Catalyzing innovation with existing resources and ... - kth .diva

IN DEGREE PROJECT INDUSTRIAL ENGINEERING AND MANAGEMENT,SECOND CYCLE, 30 CREDITS

, STOCKHOLM SWEDEN 2017

Catalyzing innovation with existing resources and new partnershipsThe case of the Climate Data Project

ALEXANDER SCHULTZ

MARKUS ROMEIS

KTH ROYAL INSTITUTE OF TECHNOLOGYSCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT

Catalyzing innovation with existing resources and new partnerships

The case of the Climate Data Project

by

Schultz, Alexander Romeis, Markus

Master of Science Thesis INDEK 2017:125 KTH Industrial Engineering and Management

Industrial Management SE-100 44 STOCKHOLM



Schultz, Alexander Romeis, Markus

Examensarbete INDEK 2017:125 KTH Industriell teknik och management

Industriell ekonomi och organisation SE-100 44 STOCKHOLM

Master of Science Thesis INDEK 2017:125



Schultz, Alexander

Romeis, Markus

Approved

Examiner

Cali Nuur Supervisor

Niklas Arvidsson Commissioner

Telia, Division X Contact person

Rickard Damm

Abstract Large companies are in the modern world often outrun by smaller companies and start-ups by being agile and able to exploit new business opportunities fast. One industry that is facing this transformation and is in need of innovation is the telecom industry, where data and bandwidth has become a commodity. The study is based on the assessment of a potential business opportunity where climate data is reviewed to be a new source of revenue for the telecom company Telia by exploiting existing resources combined with new partnerships. The thesis provides a framework for assessing new business opportunities from existing resources. The framework consists on four stages and revolves around how to utilize internal resources in combination with external partners to create, capture and deliver value. The framework is then applied in the division X at Telia Company to see how Telia’s existing base station network can be used to profit from the collection of climate data. Through interviews and workshops the authors combine empirics with the developed framework to build a business case around the collection and distribution of climate data. The study suggests a specific partner, in the early phase of the innovation process, for Telia to engage a partnership with.

Examensarbete INDEK 2017:125



Schultz, Alexander

Romeis, Markus

Godkänt

Examinator

Cali Nuur

Handledare

Niklas Arvidsson Uppdragsgivare

Telia Company, Division X Kontaktperson

Rickard Damm

Sammanfattning I det moderna samhället blir stora företag ofta omsprungna av mindre firmor och start-ups som är agila och har möjlighet att utnyttja nya affärsmöjligheter snabbt. En industri som står inför denna transformation och är i stort behov av innovation är telekomindustrin, där data och bandbredd har blivit till en handelsvara. Denna studie är baserad på undersökningen av en potentiell affärsmöjlighet där klimatdata ska utvärderas som ny intäktsström för telekombolaget Telia genom att utnyttja existerande resurser med nya partnerskap. Uppsatsen presenterar ett ramverk för att undersöka nya affärsmöjligheter från existerande resurser. Ramverket består av fyra steg och kretsar kring hur man kan utnyttja interna resurser i kombination med externa partnerskap för att skapa, fånga och leverera värde. Ramverket appliceras sedan på Division X inom Telia Company för att se hur Telias existerande nätverk av basstationer kan utnyttjas för att göra vinst från inhämtning och distribuering av klimatdata. Studien föreslår en specifik partner i en tidig fas av innovationsprocessen för Telia att bilda partnerskap med.

TABLE OF CONTENTS

1 INTRODUCTION .................................................................................................................... 1

1.1 Background ..................................................................................................................... 11.2 Problematization ............................................................................................................. 2

1.3 Purpose & Aim ............................................................................................................... 21.4 Research Questions ......................................................................................................... 2

1.5 Delimitations ................................................................................................................... 31.6 Disposition of Thesis ...................................................................................................... 3

2 THEORY .................................................................................................................................. 32.1 Resource Based View ..................................................................................................... 5

2.1.1 Identifying and assessing resources .................................................................... 72.1.2 Data and analytics as a resource ......................................................................... 9

2.1.3 Core competencies ............................................................................................ 102.2 Partnerships ................................................................................................................... 11

2.2.1 Open innovation ................................................................................................ 112.2.2 Lead Users ........................................................................................................ 13

2.2.3 Resources in partnerships ................................................................................. 142.3 Innovation Processes ..................................................................................................... 14

2.3.1 Front end of innovation ..................................................................................... 152.3.2 Feasibility analysis ............................................................................................ 16

2.4 Business model generation ........................................................................................... 172.4.1 Opportunity recognition .................................................................................... 21

3 THE FRAMEWORK .............................................................................................................. 223.1 Step 1 – Identify resources ............................................................................................ 24

3.2 Step 2 – Build use cases ................................................................................................ 253.3 Step 3 – Feasibility analysis .......................................................................................... 26

3.4 Step 4 – Build business case ......................................................................................... 27

4 METHOD ............................................................................................................................... 28

4.1 Research strategy .......................................................................................................... 294.1.1 Systematic Combining ...................................................................................... 29

4.2 Research Process ........................................................................................................... 304.3 Research Design ............................................................................................................ 31

4.4 Data Collection ............................................................................................................. 32

4.4.1 Workshops ........................................................................................................ 32

4.4.2 Interviews .......................................................................................................... 324.5 Reliability and validity .................................................................................................. 33

5 THE CASE STUDY ............................................................................................................... 345.1 Step 1 – Identify resources ............................................................................................ 35

5.1.1 Phase 1 – search & find .................................................................................... 365.1.2 Phase 2 – assess & value ................................................................................... 37

5.2 Step 2 – Build use cases ............................................................................................... 395.2.1 Search and Select .............................................................................................. 39

5.2.1 Assess and value ............................................................................................... 415.3 Step 3 – Feasibility analysis .......................................................................................... 44

5.3.1 Technical Feasibility ......................................................................................... 445.3.2 Economic Feasibility ........................................................................................ 45

