An exploration of drivers and inhibitors of digital transformation in professional service firms : A multiple case study in management consulting industry

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An exploration of drivers and inhibitors of

digital transformation in professional service

firms

A multiple case study in management consulting industry

BACHELOR THESIS WITHIN: Business Administration NUMBER OF CREDITS: 15 ECTs

PROGRAMME OF STUDY: International Management AUTHORS: Sara Hooton, Yiming Yuan, Xiaoyu Zhai JÖNKÖPING May 2020

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Bachelor Thesis in Business Administration

Title: An exploration of drivers and inhibitors of digital transformation in professional services

firms

Authors: S. Hooton, Y. Yuan, and X. Zhai Tutor: Ryan Rumble

Date: 2020-05-18

Key terms: Digitisation, Digitalisation, Digital Transformation, Disruptive Technology,

Professional Services Firms, Managing Consulting Firms

Abstract

Background: Professional services have not been digitally disrupted in more than decades. Different

emerging technologies are changing the business environment today. The rapidly increasing amount of different available technologies are affecting organisations and their industries and require them to conduct digital transformation (DT). Yet little attention has been paid to professional service firms. This gap in the literature, together with the relevance of the topic guided the authors to research further what the specific influencing factors in the adoption of digital transformation in professional service firms (PSFs) are.

Purpose: Thepurpose of this study is to explore the underlying factors influencing and affecting DT in PSFs, one type of PSFs in particular - management consulting firms (MCFs). The aim is to find the most influential factors and better understand their effects on the adoption process. By exploring these factors, this study can contribute significantly to the existing literature and increase the understanding of the phenomenon.

Method: This is an exploratory qualitative multiple case study with four pilot interviews to create a

broader and in-depth knowledge on the phenomenon, and 6 case companies to collect rich and insightful data. The qualitative approach of interviews created primary data for empirical findings which were further coded and analysed together with secondary data.

Conclusion: From the findings and analysis, the authors extended the TOE framework to fit the topic

of DT in PSFs. This was created based on the empirical findings and analysis to answer the research question. Altogether, 15 factors were classified within the super-themes of technology, organisation, and environment with driving or inhibiting effects. The findings indicate that most factors found are organisational. However, some interesting contradictions were noted between the empirical findings from both primary data as well as the secondary data. The research demonstrates the similarities and the different perceptions of the phenomenon and therefore it provides insights and understandings of the topic in its specified context. What is more, it leaves room and suggestions for future research regarding DT in PSFs.

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Acknowledgments

Firstly, we would like to give special thanks to our tutor Ryan Rumble, whose support from the very start has been substantial and has helped us to challenge and improve ourselves and whose contributions helped shape this thesis. We wish to thank Ryan for his input and guidance. We are truly grateful for all his advice, time he has put into assisting us, and essentially sharing his knowledge and expertise with us.

We would also like to thank all the pilot interview and case interview participants, as for them this research would not have been able to be conducted. We highly appreciate all the participants for taking the time from their busy lives to talk to us and share their knowledge and experiences. We thank each participant for showing interest in the topic and for their inputs to the research. We recognise the worth of their contributions and want to thank each participant for their kind support and willingness to be a part of this research.

We want to give thanks to anyone who helped us along the process and took the time to review and comments on our paper. To our friends and family who helped and endured us through the more challenging and stressful times as well as the good ones of this process. This thank you especially extends to our peers in the seminar group who gave valuable feedback and questions to consider throughout the process.

Finally, we wish to thank Jönköping International Business School for making all of this possible and giving us this possibility to showcase our skills, develop ourselves, and ultimately for this incredible learning experience. Thank you to all our professors who have taught us along the way, as it is for them, we had the knowledge and competences to carry out this research. All the staff, our peers, and the amazing people we have gotten to know have each helped us shape our academic career, which we are truly grateful for.

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3 Methodology ... 21 3.1 Introduction to Methodology ... 21 3.2 Research Philosophy ... 21 3.2.1 Case Philosophy ... 22 3.3 Research Approach ... 23 3.4 Research Design ... 23 3.4.1 Typology ... 23 3.4.2 Research Strategy ... 24 3.4.3 Research Method ... 24 3.5 Sampling ... 24 3.6 Data Collection ... 26 3.6.1 Primary data ... 27 3.6.2 Secondary data ... 29 3.7 Data Analysis ... 29 3.8 Data Quality ... 30 3.8.1 Reliability ... 30 3.8.2 Validity ... 31 3.8.3 Bias ... 31 3.8.4 Generalisability ... 32 3.9 Research Ethics ... 32

4 Empirical Findings and Analysis ... 34

4.1 Technology ... 35

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4.1.2 Availability of Technology (+) ... 36

4.1.3 Nature of Technology (-) ... 37

4.1.4 Data security (-) ... 38

4.2 Organisational Context ... 38

4.2.1 Top management team (+/-) ... 39

4.2.2 Resistance to change (-) ... 40

4.2.3 Personnel Capability (+/-) ... 41

4.2.4 Company Culture and Value (+/-) ... 43

4.2.5 Value Proposition (-) ... 45

4.2.6 Financial Resource (+/-) ... 46

4.3 Environmental Context ... 47

4.3.1 Client (+) ... 47

4.3.2 Government policy and regulation (+/-) ... 48

4.3.3 Competitor (+) ... 49 4.3.4 Industry Trend (+) ... 50 4.3.5 COVID-19 (+) ... 51 5 Conclusion ... 54 6 Discussion ... 55 6.1 Implications ... 55 6.1.1 Theoretical Implications ... 55 6.1.2 Practical Implications ... 55 6.2 Limitations ... 56

6.3 Suggestions for future research ... 57

7 Reference ... 59

8 Appendix ... 67

8.1 Appendix 1 Interview Guide ... 67

8.2 Appendix 2 Consent Form ... 69

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1 Introduction

In this chapter, the topic of digital transformation in professional service firms is first introduced to provide the background of this study. It follows a problem statement highlighting the current research gap. Thereafter, research purpose, question, perspective and delimitation are provided to express how this thesis intends to close the gap. Lastly, a list of key term definitions is presented.

