Telecom & Media 3

A2 Sales Director Teito Industrial Internet 2

A3 Chief Operating Officer Tieto Industrial Internet 1

A4 Customer Manager Manufacturing, Retail and Logistics 1

A5 Application Supervisor Tieto Industrial Internet 1

A6 Solution Consultant Tieto Industrial Internet 1

TeliaSonera

B1 Partner Manager TeliaSonera Global IoT Solutions 2

B2 Partner Manager TeliaSonera Global IoT Solutions 1

B3 Partner Manager TeliaSonera Global IoT Solutions 1

B4 Sales Manager TeliaSonera Global IoT Solutions 1

B5 Product Manager TeliaSonera Global IoT Solutions 1

Huawei C1 Systems Specialist - 1

Evothings D1 CEO - 1

KTH E1 Professor6 Industrial Management 1

18

Table 2. Interviewees conducted, organized by company

6 The interview were based on the interviewees own experience, and may not be mistaken with the opinions that the

university advocates.

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This summation of all interviewees can also be found in Appendix 1. The table is organized by which company each interviewee was working on, as well as which department. The number to the right in the table indicates the number of conducted interviews with the specific interviewee. The questions asked during the interviews can be found in Appendix 2.

Even if most of the interviewees at Tieto not o located in the same department of the company, their work is highly dependent on each other’s. Later on in this report, the reliability and validity of the interviews will be discussed.

4.2.4. Data analysis

In the section, it is presented how the interviews were analyzed. For the data analysis, a cross-case analysis was used. This means that the collected empirical material was sorted into categories which then were used to answer the posed questions. The content analysis used to analyze the qualitative data consists of three main elements: reducing the data, restructuring the data, and detextualizing the data (Collis & Hussey, 2014). The first phase involved removing data with less relevance for the study. The included removing subject that the researcher found irrelevant. The second phase involved restructuring the data. This was based on transcription of the interview. During the interviews the researcher took detailed notations in order to simplify the later on transcription. By transcription the interviews independently of each other, lead to minimization of loss of data. Thereafter, data from each interview were summarized and roughly sorted. It was beneficial to sort the empirical material from the interview according to themes, because clear areas of intere st were identified in the study.

During the interview several focus areas was identified. This was categorized according to two main categories: main focus areas of investigation; and main challenges when implementing and adopting to IOT.

The categories became rather corresponding, but then again, much of the information said during the interviews was in a way connected. The chosen categories were closely connected to the research questions, and this was done to simplify the later on process. After the fi rst categorization, the interviews were sorted based on themes that they covered. This lead to that different perspectives could be drawn together, that could support the triangulation methods. Leading to provide the research with a common view of how companies today is adopting and implementing IOT. The third phase involved detextualizing the data. This was done with different types of process charts, figures and tables. All in order to simplify the explanation process for the reader, and to demystify terms and processes. When the themes and categories and the primary finding from the existing literature was joined together, conclusions from the study could be formed and an answer to the research question could be provided.

4.2.5. Theoretical review

To get and understanding for the IOT concept, the researcher has searched several different sources. The collection of the literature has been chosen based on reliability and what the researcher assess to contribute with to the study. The researcher has used exploration where previous findings have been reported, for example Watson et al. (2004), Rogers (1962), Kevin Ashton (2010), Chesbrough (2006) and many more. The authors’ knowledge in the field was in these cases considered to be important to assure that the material was reliable. The information that has been collected in reports has been compared with information found in other reports to confirm that they are reliable. The literature in the following section provides a stable base for continued investigation in the area of IOT.

Since the topic of investigation is affecting several industries and fields, greatly investiga tion from companies working within the field of investigation has been made. The researcher has used exploration where previous findings have been reported from the industry, for example MIT (2014), Cisco (2013), Gartner (2014), IDC (2014), Capgemini (2015) and many more. By that, some of the most influenced and well-known frameworks from the industry will be collected. The researcher

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believes that the collected industrial findings provided a stable base for further investigation within the areas of IOT.

4.3 Reliability and validity Reliability refers to the extent to which another researcher could prov ide a study with the same results, if the study were to be repeated (Collis & Hussey, 2014). The result of the study were dependent on the specific setting provided on the current time of the study, the persons interviewed and unique setting in the development in the selected subject. This might lead to that the findings might gain poorer reliability.

Validity refers to the extent to which the researcher’s findings accurately reflect to phenomena of the study (Collis & Hussey, 2014). As mentioned previously, a triangulation method was used, to validate the findings. The data triangulation method allowed the researcher to collected data at different times or from different sources in the investigation. And, since the investigation also looked at the process for implementing IOT, the so called methodological triangulation method was used. This method validated that the founded processes and methods for integrating IOT, could be critically evaluated and conclusion of the most appropriate methods could be drawn.

In the following section, the reliability and validity of the interviews conducted will be discussed.

4.3.1. Interviews

This study was based on a qualitative approach, including a smaller amount of interviews. Even doe that the interviews are of greater qualitative, this kind of approach tend to have low reliability, as interpretations and observations depend on how the researcher explain and understand the reality (Collis & Hussey, 2009). There is a risk that the representation of reality may depend on what the interviewees might have chosen for the interviews. To reduce bias in data sources and inc reases the validity and reliability of the results (Collis & Hussey, 2014), the data triangulation method were used. This includes using multiple sources from the same department or division, in order to collect the same information.

Depending on the interviewees and the researchers’ perceptions, one might dispute the answers from the interviewees. This since some interviewees might try to provide the researcher with the “right” answer according to the company or the researcher (Bell, 1995). In order to minimize this effect, open-ended questions were asked during the interviews. Later on, to maintain the research as true as possible, the interviewees are recited. In a way to also increase the validity, theme findings of focus topics from one interviewee was discretely introduced during interviews with other interviewees. This means that the main themes that emerged from the interviews were further confirmed by other sources. This gives the researcher the ability to validate, the findings from previous interviews. On a way to also assure a higher validity were that, interviewees of greatest importance have been interviewed several times. This to validate that the finding from the first interview, corresponded with findings in later on conducted interviews.

The time frame of the thesis project limited the sample size, and during the time frame 18 semi -unstructured interviews were conducted. Due to the small sample size, this might have affected the reliability and validity of the findings. This since the interviewees’ opinions and thoughts might not reflect the other in the same department and the managers at the division. To reduce this risk of this, attempts to interview additional employees was performed. However, due to ta fact that most employees at IT consulting companies are highly booked during the spring, this could not be remedied.

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5 EMPIRICAL SETTING

This chapter gives a presentation of the case company and its current relation to the Internet of Things initiatives, together it interlinks into what makes the chosen company a suitable case company from where to conduct a case study. This chapter will also present the benchmarking companies, and their Internet of Things initiatives, and interlinks what makes the chosen companies suitable benchmarking companies.

5.1 Introduction to the case company: Tieto Sweden AB Go get a closer line to the industry, Tieto Sweden AB will act as a case company. Tieto Sweden AB, later referred to as Tieto, was founded 1968, and specializes on product development services and IT services. Tieto is based on a strong Nordic heritage with headquarter Helsinki, Finland, and has over 20 years of experience with in telecom engineering. Tieto enables IT-transformation through digitalization and creates ecosystems to speed up other clients business. There is over 13 000 employees working at Tieto and they are located in 20 countries. The chosen department for this study at Tieto is Telecom & Media. Tieto has been chosen on the basis that they now are investigating the use of Internet of Things, and exploring their possibilities within the field. They have outlined IOT initiatives, and therefor they implicated suitable for a case study. In line with Tieto’s strategy, the main focus in 2015 was to accelerating in their so called growth portfolio. The growth portfolio consists five focus areas which Tieto has identifies as potential growth areas in the long term market, and are the following: (1) Customer Experience Management; (2) Cloud Services; (3) Life care; (4) Industrial Internet; and finally (5) Security Services. See Figure 15 below.

Figure 15. A simplified version of Tieto’s organization

Customer Experience Management, Industrial Internet and Security Services are all launched as internal start-ups, which means that a certain amount of employees are selected to a team, with ambition to accelerate the innovation growth. Kimmo Alkio, CEO of Tieto, comment the following during an interview (Tieto, 2016):

“…Our experience of internal start-ups has been highly positive in terms of increased flexibility and agility – all for the benefit for our customers gaining increased ability to speed up digitalization. Based on our expertise and including our own software, we expect to achieve a leading position in managed security services in the Nordic countries.”

For the further empirical investigation, employees from tree departments have been interviewed, this included; Telecom & Media; Manufacturing Retail and Logistics; and Industrial Internet.

5.1.1. Tieto’s Industrial Internet

In the spring of 2015, Teito launched their IOT initiative called Industrial Internet7. The idea of the Industrial Internet unit is to create a partner ecosystem where clients to Tieto are able to join under

7 In 2015, Tieto’s investments in Industrial Internet amounted to around EUR 4 million while sales remained below this

figure (Tieto, 2015).

Tieto's Core Business Tieto's Growth Businesses

Customer Experience Management

Lif ecare

Security Serv ices

Cloud Serv ices

Industrial Internet

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Figure 16. “M2M-in-a-Box”

partnership. Under these circumstances, companies can openly discuss new business models, new opportunities, and enables a restructuring of the value network in many industries.

The initiative provides all involved within the team with fewer organizational strains found in a big organization. This way, the internal processes can be speeded up and providing the team with overall bigger freedom. If they find a great lead, they have all the tools necessary to complete the deal. E.g. if they are not that pleased with an internal offering from Tieto, they have the freedom to buy the service from an external source. This strategy has coverage in the management board, providing them with good boundaries for further development. Beside this, Tieto’s Industrial Internet business does not have the same sales target as the overall organization of Tieto. The idea with this is to provide everyone working at Tieto’s Industrial Internet business a greater independence in de context of decision making and terms of risks.

The IOT initiative at Tieto is still new, and the idea in the long run is to develop a strong portfolio which can meet a generalized demand. Tieto in general have the influence needed can go to the large enterprise companies, such as manufacturing companies and other big players, and provide a full IOT service. But to reach the other segments, Tieto Industrial Internet atmospheres the need of joining under partnership with other operators. Therefor the partnership is of great use, and the partner relation provides them with the unique opportunity to negotiate, instead of the classic sell -buy-relation. However, this provides a delicate situation, since they can joint under partnership with several operator in each segment. Therefore, they have to be careful to not damage each partner relation, and stay homogeneous in each relation.

5.1.2. The IOT offerings at Tieto

In the following section some of the most highlighted offering that Tieto provides within IOT will be presented and explained. The data is gathered during the pre-study with the employees at Tieto and specific detailed has been obtained in retrospect.