5.3.3 Legal Feasibility ................................................................................................ 455.3.4 Operational Feasibility ...................................................................................... 45

5.3.5 Schedule Feasibility .......................................................................................... 455.4 Step 4 – Build business case ......................................................................................... 46

5.4.1 Infrastructure ..................................................................................................... 465.4.2 Offering ............................................................................................................. 47

5.4.3 Customers ......................................................................................................... 475.4.4 Financial viability ............................................................................................. 48

5.4.5 Business model canvas ..................................................................................... 49

6 DISCUSSION AND ANALYSIS .......................................................................................... 50

6.1 Step 1 – Identify resources ............................................................................................ 516.2 Step 2 – Build use case ................................................................................................. 51

6.3 Step 3 – Feasibility analysis .......................................................................................... 526.4 Step 4 – Build business case ......................................................................................... 53

6.5 A successful framework? .............................................................................................. 536.5.1 Generalizability and validity ............................................................................. 53

6.5.2 Learnings from an innovation project at a large telecom company .................. 54

7 CONCLUSION AND RECOMMENDATIONS ................................................................... 56

7.1 Conclusion .................................................................................................................... 577.1 Contribution and future work ........................................................................................ 58

8 REFERENCES ....................................................................................................................... 60

9 APPENDIX ............................................................................................................................. 64

LIST OF FIGURES

Figure 1. The scope of academic literature used in this thesis. ....................................................... 5

Figure 2. The traditional SWOT-framework .................................................................................. 6

Figure 3. Davenport and Harris analytic value framework (2007) and the Gartner analytic

ascendancy model (Laney et al., 2012) ................................................................................. 10

Figure 4 Knowledge landscape of closed and innovation (Chesbrough, 2007) ........................... 12

Figure 5 Fuzziness level pattern (Kim and Wilemon, 2002) ........................................................ 16

Figure 6 The Business Model Canvas (Osterwalder and Pigneur, 2010a) ................................... 18

Figure 7 Theoretical framework for the innovation process ......................................................... 23

Figure 8 Step 1 of the innovation funnel is divided into two phases ............................................ 24

Figure 9 Systematic combining (Dubois and Gadde, 2002) ......................................................... 29

Figure 10 Empiric process ............................................................................................................ 32

Figure 11 Identified Stakeholders ................................................................................................. 40

Figure 12 Identified Use Cases ..................................................................................................... 40

Figure 13 Most plausible stakeholders connected with use case and data of interest .................. 41

Figure 14 The business model canvas of the Climate data project ............................................... 49

LIST OF TABLES

Table 1 The VRIO-framework and its competitive implications (Barney and Hesterley, 2006) ... 8

Table 2 Risk drivers for Open Innovation (Coras and Tantau, 2014) .......................................... 12

Table 3 Characteristics of the FFE Phase (Kim and Wilemon, 2002). ......................................... 15

Table 4 Types of partnerships and motivations for partnerships (Osterwalder and Pigneur, 2010)

............................................................................................................................................... 19

Table 5 Types of Key activities and Key resources (Osterwalder and Pigneur, 2010) ................ 19

Table 6 Channel types and Channel phases (Osterwalder and Pigneur, 2010) ............................ 20

Table 7 Initially identified resource and the potentially new area of utilization .......................... 36

Table 8 Potential benefits from new utilization of base stations .................................................. 36

Table 9 VRIO-framework applied on Telia’s base station network ............................................. 37

Table 10 VRIO-framework applied on the climate data project ................................................... 38

Table 11 Stakeholders evaluated after lead user requirements (HoPMA, 2017; HoDe, 2017; PM,

2017) ..................................................................................................................................... 42

Table 12 Base station requirements .............................................................................................. 44

Table 13 Technical requirements from stakeholder 2 ................................................................... 44

Table 14 Summary of feasibility analysis ..................................................................................... 46

Table 15 Building block for Key partners in the Climate Data project ........................................ 46

Table 16 Building blocks for Key activities and Key resources in the Climate Data project ...... 47

Table 17 Building block for Value proposition in the Climate Data project ................................ 47

Table 18 Building block for Customer relationship in the Climate Data project ......................... 47

Table 19 Building block for Channels in the Climate Data project .............................................. 48

Table 20 Building blocks for Cost structure and Revenue streams in the Climate Data project .. 48

FOREWORD

This thesis was written in the spring of 2017 in collaboration with Division X at Telia Company. We want to thank everyone who has given us the time and provided the crucial insights that has helped form this thesis. Both among the employees within Telia, as well as within the potential target companies. The insights provided from these sources have been invaluable for the thesis.

We want to especially thank Rickard Damm at Division X who gave us the assignment to begin with, as well as giving us some pointers to potential approaches and interview subjects. Furthermore, we want to thank Niklas Arvidsson who has been great help with guiding us to some relevant and highly contributing areas of academic theory used in the thesis.

Alexander Schultz & Markus Romeis

Stockholm, June 2017

NOMENCLATURE

Here are the Abbreviations that are used in this Master thesis.

Abbreviations VAS Value added services B2B Business to business

B2C Business to consumer RBV Resource Based View

FFE Fuzzy Front End VRIO Valuable, Rare, Imperfectly imitable, Organizationally appropriable

TELOS Technological, Economical, Organizational, Scheduling BMC Business Model Canvas

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1 INTRODUCTION This chapter includes the background and purpose of the thesis and defines a problem formulation, followed by the research questions, delimitations and academic contribution of the study. Finally, a disposition of the thesis will be presented.