1.1 Background

In recent years, the proliferation of digital technologies, such as artificial intelligence (AI), data analytics, machine learning, and cloud computing, has accelerated the change of consumer behaviour, initiated digital innovation, and created new business models (Christensen, 1997; Bharadwaj, EL Sawy, Pavlou, & Venkatraman, 2013; Matt, Hess, & Benlian, 2015; Kavadias, Ladas, & Loch, 2016; Fielt, Desouza, Gable, & Westerveld, 2018). Triggered by digital technologies, a new reality of digital disruption where industries are upended and rules of business are changed, requires firms to increase their commitment that goes beyond business process reengineering or information technology (IT) implementation (Kane, Palmer, Philips, Kiron, & Buckley, 2015; Schallmo, Wlliams, & Boardman, 2017; Kane, 2019). The adaption to this new reality that improves an entity by launching significant changes to its properties through a combination of information, computing, communication and connectivity technologies is therefore named as digital transformation (DT) (Vial, 2019). This revolutionary change has had DT raise enormous attention from practitioners, public entities, and scholars. For example, there is a vast amount of DT related consultancy reports (Chui, Manyika, & Miremadi, 2016; Hemerling, Kilmann, Danoesastro, Stutts, & Ahern, 2018; Bughin, Manyika, & Catlin, 2019); World Economic Forum launched a digital transformation initiative in 2015 to unlock $100 trillion opportunities for businesses and society (World Economic Forum, 2018); a highly cited literature in Information System research domain found 28 academic sources offering 23 unique definitions of DT (Vial, 2019). Unlike technologies that caused previous industrial revolutions, it is believed that this round of digital technologies and DT will fundamentally change the way knowledge workers make their living, and the impact on professional service firms (PSFs) will be fundamental and irreversible (Susskind & Susskind, 2015).

PSFs include a long list of different types of expert firms, such as law firms, accounting firms, engineering, and management consulting firms (Greenwood, Suddaby McDougald, 2006). In modern days, PSFs have significant economic and social value. They have not only contributed to profound

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economic growth but also have become a fast-growing source of employment in both developed and developing countries. In 2018, the Professional and Business Sector accounted for more than 11% of the United States’ gross domestic product (GDP) (US Bureau of Economic Analysis, 2020), and these estimates are likely being conservative as they excluded PSFs in industries like real estate, financial services and medical services. In the United Kingdom, Professional Service employed 14% of its workforce (World Economic Forum, 2018). In China, the service sector’s share of GDP reached 53.3% in 2018, and it has become the main driver for economic growth (Reuters, 2020). As their role of providing expertise to other industries, PSFs are the vanguard of digital transformation, and they have a critical impact on industries far beyond their own. For example, some leading management consulting firms have started revisiting their services portfolio and adjusting business models to drive disruption and help their clients initiating DT. McKinsey & Company (McKinsey) established McKinsey Digital and Boston Consulting Group (BCG) rapidly expanded “BCG Gamma” (Curuksu, 2018). Despite PSFs’ outward agility in responding to clients’ changing needs, DT of themselves is a different matter. As PSFs are primarily comprised of professionals and their key resources are intellectual capital provided by professionals’ knowledge-intensive services (Greenwood et al., 2006), DT on the other hand, emphasises on leveraging digital technologies to create value. Thus, DT requires PSFs to adapt business models and practices, employ different resources, and propose new value propositions (Teece, 2018). However, the business model of PSFs has changed little in this past century (Christensen, Wang, & van Bever, 2013). For PSFs to initiate DT on their own, it poses a particular difficulty.

Nevertheless, with increasing and accelerated influence from digital technologies, PSFs are facing more and more disruptions, particularly having more automation and commoditization of their knowledge-intensive work (Susskind & Susskind, 2015). It is believed that drastic changes under the surface are stronger than many people realize, and DT is at a tipping point (World Economic Forum, 2018).

1.2 Problem

Although digital technologies are expected to have an increasing and accelerated impact on PSFs, this phenomenon has received little attention in the literature. Very few empirical studies supporting the statement of drastic change exist, and it is unknown about the way in which PSFs will change or what consequences digitalisation will have for them (Manyika, Chui, Bughin, Bisson, & Marrs, 2013; Jesuthasan, Malcolm, & Zarkadakis, 2016; Breunig & Skjølsvik, 2018; Andersson, Movin, Mähring,

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Teigland,& Wennberg, 2018). The shortage of literature is mainly due to the considerable difficulty in gaining up-to-date information as a majority of PSFs are privately owned and accordingly are not legally required to disclose financial information; another reason is professional service scholars representing a still small, though rapidly developing niche field in management research (Empson, Muzio, Broschak, & Hinings, 2015).

This leaves an important gap on the topic of DT in PSFs. Due to its empirical significance and theoretical distinctiveness, it would be beneficial for the current study to expand a perspective of digital transformation to another type of firm - PSFs. Meanwhile, management consulting firms (MCFs), which are categorised as Neo-PSFs (von Nordenflycht, 2010), are going through a talent challenge resulted from the flourish of digital technologies. Management consulting is one of the most common and most popular sought-after industries among MBA graduates; however, it has been perceived to be less appealing and aspirational to young talents compared to start-ups in the technology sector (Llewellyn, 2017; Larsson, Andersson, Markowski, Nilsson, & Mayor, 2019). Likewise, literature about DT in management consultancy is rare. Most literature has focused on virtualizing consulting services in Germany (Nissen, 2018). As a result, the limited empirical knowledge on DT in PSFs means researchers need to explore activities that MCFs perform to implement DT and discover why MCFs are slow in adopting disruptive digital technologies and initiating a transformation. An exploration of this topic will be beneficial for enriching academia’s understandings, helping practitioners form a better strategy to compete at the era of DT, and guiding business graduates to wisely develop their career path.

1.3 Purpose

The purpose of this study is to explore the underlying factors influencing and affecting digital transformation in professional service firms, one type of PSF in particular - management consulting firms (MCFs). Similar to other types of PSFs, management consulting firms share the same characteristics of low capital intensity and high knowledge intensity and the only characteristic that makes it Neo-PSF is the absence of strong professional ideology and weak regulation and control (Nordenflycht, 2010). Nonetheless, this unique characteristic does not inhibit this thesis’s theoretical transferability as digital transformation focuses solely on the conflict between the usage of technological capital and human capital. Furthermore, compared to researching the most typical type of PSF – law firms, a business administration thesis that studies management consulting firms could generate more practical insights for its intended audience, students with an academic background in

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management. Besides, choosing MCFs among other types of PSFs is due to authors of thesis having work experience of this industry, which provides a certain amount of background knowledge and familiarity of specific language and terms that are valuable in preparing and conducting this research. Due to the time limit of roughly five months, having previous working experience in this industry is beneficial for getting access to intended interviewees.

Although previous literature has found that the proliferation of digital technologies has enabled disruption in management consulting firms (Christensen et al., 2013). It is, however, not yet empirically established how internal digital transformation has been conducted by PSFs and what factors are accelerating or slowing down the implementation of digital transformation.