Tieto I&I Connect This year, 2016, Tieto Industrial Internet launched their new Cloud Service called Tieto I&I Connect, powered by the partner company Cumulocity. This was, for Tieto, a huge step towards entering the IOT market and starting to provide IOT based services to their clients. Tieto I&I Connect, is a connectivity platform, and are provided with Tieto’s software. The service is an open source industrial Internetbased platform, which help Tieto Industrial Internet’s clients when analyzing their data and understand their data. It controls remote devices, analyses the information received, and enables services that are embedded in a device. To help companies fully benefit from the data, the platform is accompanied with an analytics toolbox. The IOT platform is based on the tree step process: (1) Measure; (2) Analyze; and (3) Automate, which means that the first thing that has to happen is data being collected. After this the data is being analyzed. And thirdly, if a threshold level is passed, an alarm sound is alerted. The idea with the platform is that it can be integrated in all industries.

M2M-in-a-Box M2M-in-a-Box, see Figure 16, is a box that contains sensors that can be used to connect everything from buildings to machines. The service contains 25 devices, with sensors either on it or in it. The internal (built-in) sensors are; a GPS and; an accelerometer for vibration and movement detection, while the three external sensors measures; temperature; humidity; and has an infrared motion sensor. The box is used in the following two set-ups:

Churches are providing their property manager with the box. In this way they can get real time updates about conditions the in churches, and instead of visiting

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each church they can see how “the church is doing” by accessing the mobile platform.

Caterer now are using box to keep track of the temperature of refrigerators and freezers. This way they get an alarm if the temperature is dropping or escalating, and take action before the groceries are damaged.

In this specific case, Tieto is responsible for maintenance of the database and the platform. The product was launched about a year ago, and so far the box is found in the previously presented cases. In this set-up Tieto participated in the product development, along with several other parties. However, Tieto feels that they have to work closer to the customer, continuous and develop business together. Now the product is launched in Sweden and Finland, in a couple of weeks in Norway, and by spring in Baltic.

Tieto Real Time Factory The system is designed for the retail industry and the idea behind the concept is to provide the company with a production platform, based on real time data. This provides their customers with the opportunity to predict forecast on actual data, and plan maintenance more effectively. The idea of real-time data is also to assure that the workers in the production line is updated with the latest information, such as previous events or material specification.

HSB Living Lab HSB in collaboration with other partners, have created an observatory lab under the project name HSB Living Lab. During a time frame of 10 years, Tieto has been chosen as the full -service IT partner. HSB Living Lab consists of 29 apartments, built nearby Chalmers University, in Gothenburg, and is expected to be finalized by June, 2016. During the 10 years research, either students or guest researchers, will live in a constantly changing environment and be evaluated. The facility will test new products and solutions, and thereby offer Tieto with a helpful corporation for innovation. In the installation, Tieto will provide the building with 4,000 sensors connected to Tieto’s system. This includes installing infrastructure including Wi-Fi. The sensors will then be used to monitor energy- and water consumption, but also behavior and safety solutions in the apartments. The HSB Living Lab provides Tieto with a unique insight in everyday living, and ideas on mak ing the everyday living more effective and inspiring, can be developed during this project. This initiative also provides Tieto with a unique observation when dealing with the challenges for urban society. E.g. how it is possible to aging populations to live home, longer and more safely. Tieto’s vision for the project is to accelerate modernization in a cooperative context and bring innovative technologies to the forefront.

5.2 Introduction to the benchmark companies In the following section, a breaif presentation of the benchmark companies will be done and their IOT intiatives. The data is gathered during the pre-study with the employees at the benchmark companies and specific detailed has been obtained in retrospect.

5.2.1. TeliaSonera

TeliaSonera was chosen on the basis that they, as well as Teito, is operating within the telecom sector. They have also outlined IOT initiatives, and therefor they implicated suitable for a benchmarking study. In the autumn 2009, TeliaSonera launched their M2M/IOT initiative . A collection of employees at TeliaSonera had realized that they needed a network of partners, since they are investigating to broaden their IOT initiatives. The idea at this point was to create a network of companies that all were interested in exploring the market of M2M and IOT.

During 2010 they arranged breakfast seminaries every 14 days, and by time partner companies started to develop relations. During 2011 the work with the network started to take so much time, which lead to that they created a “special unit” at TeliaSonera that were responsible for the further research within the area of M2M and IOT. This was later on named “Telia Global IoT Solution”, which is the department were the interviewees for TeliaSonera are working. During this time

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TeliaSonera organized a strategy covering the whole organization, focusing on 6 main areas: IOT, eHealth, Music; Security; Financial Services; and TV. The strategy was launched globally and now each country has their organization. TeliaSonera is mainly working with two IOT services. The first initiative has already been described in previous section and is the “M2M-in-a-Box”. The second initiative TeliaSonera has named Telia Sense, and is a service that TeliaSonera is offering to their customers. The service allows you to “connect your car”, and this is done by installing a small hardware in the vehicle's OBD port (an outlet that normally sit under the steering wheel). This provides the costumer with “full control over their car”. The information is access via a mobile application, which provides the user with features such as logs, GPS location, Wi-Fi throughout the car. An insurance company now is collaborating with this service, and collects data from the end-user. The collected data allows the insurance company to access real-time data, instead of forecast, and can by this offer a better service to their clients.

5.2.2. Huawei Technologies

Huawei Technologies was chosen on the basis that they, as well as Teito, is operating within the telecom sector. They have not outlined IOT initiatives, however the pre study implicated that they have been working with IOT for some time. Therefor they implicated suitable for a benchmarking study. Huawei Technologies are investigating at how the mobile network needs to be developed for the different IOT applications. Technologies primary work with the development of connectivity in general, referring to the development of 3G8, 4G9 and 5G10. When it comes to 4G, Huawei Technologies primary work with; M2Es, base stations, antennas and transmission, servers and routers, that are all capable of 4G. Mobile systems need to be up all the time. Today it is 99% reliability. But now when the IOT solution for the cars is coming this puts up demands on the mobile networks. Since the car travels in a much higher speed, compared to normal traveling, they have to validate that the car does not lose the connectivity when travelling between pylons.

5.2.3. Evothings

Evothings was chosen on the basis that they are profiling themselves as IOT providers. They have built their business in their outlined IOT initiatives, and therefor they implicated suitable for a benchmarking study. Evothings is a small innovation company, consisting 6 employees. Except the CEO, they have two developers, and three professional programmers. They mainly work with producing mobile IOT solutions in the form of mobile applications and platforms, but they are also big within producing articles, tutorials, and so-called “open source” materials. They have two costumer segments: the enterprise sector, which consists of partnerships with companies both inside and outside Sweden, which is “mature” when it comes to IOT; and the consumer sector, where they have 10,000 unique users in 130 different countries. 3,000 of those are returning users, which use their products on monthly basis.

8 Third-generation mobile telecommunication, providing mobile phone services with transfer rates of up to 2 MB/s for

stationary systems and 384 kB/s for mobile systems. 9 Fourth-generation mobile services, providing mobile phone services with transfer rates of up to 1 GB/s for stationary

systems and 100 MB/s for mobile systems. 10 Fifth-generat ion mobile telecommunicat ion. Have not been defined, hence standards will be beyond the 4G.

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6 EMPIRICAL RESULTS In this chapter, the findings from the conducted semi-structured interviews are presented. The findings aim to provide and empirical foundation needed in order to be able to answer to the main research question.

6.1 Introduction to empirical results To get a deeper understating of this IOT initiative, several interviews were conducted. Both with employees directly connected to the IOT initiative, as well as employees semi-connected to the IOT initiative. On total there were 18 interviews conducted, with interviewees from four companies and one university. During the interview several focus areas was identified. Some of these focus areas were found to be that, Tieto as well as other companies, are:

Investigating in the ecosystems of IOT;

Starting to realize the use of partnerships; and

Investigating in approaching industries for the IOT.

During the interview several challenges when implementing IOT was identified. Some of these challenges were found to be:

Maturity in the market;

Complexities in the partnerships;

Complexities in the IOT solutions;

The demand of forming new operational models; and

The realization of that one cannot be everywhere.

Therefore, the following chapter has been dispositioned according to Figure 17.

Figure 17. The disposition of the empirical results chapter

6.2 Focus areas of investigation As mentioned, the interviews identified two key areas which companies now are investigating. This is summarized as: the ecosystems of IOT; and partnership possibilities. The findings regarding these two areas will be presented in the following section.

6.2.1. The ecosystems of the IOT

Interviewee A2 point out tree essential segments in need when developing an IOT service: systems integrators, service providers and cloud providers, and it is from which these they have developed their ecosystem. Interviewee A3 further explains the ecosystem. He sees an accurate meaning of forming a working ecosystem. He explains the following:

• The ecosystems of IOT

• Partnership possibilities

• Approaching industries for the IOT

Focus areas of investigation

• The market maturity

• The partner complexity

• The IOT service complexity • Internal changes in the business models

• The realization of that one cannot be everywhere

Main challenges when implementing IOT

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“When it comes to Industrial Internet, only a few of the existing solutions consist solely of the company's own software and hardware. It's more common, and ultimately inevitable , to fit several technologies together to get the required functionalities”.

And this is partly one of the reasons why he believes that all the IOT solutions or services are in need of an ecosystem. Each partner company, specialists in their field, can provide the IOT service with the best thinkable technology, while continuing doing what they do best.

Both Interviewee A2 and A3 see great possibilities with the ecosystem. Interviewee A2 explains, that they uses the ecosystem when they describe their way of thinking and working to the client, and how Tieto can be an enabler technically for them to be able to change their business models. The ecosystem provides a good overview of the process, and helps then when describing the IOT initiative.

Tieto’s Industrial Internet unit has, in a way to organize the complexity around IOT, developed an ecosystem that explains how they are working with IOT. The idea behind the ecosystem is combining the knowledge and experience yet existing at Tieto, together with the “new thinking IOT ideas”. This by adding a layer of IOT application to the existing modules and things. The ecosystem can be found in Figure 18.

Figure 18. The ecosystem of IOT at Tieto Industrial Internet

However, not everybody at Tieto is familiar with the ecosystem of IOT. This puts creates internal constrains when pushing the initiative forward. This is confirmed during both Interviewee A1 and A4. And this is probably since they are connected to different department, compared to Interviewee A2 and A3.

Interviewee C1 is well familiar with the ecosystem. They see possibilities of expanding the value chain, in other word exploring the possibilities of the ecosystem. This is also identified during the interviews with Interviewee B1, B2 and B3. They recently published a report called “Connected Things” (2016). In the report the present their way of thinking regarding the ecosystem of Internet of Things, see Figure 19.

Their ecosystem is based on three main players; the lead users; the enablers; and the innovators. Lead Users are the costumers and companies that adopt the new technology before others. Can also be referred to as “early adopters”, and is leading the way in their respective industry. Enablers are companies that ensure the Internet of Things solutions. They provide e.g. provisioning, installation, security and connectivity. Innovators are the companies focusing on entrepreneurship and technology. They are the companies that actually develop the new IOT applications and devices. The ecosystem is later on controlled by the political and regulatory environment.