1.1 Background Recent development in digitalization across several industries have increased the demand on firms to innovate, both from a customer perspective in terms of product offering as well as internally striving for increased resource utilization and process efficiency. Highly involved in this web of industrial transformation is the telecom industry, whose main business model since the rise of internet has been surrounding the transferring and hosting of data. However, as data space and bandwidth is becoming more of a commodity (commoditization), the competitiveness of telecom companies turn from factors such as speed, reliability and security to price, their margins become minimized (Arthur D Little, 2016). With lower margins, telecom companies need to find new ways to increase customer value proposition and stay competitive. Until now, such efforts have mainly consisted of offering different types of add-ons with their subscriptions like free headphones, free months of subscription services, etc. While value added services (VAS) does increase the value in product offering, it usually does little when it comes to driving innovation and increase resource utilization. The traditional and most widely accepted and used methods for innovation today suggest exploring externally for sources of opportunities (Porter, 1980; Martin, 2009). These are based on, and driven by, identifying changing customer behavior and demand and then try to adapt the firm by innovating to meet these new demands. New products and new add-ons are designed to increase the value of the core product rather than exploring new opportunities. While this can enable growth , as the current market is growing, with a saturated market, product becomes commoditized, a new approach needs to be applied (Quelch, 2007). A dynamic and agile small company or a start-up is easily able to transform their processes and resources to fit the new environment. The same pivot is however a lot more costly and difficult for a large company (Ashkenas, 2011). An advantage for large companies however, is that they possess large quantities of resources that has enabled a sustained competitive advantage, but can likely be utilized in new ways (Schneider, 2016). In order to utilize these resources in new areas and in new ways, there are at least two aspects that need to be taken into account:

• The company needs to identify its existing resources that are available for new areas of utilization

• The company needs to find new customers and address them.

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1.2 Problematization Telia Company is a large telecom company based in Sweden, with presence internationally with focus on the Nordics and Baltic region. It is owned to almost 40% by the Swedish Government and had 84,2 Billion SEK in revenue 2016 (Telia Company AB, 2017). Its outspoken strategy during the past few years has been to develop its core business of connectivity, combined with investments in new areas that strengthen core business as well as build new business in growing areas (Telia Company, 2016). As a telecom company, Telia Company is facing increased pressure to find new revenue streams due to the commoditization of data and bandwidth which could lead to low margins (Bain & Company, 2014; Arthur D Little, 2016; PricewaterhouseCoopers, 2017). Being aware of current market trends, Telia Company an innovation division was formed, Division X, with the purpose of finding new revenue streams by utilizing Telia’s existing resources in new ways and investing in tech companies. An idea was presented that Telia Company’s 15 000 base stations1, located across Sweden in both rural and urban areas, could be utilized in new ways, for example by mounting sensors to collect climate data, allowing a granular grid of climate data to a degree today not available. This would address the goal of increasing resource utilization. In addition, climate is an unfamiliar sector for Telia and thus, there is interest in finding partners who could be involved and provide support during the innovation process as well as function as customers. In order to evaluate the value of this idea, a business case had to be created.

1.3 Purpose & Aim The purpose of this thesis is to investigate if climate data can be a new revenue stream for Telia through utilizing existing resources together with new partnerships. The findings will be used to assess whether the idea should be pursued or not. By addressing this case, the aim is to show how large companies can work with finding and evaluating new business opportunities when searching for new revenue streams.

1.4 Research Questions Can a large telecom company catalyze innovation with existing resources and new partnerships? The main research question of this thesis is:

MRQ: How can a large telecom company catalyze innovation with existing resources and new partnerships?

To answer the main research question, the following sub questions will be answered:

SQ1: How can existing resources be assessed for new areas of utilisation? SQ2: How can new partnerships be found?

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1.5 Delimitations To limit the scope of this thesis to a manageable extent, this thesis will focus on investigating the case of climate data at Telia Division X from initiation of idea to first business case, based on the Swedish market. Therefore, the aim is not to develop a comprehensive technological or financial, analysis. Due to both practicality and intuitive reasoning surrounding the usage of climate data, the thesis will mainly focus on exploring business cases where Telia has the ability to structure partnerships focusing on B2B-relationships. No B2C business cases will be explored.

1.6 Disposition of Thesis This section aims to provide the reader with an overview of the report to better understand it and easier get the whole picture. This thesis consists of eight chapters, for which the contents are explained briefly below. 1 INTRODUCTION The first chapter presents the background of the study and the context of the case as well as the problem statement, the purpose and aim of the thesis and the questions which this research aims to answer. This leads to the delimitations as well as an outline of the report. 2 THEORY The theoretical background needed to understand the research problem and which forms the basis for the research is presented, explained briefly and put into context. 3 THE FRAMEWORK In chapter 3, the framework used to support the case study is presented. As this research has been conducted through systematic combining, the framework in question has been developed in parallel with the case study. 4 METHOD The method used for answering the research questions is presented. Including the choices of research strategy, research design and the sources of data. 5 THE CASE STUDY The case which the theoretic background and framework is applied on is presented. Furthermore, the results and output from applying the framework on the case are presented. 6 DISCUSSION AND ANALYSIS The empirics from the case study and the framework used is analysed through the lens of the theoretical background and in terms of success of framework. 7 CONCLUSIONS AND RECOMMENDATIONS The conclusion from the research project is presented and the research questions are answered. Furthermore, key recommendations with basis from the thesis are presented and suggestions for further research are proposed.

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2 THEORY This chapter introduces the academic literature used to build the framework that is applied on the case and used to answer the research questions. The purpose of this chapter is to provide a basic understanding of the theories used.

To answer the stated research questions, academic fields of enhanced interest includes the subjects of resource based view (RBV), partnerships and innovation processes. The interceptions of these fields are of particular interest, as well as where there are connections to business model generation methodology, as illustrated in Figure 1. These fields are deemed to encompass the rationale of identifying resources, building new partnerships and innovating and are thus regarded as valuable for this thesis. The connections between these subjects will form the basis of the theoretical framework that is developed and presented in Chapter 3.

Figure 1. The scope of academic literature used in this thesis.

