Surviving the Digital Transformation

(1)

IN THE FIELD OF TECHNOLOGY DEGREE PROJECT

DESIGN AND PRODUCT REALISATION AND THE MAIN FIELD OF STUDY INDUSTRIAL MANAGEMENT, SECOND CYCLE, 30 CREDITS STOCKHOLM SWEDEN 2020,

Surviving the Digital Transformation

- The Case of an Incumbent Insurer

CAMILLA BRATT FORSS EMMA JANSSON

KTH ROYAL INSTITUTE OF TECHNOLOGY

SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT

(2)

(3)

Surviving the Digital Transformation

– the Case of an Incumbent Insurer

by

Camilla Bratt Forss Emma Jansson

Master of Science Thesis TRITA-ITM-EX 2020:217 KTH Industrial Engineering and Management

Industrial Management SE-100 44 STOCKHOLM

(4)

Att överleva den digitala transformationen

- en fallstudie av ett väletablerat försäkringsbolag

Camilla Bratt Forss Emma Jansson

Examensarbete TRITA-ITM-EX 2020:217 KTH Industriell teknik och management

Industriell ekonomi och organisation

(5)

Master of Science Thesis TRITA-ITM-EX 2020:217

Surviving the Digital Transformation - The Case of an Incumbent Insurer

Camilla Bratt Forss Emma Jansson

Approved

2020-May-25

Examiner

Cali Nuur

Supervisor

Richard Backteman

Commissioner Contact person

Abstract

The digital transformation, providing disruptive digital technologies, changed customer needs, and new digital entrants, is starting to affect the insurance industry. Although, the insurers are struggling to become digital and excel on technologies such as Artificial Intelligence.

Therefore, the purpose of this thesis was to identify and investigate the factors necessary for incumbent insurers to achieve digital transformation and excel on related technologies, to stay competitive in the fast-changing environment.

The overall theoretical foundation was built on the ability to create dynamic capabilities to achieve digital transformation. The study further linked the dynamic capabilities theory to the context of the change currently happening in the insurance industry, achieved by performing a single case study on a Swedish incumbent insurer. The case study included two units of analysis which investigated (1) how, and under which circumstances, the identified key factors were met, and (2) how the attempts of implementing Artificial Intelligence have been perceived, received and achieved. Both qualitative and quantitative data collections were performed, but where the qualitative was predominate.

The findings proved that the incumbent insurer is at the start of its digital transformation and does realise the need to transform. However, it was found that many of the essential dynamic capabilities’ activities are limited at the case company and that hierarchical structures, risk- aversion and legacy systems are hindering the insurer’s attempts to transform. Some good initiatives though proved that the insurer is starting to build more dynamic capabilities, but there are also many areas where the company must improve. A central contribution to the study was further the realisation that the implementation of Artificial Intelligence was well related to the parts of the dynamic capabilities’ theory. As digital transformation is an ongoing journey of strategic change, once more dynamic capabilities are in place, the incumbent insurer will be ready to excel on the possibilities that digital transformation entails.

Keywords: Dynamic Capabilities, Digital Transformation, Insurance, Incumbent Firms, Artificial Intelligence, Chatbot, RPA

(6)

Examensarbete TRITA-ITM-EX 2020:217

Att överleva den digitala transformationen – en fallstudie av ett väletablerat försäkringsbolag

Camilla Bratt Forss Emma Jansson

Godkänt

2020-Maj-25

Examinator

Cali Nuur

Handledare

Richard Backteman

Uppdragsgivare Kontaktperson

Sammanfattning

Den digitala transformationen har börjat påverka försäkringsbranschen och medför nya omvälvande digitala tekniker, förändrade kundbeteenden och nya digitala konkurrenter. Många försäkringsbolag kämpar därför med att bli digitala samt att förstå sig på nya tekniker, så som Artificiell Intelligens. Syftet med denna studie var därför att identifiera och undersöka vilka faktorer som är nödvändiga för väletablerade försäkringsbolag att klara sig igenom den digitala transformationen, och adaptera nya uppkommande tekniker som förändringen medför. Detta för att kunna behålla sin marknadsposition och klara sig i en snabbförändlig värld.

Huvudsakligen var den teoretiska grunden för detta arbete byggt på förmågan att kunna skapa dynamiska förmågor för att överleva den digitala transformationen. Vidare så sammankopplade studien teorin om dynamiska förmågor till den pågående förändringen inom försäkringsindustrin, genom att utföra en fallstudie av ett väletablerat försäkringsbolag i Sverige. Fallstudien innefattade två analysdelar beskrivna enligt följande: (1) Hur, och under vilka förhållanden, uppfylls de identifierade faktorerna och (2) hur har försöken att implementera Artificiell Intelligens uppfattas, mottagits och uppnåtts av försäkringsbolaget.

Både en kvalitativ och kvantitativ datainsamling utfördes, där den kvalitativa delen dominerade.

Resultaten visade på att det studerade försäkringsbolaget är i början av sin digitala transformation, men har insett betydelsen av att behöva förändras. Det blev även bekräftat att många av de grundläggande dynamiska förmågorna var begränsade hos företaget samt att hierarkiska strukturer, riskundvikande och legacy förhindrar möjligheten att förändras. En del goda initiativ visar att företaget börjar bygga dynamiska förmågor men att det finns många områden där ytterligare fokus krävs. En stor insikt i studien var att implementationen av Artificiell Intelligens var relaterad och stämde väl överens med faktorerna identifierade i teorin.

Den digitala transformationen är en pågående resa av strategiska förändringar, och försäkringsbolaget kommer kunna ta del av dess möjligheter när fler dynamiska förmågor uppnås.