Being the first literature to explore this phenomenon, a holistic view is expected. This exploratory study, therefore, seeks to uncover drivers and inhibitors coming from technological, internal and external environments for management consulting firms to implement digital transformation for themselves. If these drivers and inhibitors can be well understood, decision-makers in professional service firms could then develop corresponding strategies and result in a more successful outcome of digital transformation.

Derived from the purpose, we aim to answer the following research question (RQ):

RQ: What are the firm-level drivers and inhibitors for digital transformation within professional service firms?

1.4 Perspective

Considering the purpose, this thesis is looking into influential factors from the firm level, it would be reasonable to take a perspective from the management team within the firm as their decision making influences the firm as a whole and their decision making requires a thorough and holistic consideration on technological, internal and external environments. In this case, the perspective of this thesis is from senior executives in management consulting firms.

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1.5 Delimitation

This thesis intends to explore the firm-level drivers and inhibitors for digital transformation in professional service firms from the management teams’ experience in the management consulting industry. Therefore, the scope of professional service firms is limited to the management consulting industry, and the chosen interviewees are senior executives who have been working in world leading MCFs. Since most world-leading MCFs are multinational with more than thousands of employees, this thesis does not include small and medium-sized boutique management consulting firms.

Despite the aim of exploring different factors, this thesis does not seek to find all factors that could influence the implementation of digital transformation. This thesis rather tries to understand the most important and influential factors in the context of management consulting. Therefore, this thesis will choose qualitative instead of quantitative research method.

1.6 Key Term Definitions

Digital Transformation (DT): A company-wide process, in which emerging and disruptive technologies, operational technology, and strategic technology are leveraged in the aim to improve an entity.

Disruptive Technology: Technology that ultimately changes the organisation, systems, or habits. For example, automation, artificial intelligence, and blockchain.

Professional Service Firms (PSFs): Knowledge intensive firms that provide services and advice to other businesses by leveraging professionals’ intellectual capital and expertise.

Management Consultancy Firms (MCFs): An advisory service contracted for and provided to organizations by specially trained and qualiﬁed persons who assist, in an objective and independent manner, the client organization to identify management problems, analyse such problems, and help, when requested, in the implementation of solutions. MCFs is a type of PSFs that falls under the Neo-PSF category, in which professional advisory is provided regarding management problems specifically.

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2 Frame of Reference

2.1 Literature Searching Method

T present scientific evidence in the field, an in-depth yet objective, as well as holistic analysis of relevant academic studies, is conducted. Under the formulated research question, the boundary of this study is defined within the topic digital transformation of professional service firms.

In this context, a structured procedure is taken to identify relevant literature. All literature is collected through Jönköping University's library search engine Primo as well as the databases of Google Scholar and Scopus. Articles are academic and peer reviewed. In particular, references for each article are also critically reviewed. The selection criteria of the peer-reviewed article are considered to increase the reliability and trustworthiness of this thesis. Since this research is investigating a relatively new phenomenon, there is a shortage of articles. In this case, conference papers and academic books written by reputable scholars with high relevance on this topic are also reviewed.

The keywords used in the search process are: "Digital", "Professional Service Firm", "PSF", "Knowledge Intensive Firm", "Management Consulting", "Digital Transformation", "Driver", "Inhibitor", and "Challenge". Relevant literature to the research topic was selected, read and synthesized.

2.2 Evolution of Digital Transformation

Over the last few decades, the terms digitization, digitalization and digital transformation have been used interchangeably (Schallmo, Williams, & Boardman, 2017); however, the development of technology and changing business environment have made their meanings distinctive to each other. Thereafter, definitions of each term are synthesized and then adopted to guide this research study.

There are many kinds of definitions of “digitization” which differ depending on the context. One of the most popular definition is the conversion of specimen data from analogue to digital signals (Schallmo & Williams, 2018). More recently, Verhoef, Broekhuize, Bart, Bhattacharya, Dong, Fabian & Haenlein (2019) reviewed multidisciplinary literature and defined digitization as the first phase for digital transformation, and it only digitalizes internal and external documentation processes but does not alter value creation activities.

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In contemporary time, the first use of “digitalization” can be found in an essay published in the North American Review in 1971 (Schallmo & Williams, 2018). Since then, this word has been a changing concept and there is not a universally accepted definition (Fors, 2010). IT, digital technologies, and business processes are often involved in creating the definition for digitalization. For example, Li, Nuciarelli, Roden & Graham (2016) describe that digitalization is altering existing business process through implementing IT and digital technologies. Verhoef et al. (2019) emphasise IT as a critical enabler to capture new business opportunities through digitalization where business processes and relationship management are changed. Thus, digitalization is considered as a more advanced phase in using digital technology in comparison with digitization, and it often changes organisational products and processes for cost saving and enhancing customer experience.

Digital transformation, likewise, does not have a widely accepted definition. Although back to 1990s and 2000s, digital products, services and medium have arisen (Schallmo et al., 2017) and certain literature used the term DT to call for industrial and academia’s attention in realising the value of new informational technologies (Andal-Ancion, Cartwright, & Yip, 2003), scholars did not seek to conceptualize it in detail. Until more recently in 2014, there was an exponential growth on the literature about this term. However, its definition is still fragmented. Vial (2019) reviewed a comprehensive body of Information System literature on digital transformation and found 28 academic sources offering 23 unique definitions of DT. Based on that, Vial (2019) constructed a conceptual definition of DT 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” (p. 121). Besides, Verhoef et al. (2019) reviewed literatures from

information systems, strategic management, marketing, innovation, and operations management and provided a multidisciplinary definition as describes “a company-wide phenomenon with broad

organizational implications in which, most notably, the core business model of the ﬁrm is subject to change through the use of digital technology” (p. 4). However, it should be noted that digital

transformation does not mean only leveraging emerging or disruptive technologies, it also could come from using operational technology (such as databases) and strategic technology (such as enterprise resource planning system) (Andriole, 2017).

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2.3 Extant Research on Digital Transformation in Professional Service Firms 2.3.1 Professional Service Firms

Professional Services Firms (PSFs) are knowledge intensive organisations that facilitate economic and commercial exchange by providing advice to other businesses (Greenwood et. al. 2006). They are comprised primarily of professionals with key resource as intellectual capital and expertise; therefore, PSFs operates in different industries such as law, accounting, management consulting, etc. (Greenwood et al., 2006).

There are certain norms in PSFs. Professionals show a preference for autonomy, exhibiting a distaste for control, supervision, and formal organisational processes (Greenwood & Empson, 2003; Løwendahl, 2005; von Nordenflycht, 2010). This results in flatter organisational structures and authority is based upon individual capability and expertise rather than position (Greenwood et al., 2006) Another norm is showing responsibility towards their clients in protecting their interests (Løwendahl, 2005). As Løwendahl (2005) indicates PSFs employ a very high percentage of highly educated people, and they are overly dependent on their ability to attract, mobilize, develop and transform the knowledge of these employees to create value for their clients, the competitive advantage of PSFs (von Nordenflycht, 2010) has therefore been explained by the high degree of information asymmetry that exists between the professionals and their clients, which leads to opacity related to the client’s ability to assess the quality of offered services.