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Figure 19. Key roles in the IOT eco-system at TeliaSonera (TeliaSonera, 2016)

This is TeliaSonera’s way of communicating with their costumers, when it comes to IOT. However, one can conclude that this way of working is not common, at least not yet. But this is their way of launching an initiative and getting their costumer to start “thinking in a new way”.

6.2.2. Partnership possibilities

Tieto has realized that co-creation with partner and their clients are becoming increasingly important in the matters of providing them with new improved services, which fully takes the best technologies in account. The business model builds on the dependence on the client. This means that as long as the client is successful, so will Tieto be. This creates a strong partnership, and validates that Tieto always is doing their greatest in each case for the client . Interviewee A4 sees this and explains that this is partly one pf the main idea behind HSB Living Lab:

“Being collaboration partner in HSB Living Lab means that we open ourselves even more of both internal and external borders. Users are in focus and we can test new solutions and allow residents to influence developments at a very early stage. The idea behind jointing under this type of partnership is to collaborate with other companies and researchers in the processes for open innovation”

Interviewee A2 explains the plans for future of partnership with M2M-in-a-Box. He expects Tieto to work close to their client, in able to do joint forecasting, investigate in which customers they are reaching out to, which segments are what areas they are expected investigate in and so on. This puts demands on Tieto to work in a tight relation with the client, to assure that the roll -out and the selling is actually happening. But in order to validate that the client focuses on them, and not the other collaborative companies in the project, is that they can add value to the project. This can be done in several ways, but is mainly based on developing the existing products.

Interviewee B1 and B3 emphasizes the importance of the partner network, and what possibilities the network is providing them with. Interviewee B1, B2 and B3 opinions are that believe that the partner network has helped TeliaSonera when approaching new industries and new partnerships. Today 41 companies are connected to the network, and both Interviewee B1 and B3 look positive at this. They say that the partner network enables “more knowledge around the table”.

Interviewee B4 also talks about the different ways of joining under partnership with them. Interviewee B4 explains, in a way to organize the partner network they are now launching a new model for partnerships. This includes partnerships under four different classifications: Solution Partner, Business Partner; Reseller Partner or/and Innovation Partner, see Figure 20.

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The main idea with the different classifications is that the partner and TeliaSonera can form a joint strategy for how they together will approach the market, and they strongly believe that this approach will help them organize the whole partner network.

Figure 20. TeliaSonera IOT Partner Program

The different classifications are based on their so called “go-to-market-strategy”. This means that e.g. Tieto can be a solution partner and that TeliaSonera is responsible for reaching the market. This is moreover found in the M2M-in-a-Box case, were Tieto works as an enabler and TeliaSonera is responsible for marketing the product. This strategy does not however mean that the same company can join under different partnerships. E.g. being a solution partner and business partner is absolutely possible, and it is only the manpower that is holding back the development of the partnerships.

According to Interviewee C1, Huawei Technologies does not really work with partnerships. This is the case, since they are working as “enablers”. Therefore, they do not feel the same need to focus on this. They already have a strong partnership with their existing clients, and he believes that this will not change. In this setup the clients is more or less responsible for the development. He explains that:

“We deliver what the customer is asking for. One can say that the customer has a strong action on what we should focus on. So, even though many come with new innovative ideas , we work very focused with the connectivity.”

When it comes to Evothings, the partnership is also highlighted. They develop IOT solution together with companies, which are investigating in the area of mobile IOT solutions , creating partnerships in all kind of different setups.

All this kind of partnerships is relevant for the interviewees companies, but in different matter. Evothings is striving hard to enable innovation partnerships, while Huawei Technology is satisfied with being the enabler. Tieto on the other hand, which is one the leading consulting companies in the Nordics, sees possibilities in being everywhere.

6.2.3. Approaching industries for the IOT From Interviewees A1, A2 and A3, it is known that they are investigating in the different industry segments that the concept of IOT can be applied within. However, a conclusion regarding which area to focus the investments within is not found. This has led to that the company is investigating further on this matter.

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When it comes to Interviewee B1, B2 and B3, they see it on a different way. Ffrom internal research they have estimated the most promising industries within the car industry, and this is partly due the reason why they have launched their second IOT initiative, Telis Sense, within this industry segment. Therefore, they are also doing essential research within the area to; discover “the possibilities of the car industry”. Also they believe that the learnings, which they gain through this, can later on be applied in other industry segments.

Interview C1 confirms this theory, and for his experience he has encountered several examples of where now the vehicle industry is launching IOT initiatives, e.g. Tesla 11 and Volvo12. Besides this, Interview C1 strongly believes in medical care, home care, fleet management and the vehicle industry, e.g. Scania13. This is confirmed by Interviewee A2, however he is missing the so called “success stories” in able to truly have faith in these findings.

Interviewee D1 strongly believes in the manufacturing industry and this is the segments where the value of the IOT solutions can be fast proven.

When it comes to Interviewee E1, he concludes by acknowledge that it is almost impossible to tell, which industry will have the biggest impact. This is all connected to each industry’s ability to adapt to the “new technology” or the industry’s possibility to change their processes. This is partly confirmed in the interview with Interviewee A1. He explains that when they launched the M2M-in-a-Boxsolutions, they had no idea that the first customer was to be the property manager of the churches. However, this area possess that more research are of interest for all stake holders involved.

6.3 Main challenges when implementing IOT There are many challenges that Tieto is on one or another way struggling with. The research has identified five main challenges: market maturity; partner complexity; IOT service complexity; internal changes in the business models; and one cannot be everywhere. In the following sec tion some of the issues highlighted will be presented.

6.3.1. The market maturity Interviewee A1 recognizes the fact regarding “maturity in the IOT market”. He experiating that both

them as a company, and their clients are having difficulties approaching the market. This is also confirmed during the interview with Interviewee A4. They express some confusion, since they do not

know what types of tools they are missing. They emphasizes that the technology is here, but

“nothing is happening”. And this partly is due to the maturity of the IOT market. One cannot force

the IOT services to the market, if not the clients and customers do not see a value in the solutions.

Interviewee A2 and A3 are experiating the same thing. But what they are trying to do is to get the

customer to understand the value of the IOT solutions. Interviewee A3 explains the following

regarding M2M-in-a-Box:

“The analytics toolbox gives companies the ability to explore and visualize their data with further capabilities

to include machine learning and advanced algorithms. In this way data turns into information that can speed up

business processes and open doors to whole new business opportunities for our customers”.

When then going to the partners, they have to manage to explains the value of a partnership like

this. The facts are there, however, the clients are not ready to invest in a service like this. Interviewee

11 Tesla has in its latest cars installed hundreds of sensors that communicate with the car. If something happens in the car, e.g. with

the engine, or is there if there are obstacles on the road, the car alarms the driver about on this. This information can the n be sent to the customer, service or developers at Tesla. They virtualize this information by an application in the car, where the driver can

also surf the Internet and listen to music via Spotify (Interviewee C1). 12 The similar solution can be found at Volvo (Interviewee C1). 13 Also Scania is enabling a mobile service for the vehicle drives. The drives can get information about how much the car consumes, way they drive, where they are, optimize mileage and driving behavior (Interviewee C1).

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A2 explains the importance of the M2M-in-a-Box project, and what it provides back to the

company:

Since we are responsible for the database and the platform, the partnership provides us with a monthly share.

This is based on between 35-55 SEK per sold service. Let us then say that the service is sold to 4000 churches.

That would give us around 200,000 SEK in monthly revenue.

Interviewee A3 explains that they see the potentials; however this is not validated when it comes to the customers. The progress of turning the maturity around is happening, but not in the pace that one would want.

Interviewee E1 does not believe that “Internet of Things” is just a buzzword. He emphasizes the fact that buzzwords exists due to its significance, and that it is rather a sign of something important and interesting “happening”. He continues and says that one they should always take buzzword in all seriousness. However, one should not always believe in “what is said about IOT”. From his experience, he sees many companies that are working hard with “connecting things that is not connected”. He also recognizes the demand from the consumer. So looking at that simple setup, one could argue that companies are ready and that there is a market for it. But there is much more to the equation. Interviewee E1 also recognizes the challenges in pointing out approaching industries. Regarding the future for IOT, he states the following:

“It is obvious that we will get more and more connected gadgets (i.e. IoT). But it will not happen overnight, and it will not happen at the pace and in the manner as all these “technology maniacs” believes. Some things will go faster than expected, and others will be slower than expected.”

He recognizes that it is much more, e.g. economic drivers, societal resistance, that plays a role and matters, when looking at the future for IOT and digital transformation. Interviewee E1 emphasizes that in some cases, even if the companies are ready, the consumer might not be and vice versa.

Interviewee D1 talks about the importance of maturity from the partner company. They are not able to drive their business forward, if not their clients are not ready for it. They demand the companies that they partner up with to be “IOT mature”, since they develop solutions that are IOT specific. This lead to that they are experiating much restrains when trying to sell their service to the clients. Must companies are so far just investigating the area of IOT, and have not reached the point of where they actually are implementing the IOT services.

6.3.2. The partner complexity

Interviewee A2 explains, partnership means that everyone involved, are dependent on each other. To validate that the partnership is tight and ongoing, a frequently dialog is of great importance. And, at the end one might have to question who has the biggest right to earn the biggest share, and who hold the responsibility when a service is not working. And when it comes to pricing, most of the partner deals are based that each company gets its revenue share 14. However, the partner relation generates complex situations and unanswered questions, e.g. how can companies validate that they receive their share of revenue? How can they validate that the revenue share, manage to climb its way back in the value chain? This kind of unanswered questions and dynamics makes it hard for companies to push the solution forward. Also, when looking at innovative solutions, different dynamics comes to surface. Interview A2 takes an example from the hospital industry:

“Many sees the benefits of people being medical treated at home, instead of at the hospital. Meaning that the last year could be spent at home, instead at a hospital. The life quality of a person dying could radically increase during the last year. But the development of this is being held back, since no one knows how to answer the question on who hold the responsible when something goes wrong? How should the hospitals systems integrate with ours, and how should we handle the support functions?”

14 E.g. M2M-in-a-Box, which has an initial cost and then is based on monthly payments. The revenues of these monthly

payments are divided within the partner relation, were Tieto gets their share and the client gets their share.

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Therefore, it might come down to ethical questions like “Who hold the responsibility?” and “What should happen is an accident is present?”. Both Interviewee A2 and A3 believe that these kind of questions need to be answered first, in able to drive the partner relations forward.