Nyckelord: Dynamiska Förmågor, Digital Transformation, Försäkring, Etablerade bolag, Artificiell Intelligens, Chatbot, RPA

(7)

List of Figures

FIGURE 1. THE DYNAMIC CAPABILITIES: SENSING, SEIZING AND TRANSFORMING ... 13

FIGURE 2. THEORETICAL FRAMEWORK; BUILDING DYNAMIC CAPABILITIES FOR DIGITAL TRANSFORMATION AS AN INCUMBENT FIRM ... 22

FIGURE 3. THE SYSTEMATIC COMBINING APPROACH. ... 25

FIGURE 4. THE CASE STUDY DESIGN, ADAPTED FROM YIN,(2014). ... 26

FIGURE 5. ILLUSTRATION OF THE RELATION BETWEEN ASSETS AND LIABILITIES OF AN INSURER (^STRANDBERG,2013) ... 35

FIGURE 6. ILLUSTRATION OF THE DIFFERENT CATEGORIES OF AI ... 38

FIGURE 7. ILLUSTRATION OF THE RELATION BETWEEN AI AND MACHINE LEARNING ... 39

FIGURE 8. GRAPH SHOWING HOW MANY YEARS EMPLOYEES HAVE WORKED AT THE CASE COMPANY IN GENERAL ... 58

FIGURE 9. THE PARTICIPANTS VIEW ON WHO IS RESPONSIBLE FOR DIGITAL TRANSFORMATION ... 65

FIGURE 10. EXAMPLE OF AN ORGANISATIONAL STRUCTURE TO ENHANCE SENSING AND SEIZING CAPABILITIES ... 83

FIGURE 11. THE KEY FACTORS INFLUENCING THE DIGITAL TRANSFORMATION OF AN INCUMBENT FIRM ... 87

List of Tables

TABLE 1.OBSERVATION INFORMATION. ... 27

TABLE 2.APPELLATION OF PARTICIPANTS ... 29

TABLE 3.INTERVIEW INFORMATION ... 29

TABLE 4.ACTIONS TAKEN TO ENSURE AN ETHICAL STUDY ... 31

TABLE 5.CODING CATEGORIES FOR THE FIRST UNIT OF ANALYSIS... 44

TABLE 6.CODING CATEGORIES FOR THE SECOND UNIT OF ANALYSIS ... 45

TABLE 7.THE MOST CRITICAL TECHNOLOGIES FOR FUTURE BUSINESS SUCCESS, ACCORDING TO THE PARTICIPANTS ... 48

TABLE 8.REITERATION OF THIS STUDY'S RESEARCH QUESTIONS ... 76

TABLE 9.THE CASE COMPANY'S CURRENT STATE IN REGARD TO THE KEY FACTORS INFLUENCING THE DIGITAL TRANSFORMATION ... 89

(9)

Glossary

Name Description

Digital Age The time period starting in the 1970s with the introduction of the personal computer with subsequent technology introduced providing the ability to transfer information freely and quickly (Your Dictionary, n.d.).

Digital Natives The generation growing up with technology, born after the 1980s (Čut, 2017).

Digital Immigrants The generation who did not grow up using technology, born before 1980s (Čut, 2017).

Digital Innovation “Digital innovation is the carrying out of new combinations of digital and physical components [in a layered modular architecture] to produce novel products” (Yoo et al., 2010, p.725) Digital Technology Digital technologies includes combinations of information,

computing, communication, and connectivity technologies (Bharadwaj et al., 2013)

Digital Transformation Taking advantage of digitalisation to create entirely new business concepts (Irniger, 2017).

Digitisation Transitioning from analogue to digital (Irniger, 2017).

Digitalisation Making digitised information work for the business (Irniger, 2017).

Incumbent Firm A firm which already has a strong market position.

PSD2 The PSD2 directive enables customers to give consent to a third-party to access their payment account where the third party can retrieve account information (Finansinspektionen, 2019).

(10)

Abbreviations

Short Form Description

AI Artificial Intelligence

API Application Programming Interfaces

BIDA Business Intelligence & Data Analytics

CDO Chief Digital Officer

CEO Chief Executive Officer

CIO Chief Information Officer

COVID -19 The pandemic of the corona virus in 2019/2020

CTO Chief Technical Officer

FinTech Abbreviation for a company working with financial technology FNOL The first notification of loss -a first step in the formal claims process

lifecycle.

InsurTech Abbreviation for a company working with insurance technology

ML Machine Learning

NLP Natural Language Processing

NLU Natural Language Understanding

RPA Robot Processes Automation

SAFe® An agile framework for scaling agility across a business

(11)

Foreword

This report is the result of our Master of Science thesis' research during the first half of 2020.

The thesis is a part of the seminar group Industrial Dynamics at the School of Industrial Management and Engineering at KTH Royal Institute of Technology. The thesis has been written to fulfil the graduation requirements of the Industrial Management Master of Science programme.

Moreover, the thesis was written in collaboration with a Swedish Insurance company, in this report referred as the case company, to help them understand the Digital Transformation as the company is facing. The work has been interesting on many levels, but also challenging due to the circumstances of the COVID-19 pandemic. Luckily, the case company has been very flexible and helpful; which made it possible to complete this thesis in a challenging time for society.

The research could not have been done without the significant support by the supervisors at the case company, and we would like to dedicate a special thanks to Lars Engvall and Johanna Gillberg, for their massive support during the research. Your enthusiasm and guidance have been of great encouragement throughout the thesis. We would also like to dedicate our thankfulness to every participant in the study, for your great insights and thoughts that contributed to the findings.

Moreover, we would like to thank our academic supervisor Richard Backteman at KTH, with your great guidance, helpful thoughts and feedback throughout the project. We would also like to thank Professor Cali Nuur and Milan Jocevski for the inputs provided during the thesis seminars. A special thanks are also dedicated to the opponents that helped to provide new insights to the research.

As the last statement, we, the authors, would like to thank each other. Writing a thesis together can be challenging, but the collaboration has been seamless throughout.

We hope you enjoy your reading!

Camilla Bratt Forss and Emma Jansson Stockholm, 18th of May 2020

(12)

1. Introduction

__________________________________________________________________________________________________________________________________________

This chapter presents the introduction and explains the context of the research problem. The chapter starts with the studied problem’s background, followed by the problem formulation, research purpose and the formulated research questions. Thereafter, a determination of the study’s delimitations and limitations is presented. Conclusively, a disposition is presented to guide the reader of the layout of the thesis.