2.1 Resource Based View In very basic terms, the Resource Based View (RBV) of the firm suggests that a firm can build a sustainable competitive advantage by identifying and exploiting valuable resources internally in the firm (Barney, 1991). The ideas laying the ground work to the RBV was first introduced by Edith Penrose in 1959 (Penrose, 1959; Wernerfelt, 1984; Rugman and Verbeke, 2002). However, the concept of RBV started gaining popularity first in the late 1980’s following publications by Barney (1986, 1991) and Wernerfelt (1984). RBV provides an alternative, internally-looking, perspective to identifying competitive advantage as opposed to the more well-known and externally focused Porter’s five forces (Porter, 1980). An appropriate way of illustrating the perspective of the RBV is to put it in context of other popular strategic frameworks. The SWOT-framework, illustrated in Figure 2, is arguably the most widely used framework for structured planning of strategic execution (Hofer and Schendel, 1978; Andrews, 1987; Barney, 1991). It’s based in the idea that the first step of strategic planning is to evaluate, first the external environment to identify a firm’s market opportunities and threats, and then look inside the firm to ascertain its strengths and weaknesses. As seen in Figure 2, the SWOT-framework is structured in a 2x2-matrix where

Resource Based View

Innovation processesPartnerships

Business model

Generation

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the internal aspects, strengths and weaknesses, are on the left side and the external aspects, opportunities and threats, are on the right side.

Figure 2. The traditional SWOT-framework

For a long period, most research focused on finding sustained competitive advantage through first identifying the opportunities and threats (external aspects, to the right) and then align the strategy with these. Theories and strategic frameworks such as Porter’s five forces make two simplifying assumptions. Firstly, firms are considered homogenous when it comes to strategically relevant resources, and secondly, they assume that if resource heterogeneity would develop within an industry, it would be short-lived at best (Barney, 1991). These two assumptions lead to the conclusion that in order for a firm to successfully sustain competitiveness, it should identify external opportunities, align with these and avoid threats. However, research and frameworks focusing on the external environment risk missing new competitiveness that can be created through extended utilization of the already existing resources. So, instead of starting with analysing the external environment for business opportunities that build competitiveness, RBV applies an inward look, where firms are instead conceptualized as heterogeneous entities consisting of bundles of idiosyncratic resources (Barney, 1991). This means that RBV applies a view that each firm has a unique position from its unique composition of resources and thus have different abilities to achieve competitive advantage in different markets. The implication of this view is that RBV makes two assumptions that are in direct contrast with the external looking theories. Firstly, it is assumed that firms within an industry may be heterogeneous with respect to the strategic resources they control. And secondly, it is assumed that resources may not be perfectly mobile across firms and thus heterogeneity can be long lasting. RBV then examines these two assumptions in for the analysis of sources of sustained competitive advantage. Due to the different scopes of traditional externally focused strategic theories and RBV, it should be considered that RBV is to be viewed as a complement to these and not a replacement (Ford, 1998). In this use of the term, resources refer to "all assets, capabilities, organisational processes, firm attributes, information, knowledge, etc. controlled by a firm that enable the firm to conceive of and implement strategies that improve its efficiency and effectiveness" (Barney, 1991). In the SWOT-analysis, resources correspond to the Strengths. It is often the case that a firms resources are implicit, taken for granted by managers and thereby overlooked instead of being subject to thorough analysis (Eisenhardt and Martin, 2000).

Internal

Strengths(Resources)

Weaknesses

External

Opportunities

Threats

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2.1.1 Identifying and assessing resources It should be noted that the definition for a resource does vary among scholars (Wernerfelt, 1984; Barney, 1991; Amit and Schoemaker, 1993; Peteraf and Barney, 2003; Lavie, 2006). The primary goal of adapting a RBV is to identify what resources in the firm that are valuable and thus create a competitive advantage and then to maximize the utilization of these. Most importantly, a holder of a resource will enjoy the protection of a resource position barrier. That is, a holder of a resource will be able to remain in a relative position against a competitor, as long as it acts rationally, as acquiring a resource is incrementally more costly than holding one (Wernerfelt, 1984). This is similar to the traditional dynamics of the “product-based” entry barrier concept. However, Wernerfelt (1984) points to a key point of difference with the following to logic statements:

- If a firm has entry barriers towards newcomers in market A, which shares the use of a resource with market B, then another firm which is strong in B might have a cost advantage there and enter A in that way.

- If the firm has a resource position barrier in resource a, which is used in market A, it might still survive the collapse of A if it could use a somewhere else.

However, putting this into practice can prove difficult as it is hard to identify what assets, processes and capabilities that are considered to create competitive advantage (Arend and Lévesque, 2010). For an organization, the uncertainty of the definition of a resource pose a concern in the ambition to identify and leverage on the right resources. The previously stated definition of a resource means that an asset for instance, can be considered a resource in a firm with a strategy where the asset is seen as enabling, whereas the same asset can be simply an asset under another strategy, further adding to the complexity of resource identification (Markard and Worch, 2009). Further on, a company’s resource can be both tangible and intangible (Wernerfelt, 1984). The important characteristics that a resource should embody in order to be deemed valuable is abbreviated VRIO (Barney and Hesterley, 2006). The VRIO-framework includes four conditions for assessing whether a resource has the potential to generate sustained competitive advantage. The conditions being that the resource needs to be valuable, rare, imperfectly imitable and that the organization needs to be able to exploit the full potential of the resources. Analysing a resource with the VRIO-framework, 1 Valuable – A firm’s resources can only be a source of competitive advantage when they

are valuable. The resources needs to enable the firm to exploit the external opportunities and through the combination of the resource and the opportunity can create a sustained competitive advantage and thus enhance its competitive position (Barney, 1991). The value of a resources is also subjective to its context. The same resource can be strength in one context and weakness in another. Typically, a valuable resource should increase the firms revenue and/or decrease the firms costs, directly or indirectly (Barney and Clark, 2007).

2 Rare –A resource should be rare. If a resource is possessed by a large number of firms, this is no longer the case, and thus, the resource can no longer be considered to a enable a competitive advantage (Barney, 1991).