The customer’s fear of relinquish data and the fear of joining under “wrong” partnerships

Interviewee A3 explains, someone once said “data is the new oil”. This has led to that now the customers are starting digest this, and starting to draw conclusion about that their data may be useful. However, unless one manages access this data, no one can for sure know if it is of great use or the opposite. This has led companies to a quite tricky situation, where they are now experiating trouble when starting a conversation with the customer.

Interviewee A2 also point out the importance of partner loyalty, and that this come to the surface, if they want to invest in to several partners. Interviewee A2 continues, and explains that is might as well come down to that Tieto is not the right enabler for this. Even despite that the offering is exactly what the client is searching for, they might not be willing to invest due to competitiveness or uncertainties. And this of course has to do with the market, since everyone wants to be the leader in the market. Interviewee A2 provides an example in this matter:

The operators are often “terrified” of companies such as Microsoft, since they provide and deliver complete solutions. This place the operators as so called “BIT providers”, and many operators, such as Telia and Telenor, have higher ambitions then this. So in a way, they are completely terrified of Microsoft. Tele2 is acting a little bit different, since they have this “low price philosophy”, so they are willing to be a BIT p rovider. Therefore, one can say that the complexity of market puts a stop starting some partnerships, and one cannot start collaborations with everyone.

When one has a business model like the ecosystem provides it is important to create the right conditions for the partner. Interviewee A3 also states out the importance of being a trustworthy supplier. This can only be gained when the trust from the client is in place.

The client’s fear of cost, is driving away the sales

Interviewee A3 explains, clients’ are willing to invest in, but they hesitate since they are anxious of the cost. It has led to many companies do not make giant investments at a time, without investing in proof-of-concept15. When it comes to IOT, there it is the lack of standard, generally in the market. Leading to that there is not many proof-of-concepts. One way that Tieto today is reducing this situation, is to offer a “Business-as-a-service”. This validate that the initial cost for set-up is much lower, and companies that are interested in investing within IOT can do it for a much lower cost. Tieto’s main idea is therefore to be a partner in the process of change. They can provide the situation with capacity, in form of expertise, and during conversation find solution that fits both them as a partner but of course also the partner.

Interviewee B1 and B2 also see this problem. And this is partly why they those to launch the M2M-in-a-Box under the so called “subscription model”. This allows companies to start investigating the use of M2M/IOT, without doing a great investment.

6.3.3. The IOT service complexity

Many of the interviewees argue that the technique for IOT is “already here”, but the hard part is to get the value chain to work. Interviewee A3 explains this further, and says that the IOT services gets complex since companies under partnerships might have their standard for developing products, and proving support functions. This means that developer at on company has to cooperate with developer at the partner company. Leading restrains to be created, when developing the complete solutions.

Interviewee A2 says that they have identified several “value chain cases” where they can offer the Business-as-a-service concept, and takes an example of a machine manufacture:

15 is a realization of a certain method or idea to demonstrate its feasibility.

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“If one imagines a machine manufacturer, those who sell a machine that presses rims. After him comes someone which makes wheels and the sells wheels for automobile manufacturer. If we go to the person who makes the machine, and then say that you can then instead of selling each machine up front16, you can sell the machine as a service. By providing him with monitoring, he can predict maintenance and service, and secure income over time. By providing the machines with monitoring, you can in advance find out and get statistics about wh en you should do action, so that you keep your SLA17. The machine manufacturer definitely sees the value in a service like this. And so, we have described the value of he who makes the wheels. That they gets better access of the machines, he gets more even production, and he can in its turn provide information to the automobile manufacturer. So, if something happens, he knows this a lot sooner than now and how it affects the chain.”

Another example refers to a refrigeration supplier:

“Today, suppliers of refrigerators are missing monitoring of its refrigerators. Here we can convince them to start selling their refrigerators as a service. We provide them with monitoring of all their refrigerators; we provide one with statistics on everything that happens in the refrigerators, so that they know before they need to do the maintenance. I.e. they do not need to wait until the refrigerator is standing still and it becomes acute. Then they sign contracts with undersupplies, who distribute this data. I.e. someone who does on-site support etc. The clients have now created their own ecosystem of partners, and soon they can actually start making money of this. This since they are in the middle of the ecosystem, you they have access to all the information, and they do all the analysis of the data. And later on, they can take a small amount of money, for anyone who wants to join your network.”

It is clear that all stakeholders see a value in this setup and value chain. However, the setup contains some hard and complex questions to be answered. For example, “Where do you start?” and “Who can validate that a solution like this actually will work?” etc.

Interviewee B5 explains that the service (M2M-in-a-Box) is ready, and clients to them can order the product and right away start with “working with IOT”. However, since the product is developed under a partnership, the development phase of the product gets prolonged. They have already identified several interesting updates for the system. But the development gets prolonged due to the distant relations to the developers.

Evothings has mainly built their business due to the complexity of developing IOT services.

Interviewee D1 explains the main idea behind their product:

“It is a tool to quickly build IOT applications. We work with hybrid18 solutions, to shorten down the

development phase. This offers the developer a clear picture of the final product, right from the start and enables that the development phase can be shortened from months, to days, and even hours.”

Interviewee D1 continues, and states that even if these kinds of services are approaching the market, one can conclude that developing an end-to-end solution for IOT services, is quite challenging. Both seen from the technical aspects, since most services have to have a higher flexibility then compared to “normal IT solutions”, both also due to the value chain aspects.

6.3.4. Internal changes in the ongoing organization Interviewee A2 explains, the main idea that Tieto’s Industrial Internet unit is trying to get their clients to realize, it that their client must change their business models. This way of working is quite new for them, since one practically starts without a product to offer to the clients. Instead they are offering their expertise and knowledge, and their drive in being willing to create something unique for their client. This is confirmed during the interview with Interviewee A3. He believes that the biggest challenge is changing the operational models.

16 direct payment 17 Service Level Agreement, is a part of a standardized service contract where a service is formally defined. 18 flexible

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Since the ecosystem in the IOT solution is that complex, a change is needed. If they are not willing to change, there is not going to be an effective partnership. Interviewee A2 believes that the technology already is here. The difficult part is to change the internal business models. So far, no one has presented a business model that takes all stakeholders in consideration. This means that there are many good ideas on the market, but the economics and organizational processes have yet not been solved, but also looking internally.

Interviewee A2 also believes that the business model will be further developed, and instead of being based on how many devices you have; it will be based on actual consumption. Interviewee A1 mainly believes that this can be done by providing the client with so called success stories, by providing examples on were IOT has done major impact, and can be used as guidelines. Interviewee A1 continues, the idea with the cooperation is to continue develop their partnership.

Interviewee A1 emphasizes the fact that the complex IOT solutions and services are also creating demands on the ongoing organization. All the suddenly one must ask who is responsible for what. Even if he holds a responsibility for a client, the actual development might come from another department. This causes internal stress, even for Tieto as an enabler. This is where maturity and internal knowledge becomes a present issue. A company has to be ready, and have all the internal knowledge required to be able to understand the importance in the investment. This is nothing the Tieto can force the client. The drive to invest will come when the value of the service is seen. Interviewee 2 sees two main obstacles, both that the business models yet not have been formed, but also the complexity in the internal processes. And the major challenge, that Interviewee A2 sees, is changing the operational models.

Besides this, Interviewee A1 expressed some confusion regarding the IOT initiative. He experienced some restraints when trying to drive this initiative forward. And this, he says, is probably based on that the IOT initiative has different driving forces, depending on which department within Tieto one is working on. This is partly confirmed by Interviewee A2. The internal complication covers that the persons involved to the IOT initiative are located at different departments, and even different cities.

This is partly confirmed during the interviews with Interviewee A5 and A6. They work were insolated with the development of the products, and this is probably due the fact that they are located in Czech Republics. Therefore, they have their processes and their way of pricing the product that most likely differ compared to the rest of Tieto’s organization.

6.3.5. The realization of that one cannot be everywhere

The main strategy that Interviewee C1 is working with developing their skills within platforms. This since they see a strong development within this field. Interviewee C1 point out the development19 of the 5G, which puts another focus for them to be able to deliver products that are more stable and in particularly quicker.

Interviewee C1 emphasizes that this will continue to grow the same, the following 10 years. This puts pressure on Huawei Technologies to keep up with the development, and be able to deliver many new and innovative ideas. This is all in a way connected to the development if IOT, since these applications puts enormous pressure on the existing systems. Interviewee C1 explains, that since the connectivity, as well as the sensors, is becoming such a low cost 20 for a company it get easy to add this to an application.

Interviewee C1 emphasizes, since the development of IOT services is going so fast, the best thing to do in a situation like this is to focus on one’s core competences. At some point companies have to realize and understand its own capabilities, and states that:

“No company can be everywhere, ultimately one must choose”.

19 The mobile data growth, which has increased 40-50% in the world the last few years. 20 e.g. Volvo with over 100 sensor that measures all sorts of things

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The future of the IOT

Interviewee A3 believes that the big challenges when going forward is how Tieto as a company choses to attack the challenges that comes with IOT services. And how Tieto manage to get other companies to work in a more open and innovative way. Some companies invest in an isolated part of their production, were they have great knowledge. This lead to that the implementation phase gets quite prolonged. Interviewee A2 believes that some companies already is done when forming a strategy, however, many have not.

Interviewee B1 explains that their IOT initiatives are just the first step into entering the market for IOT services, e.g. the initiative with Telia Sense. This service actually enables a growing ecosystem of services partners, e.g. now when insurance company can join and offer the user lower car insurance.

The challenges that Interviewee C1 see in the future is how they are going to develop the mobile network, now when the IOT solutions is much more demanding and more or less dependent on connectivity. When speaking of the joining under new partnerships, he definitely sees some potential for developing this.

Interviewee D1 explains, today Evothings is offering their services for free, as an open source. For the future they have to figure out if they want to continue like this, since is enables them great growth, or start charging for their services. When this truly comes to surface they are quite convinced how they are going to offer their service. Interviewee D1 explains that this will based on the “Software-as-a-service” model.

6.4 Concluding remarks During the interview several focus areas was identified. Some of these focus areas were found to be that, Tieto as well as other companies, are:

Investigating in the ecosystems of IOT;

Starting to realize the use of partnerships; and

Investigating in approaching industries for the IOT.

During the interview several challenges when implementing IOT was identified. Some of these challenges were found to be:

Maturity in the market;

Complexities in the partnerships;

Complexities in the IOT solutions;

The demand of forming new operational models; and

The realization of that one cannot be everywhere.

The areas possess interesting topics within the field of then implementing and adapting to IOT, and provide a good basis for further discussion regarding this matter.

6.4.1. Main insights To get a fair understanding for each company, it is essential to understand how they operate in the context of IOT. Therefore, estimation on how each interviewed company is working with IOT was made. See Figure 21 for an outline regarding this.