__________________________________________________________________________________________________________________________________________

1.1 Background

The transition toward the digital is changing the way business is performed (Rogers, 2016), and the act of digital transformation is creating new opportunities for companies by making it possible for them to create entirely new business concepts (Irniger, 2017). Digital transformation is defined by Warner and Wäger (2019 p.344) as “an ongoing process of strategic renewal that uses advances in digital technologies to build capabilities that refresh or replace an organisation's business model, collaborative approach, and culture.” The evolution of digital technology will provide digital disruption (Walter and Karimi, 2015), and companies operating in industries born before the digital age are starting to be affected by the quick technological change and changing market dynamics with entry from global or new competitors (Felin and Powell, 2016). As a result of these disruptions, organisations must find a way to remain competitive (Vial, 2019).

The integration of the analogue and digital worlds with new digital technologies has transformed, or is transforming, many industries globally and is also starting to affect industries that have been considered stable for centuries, such as the insurance industry (Eling and Lehmann, 2018). Digital transformation is destined to reshape the entire landscape of the insurance sector and make a significant impact on the value chains (Cappiello, 2018).

Although, the incumbent insurers, where the term “incumbent” refers to a firm which is already in a strong market position, are struggling to become digital leaders and knowing where to start (Stoeckli et al., 2018). Insurance Sweden (2019) explains the importance of insurance given that everyone on Earth is affected by the risk of having something unexpected happening, such as illness or damage of goods. Instead of facing a financial disaster if this happens, one has insurance. The idea behind insurance is that every risk group shares the risk within different subgroups, such as the home or health insurance group. These separate groups share the risk among the customers within the same crowd. If something were to happen, the accident would be paid by the other customers' premiums from that particular risk group (Insurance Sweden, 2019).

The external triggers pushing for change within the industry indicate that insurance will have to shift from its current state of ‘detect and repair’ to ‘predict and prevent’, where many of the technologies that are changing the customers' behaviours already exist (Balasubramanian et al., 2018). The insurance industry has historically been slow in its development in comparison to

(13)

(Eling and Lehmann, 2018). Even though a significant part of customer interactions in the insurance industry was expected to be moved from analogue to digital by 2020 (Stoeckli et al., 2018), the pace of digital transformation is behind compared to other industries (Eling and Lehmann, 2018). The industrial dynamics are likely to change, and the big players need to keep up with innovation to not be outrun by with better digital value creation (ibid). The stagnant development of the insurance industry over the past century is described by Pearson (1997) as being due to reasons such as insurers having to depend upon the money market yields on their investments to acquire the liquidity needed to provide insurance cover, and that the insurers have faced difficulties in trying to finance development and innovation (ibid.). Sweden was in 2019 appointed to be the most innovative country in Europe (Caudet and Von Hammerstein- Gesmold, 2019) and is also one of the countries having the most substantial percentage of people insured in the world (Insurance Sweden, 2019). Meanwhile, it seems to be hard for the incumbent insurers to follow the digital trend and be leaders in digital transformation (Stoeckli et al., 2018).

Also hampering the development of incumbent insurers is a large number of regulations in the insurance industry, both regarding all the resources needed to follow the regulations, as well as working as a barrier to new entrants, protecting the large players (Eling and Lehmann, 2018).

The study on a large Swedish insurer by Grünberger and Holm (2018), emphasises on the fact that the regulated market on which the insurers operates creates a company culture that to some extent is characterised by control and a fear of making mistakes, which can inhibit innovation and development. The culture of being risk avert within the insurance industry can be a reason why development is blocked even further. However, regulations are also shown to change the industry dynamics and are currently a reason why the insurance industry might change further.

The sensation of Open Banking occasioned in regulations such as PSD2 that intended to open up the finance industry and involve more players, pushing for a more competitive market in Europe (Finansinspektionen, 2019). The PSD2 directive enables customers to give consent to third parties to access their payment account where the third party can retrieve account information. Such third-parties include FinTechs (Bakker, 2018).

Braun and Schreiber (2017) further mention that even though no such regulation is directly targeting the insurance industry yet, third parties are starting to create similar approaches to the insurance industry. In the Nordic InsurTech Report by Gromek et al. (2019), it is stated that there were 36 companies under the branch of InsurTechs (i.e. the FinTechs targeting the insurance industry) incorporated in Sweden in 2019. No empirical findings are yet providing any signs that the incumbent players will be out-performed by the InsurTechs (Braun and Schreiber, 2017), nor if they will completely disrupt the insurance industry (Eling and Lehmann, 2018). Though, due to the accelerated innovation dynamics, a great advantage will be achieved by the incumbents that successfully adapt to the new circumstances (Braun and Schreiber, 2017), possibly collaborating with the InsurTechs. The new InsurTechs are known to be efficient and directed towards the new generations way of navigating the internet (McKinsey & Company, 2018). Although, another possibly even more significant threat to the incumbent insurers are the data giants such as Google, Facebook and Amazon to enter the insurance industry, being well prepared to disrupt the entire value chain (Waschto et al., 2018).

(14)

Having large tech giants entering and disrupting the current regime is a threat that many industries face (McKinsey & Company, 2018).

Digital technologies are also challenging the fundamentals of the highly regulated financial and insurance sector (Leong et al., 2017) making the sector standing in front of radical and digital change (McKinsey & Company, 2018). One of the main technologies predicted to impact the insurance industry is Artificial Intelligence (AI). It can help by segmenting claims by complexity using factual and predicted claims characteristics. These claims can afterwards be directed to specific downstream handling and make the process much more efficient by offering almost full digital self-service journeys for their customers. A human would only be involved in the case of the claim being too complicated (Waschto et al., 2018). Gartner (2018) further confirms the possibilities of AI, as AI-driven development is predicted being one of the top ten technology trends of 2020. Even though many reports emphasise the importance for insurers to ensure the digital transformation and implement these expected disruptive technologies, there are currently neither literature nor reports presenting an understanding how to measure whether an incumbent player can endure these changes, new strategies and technologies.