Maister (1993) notes that PSFs perform three types of work: (1) procedural work for which the solution/approach is (mostly) well-known and the focus is on efﬁciency, (2) grey hair work requiring skills and experience, and (3) brain work requiring expertise and innovation. Maister (1993) also states that there are two important characteristics of professional work: (1) professional services involve a high degree of customisation in their work and (2) professional services have a strong component of face-to-face interaction with the client. All of these can be summed up into a set of characteristics that comprise the professional services firms’ industry, where are highly knowledge intensive (Starbuck. 1992), require a high degree of customisation and discretionary efforts, and the interaction between clients is substantial (Greenwood et al., 2006).

The most relevant literature for this paper regarding PSFs is von Nordenflycht’s (2010) theory of knowledge intensive firms. He, likewise, recognises three main characteristics for PSFs: knowledge

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intensity, low capital intensity, and a professionalised workforce. From this, this scholar developed a typology which categorises PSFs into four types: Technology Developers, Neo-PSFs, Professional Campuses, and Classic/Regulated PSFs (von Nordenflycht, 2010). Management consultancy firms fall under the Neo-PSFs paradigm as they are a mix of public and private ownership, low in capital intensity, high in knowledge intensity, and there is an absence of a strong professional ideology and weak regulation and control (von Nordenflycht, 2010). Table 1 helps to visualise this typology.

Table 1: von Nordenflycht´s Taxonomy of PSFs

2.3.2 Management Consulting

Greiner and Metzger (1983) define management consulting as “an advisory service contracted for and provided to organizations by specially trained and qualified persons who assist, in an objective and independent manner, the client organization to identify management problems, analyze such problems, and help, when requested, in the implementation of solutions”. Recently, Fincham, Mohe, & Seidl (2013, p. 5) define management consulting as including “any activity that has as its apparent justification the provision of some kind of support in identifying or dealing with management problems, provided by individuals, groups, or organisations that are external to the particular management domain and which are contracted by the management on a temporary basis”. In 2014, Srinivasan (2014) seeks to characterise the landscape of the management consulting industry through four characteristics (a) external to the organisation; (b) hired on a temporary basis; (c) valued for their specialised experience and expertise that is not easily available within the client organisation; and (d) compensated for their advice on improving the organisation’s performance and educating the client on handling similar problems in the future.

Knowledge Intensity Low Capital Intensity Professionalised Workforce Biotech R&D labs Consulting Advertising

Professional Campuses Hospitals X X

Law Accounting Architecture Category Industry Examples X X X Technology Developers Neo-PSFs Classic PSFs (or Regulated PSFs) Characteristics X X X

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Management consultancy firms' output is dependent on a complex body of expertise and knowledge which they possess amongst their employees and routines, or have access to through their networks (Creplet, Dupouet, Kern, Mehmanpzir and Munier, 2001). Meanwhile, scholars argue the professionalism exists in management consulting industry. Furusten (2013) argues the mechanism for authorisation of professionalism and expertise is through the acceptance in the market that is gained through institutionalized versatility, availability, relevance and differentiation in the field. Susskind & Suskind (2015) also spoke for the passion for professionalism in management consulting, even though it is not a regulated profession.

Based on the specialisations of management consulting firms, Srinivasan (2014) evolved a typology of management consulting firms (See the following table) which has been used to frame this study.

Table 2: A Typology of Management Consulting Firms

Thus, it is difficult to create a widely accepted definition about the concept of management consulting, and there are few considerations to be made about them that create challenges. Firstly, it is highly fragmented with a variety of consulting firms (Srinivasan, 2014). Secondly, unlike other professional service ﬁrms, such as accounting and law, management consulting industry has not been regulated and little attention has been paid to even the establishment of professional bodies such as consultants’ associations (Nordenﬂycht, 2010). Thirdly, despite the differences in firm size and scale, there exists a wide variety in the positioning and differentiation of services. There are consulting firms that provide management consulting services about strategy, marketing, operations management, financial management, human resource management and information technology management (Curuksu, 2018). Management Specialization Basis of differentiation Temporal involvement Implementation responsibilities Extent of client capture

Strategy and organizational

restructuring Tacit knowledge Short to medium term Minimal involvement Very high

Technology/

Operations and Cost control

Breadth of experience and expertise

Long term, throughout the assignment

Strong involvement in implementation of the

advice Moderate to high

Niche consulting Deep domain expertise

Long term, typically as retainers

Ownership of the

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2.3.3 Digital Transformation in PSFs

Scholars have recognised the importance of studying the impact of digital technologies to professionals more than two decades ago. Christensen (1997) found that there are two types technologies driving innovation and changes, sustaining and disruptive technologies. Sustaining technologies are those that support and enhance traditional way of operating in an organisation or an industry, whereas disruptive technologies are those fundamentally challenge working practices (Christensen, 1997). More recently, Susskind & Susskind (2015) further progressed these two concepts by categorising the impact of any technology into two broad headings – automation and innovation. Susskind & Susskind (2015) indicated that automation generally means the same as sustaining technology where efficiencies and cost-savings are the two factors leading the automation of traditional professional work; innovation, however, adds positive impression to disruptive technologies by arguing that disruptive technologies may empower professionals and benefit services receivers with more accessible and affordable services.

Scholars have also theoretically discussed how digital technologies would transform professional services. Christensen et al. (2013) predicted over time, using data analytics and big data will change the consulting business and other professional services where opacity is high, and automation in this industry will result in the commoditisation of knowledge-intensive and expert-based work. From the disruptive perspective, the application of digital technologies could also lead to experts being replaced (Byrnjolfsson & McAfee, 2014) For instance, the rapid development of artificial intelligence (AI) may alter the human-intensive work in PSFs by utilising machines conducting the work of human (Huang & Rust, 2018). Meanwhile, digital technologies could also augment the abilities of the expert (Davenport & Kirby, 2015). From a more innovative perspective, commoditisation could also lead to opportunities for scaling and mass production (Sawhney, 2016; Kolbjørnsrud, Amico, & Thomas, 2016). Susskind (2015) also predicted in the 2020s and beyond; there will be emergence and adoption of the AI system in the professions.