One can say that Teito mainly if focusing on security, analytics, devices and platforms. And one can say that TeliaSonera is mainly working with connectivity. While Huawei Technologies is working with connectivity and platforms. And lastly one can say that Evothings is working mainly with applications.

The red market areas in the figure, is according to the researcher, an IOT service that the interviewed company is not providing. It is esstential to understand, that these conclussion might

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vary depending on which person at each company one interviews, since every employee might have their view of how they are working with IOT.

Figure 21. Estimation on how each company is working with IOT

IOT Services

Tieto

Security

Analytics

Modules / Devices

Connectivity

Platforms

Applications

TeliaSonera

Security

Analytics

Modules / Devices

Connectivity

Platforms

Applications

Huawei Technologies

Security

Analytics

Modules / Devices

Connectivity

Platforms

Applications

Evothings

Security

Analytics

Modules / Devices

Connectivity

Platforms

Applications

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7 ANALYSIS AND DISCUSSION This chapter presents the results that were obtained during the research. This includes findings from the interviews rounds and the development of relevant theories. The analysis of the results is presented throughout the chapter.

7.1 Introduction to analysis and discussion To not disorder the structure of the study, the following section has been organized equally to the previous chapter. See the disposition of the discussion chapter in Figure 22 below.

Figure 22. The disposition of the analysis and discussion chapter

7.2 Focus areas of investigation The research identified three main areas where investigation is being made: the ecosystem of the IOT; partnership possibilities; and approaching industries for the IOT. In the following section each area will be discussed.

7.2.1. The ecosystem of IOT

The complexity around IOT services are also making companies investigate the possibility of IOT, meaning that they are investigating it they can broaden their IOT solution portfolio. Here the ecosystem of IOT, see Figure 3, comes to great use since it outlines the segments of most importance, of which companies have to investigate in order to set up an IOT service.

The Internet of Things forces companies to start elaborating and start partnerships. All companies and industries have their way of looking at the ecosystem of Internet of Things. Nevertheless, IOT services generate several complexitivities, since companies have to decide whether to partner up with other companies, or develop internal. Only a few companies today have the possibilities to deliver an IOT solution that covers all segments in the ecosystem. Even if companies not today can deliver the whole solution, they might be able to deliver major parts of the solution. This is why the use of partnerships now comes to the surface. Not every large IT consulting companies have this possibility, and at some point one must take a decision. This is also validated by Interviewee C1. One can choose to put the company in the middle of the ecosystem, since the greatest profit can be found being responsible for the ecosystem, or settle with being an enabler in another ecosystem.

Interviewee C1 says that they ‘focus on what they do best’ and this is what one could call an enabler. This way, they are able to focus on being innovative in what they already do, and still be working with IOT solution.

• The ecosystems of IOT

• Partnership possibilities

• Approaching industries for the IOT

Focus areas of investigation

• The market maturity

• The partner complexity

• The IOT service complexity • Internal changes in the business models

• The realization of that one cannot be everywhere

Main challenges when implementing IOT

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7.2.2. Partnership possibilities

Today, collaboration is starting to become essential for companies to not fail in a market. Developers, network operators, hardware manufacturers, and software providers need to come together to make it work (Vermesan & Friess, 2013).

Companies need to innovate more freely. Cooperation has long been a low-cost route for competitors to gain technology and market access. This can be summarized under the term “competitive collaboration”, and includes joint ventures, outsourcing agreements, product licensing cooperative research (Hamel, et al., 1989). If companies would welcome open innovation in bigger matter, more innovative ideas would emerge the company, giving them a strong market portfolio.

If companies put their selves in the middle of the ecosystem, they have to investigate which segments they are able to deliver, and which is suitable to start partnership with a company that actually can deliver the solution. In this discussion the partner relation comes to great importance. From the empirical finding, one can conclude that companies today are not able to deliver a full end-to-end solution. Dear (2016) argues that companies should focus on their core competences, and outsource “the rest” of which they are not capable of becoming market leading within. This provides a good argue for the use of partnerships, and is partly confirmed during the interviews.

7.2.3. Approaching industries for the IOT

Interviewee E1 believes that prophesying promising markets is almost impossible. However finding shows that companies have done some research with in the field. Alstyne, interviewed by the MIT (2014), believes the IOT applications can be found everywhere. Atzori, et al (2010) argues that the most obvious effects of the IOT introduction will be visible in both working and domestic fields. Jankowski, et al (2014) argues in her joint article that they see eight promising areas: wearable devices; connected cars; connected homes; connected cities and the industrial internet. While IDC (2014) possess that the most promising industry segment can be found in the transport & utilities segment, with a total market potential is estimated to a total 7,373 Million Euros by 2020, see Figure 23. A segment which Jankowski (2014) meantions, but not as the most promissing.

Figure 23. Market potential divided by industry segment (IDC, 2014)

At the same time Garter (2013), forecasts the economic value-add to be forecasted to by $1.9 trillion across sectors in 2020. These sectors mainly include manufacturing (15%), healthcare (15%) and insurance (11%), while also arguing that “Connected Kitchens” has the potentia l to save the food and beverage industry 15% annually (Gartner, 2013). And lastly adding, that by 2020 a quarter of a billion vehicles will be connected to the Internet (Gartner, 2013). Same company, possing different messages.

Transport & Utilities 28%

Manufactuirng 16%

Retail 7%

Public Sector 5%

Other 31%

Consumer 13%

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When it comes to estimate approaching industries, one must understand that the development of IOT is dependent on much more than just facts and figures. Knowing all this, it is impossible at this stage to know which which segment will develop fastes, or which segments holds the best benefits for a company. It all depends on companies’ ability to adapt to the emerging market, and if they manage to fulfill the customers demand. With these curcumstanes it is impossioble to know what will happen in the future if IOT.

7.3 Main challenges when implementing IOT The research has identified five main challenges: market maturity; partner complexity; IOT service complexity; internal changes in the business models; and one cannot be everywhere. In the following section each area will briefly be discussed.

7.3.1. The market maturity

During the end of 90s a new legislation were introduced to the market. The legislation covered the energy market, that instead of invoicing on estimation, the invoice sound be done on actual data. This initiative was driven by the government. Now, when Tieto and many other companies, are trying to drive the IOT initiative into the market, it is going slower. This is probably since this case covers business value, and not legislations, meaning that companies still have time to argue and discus the business models. Also, since there was a legislation, companies were forced to act. In this later case, companies are not forces to act. This is also confirmed by Govindarajan et al (2011), which argues the all change within companies happens, because of companies are forced to it. The force might be customers, competitions, advantages in science and technology or by governmental regulation.

Many says that both drivers and enabler are ready (Capgemini, 2015; Forbes, 2015; Intel, 2016; Business Insider, 2014; ABI Research, 2013), however many of the empirical findings emphasizes that the companies are not ready. Evothings might be categorized as a company which is an innovator or early adopter, when looking at Rogers (1962) framework “Diffusion of innovation”. However, this also lead to that the market that are aiming for is extremely small, see Figure 7. IDC’s (2015) framework “Digital Transformation Maturity Scape” is built on the same way. One can say that it is a simplification of the “Diffusion of innovation”. IDC (2015) policed their overall forecast of the so called Digital Transformation and concludes that most companies are still acting as either a digital explorer or a digital player. See Figure 24.

Figure 24. The IDC’s Digital Transformation Maturity Scape Forecast 2015 (IDC, 2015)

This implicates that several action is in need to be taken, before most companies can even participate as a digital transformer. Unfortunate, at most situations, the ability to implement actually comes down to the organization. If the organization not is ready for the technology, there is nothing

Digital Resister 14%

Digital Explorer 32%

Digital Player 32%

Digital Transformer 14%

Digital Disrupter 8%

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a single man can do. Looking at Gartner’s Hype Cycle from 2014 (see Figure 25) one can see that they have categorized Internet of Things with a dark blue circle at the very top of the Hype Cycle. That means that the hype for the IOT is right now, but the breakthrough within organization can first be found within 5-10 years. The curve includes technologies such as Big Data; Energy Harvesting; Connected Home; and of course Internet of Things. According to the curve, Big Data is ready for the market in less than 2 years. This means that customer know how to address it, and that they have formulated strategies how to proceed. When looking at the architecture for IOT, one can see that they have categorized it with a light blue circle approaching the top of the Hype Cycle. That means that the hype for IOT Architecture is not yet here, and when it is here, the breakthrough within organization can within 2-5 years. This means that the components IOT are coming. The architecture of Internet of Things is taking place, and eco systems are being presented, and even though the curve mostly dark blue, the future of IOT is approaching. (Gartner, 2014)

Figure 25. The Hype Cycle for the Internet of Things in year 2015 (Gartner, 2014)

Due to the adoption rate if innovation some implementation can already be seen, and companies such as energy companies has been working with this for a long time. This implicates that companies like them are more of a so called digital transformer, or can even be categorized as digital disrupter. Maturity and knowledge is the two main challenges when it comes to the implementation of the IOT. This was also confirmed during the interviews, that the companies are missing fundamental knowledge. But if companies would stop for a second, and really think about what they can do in able to implement the IOT, they might leap some steps on the maturity scale. However, one important fact that Gartner (2014) point is the fact that if there are too many unanswered questions around the commercial capability of an evolving technology, it may be better to postponement the research or investment until others organizations and companies have proven tangible value.

7.3.2. The partner complexity

To be able to cherish from IOT, it is needed that more than one stakeholder is putting pressure in the progress (Rosengren, 2016). Companies need to transform from being a digital explorer to an digital transformer (IDC, 2014). Companies to implement the ecosystem of IOT, are more or less forced to enroll a partnership with other companies interested in investing in the IOT services.

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The researcher finds great use of categorizing the different kind of partnerships under the categorized posed by Interviewee B4. This way of categorizing the partnership provides a stable ground where the expectations are well outspoken and clarified. In each ecosystem each companies at least plays one role, but roles are possible (ITU, 2012).

This is based on that the theories are well outspoken and focused, and is argued by Drucker (1994). This can be seen as an initial step towards taking over the market of IOT. Hamel, et al. (1989) argues that one should collaborate with competitors and trough this constellation, win long run. Companies must start in some edge of the equation, in able to be able of delivering a bigger solution. However, companies much be aware of the many complexities that in known when partnering up with other companies.

When establishing a partnership like this, this might cause internal confusion since partner models not yet has been fully established. To ensuring a strong partnership has the possibilities to gaining a trusted role in the market. This emphasizes the importance of transforming view of looking Company-Customer relationship, and forces companies to turn the so called cost perspective (Weichselbaum, 2015). This is about developing business and “without noticing” making money in the background. But since the models still lack full development, companies must be aware of the fact that the transformation phase might take some time, and has been recognized in several cases (Iansiti & Lakhani, 2014).