New customer behaviours and needs are also affecting the environment for insurers. A report by Accenture (2019) explains that the insurance industry has for decades directed their services to a generation who did not require any digital services and who possess trust to the large organisations. Due to a new digital era, it is now expected from every business, including the insurance industry, to offer digital services (Accenture, 2019). Customers today are interested in fast and straightforward interactions, something which many traditional insurance companies do not offer (McKinsey & Company, 2018). The generation affecting the companies need for digital transformation and behavioural change the most, is called the digital natives, which includes people born after the 1980s (Čut, 2017). Commonly for digital natives are that they grew up during the digitalisation of different industries and are therefore native to digital technology, with social media and text-messaging, consequently increasing their expectation on response time (Gaston, 2006). On the contrary, people born before 1980 are called digital immigrants (Čut, 2017). This generational shift is difficult both given that the digital natives act and even think differently than digital immigrants (Gaston, 2006), but also because it is hard for organisations (often run by digital immigrants) to keep up and change, being used to satisfying the needs of the digital immigrants (Prensky, 2001). Therefore, the traditional giants within the industry need to work hard to retain their customer base and continue to attract new clients (McKinsey & Company, 2018).

Past success does not ensure future success (Sebastian et al., 2017). Driven by disruptive digital technologies, new customer needs and behaviours, and new market dynamics, insurers find themselves in a changing environment. However, implementing change in large, incumbent organisations is difficult (Teece, 2018). Incumbents are often more rigid and resistive to change, prioritise the existing routines rather than exploring new ideas (Teece, 2018), have slow decision making, and are constraint by laws, regulations and business ethics (Teece,

(15)

solutions (Laumer and Eckhardt, 2010). The resistance of change depends on many factors, such as lack of direction, competence, opportunity and motivation (Wadström, 2019). Laumer and Eckhardt (2010) mention how, in the IT-related organisational change projects, failure can be seen when individuals at the firms do not behave nor use the technology as initially expected.

Scholars have for decades tried to understand the competitive advantage of firms, where theories, such as the dynamic capabilities theory (Teece et al., 2016, 1997; Teece and Leih, 2016; Teece, 2018, 2014, 2012, 2007) explain how different routines and processes positively influence firm performance in a changing environment and could offer an explanation as to why some companies succeed in such an environment, while others do not (Giniuniene and Jurksiene, 2015). The way incumbents ran their business before the digital age might no longer provide competitiveness, but with the right actions, these companies can transform to thrive in the digital age (Rogers, 2016).

1.2 Problem Formulation

Driven by the factors of new digital technologies, changing customer behaviour, needs and market dynamics, the setting for an incumbent insurer is about to change. Digital transformation might profoundly change all industries, and the same goes for the insurance ecosystem. An academic discussion, as well as an extensive number of targeted reports by consultancy firms, emphasise the importance of digital transformation to survive in the future market of the insurance ecosystem, with new digital technologies and changing customer needs. Many of the technologies required to achieve digital transformation within insurance already exist and, more importantly, are already starting to change the customers’ behaviours and needs. For example, AI technology is predicted to have a significant impact on the insurance industry, the way the insurers run their operations and create customer value but learning to excel on new technologies are easier said than done.

Following these aspects, problems arise when the incumbent insurers are struggling to be digital. If incumbent insurers are struggling to excel on new technological solutions in such an innovative country as Sweden, it is of importance to understand what factors that are affecting the incumbent’s journey to achieve digital transformation, and what enables or hindering such change. These different viewpoints are making an incumbent insurer in Sweden the ideal case delineation.

Theories, such as dynamic capabilities, define capabilities needed to transform in a changing environment. There is, though, a gap in linking the dynamic capabilities theory to the change currently happening to the insurance industry, where literature and consultancy reports mainly focus on the new InsurTech players, their capabilities, and future strategies for incumbents to pursue. It is still to understand how to measure whether an incumbent player can perform these changes and new strategies, given the many dimensions of the change. The question arises whether the incumbent insurers will survive this shift and how ready they are to transform.

(16)

1.3 Purpose & Research Questions

The purpose of this thesis is to identify and investigate the factors necessary for incumbent firms to achieve digital transformation and excel on related technologies, to stay competitive in the changing environment. The aim is thereafter to place those key factors in the context of an incumbent insurer on their journey to become digital and their attempts in implementing new technologies; and thus to determine whether they have the factors necessary and are ready to adapt to the changing landscape, evaluated from a functional perspective. The purpose leads to the following research questions:

• RQ1: What are the key factors influencing the digital transformation of an incumbent firm?

The identified key factors will be assessed from theory, including perspectives of incumbent firms, and firms that are providing services, and will then be applied onto a case study of an incumbent insurer to explore their current ways of working, as well as their attempts to implement crucial technologies, such as AI. This aim intends to be answered by the second research question:

• RQ2: How do these key factors determine the readiness of an incumbent insurer to achieve digital transformation?

The answer to the second research question RQ2 is aimed to be fulfilled by the case study, and the answers to the following sub research questions SRQ1 and SRQ2:

• SRQ1: How, and under which circumstances, are the key factors met?

• SRQ2: How have the attempts of implementing AI been perceived, received and achieved?

1.4 Delimitations & Limitations

To achieve the aim of the thesis, and given the problem’s context, the empirics and the result of the study are delimited to a single-case study of a Swedish incumbent insurer. It means that the empirical result will be based on data from a single company. The study is investigating the different possibilities brought by many digital technologies, but the implementation of AI has been selected as a unit of analysis in the case study, which will result in a more in-depth perspective of the AI technologies in this thesis. The technology is chosen due to its predicted large impact on the insurance industry, and because the case company is currently attempting implementations of AI, making it a relevant case delineation. The work is further delimited to the defined research questions, which means that the studied technologies will only be discussed conceptually to help to answer the research questions and not with the intention to evolve any actual technical parts. Any implementation of the actions identified is also left

(17)

The thesis is further limited by the pre-determined time period, which extends over five months during the first half of 2020, which also sets the timeframe for the case study. This will limit the result, solely focusing on contemporary events, covering what is happening during these months. However, to emphasise the findings, historical and future aspects will also be taken into consideration.