Furthermore, researchers have also explored how PSFs could transform due to technology advancement. Fielt, Desouza, Gable, & Westerveld (2018) examined digital business model innovation in relations to PSFs and proposed a number of possible transitionary pathways for augmentation or automation and the need to scale. Breunig & Skjølsvik (2018) explored the impact of digitalisation on the legal industry through a longitudinal media study on the topic of ‘virtual law firms and discovered the virtual law firm increases flexibility and improves the work-life balance

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without jeopardising professionalism or business interests. Skjølsvik, Breunig, & Pemer (2018) later also combined empirical interview with a media study to explore the consequences of digitalisation for professional service firms operating within the legal sphere.

Besides, scholars have also discussed a revenue dilemma between PSFs and efficiency brought by technologies. PSFs have been generating revenue by providing judgement-based advice in the hourly rate, and it has been the core of its value creation for centuries (Susskind, 2010). Yet, increasing efficiency through automatisation, standardisation and re-use, allows more output to be produced per hour could result in the less billable hour (Maister, 2012).

In conclusion, little literature has discussed digital transformation in professional service firms and most articles with empirical evidence focus on law industry. The combined effect of disruptive technologies on PSFs is yet unknown, and scholars predict there could be potential for major changes (Jesuthasan, Malcolm, & Zarkadakis, 2016; Skjølsvik et al., 2018).

2.3.4 Digital Transformation in Management Consulting Industry

The business model used by many traditional management consulting firms has changed little in the past century, and their value proposition has always been grounded in deploying human capital and bespoke diagnoses (Christensen et al., 2013). Thus, some people from the consultancy world are sceptical about the changes brought by digital technologies and regard consulting as an immune industry against disruptions (Susskind & Susskind 2015; Llewellyn, 2017; Curuksu, 2018).

Christensen et al. (2013) argued that the opacity of working process creates difficulty for judging consultants’ recommendation and high agility in allocating human capital to smoothly realise big ideas have made the consulting firms bulletproof during the last years. However, these two characteristics are rapidly eroding in the digital environment. The knowledge created by experts has been democratized as many MCFs are willing to share much of their Intellectual Capital (IP) in content marketing campaigns (Llewellyn, 2017). Besides, the rising need for the innovative digital solution that clients require, poses a challenge as the largest consulting firms are unable to claim the years of experience as they do not have relevant capabilities for it. Although some consulting incumbents have responded with offerings such as McKinsey Digital to complement their more traditional offerings, this has made offers modularized and has blurred the line between management consulting and IT service providers (Christensen et al., 2013).

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More recently, Nissen (2017) reviewed the development of virtual consulting and compared it with traditional face-to-face consulting and considered that digital transformation of consulting will ultimately lead to a partially or completely virtualized process. However, his perception of digital transformation is different from the definition of digital transformation this thesis focuses on. Deelmann (2018) investigated consulting industry in German-speaking countries and realised that internally they are reluctant to be automated: high-resolution video conferencing, fast knowledge databases working with semantic technology and business intelligence technology are only three areas of application. However, automation will be very likely to be increasingly adopted by large size consulting firms, and the business model will change (Deelmann, 2018).

2.4 The Technology–Organisation–Environment Framework

The technology–organisation–environment (TOE) framework is a theoretical framework proposed by Tornatzky & Fleischer (1990), which describes how the adoption and implementation of technological innovations are influenced in the firm context. It states three different elements that influence technology adoption decisions in a firm level which are the technological context, the organisational context, and the environmental context (Baker, 2012).

The technological context includes all technologies, both the ones implemented at the firm as well as the ones available in the marketplace (Tornatzky & Fleischer, 1990). According to Collins, Hage, & Hull (1988), the existing technologies of the firm are crucial to the adoption process as they set a broad limit on the scope of technological change that a firm can accept. At the same time, Baker (2012) emphasises the firm influences innovation from unused existing innovations, which both demarcate the limits of possibility and show firms in different ways to evolve and adapt to technology. Innovations could bring progressive organisational change by adapting new features and new versions of existing technologies (Baker, 2012). Thus, firms must carefully consider the type of organisational changes they will undertake as a result of implementing innovative technologies.

The organisational context refers to the firm's characteristics and resources, which include linking structures between employees, communication processes, firm size, and the amount of slack resources (Tornatzky & Fleischer, 1990). The organisational context affects adoption and implementation decisions in several ways. Firstly, Baker (2012) indicates that mechanisms that link the organisation's internal subunits have impact. Here, the organisational structure is decentralised and focuses on teams that facilitate adoption of innovations, whereas organisational structure that

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emphasises formal reporting lines and centralised decision-making fits best for the implementation of technologies (Zaltman, Duncan, & Holbeck, 1973). Secondly, the behaviour and communication between top management team and other subordinates could promote or inhibit the adoption and implementation of novel technologies (Baker, 2012). Thirdly, Baker (2012) points out the lack of a conclusive link between firm size and innovation, and that further discussion should focus on the availability of specific resources. Last, slack is a factor that scholars consider “neither necessary nor sufficient for innovation to occur” (Tornatzky & Fleischer, 1990, p. 161).

The environmental context includes the industry structure, the availability of technology service providers, and the regulatory environment (Tornatzky & Fleischer, 1990). Within the industry structure, it is suggested that intensive competition could foster innovation and dominant firms often influence the value chain to change (Mansfield 1968; Mansfield, Rapoport, Romeo, Villani, Wagner, & Husic, 1977; Kamath and Liker 1994). Baker (2012) also argues that the relationship between technological innovation and industry life cycle should be further investigated. Furthermore, the availability of technology service partners is influencing the decision making as the absence of technological infrastructure is unable to support innovation (Baker, 2012). Moreover, government regulations can either encourage or discourage innovation; for instance, when governments force new restrictions on the industry, innovation is virtually mandated for the firms (Baker, 2012). Figure 1 depicts this framework visually.

Figure 1. The technology–organisation–environment framework

External Environment Industry Structure Availability of Technology Government Regulations Organisational Context Organisational Structure Communication Process Size Slack Technological Context Availability of Technology Characteristics Technological Innovation Decision Making

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The TOE framework has been broadly applied in different national and industrial contexts to explain different phenomenon and explore other factors for technological, organisational, and environmental contexts (Baker, 2012). The most recent study that has utilised this framework within the domain of DT is from van Dyk & Van Belle (2019), which explores the drivers and inhibitors for digital transformation in the South African retail industry. The adaptability of this framework gives the freedom to vary the factors for each new research context (Baker, 2012). Therefore, the authors consider TOE framework suitable in this relatively new research domain – digital transformation in professional service firms. At the same time, this firm level framework is compatible with the research purpose which seeks to understand the firm level drivers and inhibitors for DT, a phenomenon that requires innovation and implantation of new technologies.