7.3.3. The IOT service complexity

Network management technologies will have to address several important issues, including security, performance and reliability (Bandyopadhyay & Sen, 2011). This means that the support models must be the same in the organization, and companies has to device who is responsible for what. This emphasizes the fact that every organization has an ideal theory for their business (Drucker, 1994). This means that the network management service employs several tools such as tools, applications and devices to assist monitoring and maintaining networked in the IOT services (Bandyopadhyay & Sen, 2011).

Security is particularly important when developing an IOT service for another company (Vermesan & Friess, 2013). Risk has a huge effect on all segments in the industry. It impact on: costs, customer satisfaction, brand recognition, public perception and security (Callender, 2016). It is well argued, both by the interviewees and by the industry, that the security demand questions are deeply underdeveloped. This means that even though the technology for IOT exists, the security for it does not. An example is the Cloud Services. Cloud-based processing requires a new generation of communications processors, which are able of keeping track of all connected devices, communicate with them and translate their functionality into useful services. The idea is clear, but the real issue to solve is building s secure network that can keep up with the demand (Karimi & Atkinson, 2013). Intel (2016) said during a seminary in the beginning of the year “IOT devices are likely under the biggest risk, since many of these devices and appliances are not subject to frequent software updates”. Due to these circumstances, one might say that the development of the complete IOT solution, will properly take much longer than one might expected.

Most of the implementation will be done on a development platform, this mean that most of the development is dependent of developers. Therefore, the developers have to develop in the same type of tools and development solutions. The work done across the IOT platforms playing a key role for future deployment (Vermesan & Friess, 2013). However, the main challenges are that most companies have their own support functions; their own business models their own interface and so on. The IOT solutions and services both lead to technical complexity and business complexity.

7.3.4. Internal changes in the business models Much can be said about Internet of Things, and examples can be found worlds wide. Just like all innovation, IOT demands change. So far, many argue that “the future of IOT is not here yet”. That might be the case, but companies much understand that, change within organization does not

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happen by itself (Govindarajan, et al., 2011). But how does a company really cherish and implement this new approaching technology? It is therefore of great importance to look at the economics of Internet of Things. Internet of Things is more or less forcing the companies to rethink their way of offering services and putting a price tag on it. Today most companies are keeping track on their KPIs21 by running reports at each month’s end. But now with the IOT technology, they can obtain real-timer data from “things” they never have expected before. This means that they can develop KPIs that is based on real-time figures and companies can provide new and improved services for their clients (Kavis, 2016). The IOT technology provides both the customer and suppliers with real-time updates on consumption and usage.

However, not all industries are adjusted to this real-time data. For example, forecasting production and predicting demand.is highly dependent in commodities trading. But the real -time time data can actually be translated into forecasts. By providing wind turbines with sensors they can measure wind, vibrations and weather patterns and automatically adjust turbine blades to optimize energy outputs. By then combining data feeds on local weather conditions and patterns, the supplier is left with a data ready to be analyzed. By applying machine learning algorithms to the data, accurately forecast on wind energy output can be done for future months (Kavis, 2016). This is illustrated in Figure 26 below.

Figure 26. A simplified description of estimating future demand on present data (Kavis, 2016)

Companies are now investigating into the matter of starting to offer services according to the so called “tiered pricing model”. This means that customers pay a low fee for a basic package of the service, and then there are tiers of charges for various other services.

This model can be applied in several industries, and one example is the mining and oil industries. To predict how much they can extract from the mine or oil rig, producers can inspect atmospheric attributes. Another example is livestock producers. To predict the amount of meat that they will produce, they can compare an animal’s growth against historical patterns. By doing accusations on real-time data combined with historical data, companies can do more accurate forecasts and reduce or even eliminate the “speculation factor”, which drives down the cost. This both drives down the cost, but it also provide the company with the opportunity to outperform their competitors, giving them a competitive advantage.

New pricing models are being introduced

Each IOT service has to have a price model that reflects the product. One cannot just launch a product and hope that is sells for it selves. This should be based on simplicity. IOT allows real-time tracking new business models for making revenue to be introduced, and this can be found on many new cases. For example, insurance companies can offer a lower pricing model to their customers who connect to their IOT solutions. This since they provide real-time data that can prevent unfortunate events, or improve response times if they do happen and thus reduce collateral damage. Also, the real-time data sent to the insurance providers gives them a better understanding of a customer’s risk profile. This means that they can offer lower rates to lower risk customers (Kavis, 2016). The examples are many and companies are investigating how the use of new pricing models can help them accelerate their IOT businesses. Some alternatives as previously mentioned were:

21 Key Performance Indicators

Real-time data + Storaged data

Applying machine learning algorithms to the data

Accurately forecast for

future months - based on

realtime data and storaged

data

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Micropayments; Pay-Per-Use; The Subscription Model; The Membership Model; Freemium/Premium; Open Access; Peer-to-peer (P2P) (Celaya, 2016).

Here companies have to choose which one they find most suitable for their service. At Tieto there are several sectors using the so called “Pay-Per-Use” model. This allows them to invoice their customer at the actual use of a service. When Spotify came to market, launched they so called freemium/premium service, and PayPal started with the micro transactions and gyms are using the membership model22. When choosing a revenue model one most understand what value it reflects back to the customer. When it comes to M2M-in-a-Box, they have launched it with “The Subscription Model”. The service is a so called “Business-as-a-service” offering. Instead of doing a large investment, companies are offered monthly subscription of the service, and the fixed fee is based on the amount of sensors. Many sensors increase the cost, while fewer sensor decreases the cost. This provides companies and organizations the possibility to explore the potential of M2M and IOT.

The researcher find use for all of these models, since it allows the offering to be customized based on the service.

7.3.5. The realization of that one cannot be everywhere

It easy to get carried away, and think that the company will deliver the whole solution. The experience from the interviews gave the impression that, being responsible for fewer IOT application, such as application, connectivity etc., gave lower stress at the internal organization. It gave them an easier focus to deliver their IOT service to the best and validate that they were progressing within the area of IOT. Dear (2016) argues that companies should focus on core competences in order to save money, time, and risk. This includes not focusing on all the segments of an IOT services (Dear, 2016; Miller, 2016). Today there is no company of being able to fully provide the complete IOT solutions. This due to that the ecosystem is so widely spread, and that service models of IOT can be found in almost every segment. At this time, companies must understand that it is not possible to provide the whole “all by themselves”. This is one of the most fundamentals questions most art-ups to SMEs to corporate behemoths (Dear, 2016).

The hard part to understand is that companies want to deliver this. But both from the empirical findings, it has been shown that this is, so far, not possible. Therefore, the realization of that one cannot be everywhere, must appear. Even if the “we do it ourselves” attitude, might take some time to overcome, it has to be past come in able to cherish from IOT. This is all about changing the organization, in able to deal with digital transformation (Miller, 2016).

7.4 Concluding remarks Tieto, TeliaSonera, Huawei Technologies, and Evothings are all seeking, together with ma ny other companies, for new innovative way to offer IOT services. However, as said, new complexities emerged when analyzing IOT solutions and services.

There are many things holding back the market. Some of these are the maturity; both within the companies and the clients, and others are complexity with in the IOT solutions. But companies must understand that they cannot be everywhere. The experience from the interviews gave the impression that, being responsible for fewer IOT application, such as applicat ion, connectivity etc. (See Figure 4Error! Reference source not found.), gave lower stress at the internal organization. t gave them an easier focus to deliver their IOT service to the best and validate that they were progressing within the area of IOT.

From the finding three main challenges at Tieto has been established: is that the client has a fear for the cost, a fear of relinquishing data, and fear of partner up with the wrong company, leading the

22 empirical finding

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sales to get driven away; and lastly there is challenges is formulating the IOT solutions, since the solutions is so complex; internal and external maturity in combination with the adoption rate are slowing down the process; and IOT forces companies to re-think their ecosystem and their way of doing business.

Even if “nothing is happening right now”, something will happen in the future. In this way Tieto, as well as the other companies has to be prepare. If IOT were coined 1999, one might ask why a leading IT consulting company have not mad a bigger move by now. In the following section, the researcher presents drivers found and suggestions on approaching industries for IOT.

One can say much about the market for IOT, but one cannot hide or the fact that most signals tend to sign that the market is not mature for IOT. One of these facts is looking at Gartner’s Hype Curve. As said, it is estimates the market to be mature within 5-10 years (Gartner, 2014). And one cannot just overlook the fact today most companies are still categorized as either “digital explorer” or “digital player” (IDC, 2015). This can also partly be confirmed during the interviews. The initiatives that have been lunched are in volume still quite small and to be able to reach a broader marker, a broader initiative has to be taken.

When it later on comes to the partnerships much can be said. Today, the fear of relinquish data and losing business opportunities is putting up a bigger resistor, then the drive of be willing to invest the data. At the same time, the “early birds” of IOT is trying to get their clients or customers to change their operational process, and join under partnerships.

There are also complexities when it comes to the actual in the partnerships, both to answer questions like “who” will deliver “what” and “who” holds the responsibility, as well as the fear of joining under “wrong” partnerships. This lead to that the sales process gets stuck, and that the partnerships never to be created. This causes internal stress within the sales organizations, both internally between departments, but also externally to the client. Employees recognize that the “solutions of IOT services is complex”. When it comes to the technical solutions, some complexities are still too present. Just take the security aspects, or the paying model complexitivity. Karimi & Atkinson (2013) that the market is still lacking standards and this issue is also brought upon during the interviews. On top os this, most companies are still categorized as either “digital explorer” or “digital player” (IDC, 2015) when it comes to digital transformation. And looking at the consumer segment, the majority of people (87%) have not heard of the term ‘Internet of Things’ (Forbes, 2015).

To be able to adapt and implement IOT, these resistors have to be oven come. And today, no one knows when that is going to happen.

7.4.1. Main insights

All around the market, one can read about investments being done (Business Insider, 2014). This lead to that, day by day, more money is added to the market of IOT. While this is happening, the cost for sensors is declining, leaving an enormous potential to within the field (Capgemini, 2015). Through the use of Cloud Services, companies now can implement the services easier than even, and have a system up and running within minutes (Business Insider, 2014). The value of analytics is seen all through the market, and companies are starting to realize that “data is the new oil”. Due global competition, the market is now forcing companies to innovate (Capgemini, 2015) and everyday there is a new report about a promising industries, or business segments. But one has to stay realistic, and questionize the information.

In 2008, there were already more objects connected to the Internet than people (Cisco, 2013) and ATMs, which is considered some of the first IOT objects, and went online as far back as 1974 (Intel, 2016). Energy companies have been working on this for 10-15 years (empirical finding). It time to take a step back and think. What have this society of over informing done with our perspective? No one can say for sure what will happen in the future, one can only say about what is happening today.