1.5 Disposition

The layout of the thesis is constructed as follows:

Chapter 1. Introduction: intends to present the introduction and explain the context of the research problem. The chapter covers the background, problem formulation, research purpose and the formulated research questions. The chapter further presents a determination of the study’s delimitations and limitations.

Chapter 2. Theoretical Aspects: intends to present the study’s theory base; with a review of the literature covering the anticipated theory. The chapter is concluded with a theoretical summary and the study’s theoretical framework.

Chapter 3. Method and Data Collection: intends to present the methodology of the study, which includes the methods used in the research. The chapter covers a description of the research strategy, case study as well as data collection techniques and the data analysis method.

It further includes a justification of ethical aspects, reliability, validity and generalisability.

Chapter 4. Research Context: intends to present the research context, with the information needed to understand the case study, its technical aspects and industrial context. The first subchapter presents the context of insurers, and the second subchapter presents an overview of the AI technology.

Chapter 5. Results: intends to present the results of the case study. The results consist of the empirical findings from interviews, observations and data from the case company’s internal documents.

Chapter 6. Discussion: intends to analyse and discuss the findings from the case study in relation to the theoretical aspects gathered from the literature, and to provide an answer to the research questions.

Chapter 7. Conclusion: intends to conclude and summarise the key findings of this study.

The conclusion includes the study’s theoretical contribution, practical implications, limitations and suggestions for further work.

(18)

2. Theoretical Aspects

__________________________________________________________________________________________________________________________________________

This chapter includes the study’s theory base; with a review of literature covering the anticipated theory, as well as perspectives of the anticipated theory from related literature, structured under themes identified by the authors. The chapter is later concluded with a theoretical summary and the study’s theoretical framework.

__________________________________________________________________________________________________________________________________________

As seen in the introduction, many factors affect a transformation. There are drivers, pushing the change forward, but also barriers blocking the change. This chapter will dig deeper into the definition and meaning of digital transformation, initially covering the existing body of knowledge from the literature and the impact of digital technologies. The digital transformation chapter is followed by a description of the dynamic capabilities’ theory, to discover what factors that will ensure a firm to survive within an ever-changing environment. Literature covering digital transformation, dynamic capabilities, and their relation to each other will be presented, evaluated and reviewed.

2.1 Digital Transformation

In contrary to digitalisation (the process of using digitised transitioning from analogue to digital, and making it work in a current business), digital transformation refers to creating entirely new business concepts driven by digital technologies (Irniger, 2017). Even though the term digital transformation is well-known and discussed broadly, the definitions vary between scholars. For example, Warner and Wäger (2019, p.344) define digital transformation as “an ongoing process of strategic renewal that uses advances in digital technologies to build capabilities that refresh or replace an organisation’s business model, collaborative approach, and culture”. Vial (2019, p.121) studied 33 different definitions, and presents a conceptual definition of digital transformation as “a process that aims to improve an entity by triggering significant changes to its properties through combinations of information, computing, communication, and connectivity technologies.” (Vial, 2019, p.121)

If digital technologies are managed well, they can generate remarkable business value (Martínez-Caro et al., 2020); nonetheless, new digital technologies present both significant opportunities and threats to companies whose success were built before the digital age (Sebastian et al., 2017). For example, companies who invest in crucial new technologies and manage them well are more profitable compared to their competitors, and proper use of digital technology has proven gains in customer value, efficient operations and new lines of business or business models (Fitzgerald et al., 2014). Vial (2019) identifies the disruptive effects of digital technologies as altering customer behaviours and expectations, disrupting the competitive landscape and increasing the availability of data.

(19)

2.1.1 Digital Technologies

The disruptive effects of digital technologies push the digital transformation, which, in turn, create the need organisations to formulate a strategic response (Vial, 2019). The term ‘digital technology’ includes the combinations of information, computing, communication, and connectivity technologies (Bharadwaj et al., 2013), where the literature highlights that digital technologies referring to: social, mobile, analytics, Cloud, Internet of Things (IoT), and digital platforms are the technologies most related to digital transformation (Vial, 2019). For example, AI contributes to the digital transformation, being a technology that can analyse data in a much shorter time than possible for a human. An organisation can benefit from AI, using resources more efficiently, be more environmentally friendly, increase the overall transparency and find better and more optimised ways of working (Franken and Wattenberg, 2019). Moreover, AI applications can personalise and customise offers and marketing, derived from the available data (Kumar et al., 2019). Currently, there are no solutions intelligent enough to exceed the human’s mind (Zappa et al., 2019), due to the technology not being equipped enough to act differently from the processes prescribed to them (Lamberton et al., 2016). A more in-debt description of the AI technology is presented in Chapter 4.2.

Moreover, to be able to handle data, Premchand and Choudhry (2018) emphasise that Application Programming Interfaces (APIs) are of importance. APIs make it possible for organisations to share their data, services, business processes and applications with partners of their choice, both internally and externally. Using API can make it possible for programmers to use and understand a small piece of software without having to understand and know the entire algorithm. It makes it easier to collaborate both internally and externally since it allows companies to integrate their data with partners. If an API is only accessible within an organisation, it is considered to be a closed API, if accessible externally it is considered to be an open API. It is a digital technology which can help and facilitate to enhance service offerings, improve customer engagement and create new revenue channels, for instance. It too can be done in a more straightforward, securer and controlled way (ibid.).

The evolution of digital technology will provide digital disruption and present opportunities and challenges for all organisations (Walter and Karimi, 2015). Yoo et al. (2012) describe pervasive digital technologies as fundamentally reshaping organisations as the digital technology is changing the pace of innovation; where the increased pace results in a situation where innovation and change must be fast and continuous. The digital technologies have a high impact on customer behaviour and expectations, and the customer’s expectations of digital interactions are increasing, given that customers now actively integrates with organisations over mobile devices and social media (Vial, 2019). Moreover, the disruptive effects are seen as digital technologies such as AI, including big data analytics, robotic process automation, among others. In a digitised world, employees must navigate through an extensive amount of data yet make sense of it to provide quick decision making (Bhattacharyya and Nair, 2019).

Bhattacharyya and Nair (2019) further predict these technologies to increasingly create routines out of intellectual work and not only out of repetitive work.