3 Imperfectly imitable – For sustained competitive advantage to be created the resources held by a firm needs to be difficult to imitate. This is the key differentiator between temporary competitive advantage and sustained competitive advantage that will hold for

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a longer period of time (Barney, 1991). A resource that is easy to imitate will quickly lose its rarity. According to Barney and Hesterley (2006) and (Dierickx and Cool, 1989) a firms resources can be perfectly imitable for one or more of three reasons: (1) the ability of the firm to obtain these resources depend on unique historical conditions, (2) access to the resource is a function of casual ambiguity, that is, the chance of imitability is a consequence of a stochastic process with low chance of success or (3) the resource generating competitive advantage is socially complex.

4 Organizational appropriability – the organization acts as an “adjustment factor” that either enables or prevents a firm from fully realizing the benefits embodied in its valuable, rare, and costly to imitate resources (Barney and Clark, 2007). An organization which has been designed in a certain way will more likely be appropriate to hold and leverage that specific resource (Arend and Lévesque, 2010). An extremely poor organization could for instance lead a firm that has resources holding the potential for competitive advantage to gain only a competitive parity or even competitive disadvantage through not exploiting the resource correctly (Barney and Clark, 2007). Thus, a firm must be designed to utilize its valuable resources correctly in order to gain a sustained competitive advantage.

The competitive implications from meeting the conditions in the VRIO-framework are summarized in Table 1.

Table 1 The VRIO-framework and its competitive implications (Barney and Hesterley, 2006)

Valuable? Rare? Imperfectly imitable

Organizational appropriability

Competitive implications

No - - No Competitive disadvantage Yes No - Competitive parity Yes Yes No Temporary competitive advantage Yes Yes Yes Yes Sustained competitive advantage

Depending on what conditions in the VRIO-framework that the resource meets, the potential resource in question will give different competitive implications. The implication should be used as a basis for strategic direction as well as type and level of exploitation of the resource. The different competitive implications in Table 1 will be explained below. Competitive disadvantage If a resource or capability is no valuable to the firm, it will not enable a firm to exploit opportunities and neutralize threats and should thus not be considered a resource. A strategy that increases exploitation of a non-valuable resource will risk increasing costs and decreasing revenue. These are thus considered weaknesses and should thus be divested (Barney and Clark, 2007). Competitive parity If a resource or capability is valuable but not rare, exploitation will generate a competitive parity. A strategy focused on these will not generally create a competitive advantage, however failing to exploit them might risk putting a firm in competitive disadvantage. In this sense, such resources should be considered organizational strength (Barney and Clark, 2007). Furthermore, Barney and Clark (2007), suggests that when a firm creates value in the same way as its competitors, to do better than competitive parity, it must engage in valuable or rare activities. This requires a firm to discover or develop its own unique resource or capability.

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Temporary competitive advantage A resource or capability that is valuable and rare, but not considered costly to imitate will merely enable the firm to gain a temporary competitive advantage. A firm that exploits this resource will gain an enjoy a first-mover advantage. However, as competitors identify this opportunity, due to the low entry barrier for exploitation, they will only suffer slight or no cost disadvantage is likely that they will follow. Over time, the first-mover will have to compete as other firms imitate the resource unless the first-moving firm implements resource entry barriers when it comes to the value that the resource enables. A resource or capability that enables a temporary competitive advantage can be considered as an organizational strength and a distinctive competence (Barney and Clark, 2007). Sustained competitive advantage The aim for a firm is to identify and exploit resources that can form a sustained competitive advantage (Barney and Hesterley, 2006). Exploiting a resource or capability which is both valuable, rare and costly to imitate will enable the firm to gain sustained competitive advantage. This indicates that competing firms must face significant cost disadvantages in order to successfully imitate the resources of the successful firm and are thus unlikely to attempt, given that they act rationally. Due to the high level of cost disadvantage for firms trying to compete away the advantages of firms that exploit these resources, they will not generate a competitive advantage, or even competitive parity (Barney and Clark, 2007). In practice, however, it might still prove difficult to ascertain the attributes of VRIO. The framework requires that the right asset is analyzed. However, The issues are usually the high error rates for selecting the wrong assets and for not identifying the right asset (Arend and Lévesque, 2010). In reality, it may never be possible to produce a finite list of factors of production responsible for success (Lippman and Rumelt, 1982). A process for identifying and assessing potential resources will therefore require multiple approaches to successfully execute (Arend and Lévesque, 2010).

2.1.2 Data and analytics as a resource A rather new source of competitive advantage and thus a potential resource is the aggregation of collected data (Levitin and Redman, 1998; Fosso et al., 2016). Data has obviously always been present in any type of organization in different forms. However, it’s with recent technological developments that large quantities of data can be collected and distributed that the data itself has become a resource enabling competitive advantage (Fosso et al., 2016). Aggregating data from different sources and mapping these together can provide basis for analytics. Although potential value of data and analytics as a resource can be deduced by the standard VRIO-framework, as it can be regarded as a resource in the traditional sense (Bhatt, Grover and Taylor, 2017), further levels of assessment can add to the accuracy of this analysis (Fosso et al., 2016). The value of collected data and its potential as basis for analytics is dependent on the complexity of the data can be categorized and can be illustrated in the models in Figure 3.

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Figure 3. Davenport and Harris analytic value framework (2007) and the Gartner analytic ascendancy model (Laney et al., 2012)

The framework by Davenport and Harris (2007) and the model by Laney et al. (2012) illustrate the same dynamics of increasing value or competitive advantage with increased complexity of analytics however arguably pedagogically different. Conceptually, the point of both models is that with increased complexity and difficulty of the analytics comes increased value and thus competitive advantage.