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Worth mentioning is that developing a strong IOT service requires different approaches, and is dependent on several segments. All of the six areas are present, when developing an IOT service. However, there are a few areas that one must pay some extra attention. These areas has been identified and presented in the section below:

Security – needs to be built in, and be secure. One cannot over look that fact that most

services are dependent on a good and stable security.

Partnership – Accelerate in the market through the use of partnership. However, the partnership has to tight and mutually. At the end it all has to works, such as things, sensors, communication systems, servers, storage, analytics, and end user services.

Tight development and standards – demanding IOT solution demands complex solutions. The way of working is highly dependent of a joint development phase.

Open innovation – Emphasizes the companies has to start collaborate in new more

innovative way. This by launching ventures, events, hackathons, and so on.

The importance of choosing a revenue model – The payment has to be smooth, both for the end user but also for the companies launching these kinds of services. The payment models have to be well thought trough, to validate that the revenue manage to climb it way back in the value chain.

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8 CONCLUSIONS AND FUTURE WORK

This chapter contains discussions around the research conclusions and implications, and recommendations for future research.

8.1 Research questions The purpose of this thesis was to investigate how IT consulting companies can implement and apply the concept of IOT in the context of digitalization, and what type of challenges they are facing. To be able to fulfill the purpose, the main question “How do companies, within the IT consulting industry, adapt and implement Internet of Things?” was formulated. This was operationalized in the context of a case study of a Swedish-Finnish IT consulting company. In the following section, the findings and conclusions found during the research will be presented, and the main question will be answered.

8.1.1. Research Question 1

What are the main aspects companies, within the IT consulting industry, are investigating when it comes to IOT?

The research identified three main areas where investigation is being made: the ecosystem of the IOT; partnership possibilities; and approaching industries for the IOT. In the following section each area will briefly be described.

The ecosystem of the Internet of Things – The complexities around IOT services are making companies investigate the ecosystem of IOT, and companies are investigating how to broaden their IOT solution portfolio. Companies are starting to realize that the best profits found, is if they place themselves in the middle of the ecosystem. Here companies have the ability to drive the ecosystems and partner network in the aim they like.

Partnership possibilities – Companies are also starting to realize the use of partnerships, and that they might be required to join in one, if they want to provide an end-to-end IOT solution. Here they can be an enabler (solution partner), a business partner, a reseller partner or an innovation partner. The possibilities for joining under partnerships are more or less endless. It is only the companies that hold the limits.

Approaching industries for the IOT – No one can for sure know which segment which hold the most promising IOT solutions. The industry that will provide the “best” solutions is the industry where the implementation phase is the easiest. And so far, many small examples can be found in many industries. While companies within the energy market has been working with this for 10 -20 years. Therefore, forecasting approaching industry segments is as easy as to say which ones will not succeed. No one can say for sure, and this is well connected to the possibility to adapt to innovation. Some companies and industries be seen sooner, while other rather later.

8.1.2. Research Question 2

How have companies, within the IT consulting industry, changed their way of working, when it comes to IOT?

It is well argued that the IOT forces companies to re-think their ecosystem and their way of doing business. Even if most interviewees has not identifies major change in their way of working, the researcher founds implications of where changes has been made. The IOT initiatives have changes the way they think around technology. This since the services is so much complex and massive then they used to be. As a sales person, one cannot co to a client without understanding the background of an IOT solution.

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Therefore, the findings point on that many of the interviewees has changes there way of thinking when it comes to services. Now new dynamics is being present at the market, and this forces them to seek more outgoing approaches. Companies that earlier worked with closed innovation, is now investigating the use of open innovation.

8.1.3. Research Question 3

What are the main challenges in the process, when adapting and implementing IOT?

Companies are searching for new innovative way to offer IOT services. As mentioned, there are many things holding back the market for IOT. In the following section, the found challenges will be presented. The research has identified five main challenges: market maturity; partner complexity; IOT service complexity; internal changes in the business models; and one cannot be everywhere. In the following section each area will briefly be described.

Due to maturity, the market is not ready – internal and external maturity in combination with the adoption rate is slowing down the process, both within the companies and the clients. Most companies are still categorized as either “digital explorer” or “digital player” when it comes to digital transformation and Gartner (2014) has estimated the market to be mature within 5-10 years (Gartner, 2014). The client has a fear: for the cost, for relinquishing data, and for partner up with the wrong company, leading the sales to get driven away and causing internal stress within the sales organizations.

Complexities in the partnerships – this is due to complexities of answering questions like who will deliver what, and who holds the responsibility. The complexities are found in: the customer’s fear of relinquish data; the fear of joining under “wrong” partnerships; and the client’s fear of cost, which is driving away the sales.

Challenges when formulating the IOT services – the IOT solutions generates enormous complexitivities, both when working with forming a working partnership, but also when taking take of support centers, enable standardization in the development field. Besides from that there are still complexities in the technical solutions were e.g. the privacy and security concerns are still too big of a deal, as well as that the IOT market is lacking of standards.

IOT services demands internal changes in the business models – this means that companies has to start charging services in a different way, and new pricing models are being introduced. The IOT services also include staring to collect and analyze data, in a way that companies might not be used to. In either way, the biggest change is starting to offer things as a service, instead of a one -time purchase.

Companies must understand that they cannot be everywhere – Developing a strong IOT service requires different approaches. IOT forces companies to re-think their ecosystem and their way of doing business. Companies have to realize that the IOT services are demanding and that one cannot deliver an end-to-end IOT solution in all industry segments. This also includes the different components of the products. Companies much realize that they are in one way obligated to join under partnerships, and that they have to start with focusing on what they to best today.

8.1.4. Main research question

How do companies, within the IT consulting industry, adapt and implement Internet of Things?

New dynamics is being put on the market, and companies are forced to re-think their way of working with innovation. Even if a direct adaption is not made, companies have changed their way of offering services. They are, or are starting, to realize that IOT solutions demands complex solutions. Through innovative use of technologies, early implementations are already arriving on the market. But the majority of all companies are identifying challenges when implementing the concept. Today, it is few companies that can provide an IOT end-to-end solution. This due to the great complexity around the IOT service or application, and that many companies are missing knowledge

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of in which industrial segment to invest. This forces the companies to re-think their go-to market strategy and their way of working with innovation.

Many companies today are experiating big challenges when trying to offer the whole offer around IOT to its clients, and this due to breadth of their product offerings. Therefore, ecosystems and partnerships is a well discussed topic, and companies are changing their go-to market strategy and launching initiatives to joint under collaborations.

But what happened to the pricing models when these constellations are created? Some argue that today it more expensive to invoice than to deliver. These IOT solutions demands a new dynamic pricing models, and companies often end up in discussion this in such matter, which prolongs the process from-idea-to-market-phase.

IOT guides to a new innovative way of working with business and leading new business models to be introduced. Companies are questioning internal knowledge, within the area of technology, but also the external technology. Is it possible to outsource some part of the production? Or is better to join under partnership?

When it comes to implementation, companies are exploring in the dynamics of the ecosystem of IOT. In combination with this, they are investigating if the technology of IOT is ready or not. This means that even though that the “concept around IOT” is ready, the components might not be ready. Nevertheless, the challenges are just not technical implementation, the fact that the IOT services is a head of the technology is one small part of the matter, and the discussion regarding maturity of the market comes to surface.

8.2 Implications and concluding remarks In this section the conclusion of the discussion around the findings that has been made throughout the study and the possible impact these findings may have within the field of IOT. The results implicate to contribute to three perspectives: industrial; research and sustainability perspectives. However, the researcher also found implications connected the individual and organizational level and at a functional level. Therefore, the following section has been organized according to the following three subheadings: individual and organizational implications; functional implications; sustainability implications.

One can at this point draw the conclusion that there is no consensus regarding who or what is driving the market forward. And the results implicated that there is no such actor in the market that can conclude this. The development of the market around IOT is highly dependent on regulations; the society and companies possibility of adoption.

The researcher finds arguments to point out guidelines for companies to “focus on the right things”. This research has contributed to this by providing guidelines on areas that a re of high importance when it comes to implementing and adapting to IOT. This section ends with expressing the experience gained during the research process and conclude recommendation researchers interesting in doing a similar study.

8.2.1. Industrial implications

The aim with this study was to provide a greater deep in the knowledge of implementing and adapting to IOT, and also provide guidelines to IT consulting companies, manages and co-workers investigating in the area of IOT. Therefore, the expectation is that the study has contributes regarding this matter, and also provides an explanation of the process when implementing and adapting to IOT. Therefore, many of the findings have been drawn with the aim of being as concreate as possible. And therefore, the later on recommendation for companies can be considers of great use.

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The ambition to enforce the knowledge, regarding this widely spread subject, is an enormous and complex undertaking to the fact that IOT can be found in all segments, just like the use of Internet. The industrial implications of this study, thus, could be summarized as the following:

Develop strong partner relations – The researcher find implications to believe that

companies within the field want to develop closer partnerships. If working close to the partner, a tighter partner relation can be established. By this one could validate that the development of the IOT services could be speeded up.

Think about what you actually can deliver – To simplify the process of this, the proposed recommendation for each company it to continue to focus on what you do best. Focus on what you can deliver, instead of what you should deliver. And when companies feel secure in their IOT solution, they can expand their ecosystems by the help of partnerships.

Take advantages of you size – If the company if of great size, just as the case company, one can take advantage of its size. When going to market, other companies will listen. However, companies should know their limits, and remember that no one can be everywhere.

Build a strong internal communication – the researcher find motive to believe that this

kind of businesses requires strong internal relations. If launching a start-up, beware of that internal start-ups have a tendency to create internal boundaries between departments. Therefore, counteract this by the use of communication and tight business relations. The researcher also believed that the IOT initiative at any company would have the opportunity to grow, if more persons were involved in it. Company’s need to form an internal strategy, since when all knows what is being fought, they can all fight together.

It is time to stop taking, and start doing – Companies has to start investigating the possibilities “for real”. Many of the initiatives often leaded to that no value could be found in the business cases. And this way probably based on the companies fear of failing. One has to fail, before one can succeed.

The awareness regarding IOT may be increased – This can be done by investments in promotion and marketing the concept around IOT, and launching IOT initiatives. Both internally within the company, but also externally to stakeholders.

8.2.2. Research implications

The aim with this study was to provide a greater deep in the knowledge of implementing and adapting to IOT. By identifying the main challenge, factor that affected the market of IOT could be identified. This provided the research area with greater understanding of what is driving the market and what segments are of importance to monitor.

By studying the main challenges when implementing and adopting to IOT, key drivers were identifies, and areas which stakeholders should pay extra attention regarding, could be identified.

The study also aimed to contribute with a deeper understanding for how the concept could be utilized within organizations. The study also aimed to clarify many of the confusions in the progress and aimed to provide guidance with in the area, and what companies need to consider when implementing and adapting to IOT. The researcher believes this to be fulfilled, and the findings in the report can be considered generalizable. Meaning that the researcher finds arguments for generalizing the findings. However, since the study were to be made under such a short time of period, some validation of the findings is appropriate before great investment is done within the field.