(20)

The digital technologies are consequently emerging over many industries, and are starting to profoundly transform strategies, processes and capabilities of firms (Bharadwaj et al., 2013).

As a result of these disruptions, organisations must find ways to remain competitive (Vial, 2019). With more and more businesses being disrupted by digitisation (Walter and Karimi, 2015), many also struggle with digitalisation due to a vague understanding of business benefits and further struggle to cope with digital transformation, due to lack of knowledge on how to effectively drive transformation through technology (Fitzgerald et al., 2014). The confusion of the transformation creates a misalignment in how practitioners understand the term, as well as providing different perspectives of what the digital transformation represents and entails (Warner and Wäger, 2019b). The confusion can be explained due to the difference of a digital transformation strategy compared to a traditional change strategy (Bharadwaj et al., 2013) and also because digital technologies have increased the speed of change, leaving the business environments more uncertain and complex (Warner and Wäger, 2019b).

2.1.2 Challenges with Digital Transformation

As digitalisation brings opportunities, it also comes with challenges. The digital interactions force companies to pay attention to their digital reputation, which can create tension between old values, systems or procedures and the new ones and is besides an obstacle to the implementation and use of new technologies (Martínez-Caro et al., 2020). Even though most executives see the positive sides of digital transformation, many also struggle to see clear business benefits and express worries and challenges (Vial, 2019). Some managers believe it to be hard to digitally transform and are frustrated about the lack of notable results from the praised new technologies. Optimistic attempts and promising transformations often fail because the new strategy or processes collide with the company culture (Wokurka et al., 2016).

One common problem is the ‘lack of urgency’ feeling, where the main organisational processes feel more urgent to improve. The feeling is caused by; negative attitude towards digital change (mostly experienced by older workers), no clear roles or responsibilities, limitations to the IT system or not assigning enough funding (Fitzgerald et al., 2014). To reduce complexity, many managers tend to work with projects that are familiar and have a clear strategy, instead of favouring new ways of working which could enhance and achieve transformational change (Warner and Wäger, 2019b). Digital technologies can be a facilitator to developing activities of value, yet, companies will only manage them if they incorporate the correct digital culture (Martínez-Caro et al., 2020). A lack of understanding of digital, fear and resistance to new approaches are attitudes blocking the digital culture (Fitzgerald et al., 2014).

Mathule and Kalema (2016) express that many large incumbents with a long history also face the problem of legacy systems. Legacy systems are vital systems for an organisation but require older technologies and are still in use even though there are now more streamlined and more modern applications available on the market. Many organisations rely heavily on these systems, and if something were to go wrong, it would have a significant impact on daily operations. The reason for not getting rid of old legacy systems is that they are very complex and cannot be replaced by another single program. These systems are categorised to lack

(21)

and hard to understand and so on. The legacy systems can further create silos and have a lock- in effect on information and data in legacy systems, making it hard for different, more modern systems to collaborate with the original one (ibid.). Many organisations are trying to use internal APIs to improve the flow of information between legacy systems and new modern target systems (Premchand and Choudhry, 2018).

Rogers (2016) presents the central insight that digital transformation is about strategy, and not solely focused on technology. This statement is further accentuated by Vial (2019), who argues that digital technology is only one part of all the complex aspects to achieve digital transformation. Warner and Wäger (2019), add that digital transformation is about strategically renewing a firm’s business model, collaborative approach and culture, combined with an ongoing process of using new digital technologies in everyday organisational life. Horlacher and Hess (2016) describe that companies are starting to create a strategic response creating roles with the mandate to drive the strategic changes of digital transformation. For example, more and more companies have started to incorporate Chief Digital Officer (CDO) on their c- executive level. The CDO’s responsibility is usually to drive the company’s digital transformation through cross-functional teams. The CDOs role differs from a traditional Chief Information Officer (CIO) role, where the CIO usually is in charge of the technology, and the CDO of communication and strategic aspects of the digital transformation.

Firms who lack the understanding of why the digital transformation is essential are likely to be left behind (Sebastian et al., 2017). Sebastian et al. (2017) further add that since past success does not equal success in the future, the companies that have been around for long must transform and take advantage of the opportunities created by digital transformation. Many of the rules and assumptions that shaped the businesses before the digital age does not work anymore (Rogers, 2016). New business environments, emerging digital technologies and changed customer needs create the pressure for companies to find new solutions to tackle market changes, and companies that fail to change its internal structure will find it impossible to respond to the fast-changing environments (Felin and Powell, 2016). However, a quote by Rogers (2016, p.ix) shed some positivity for the incumbents struggling with change: “The good news is that change is possible. Pre-digital businesses are not dinosaurs doomed to extinction.

Their disruption is not inevitable. Businesses can transform themselves to thrive in the digital age.” (Rogers, 2016, p.ix)

2.2 Dynamic Capabilities

The theory of dynamic capabilities will be studied to understand the struggles that digital transformation entails, given that scholars emphasise that successful digital transformations are dependent on the strategies and capabilities of firms (Felin and Powell, 2016; Fitzgerald et al., 2014; Rogers, 2016; Sebastian et al., 2017; Warner and Wäger, 2019b), where the strategy, capabilities, and the business environment co-evolve (Teece, 2014).

The concept of dynamic capabilities emerged in the 1990s as an attempt to explain capabilities to sustain competitive advantage in fast-changing and uncertain industries (Felin and Powell,

(22)

2016). The emerging and fast-changing high-tech industries, with rising global competitiveness, created a need for an enlarged paradigm of management and strategy theory, which derived the theory (Teece et al., 1997). Besides, the companies operating in industries born before the digital age were likewise experiencing quick technological change and changed market dynamics (Felin and Powell, 2016). The theory implies that the business environment in many sectors is becoming more uncertain (Teece and Leih, 2016), and due to the developments of different technologies, firms have no choice but to pursue innovation and change (Kim et al., 2015). The changing environment insinuates that business resources must continually evolve for the firm to be competitive in the long-term (Ambrosini and Bowman, 2009).