2.5 Reflection on literature review

Having the literature reviewed, the current literature in the field of digital transformation in professional service firms are mostly discussing possible disruptions that might happen. The empirical studies on this phenomenon is still under research. Therefore, there is a lack of empirical understanding on the topic digital transformation in professional service firms. With this research gap identified, we expect to fill it by answering the following research question.

RQ: What are the firm level drivers and inhibitors for digital transformation within

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3 Methodology

3.1 Introduction to Methodology

After pinpointing some key facets existing in the current literature and demonstrating the relevance of the research topic, we continue to the practical applications in which the research will be carried out. The overall structuring of the study is first commenced by carefully, rationally, and creatively choosing the topic that would contribute to the existing knowledge and literature. After keeping the substantive theory of interest in mind, a proposition is formed to which a research design and method is created to further the objective of the research. Overall, the chosen methodological approach is a qualitative multiple case study with six global leading management consulting firms to create a broader and in-depth knowledge on the phenomenon. Once data from the case is collected, it will be linked directly to propositions and the initial research question through analytical generalisation. Our cases aim to shed light on the topic in hand, contribute, and further advance the existing literature with its derived empirical findings. Keeping in mind that the results of the findings are considered to be argumentative claims, as they are not numerical and based on statistical evidence, we will continue to discuss potential flaws and limitations in both our research design and findings.

The following part will discuss further regarding the chosen research philosophy, research method and design, data collection, analysis method, data quality and research ethics for this study in order to reach sufficient methodological rigor.

3.2 Research Philosophy

Research Philosophy is a much-debated topic that has reformed itself numerous times. There are overlapping ideologies and blurry lines between the different concepts of research. Commonly, research is identified as a systematic and methodical study on a specific topic in order to expand knowledge (Collis & Hussey, 2014), whereas research philosophy refers to a system of principles and assumptions regarding the advancements of knowledge through the years (Roulston, 2010). The three main assumptions today are the ontological assumption, the epistemological assumption, and the axiological assumption (Spencer, Pryce, & Walsh, 2014). These assumptions differ in relations to their nature and are interpreted differently along the continua between objectivism and subjectivism (Roulston, 2010). This research utilises these as building blocks in identifying the most applicable

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paradigm for this study as the assumptions can be directly related to different paradigms depending on their typology.

The two main opposing paradigms notable in business research today are the concepts of positivism and interpretivism (Collis & Hussey, 2014). The paradigm relevant for this paper is the interpretivist, which essentially aims to produce new, valuable knowledge and perspectives of different social and more complex contexts (Saunders, Lewis, & Thornhill, 2016). Moreover, according to Thorne (2014), it begins with the existing knowledge and beliefs of the phenomenon which it then aims to further extend and align with a purpose. This objective is grounded upon the assumption that the researchers are relatively unaware until they are fully involved and emerged, and have gained reflectivity about the findings (Thorne, 2014), which is all applicable for this study. Interpretivism looks at epistemology with the objective to gain insights, revelations, and understandings of created social reality rather than constructed systems (Collis & Hussey, 2014). With the adoption of an empathetic stance in the research, the nature of interpretivism makes it ideal for this research (Saunders et al., 2016). Thus, this study falls under the interpretivist paradigm as it focuses on theories and their generation rather than hypothesis by considering different perspectives. The paradigm will guide the further structuring and process behind the research.

3.2.1 Case Philosophy

The chosen method is multiple case study due to the applicable benefits and motivations which will be explained later. The importance of cases from a research philosophy perspective is critical. The importance in distinguishing the initial conception of this case is great as it influences the process of the research and thus the outcomes. Singularity and the concept of boundary of specific cases are the main identifying differentiation characteristics of a case study (Leavy & Simons, 2014). Consequently, according to Leavy and Simons (2014), when considering case-based methods there are several considerable factors first being the ontological recognition of case-objects where it is assumed that cases are ontologically real. Ragin (1992) maps this sociological conception of cases by first dividing it into two main assumptions: case as an empirical unit and case as a theoretical construct (as cited in Harvey, 2009, pp. 20-22).In this study cases are considered as empirical units which means that we can further analyse them into conceptually specific to the single case or conceptually subsumed under a general class of cases (Harvey, 2009). This thesis sees cases as subsumed, meaning that cases are perceived as objects rather than found (Harvey, 2009).

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3.3 Research Approach

The chosen research approach will help to connect the empirical data collected from cases to the proposed research question in an attempt to answer it. The determined framework guides the research that is based on different philosophies and assumptions (Collis & Hussey, 2014). The approach design relates to the process of theory development, in which there are three possible alternatives: inductive, deductive and abductive (Saunders et al., 2016). Most prominent ones being the deductive and inductive research. Induction moves from specific to generalisations whereas deduction is inverse. (Saunders et al., 2016) In general, interpretive description is a part of inductive research (Thorne, 2014). As there is not much empirical evidence in the literature, this thesis seeks to explore a novel phenomenon, this research therefore suitable to follow the induction approach as there exists presumptions which are utilised in order to develop untested conclusions. This helps us to explore this driver and inhibitors with an open mind and develop a theory later. Nevertheless, this does not mean we cannot use any theory or literature as they could help us draw insights for this research topic Saunders et al. (2016).

3.4 Research Design 3.4.1 Typology

Another important contributing factor that should be considered when delineating research design is the consideration of the typology which namely determines the type characteristics of the case (Elman, 2014). According to Elman (2014) there are many typologies that can be identified in business management research such as the descriptive, classificatory, and explanatory. Perhaps most recognised ones are the exploratory, descriptive, explanatory, and evaluative study (Saunders, et al., 2016). Typical for exploratory studies, this research starts from a broad focus which later narrows itself down (Saunders, et al., 2016). From these, this research follows the exploratory study as the purpose of this study is to better understand and clarify the nature of an existing phenomenon as there exists a lack of empirical findings on the topic, as of yet (Saunders et al., 2016). Another reasoning behind the choice is the ability for flexibility and adaptability to change of an exploratory study, that were crucial factors considering the limitations of this research (Saunders et al., 2016).

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3.4.2 Research Strategy

The main reason to back up the choice of doing qualitative study is the purpose and objective of this paper (Saunders et al., 2016). As qualitative studies are conducted especially when the research aims to deepen knowledge on a specific problem or issue and utilise selected participants to address it (Creswell, 2014). In addition, this paper intends to provide different and more in-depth perspectives of the phenomenon from which a larger picture can be drawn, which marks it as a qualitative study rather than quantitative (Creswell, 2014). As an exploratory study, the chosen strategy is ideal as it allows for using interview to ask open-ended questions in order to learn about the events and insights of the phenomenon (Saunders et al., 2016). To maximise the results, case study deemed to be the best fit as the adopted research method, as the main objective is to act as an effective blueprint and a strong knowledge base for the study (Yin, 2018).