By identifying these main challenges, governments, associations and regulators could get deeper insights into which areas that are of particular importance, and form regulations in able to speed up the development of IOT.

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The report also points out promising technologies that are considered to contribute significantly to the development of IOT. Through innovative use of technologies, more innovative ideas are able to approach the market, and research regarding promising technologies can be made.

8.2.3. Sustainability implications

The fact that Internet is getting more and more available, plays an important role in the development of developing countries. Even if the technology around IOT are estimated to enter the life of individuals within 10 years, once can assume that the availability of Internet will reach these contributes much faster. The research contributes to the fact that mature developing countries can access a great use of advice, when implementing and adapting to IOT. The study also allows these individuals to broaden their technology knowledge. If solution would reach the market, individuals could start using these services in much faster pace. And the hope is that some of these IOT services also cover applications on a sustainable matter.

The aim with this study is to provide a greater deep in the knowledge of implementing and adapting to IOT, and also provide guidelines to companies investigating in the area of IOT. By this purpose, the expectation is to support the growth of the market of IOT. If the IT industry could be transformed in a much more efficient way the supplementary benefits can be experienced much sooner. Therefore, the aim is also that this study facilitates a growth within the market.

8.3 Future work The researcher definitively sees a reason for further investigation of the area. The study only includes 14 interviewees, while many were not conducted at Tieto. In this matter it would be of great interests to investigate this matter more, since differences between the departments and roles are likely to find.

From extensive research, many business schools and companies globally have long been investigating in the area of IOT. This could not be confirmed to be the same case, partially for Sweden. This means that some of the conclusions were based on processes and theories formulated from reports written from other countries then Sweden. In addition, there is a lack of knowledge about Internet of Things generally in Sweden, and the researcher find great potential to enlarge to common knowledge within the general population. The study sees great provident for within the field of Internet of Things.

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10 APPENDIX

Appendix 1: Interviewees Tieto

Description / Job title Department No of interviews

1 A1 Sales Director Telecom & Media 3

2 A2 Sales Director Teito Industrial Internet/Telecom & Media 2

3 A3 Chief Operating Officer Tieto Industrial Internet 1

4 A4 Customer Manager Telecom & Media 1

5 A5 Application Supervisor Tieto Industrial Internet 1

6 A6 Solution Consultant Tieto Industrial Internet 1

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TeliaSonera

Description / Job title Department No of interviews

7 B1 Partner Manager TeliaSonera Global IoT Solutions 2

8 B2 Partner Manager TeliaSonera Global IoT Solutions 1

9 B3 Partner Manager TeliaSonera Global IoT Solutions 1

10 B4 Sales Manager TeliaSonera Global IoT Solutions 1

11 B5 Product Manager TeliaSonera Global IoT Solutions 1

6

Huawei Technologies

Description / Job title Department No of interviews

12 C1 Systems Specialist - 1

1

Evothings

Description / Job title Department No of interviews

13 D1 CEO - 1

1

KTH

Description / Job title Department No of interviews

14 E1 Lecturer Industrial Management 1

1

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Appendix 2: Interview questions In the following section the questions asked during the interviews will be presented .

Interview questions: Interviewee A1 Date: 2016-01-25

Format: F2F What is it that you at Tieto are looking for? How long have you been working on the IOT?

Tell me about your ongoing project? How is that related to IOT? How does it work internally? How many is working with IOT today?

What do you believe to be the potential of IOT?

What has happened in the market since you started looking into this? Where do you recommend me to start investigating?

o Can you provide me with some example cases where IOT has been used?

Interview questions: Interviewee A1 Date: 2016-03-18

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT?

What is your experience of the use of IOT? How do you work with IOT today? Specifically at IOT?

What is your experience of the use of IOT? o In your opinion, how far have we come today with IOT? Should we have progressed further?

What do you think Tieto expects of IOT? o How is Tieto working with IOT today?

What would you say about the market? Is the market ready for the IOT? o According to your own believe, what is happening in the market at the moment?

What are do you feel are the biggest challenges with IOT?

Interview questions: Interviewee A1 Date: 2016-04-16

Format: F2F How would you say that the cooperation with Tieto’s Industrial Internet is working?

What do you feel that you are missing, to be able to drive the IOT initiatives further?

Have the Internet of Things concept changed your way of working? How do you think, you can cooperate with other companies?

What is your vision of Internet of Things? How do you look at future? Tell me more about the IoT/II solutions that Tieto has provided

o Are the applications in specific segments? If yes, why did you choose these fields?

Interview questions: Interviewee A2 Date: 2016-02-09

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT?

How long have you been working on the IOT? Did it appear natural for you, or was it an initiative?

What is your experience of the use of IOT? o In your opinion, how far have we come today with IOT? Should we have progressed further?

How do you work with IOT today? Specifically at Tieto’s Industrial Internet?

What do you think Tieto expects of IOT? What are the conditions you see is necessary to be able to work with the IOT to 100%?

o Do you believe that Tieto those conditions?

What do you see the initial benefits of the IOT? What are the risks and / or barriers to the IOT?

According to the research, the future for IOT is looking bright. Do you share this bright vision? What do you think the future of IOT holds?

Interview questions: Interviewee A2 Date: 2016-04-19

Format: Phone interview Please tell me more about the Industrial Internet initiative

Tell me more about the IoT/II solutions that Tieto has provided - Are the applications in specific segments? If yes, why did you choose these fields?

What do you think is the biggest challenge of working with IT solutions? - Do you think all fit to working like this in the forefront with new technologies?

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- How dependent do you think that the environment for working is?

How do you think, you can cooperate with other companies? What is your vision of Internet of Things? How do you look at future?

Have the Internet of Things concept changed your way of working?

How do you think regarding pricing of IoT/II products? - Benefits are several yes, but what about the challenges? - It the technology today ready for it?

- Do you have any examples?

Interview questions: Interviewee A3 Date: 2016-04-18

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT?

What have Tieto in Finland done within the subject of Internet of Things? - Have it been successful or not?

Please tell me more about the Industrial Internet initiative

Tell me more about the IoT/II solutions that Tieto has provided - Are the applications in specific segments? If yes, why did you choose these fields?

What do you think is the biggest challenge of working with IT solutions? - Do you think all fit to working like this in the forefront with new technologies? - How dependent do you think that the environment for working is?

How do you think, you can cooperate with other companies? What is your vision of Internet of Things? How do you look at future?

Have the Internet of Things concept changed your way of working?

How do you think regarding pricing of IoT/II products?

Interview questions: Interviewee A4 Date: 2016-04-18

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT? What is your experience of the use of IOT?

o In your opinion, how far have we come today with IOT? Should we have progressed further?

Can you tell me about the HSB Living Lab that you are responsible for? How do you think, you can cooperate with other companies?

Have the Internet of Things concept changed your way of working?

What is your vision of Internet of Things? How do you look at future? How would you say that the cooperation with Tieto’s Industrial Internet is working?

What do you feel that you are missing, to be able to drive the IOT initiatives further? What do you see the initial benefits of the IOT?

What are the risks and / or barriers to the IOT?

Interview questions: Interviewee A5 and A6 Date: 2016-04-06

Format: Phone interview Would you begin by telling me briefly about yourself and your connection to the IOT?

Can you tell me about the HSB Living Lab that you are responsible for? What is your vision of Internet of Things? How do you look at future?

Please present yourselves to me and explain your involvement with IoT

What have Tieto in Czech Republic done within the subject of Internet of Things? o Have it been successful or not? o Do you have any example cases? o Are the applications in specific segments? If yes, how did they do the evaluation between different

segments? Are you familiar with the initiative Industrial Internet?

o Are you involved in this in any way?

What is your vision of Internet of Things? What do you see in the future? Have the Internet of Things concept changed your way of working?

What were the challenges?

What were the satisfactions?

Interview questions: Interviewee B1 and B2 Date: 2016-03-15

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT? What is your experience of the use of IOT?

Have the Internet of Things concept changed your way of working? o How are you working today, compared to with 3 years ago?

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How is the relation between you and Tieto today? o How are you collaborating?

What do you see difficulties today? o Do you think about how you will manage these new obstacles?

Interview questions: Interviewee B1 and B3 Date: 2016-04-21

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT?

How would you say that the cooperation with Tieto is working? Have the Internet of Things concept changed your way of working?

Tell me more about your partner program. o How did it all start? And why? o Has the expectations been as wished? o How is TeliaSonera planning on the developing this partner program

How is the relation between you and Tieto today? o How are you collaborating?

Tell me more about M2M-in-a-box? o Do you also have other initiatives?

Interview questions: Interviewee B4 and B5 Date: 2016-03-30

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT?

Have the Internet of Things concept changed your way of working?

What is your experience of the use of IOT? Tell me more about M2M-in-a-box?

o Do you also have other initiatives?

Tell me more about your partner program. o How is TeliaSonera planning on the developing this partner program?

How is the relation between you and Tieto today? o How are you collaborating?

Do you see opportunities to expand the value chain?

Interview questions: Interviewee C1 Date: 2016-04-07

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT?

Have IOT concept changed the way you work? o How did you work 3 years ago, compared to how you work today?

How do you see these new conditions / opportunities? How do look at the creation of partnerships?

Do you see opportunities to expand the value chain? What do you see difficulties today?

o Do you think about how you will manage these new obstacles ?

What do you see that IOT contributed, if you consider the benefits? Different types of partnerships. The most common is that it is the enabler, but that it is now also looking at other

types of partnerships. Have you thought of any of those courses?

They these platforms you have. How has it come to? How do you see the future? How do you validate that you hang more in development?

o Visions of the future, where would you be if say 10 years?

Interview questions: Interviewee D1 Date: 2016-04-11

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT?

Tell us more about your mobile solutions How do you reach the customer?

How do you think you can work with companies such as Tieto?

You sit in the quite a creative environment. How does it affect your operations? o Do you think all fit to work like this in the forefront with new technologies?

Have IOT concept changed your way to work?

What are your challenges? o What is the biggest challenge of working with IoT solutions?

How do you market your solution?

How do you think about the pricing of your product? How do you see for the future?

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Interview questions: Interviewee E1 Date: 2016-04-28

Format: F2F Would you begin by telling me briefly about yourself and your connection to the IOT? Many companies see the potential of the IOT, but lack the "tools". Do you see also the difficulty of IOT? Or is it

about the other things?

Do you believe that the market, companies and customers / consumers, are ready for the IOT? Do you think IOT has the potential to transform the “digital world", i.e. any type of digital transformation? There's even some skeptics who think that this IOT with "just a buzz." How do you feel about that?

How do you see for the future?