The forms of competitive advantage in a fast-changing environment were defined by Teece et al. (1997) as Dynamic Capabilities. The term ‘Dynamic’ refers to “the capacity to renew competencies to achieve congruence with the changing business environment” (Teece et al., 1997 p.515). Moreover, the term ‘Capabilities’ is described as; “the key role of strategic management in appropriately adapting, integrating, and reconfiguring internal and external organisational skills, resources, and functional competencies to match the requirements of a changing environment.” (Teece et al., 1997 p.515). The dynamic capabilities theory thus explains how different routines and processes positively influence firm performance and demonstrate why some companies achieve competitive advantage in a changing environment, while others do not (Giniuniene and Jurksiene, 2015).

Consequently, organisational processes, shaped by the firm’s asset positions and by its historical paths, explain the firm’s dynamic capabilities and thus, its competitive advantage (Teece et al., 1997). The firm’s dynamic capabilities enable the firm to integrate, build, and reconfigure internal and external resources in continually shifting environments (Teece, 2014).

Dynamic capabilities are moreover foreseen to help firms to build an intensive learning environment (Giniuniene and Jurksiene, 2015). Teece (2007) further explains dynamic capabilities as: “how a business enterprise and its management can first spot the opportunity to earn economic profits, make the decisions and institute the disciplines to execute on that opportunity, and then stay agile so as to continuously refresh the foundations of its early success, thereby generating economic surpluses over time.” (Teece, 2007, p.29)

2.3 Different Understanding of Capabilities

The dynamic capabilities theory has gained much interest from both scholars and practitioners and has thus had a significant impact on strategic management theories and concepts. Different perspectives have been covered as well as tailored versions of the theory have also gained attention (Teece, 2014). The literature has, though, not always been consolidated. Winter (2003) states that, even though the dynamic capabilities theory is a useful addition to the strategic management theory, some scholars present scepticism of the concept. Eisenhardt and Martin (2000) express the criticism towards Teece et al.'s (1997) dynamic capabilities framework, claiming that sustainable competitive advantage is dubious in dynamic markets.

(23)

or redundant, bound to break down in volatile markets. In contrary to Teece's (2007) dynamic capabilities definitions including Sensing, Seizing and Transforming further explained in chapter 2.4.1, Eisenhardt and Martin (2000) define dynamic capabilities as specific and identifiable processes such as product development and innovation. Additionally, in 2003, Winter declared that investing in dynamic capabilities might turn out to be a cost-burden when there is no change nor a volatile environment.

Additionally, there has been a debate between scholars on the exact meaning of the

‘capabilities’. Winter (2003) states that what he considers missing in the Teece et al., (1997) definition, are a ‘Zero-level capability’. He describes the zero-level capability as the core of the business, crucial to the firm’s earning of revenues. Teece (2014, p.329) responds by stating that “capabilities are what the organisation could accomplish, not necessarily what it is currently producing.”. To shed light on the confusion, Teece (2014) classes two types of capabilities; ordinary capabilities and dynamic capabilities. Ordinary capabilities entail ‘doing things right’ while dynamic capabilities entail ‘doing the right things’ (Teece and Leih, 2016).

To reduce confusion, both types of capabilities are described below:

Ordinary Capabilities: The ‘Zero-level capability’ defined by Winter (2003) refers to what a firm must do in order to earn revenues. Ordinary capabilities were defined by Teece (2014) as a response, to clarify the dynamic capability theory further; stating that the zero-level is an ordinary capability and not a dynamic. Ordinary capabilities usually fall into three categories:

administration, operation and governance; factors which facilities the company to complete tasks (ibid.) These capabilities can support competitive advantage for long periods and are thus similar to the ‘Zero-level capacity’ by Winter (2003). However, ordinary capabilities tell nothing about how a company can perform in the future (Teece, 2014).

Dynamic Capabilities: the dynamic capabilities, as opposed to a firm’s ordinary capabilities, involve higher-level activities, such as managing the company’s recourses to address and shape rapidly changing business environments (Teece, 2014). According to Ambrosini and Bowman (2009), dynamic capabilities do not come fully formed from the start but are usually the result of experience and learning within the organisation. Teece (2014) agrees by stating that these kinds of capabilities arise from a combination of learning, the organisation’s history, and the organisation’s recourses. Dynamic capabilities are not what the firm is producing as of now;

but what the firm could be producing in the future.

2.4 Formulating Dynamic Capabilities

Teece et al. (1997) emphasise that many dimensions of the business must be understood to formulate dynamic capabilities. Three categories thus shape the theory; Processes, Positions and Paths (Teece et al., 1997).

Processes: The processes imply the way things are done, such as organisational and managerial processes and routines. Within these, Teece et al. (1997) explain three roles. The first is coordination/integration, being routines related to coordination, where a capability lays

(24)

in distinctive ways to coordinate. The second role within organisational processes is learning, which involves both organisational skills and individual skills, where learning requires standard codes of communication and coordinated search procedures. The third role is reconfiguration which refers to the ability to reconfigure processes for changing environments to accomplish the necessary transformation. To be able to reconfigure processes, there is a need to investigate and understand the environment and market changes as well as keep an eye on competitors (ibid.).

Position: The position explains the organisation’s current phase. The current phase includes customer base, external relations, market position, competition, intellectual property, technological assets, financial assets, reputational assets, organisational structure, complementary assets, specific assets such as difficult-to-trade knowledge and organisational boundaries (Teece et al., 1997). All of these aspects matter in order to understand the current situation of the firm. External drivers are essential, but can, however, change during time, which makes the internal capabilities important for dynamic capabilities (Nedzinskas, 2013).

Paths: Driven by the processes and position, paths refer to where an organisation can go. Path dependencies are a function of where a firm has been in its past and current phase, and thus shapes where the firm can go further. The strategic alternatives available, technological opportunities (both dependent on technologica opportunities in the industry and the firm's past experiences with technology), shapes the paths of the future. The paths thus affect the alternatives that managers can perceive, such as the ability to identify a blue ocean, as well as the assessment of the replicability and imitability of the organisation’s processes and position (Teece et al., 1997).