2.1.3 Core competencies A complementary framework to the RBV is the concept of core competence theory (Prahalad and Hamel, 1990). Conceptually RBV and core competence theory are very similar and are primarily differentiated by terminology and perspective. The suggested focus is however the same. Prahalad and Hamel (1990) argue that the performance of a firm will be a result of its ability to identify, cultivate and exploit the firm’s core competencies. That is, in order for a firm to gain a competitive advantage, it must bare valuable resources that are used in an effective way. A core competency is defined as “the collective learning in the organization” and the ability to “coordinate diverse production skills and integrate multiple streams of technologies” (Prahalad and Hamel, 1990). Wernerfelt (1984) exemplifies his definition of resources with, among others, “in-house knowledge of technology, skilled personnel, efficient procedures”. As such, it can be deduced that a core competence is a type of resource (Eisenhardt and Martin (2000). Wernerfelt's (1984) ideas on the resource position barrier further adds to this interpretation. As pointed out, a resource should remain considered a valuable resource even if the value from the current main utilization is diminishing if it is possible to bring value in an alternative way. A core competence, could thus be the possibility to utilize the resource in a new way. The capability, or competence, of a firm to be able to generate new value-creating strategies and recombine existing resources in new ways can be referred to as dynamic capabilities (Eisenhardt and Martin, 2000). Again, this is easier said than done (Prahalad and Hamel, 1990). Finding a new utilization and revenue source for a resource demands a dynamic organization, capable of reshaping its resource base in an innovative way and as such, a dynamic organization is often considered one of the firm’s core competencies. In fact, maintaining a good fit between core competence and new product development is critical to the success of innovation (Özbağ, 2013).

Stochastic optimization How can we achieve the best outcome including the effects of variability? Prescriptive

Optimization How can we achieve the best outcome?

Predictive modelling What will happen next if… ?

PredictiveForecasting What if these trends continue… ?

Simulation What could happen… ?

Alerts What actions are needed?

Query/drill down What exactly is the problem?

DescriptiveAd hoc reporting How many, how often, where?

Standard reporting What happened?

Degree of complexity

Com

petit

ive A

dvan

tage

Difficulty

Valu

e

Descriptive analytics

Diagnostic analytics

Predictive analytics

Prospective analytics

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Core competence theory also states that it is not possible for a firm to have an intelligent alliance, or partnership, if it has not in advance managed to determine within what part of the partnership they will be competence leaders (Prahalad and Hamel, 1990). Comparing physical, tangible resources with intangible resources such as competencies and capabilities, there are two key differences that can be mentioned:

• Physical resources deteriorate over time, unlike competencies that are enhanced from application and sharing

• Knowledge, or competence, fades if not used Furthermore, Prahad and Hamel (1990) suggests three tests that can be applied in order to identify a core competency within a firm:

1. It should enable participation in a wide range of business sectors. a. A competence within a specific area can allow access within other areas.

2. It should significantly contribute to the perceived customer benefits of the product.

a. For instance, holding competence on the behavior of the telephone users.

3. It should be difficult for competitors to imitate. a. It is inherent in the definition of a competitive advantage of the competence

that the competence should be difficult or impossible for competitors to replicate.

2.2 Partnerships During the last decades, forming partnerships in various forms have been an important strategy when responding to the rapid change of the global economy (Dicken, 2011). In this section, focus will lie in presenting theory regarding partnerships as an instrument for innovation. First, the concept of open innovation is presented, focusing on the benefits and risks on exchanging knowledge between firms. Secondly, research regarding how partnerships can be found and used early in the innovation process with so called “lead users”. Finally, a section treating both the contradiction and synergies between RBV and partnerships is presented.

2.2.1 Open innovation Adj. prof. Henry Chesbrough defined open innovation as "a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology" (Chesbrough, 2003).

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Figure 4 Knowledge landscape of closed and innovation (Chesbrough, 2007)

Comparing open innovation to closed innovation, in closed innovation a company is limited to knowledge internally, illustrated by the filled lines in Figure 4. Ideas can only flow into the company at one point (the large opening of the funnel on the left), and out one way, to the current market. No knowledge or ideas has a chance to be exchanged between company A and B, even though they might be present on different markets with little or no rivalry between each other. On the other hand, in open innovation, knowledge and ideas have many possible entry and exit point in the company, as illustrated by the dashed lines in Figure 4. Here, we also see that apart from exchanging ideas between companies, open innovation can also lead to the discovery of new markets. Although open innovation has often been praised, it also inherits risks, according to Coras and Tantau (2014). Paradoxically, though the goal of open innovation is to reduce risk and costs, collaboration can also entail increased risks. Coras and Tantau (2014) identified 8 major risk drivers for open innovation:

Table 2 Risk drivers for Open Innovation (Coras and Tantau, 2014)

Riskdriver Type DescriptionWorkforce Internal Internal resistance for change.

High employee turnover Insufficient support from top management for innovation.

External Insufficient technical expertise, and knowledge about partners Knowledgesharing

External Insufficient expertise of partners. Ethical barriers due to leaking critical internal resources and core competences

Collaboration Internal Higher complexity of managing open innovation. Difficult to balance open innovation with daily tasks. Lower control of external resources than internal.

External Conflicting interests of partners, risk of dependency of partners Lack of trust and communication of partners

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Objectives may not be met due to poor quality of partners or partnership management

Market External Volatile and ambiguous industry regulation Unethical behaviour of partners Large amount of paper work (administrative barriers)

Finance External Technology leakage to rivals. Inability to adapt to new technology

IntellectualProperty

External Core knowledge flow to competitors Inexistence of formal contracts

As can be seen in Table 2, collaborating with external partners entails risks from several aspects. However, it is considered the most economical way to get access to a greater knowledge base outside the boundaries of the firm (Coras and Tantau, 2014), as illustrated in Figure 4. Chesbrough (2007) also highlights two critical challenges with open innovation. First, the NIH (Not Invented Here) syndrome, in short, the NIH syndrome entails that companies avoids using research, products, etc that is produced externally (Katz and Allen, 1985). Secondly, sustained internal commitment over time (Chesbrough and Crowther, 2006). Implementing and benefiting from open innovation takes time, there must be sufficient motivation and incitements for employees to keep working for open innovation.