3.4.3 Research Method

The methodological approach in this paper is determined as a comparative multiple case study, with 6 different case companies. More specifically this research is an embedded case study as it has several cases with several units of analysis rather than one case with several units of analysis (Saunders, et al., 2016). In general, this study can be classified as pure (basic) research as it aims to contribute to existing insights and theory with a profound gravity on academia (Collis & Hussey, 2014). As this study mainly focuses on exploring factors driving and inhibiting the adoption of digital transformation, this makes multiple case study an ideal method as it could provide similarities and differences for comparisons (Yin, 2018). The main advantage of a multiple case study over a single case study, is that the findings are often considered to be more compelling and therefore the study is more robust (Herriot & Firestone, 1983).

3.5 Sampling

Within the realm of interpretive research, different sampling approaches should be carefully considered, such as the convenient, theoretical and purposive approach (Thorne, 2014). The main challenge in regard to sampling for qualitative research, thus applicable for this study too, is the well-defined and reliable contextualizing of the nature and size of the selected samples (Thorne, 2014), meaning that the process of selection and elimination of possible interviewees required careful

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consideration. The chosen sampling method for this study is thereby non-probability sampling, and purposive sampling to be more precise (Saunders et al., 2016). This sampling method is the most applicable as it allows for the researchers to select the samples by careful judgement and consideration of the purpose of the study (Saunders et al., 2016). By selecting and directly contacting the chosen samples, the sampling criteria could be better maintained and upheld, and therefore gives room for richer and appurtenant data for the research (Saunders et al., 2016).

A systematic approach has been taken to select suitable case companies and interviewees. Since only those who have experienced digital transformation in management consulting firms could provide empirical evidence to answer research questions, the first step of sampling aims to create a list of companies that have initiated digital transformation. Due to limited public information regarding what management consulting companies have initiated digital transformation internally, pilot interviews were conducted with experts working in management consultancy, which provided necessary market knowledge to create a list of companies. More details regarding pilot interviewees will be discussed in the next section.

Since there are many specialisations of management consulting firms, the second step is categorizing selected companies based on the typology framework provided by Srinivasan (2014) in order to make sure a full coverage of all kinds of management consulting firms. Companies are there divided into three groups, (1) strategy and organisational restructuring; (2) technology / operations and cost control; (3) niche consulting. The third step is to identify ideal interviewees within those companies that are eligible for participating and effectively contributing knowledge and experience to the case study. Given that, three criteria were developed, (1) currently serving a senior management position in a target company; (2) having understood digital transformation; (3) having more than fifteen-years working experience in professional service firms. The first criterion is verified by job title and whether taking responsibility for profitability and loss (P&L). The second criterion is verified by carefully looking into their LinkedIn biography and profile listed on corporate website that could indicate their expertise or experience in digital transformation project. The reason for having the third criterion is for allowing their contribution of a greater overview and more holistic experience. It is verified the same way as the second criterion. Based on these criteria, authors carefully looked through corresponding companies’ website where executive team’s information is presented and used LinkedIn to filter senior executives with key words “CXO”, “Managing Director”, “Partner”, “Director” and “Vice President”. The job titles are unavoidably varied from firm to firm as the organisational structure and responsibilities might be different. The fourth step is sending invitation

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emails or using the InMail function of LinkedIn to contact all identified potential interviewees. In the end, only senior executives who replied invitations and met all above criteria were selected as samples.

Due to the impact of Covid-19, many potential interviewees had to cancel interviews for dealing its enormous impact and change on work routines. Therefore, executives from McKinsey and BCG, two world leading management consulting firms that have been famous for their digital transformation were unable to participate.

Following the above logic, there were in total six cases and six interviewees participated. A brief background of case companies can be found in the Appendix 3. Companies are referred to Company 1 to Company 6. Corresponding interviewees are named as E accompanied by a number to indicate which company they are from; e.g. E1 refers to an interviewee from Company 1, and E2 refers to an interviewee from Company 2. This helps authors to perform cross-case analysis, assures the anonymity of interviewees, and gives opportunities for readers to find the relationship among statements. The following table 3 helps to visualise the selected case companies and interviewees.

Table 3: Participating case companies and interviewees

3.6 Data Collection

Data collection is used to gather information on which aspects such as identifying themes and patterns can be explored and from where conceptual frameworks can be created. In the collection of data, an extensive understanding and grasp of the topic is essential along with ethical considerations. The data collection data techniques used for multiple case studies usually come from interview, direct observations and archives as various sources could strengthen the trustworthiness (Yin, 2018). Nevertheless, this research is conducted during the pandemic caused by COVID-19 which limits the choice of data collection techniques. The main concepts underlying this paper’s data collection is the

Company Type Interviewee Position Working _Region Language of _Interview Interview _Medium Date _(Minutes)Duration

Company 1 Niche E1 Director China English Phone Call 2020-04-10 52

Company 2 Strategy E2 Director India English Zoom Audio 2020-04-14 50

Company 3 Strategy E3 Managing Director Germany English Zoom Video 2020-04-15 55

Company 4 Strategy E4 Partner Germany English Zoom Video 2020-04-17 34

Company 5 Niche E5 Vice President Asia Pacific English Zoom Video 2020-04-17 57

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data triangulation, which in essence means that data is collected from different sources throughout the research (Collis & Hussey, 2014). As the research is qualitative, the research data collected will likewise be qualitative data. This increases the emphasis on contextualisation (Collis & Hussey, 2014). Both primary data and secondary data is utilised when shedding light over the unit of analysis.

3.6.1 Primary data 3.6.1.1 Pilot Interview

In order to evaluate the feasibility of the case study, improve the study design, as well as develop a feasible research question, the authors decided to conduct four pilot interviews. Being able to consult four experts who have worked in different kinds of professional service firms and are knowledgeable about the topic digital transformation, we gained the most up-to-date market knowledge on the state of DT in MCFs, which helped us later select suitable case companies. Furthermore, the second pilot interviewee who has extensive experience in taking Global CIO position in different industries had received with many leading MCFs’ service, which provided the authors with not only the technical understanding on digital technologies, but also a client’s perspective to the digitalization of MCFs. As a result of pilot interviews with industrial experts, an initial version of the interview guide was developed. We have also been lucky enough to interview one professor who is experienced in using qualitative research methods to investigate phenomena related to the future of work. The professor provided us with critical suggestions and useful techniques to formulate interview questions. In detail, the professor suggested us to build common understanding on key terms in the beginning of interview and focus on asking questions related to interviewees’ experience instead of their opinions.