2.4.1 Activities and Adjustments

Teece (2007) further develop the theory by dividing dynamic capabilities into three clusters of activities and adjustments, that must be performed well to sustain in a changing environment;

(1) identification and assessment of an opportunity (Sensing), (2) mobilisation of recourses to address an opportunity and to capture value from doing so (Seizing), (3) continued renewal and reconfiguration (Transforming). The activities and adjustments are illustrated in Figure 1.

(25)

Sensing: The sensing activities include scanning, creating and learning when and how opportunities arise, the interpretation of, for example, which technologies to pursue and when, forecast how and when different actors in the ecosystem will react and making investments for such activities (Teece, 2007). Dong et al., (2016) further divide the sensing capabilities into framing and abduction, where framing refers to the act of drawing associations between facts and situations to clarify actions. Abduction is referring to the ability to logically reason and create hypotheses to explain observations, that can be scanning the environment or to establish a solution principle and test its desired outcome. Teece (2007) mentions the importance to create organisational processes for sensing, instead of leaving these activities to a few individuals. There should, therefore, be processes for gathering information and scanning the market to identify new technologies, new trends and business opportunities.

As a consequence, organisations will avoid missing opportunities visible to others (Teece, 2007). Dong et al. (2016) further emphasise that it can be beneficial to protect such processes from the rest of the organisation, to entail proper funding and the freedom to pursue projects that provide results far into the future. Such departments are thus reliant on strong management support, and internal discussions about the changing markets and state of technology are of crucial importance to dynamic capabilities (Teece, 2007). However, Teece (2007) further adds that no matter how much sensing activities are done, they must be supported by the management’s investment skills.

Seizing: Teece (2007) explains that after the sensing stage, the perceived opportunities need a mobilisation of recourses and to capture value from doing so. When the opportunity is mature, it is time to invest in particular technologies or ideas most likely to create gains for the firm.

The activities of seizing are, for example, selecting product architectures, allocate resources, redesign internal structures, selecting enterprise boundaries, managing complements and platforms, and ensure fast decision-making. Teece (2007) adds that it is of importance to build loyalty and commitment in the organisation to handle the new processes. In 2018, Dabab and Weber (p. 5) further explained one way to seize opportunities by “configuring both tangible and intangible assets that help to overcome the business challenges. Therefore, the capability of companies to seize opportunities and threats will depend on skills and experiences that they have.”

Transforming: The transforming activity is needed when addressing opportunities or when managing threats (Teece, 2007). Transforming is about the ability to make a continuous or dramatic change in the organisation (Dabab and Weber, 2018). Transforming must, however, be exercised periodically to soften rigidities of change (Teece, 2014). To be able to transform, Teece (2007) defines the transforming abilities, critical to business performance, and a fundamental foundation of dynamic capabilities as; achieving decentralisation to embrace open innovation, learning, knowledge management, and corporate governance; enable such learning on all levels and integrating the know-how from the outside and within the firm. The transformation part of a company’s dynamic capabilities thus depends on supportive

(26)

leadership, and how well the top management influence employees to embrace and adapt to the change (Teece, 2014).

2.5 Dynamic Capabilities at Traditional Incumbent Firms

As clarified, the ability to keep along with the fast-changing environment requires strong dynamic capabilities and an innovative and flexible organisation. However, implementing change in a large, incumbent organisation is difficult, and sometimes requires entirely new and separate units (Teece, 2018). Felin and Powell (2016) mention the risk of failure in fast- changing environments when a firm continues with old ways of organisational design and structure, with hierarchy, formal reporting and divided functional areas. Those organisations are often more rigid and resistant to change because the prioritisation lays on perfecting the current ways and routines rather than exploring new ideas (Teece, 2018). An organisation can be great at sensing opportunities but still fails to invest in them when focusing on improvements related to the old processes (Teece, 2007), where the efforts to achieve best practice (i.e.

ordinary capabilities) distract the management from achieving change (Teece, 2014). Another mistake incumbents do is expressing the mixed message of encouraging innovation and fast decision-making while retaining and prioritising the old ways of bureaucratic processes and slow systems (Felin and Powell, 2016).

Most incumbents believe that they are better at innovation and change than they are, and only a few do sacrifice the centralised decision-making and hierarchy (Felin and Powell, 2016).

Decision-making in organisations with traditional structures can be long and dependent on many levels of decisionmakers, which maintains the status quo (Teece, 2007). Teece (2018) further highlights that the structure of a company affects its innovativeness and its building of dynamic capabilities, where a decentralised structure and shallow management hierarchies are a foundation of an innovative company that is responsive, creative and flexible.

Decentralisation helps to build dynamic capabilities by bringing the top management closer to new technologies and the opportunities and threats of the surrounding market (Teece, 2007).

Large incumbents usually operate on old systems and processes that do not support the new technologies, and implementation failures can occur due to a conflict between the current processes and the requirements of the new (Teece et al., 1997). The old structures and the, usually, large amounts of established assets are further causing incumbents to be more risk- averse than new entrants. Biased decision-making comes as a result of the risk-aversion and limits the likelihood of incumbents trying risky innovations (Teece, 2007).

In many industries, the market is restricted by laws, regulations and business ethics, which further influences a firm’s position and ability to change (Teece, 2007). Incumbent firms consequently face inertia when markets change and are likely to be replaced by companies that are better suited for that context (Teece, 2014). Tech giants such as Amazon, Apple, Facebook and Google are examples of companies that obtain strong dynamic capabilities and have managed to reform industries (Felin and Powell, 2016). For companies with more limited dynamic capabilities, it might require different strategies to achieve success. If the company,

Surviving the Digital Transformation

Surviving the Digital Transformation

- The Case of an Incumbent Insurer

CAMILLA BRATT FORSS EMMA JANSSON

Surviving the Digital Transformation

– the Case of an Incumbent Insurer

by

Camilla Bratt Forss Emma Jansson

Att överleva den digitala transformationen

- en fallstudie av ett väletablerat försäkringsbolag

Camilla Bratt Forss Emma Jansson

Table of Contents

List of Figures

List of Tables

Glossary

Abbreviations

Foreword

1. Introduction

2. Theoretical Aspects