2.2.2 Lead Users The importance of external involvement in innovation has been known for a long time. For example, Von Hippel highlighted the importance of external involvement in form of customers, for successful products already in the 70s (von Hippel, 1978). Innovation in more fast paced tech environments are more likely to succeed if the firms initiate relationships with the so called lead users during the innovation process (Hippel, 1988). Lead users are defined with two characteristics according to Hippel (1988):

1. Lead users have needs that will be reflected by the whole market in the future, but experience the needs long (months or years) before the general market.

2. Lead users will benefit significantly by the innovation that meets those needs. An empirical study, aiming to investigate the nature of lead users, based of much of Hippel’s earlier work, found that lead users are characterised also by the following key factors (Morrison, Roberts and Midgley, 2004; Tid and Bessant, 2013): - Recognize requirements early - Expect high level of benefits from the product - Develop their own innovations and applications - Perceived to be pioneering and innovative Tid and Bessant (2013) argues that complex products and services are especially benefitting from incorporating lead users. They would both contribute to co-developent and function as early users of the innovation. Tid and Bessant (2013) also highlights a second implication, lead users can also provide insights in to how it will be recieved broader markets.

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2.2.3 Resources in partnerships RBV traditionally envision firms as independent entities and thus focuses on internal resources within the company, so-called organizational resources as only resources for value creation. In addition, traditional Resource-based research focus on pure competition between firms, which means that all incumbents, entrants, substitutes, suppliers and customers compete and thus benefit from minimizing cross-firm cooperation. (Lavie, 2006) The trend however, is firms being more interconnected with each other, leading to the view of a firm as a separate entity less relevant in modern times. Strategic partnership and alliances has shown to have significant impact of the firms performance (Lavie, 2006). This is further supported by the theories by (Artz and Brush, 2000), suggesting that resources are context sensitive. That is, the value of a resource is usually conditional to complimentary resources of the firm. Therefore, Lavie (2006) have extended RBV theory further to include other firms resources, categorised as network resources, a term introduced by Gulati and Kellogg, (1999) , if the firms are interconnected in some way. Lavie (2006) continues to then define network resources as “resources of alliance partners transferred via direct interfirm interactions.” Markard and Worch (2009) suggests further that higher levels of aggregation can create resources available for the firm that will enhance competitiveness and can be important for achieving strategic goals. A strategic partnership, or alliance, can enable a firm to use resources possessed by the cooperation partner, so called network resources without the need of transfer or ownership over the resources, which would have been required from a traditional view of RBV. However, network resources accessed through strategic partnerships does further increase complexity when it comes to identifying and benefiting from these resources. To maximize the utility of network resources an even higher degree of cooperation is needed.

2.3 Innovation Processes Thomas Edison who registered more than 1000 patents. Being a multi innovator, he realized innovation is the process of coming up with good ideas but, more importantly, the process of growing them into practical use (Tid and Bessant, 2013). A similar stance of stressing the importance of certain structure and clear processes is taken by Kastelle and Steen (2011). They argue that the idea is the easiest part of the innovation, implementation is where the difficulty is, transforming the invention to an innovation. Therefore, there are a number of models trying to structure this process and deal with its challenges:

• Tid and Bessant (2013) suggests a general innovation process of four steps or phases that every firm needs to handle, although, there are many ways to divide up and structure the different stages of the process. A largely loosely defined process, but purposely since a large company might follow a more structured process, while smaller firms are more informal (Tid and Bessant, 2013).

• (Cooper, 1990) suggests the stage-gate model, a 7 step process where a “gate” needs to be passed in order to be able to proceed to the next step. The aim is that if the door

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cannot be passed, the project should be stopped. The structure is linear with clearly defined boundaries and thus limits flexibility.

• Three-phase front end model, also a linear model with three phases, similar to the innovation process suggested by Tid and Bessant (2013). As opposed to the stage-gate model, the three-phase front end model has no formal “gats” to pass through along the process. Instead the idea is that the model should be aligned with overall product strategy and organization structure (Khurana and Rosenthal, 1998).

2.3.1 Front end of innovation

The first stages of all innovation processes is often referred to as the “Front end of innovation” Kim and Wilemon, (2002) concatenates several definitions of the process and defines it as the period “when an opportunity is first considered and when an idea is judged ready for development”. According to Moenaert et al. (1995), it is where a firm develops a product idea or decides whether it should allocate resources to the idea or not. The phase is often characterised of being unstructured and hard to define, therefore also referred to as the “Fuzzy Front-End”. The term “fuzz” referring to the uncertainty of knowing how good the finished product will be and its market potential. This uncertainty can have several origins, for example, how different it is from a firm’s core business, market or technology risks, etc. (Kim and Wilemon, 2002). Key characteristics of the FFE phase are showcased in Table 3.

Table 3 Characteristics of the FFE Phase (Kim and Wilemon, 2002).

Factors Characteristics The state of the idea is… Easy to change, fuzzy

Information for decision making is… Qualitative, informal and approximate The outcome of the phase is… A blueprint to decide whether to continue

with the next phase or not. The focus of the project is… Broad, but thin Reject an idea is… Easy The degree of formalization is… Low The project team is… Small, or individual Management type is… Unstructured, experimental, creativity is

needed Budget is… Small Damage if the project fails is… Low Involvement and commitment from CEO is… Small or non-existent After studying several teams involved in new product development, (Moenaert et al>, 1995b) found that successful teams had the ability to reduce uncertainty (fuzziness) during the early planning stages. This both reduces the time of the project and the uncertainty. (Kim and Wilemon, 2002) also argues that one important factor in shortening the FFE phase and assisting the selection of the right product idea, is to to incorporate early customer invlovement an lead users (see section 2.2.2)

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Figure 5 Fuzziness level pattern (Kim and Wilemon, 2002)