Since interviewees expect to be anonymous with their names and organisations, the table below only includes necessary information that indicate their expert position.

Table 4: Pilot Interviewees

Pilot 1 IT & Strategy Consulting

Senior

Advisor 20 China English Phone Call 2020-03-02 45 Pilot 2 Consulting &

Insurance, etc CIO Advisor 28 Global English Phone Call 2020-03-05 32 Pilot 3 Strategy & Operation

Consulting Vice Presient 26 Sweden English Phone Call 2020-03-13 30 Pilot 4 Organizational

Behavior

Associate

Professor 15 U.K. English Skype 2020-04-04 38 Duration (Minutes) Language of Interview Working Region Working Experience (Years) Position Industry / Academia Background

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3.6.1.2 Interview

Among many data collection techniques used for multiple case study, this research choose interview as a main technique of collecting primary data form cases. Interviews are an effective way to collect primary data in qualitative research (Collis & Hussey, 2014) and vary from unstructured, to semi-structured, and structured interview (Brinkmann, 2014). Interview is a means to discover information and knowledge from one to another that has been practiced since the dawn of time. It takes numerous forms, as it is essentially a social practice and it varies in its structure, the number of participants, media used and style (Brinkmann, 2014). This research will be taking the form of semi-structured interviews as it allows more leeway for dialogue allowing it to grow and extend to different angles deemed important not only by the interviewer but also the interviewee. In addition, this builds upon the inductive approach as well as the suitability to an exploratory study (Saunders et al., 2016). The advantages of this type of approach are the ability for the interviewer to better steer the conversation in the direction which is most optical and relevant for the research (Brinkmann, 2014). Often, the goal of this type of interview is to gain descriptions of the phenomenon from the interviewee rather than theorisations. This is exactly the aim of this research too. However, more careful analysis when interpreting the validity of the findings is required (Brinkmann, 2014).

In consideration of the style, there are two main categories that can be followed: the receptive and the assertive (Brinkmann, 2014). This paper will use the receptive as it empowers the interviewees and creates an environment in which they are able to have a portion of control due to the relatively few and relatively open-ended questions. Roulston (2010) reflects qualitative interviews with a deeper look and disposes six general conceptions of interviewing that can be used as a heuristic device. The named approaches are the neo-positivist, romantic, constructionist, postmodern, transformative, and decolonizing approach (Roulston, 2010). These conceptions are created in consistency with their epistemological and theoretical assumptions on the production of knowledge and thus, strengthens the research design (Roulston, 2010). The most applicable approach for this paper is the constructionist conception as it is linked to semi-structured interview data and in it the researcher produces analyses and provides different understandings of discussion topics which applies to the process itself (Roulston, 2010).

In practice, the interviews took place over different digital platforms each of which lasting for an approximate hour. All interviews were held in English and took place in April 2020. The interview questions were divided into 5 sections. An overview is provided in Appendix 1.

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Section 1 and 2 are shared to help interviewees understand the goal and scope of the interview. Section 3 explores the background of the interviewees as well as their knowledge fit to the research. Section 4 is the main body where the actual case discussion is carried out, concluding it all with Section 5 with further questions. Notes were taken by two authors during the interviews and the interviews were recorded in order to better obtain the raw data and avoid misinterpretations. This is due to Yin (2018) and Saunders et al. (2016) have argued the importance of recording the interviews for accurate interpretation and avoidance of biases. The data collected is stored according to all GDPR rules and regulations. Anonymity is kept throughout the paper of both the name of the person interviewed as well as the company in order to protect everyone's privacy. Moreover, the increased amount of confidentiality facilitates an environment of discretion and trust between the interviewer and the interviewee allowing for more robust results (Brinkmann, 2014).

3.6.2 Secondary data

In order to triangulate the data collected from interviewees, secondary data is gathered from case company websites, interviewees’ LinkedIn pages, and consulting reports written by interviewees. The secondary data was collected prior to each interview. These types of data provide authors with the opportunities to confirm the authenticity of interviewees’ career background and expertise in the domain of digital transformation and professional service firms. They also help authors to further understand the digital transformation that is happening in selected case companies.

3.7 Data Analysis

Overall, these methods were chosen in order to complement coherently the inductive approach of this exploratory research. The decisions on analysis fit best in order to answer the research question as they originated from the aim to gather qualitative in-depth information from the case interviewees.

As our chosen research method is a multiple comparative case study which follows an analogous logic (Yin, 2018). We will use replication logic in the analysis of empirical data. In practice, this requires the data collected to be written into individual case reports, from which cross-case conclusions and modified theory are concluded. This means that each transcript will be coded by highlighting similarities and differentiations in order to build a bigger picture of the findings. This was used with the help of different tools such as excel which allowed for clearer comparisons.

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According to Morse (1994) there are four key points when analysing qualitative data: comprehending, synthesizing, theorizing, and decontextualizing (as cited in Collis & Hussey, 2014, pp. 154-155). This framework is used in the cross-cased analysis in order to highlight patterns and differences. After data collection, the first stage of analysis will be conducted which ultimately will lead to data reduction before further analysing. After the second review of data, displays will be visible (Collis & Hussey, 2014) from which final conclusions and verifications could be drawn. Moreover, this research will utilise the discourse analysis of data as it is a qualitative research with the primary data being interviews. This means that in the process of analysing data the language and context, and how it reflects reality in a social-psychological context is considered (Collis, Hussey, 2014). Specifically, the recordings and data transcribed will be a crucial element as it allows, for example, a further analysis of the language and choice of words. Ultimately the evidence is displayed alongside the findings of the literature review and the research question is answered, with suggestions for future studies on the topic.

3.8 Data Quality

In this section, we will further discuss the strategies that were used to validate the accuracy findings of the research and prove the reliability of the research.

3.8.1 Reliability

Qualitative reliability considers the precision and accuracy of the measurement and the lack of differences of the findings in the possible repetition of the research (Collis & Hussey, 2014). It is an important consideration as every study and its samples are unique and hence can vary (Collis & Hussey, 2014). In order to achieve reliability, Yin (2018) suggests setting up a case study protocol and database, and detailed documenting of the procedures of the different case studies. In this study reliability is gained from the consistency in approach in every aspect, for example, the process of collecting data, coding data, and analysing data. More specifically, the interviews were treated equally as all interviews were scheduled with the same amount of time, with the same questions, and with the same handling of recording and storing data. The interview guide was evaluated by a third-party expert from our network in order to ensure the accuracy of questions and the ability to explore necessary information within the given time. Analogous consistency was upheld throughout the entire research process in order to maintain reliability of this paper.

An exploration of drivers and inhibitors of digital transformation in professional service firms : A multiple case study in management consulting industry