Unsuccessful teams in FFE, where the development stage is started too early, before the “fuzziness level” is properly reduced experience increased risk of project delays and overdrawn budgets. In Figure 5, a pattern of the fuzziness is illustrated. Initiation of product development (point b) can only be done when the level of fuzz (uncertainty) of the project is low enough and hits the required approval level (point a), set by management (Kim and Wilemon, 2002). In Conclusion, the FFE stage has two challenges; (1) Reducing fuzz (uncertainty) as effectively as possible and (2) Setting a sufficient approval level for the project to proceed to the development phase. Even though the front end of innovation is uncertain, it can directly determine the success or failure of a new product (McGuinness and Conway, 1989; Cooper, 1998). Having control of this stage is vital, however, companies struggle in achieving high performance of this stage since it is difficult to understand the characteristics of FFE and predict the outcome of it (Khurana and Rosenthal, 1997). Nobelius and Trygg, (2002) who analysed some of the current innovation processes, mentioned in section 2.3, empirically with respect to the front end of innovation. First, they found that the different processes all have pros and cons. Secondly, they found that hunting for an optimal model for doing front end innovation is of less importance. Instead, what matter most is to have managerial flexibility. In addition, a project in the front end of innovation needs sufficient structure to make the project manageable and allow for clear decision making. However, too much structure could affect the degree of creativity, which is also important in this phase (Gassmann and Schweitzer, 2014; Gaubinger and Rabl, 2014).

2.3.2 Feasibility analysis The purpose of a feasibility analysis is to challenge the idea and logic of the project. It is often based of early stage assumptions and data but provides important insights in the likelihood of success of the projects. (Schaufeld, 2015). The purpose of the TELOS (Technical, Economic, Legal, Operational and Schedule) framework is to highlight all components needed for success of a project in an early stage to minimize failure According to Schaufeld (2015) the following will essentially be answered:

• Are the identified customers ready? Are the right features available to the right price? • Is the company ready internally? Is the technology secured, is there products,

information and people to supply the customers?

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• What to do if one or both above bullets are not met? TELOS is an acronym for Technical, Economic, Legal, Operational and should provide guidance in feasibility by assessing the major constraints of the project. A tool for management to judge the probability of success (Hall, 2010), with answering following questions:

1. Technical Feasibility a. Concerns whether the system can be developed with existing technology or if

there is need for new technology. According to Hall (2010), technical feasibility is often not an issue. Instead, the motivation and capability to apply existing technology is the real issue.

2. Economic Feasibility a. There should be sufficient economical support from management. Is

management committed to allocate sufficient capital to take the project further? (Hall, 2010)

3. Legal Feasibility a. Are there conflicts with the project and the firm’s legal responsibilities? This

includes both ethical boundaries, such as privacy, but also Intellectual Property, agreements, etc. (Hall, 2010)

4. Operational Feasibility a. Is the project compatible with the firm’s current processes and employees

existing skills? If not, is it possible to make changes to those processes, or train employees to realize the project Operationally? (Hall, 2010)

5. Schedule Feasibility a. Is it feasible to implement the project within reasonable time? Needs to

consider factors like the scope of the project, and if development will be done internally or by an external partner. (Hall, 2010)

Finally, feasibility analysis can be done in many stages of a project, the details of each step might be less uncertain, the longer the project progress. However, doing the study is better done sooner than later. According to Schaufeld (2015), it is evident that a feasibility analysis should be done prior to major funding and resources are committed to the project.

2.4 Business model generation Although the definition of a business model varies somewhat among scholars, the general idea of the concept is usually the same (Zott, Amit and Massa, 2011). For this study, the definition by Osterwalder and Pigneur (2010) is used. This definition states that “a business model describes the rationale of how an organization creates, delivers and captures value” (Osterwalder and Pigneur, 2010a). This definition of the business model concept suggests that a business model is designed to provide a holistic perspective of how a firm creates and appropriate value through the interaction with its surrounding environment (Berglund and Sandström, 2013). Teece (2010) makes the distinction that a business model should be considered “a conceptual, rather than financial model of a business”. In order to simplify the development and visualization of a business model, Osterwalder and Pigneur (2010) suggests a framework called the Business Model Canvas (BMC) (see Figure 6) Consisting of nine basic building blocks that show the

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logics behind the structure and dynamics of which a company aims to make profit. The nine building blocks cover four main areas of business: customers (C), offers (O), infrastructure (I), and financial viability (F) (Osterwalder and Pigneur, 2010a; Cantamessa and Montagna, 2016).

Figure 6 The Business Model Canvas (Osterwalder and Pigneur, 2010a)

The aim of the Business Model Canvas is to provide a blueprint for the strategy that the business should implement and build through the organization. It covers the four main aspects of a business: infrastructure management, product, customer interface and financial aspects (Cantamessa and Montagna, 2016). This is also suggested as a promising approach to experiment with new business models as it can possibly clarify the process underlying the composition of the business model. The business model canvas is an increasingly popular way for companies to illustrate the benefits and structure of a potential offering and is often used as a basis for assessment. As illustrated in Figure 6 the Business model canvas the nine building blocks of the business model canvas are: Key partners, Key activities, Key resources, Value proposition, Customer relationships, Channels, Customer segments, Cost structure, Revenue streams. The parenthesis refers to the main area of business to which the building block belongs. Key partners (I) Key partners refer to the network of suppliers and partners that should be established to enable the business model. The Key partners can provide access to key resources and key activities, why they can be seen connected in the canvas (Figure 6). Osterwalder and Pigneur (2010) suggest three motivations for partnerships and four different types of partnerships for the business model canvas, seen in Table 4.

Customer segmentsKey activities Customer relationships

Key resources

Key partners

Cost structure Revenue streams

Channels

Value proposition

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Table 4 Types of partnerships and motivations for partnerships (Osterwalder and Pigneur, 2010)

Three motivations for partnerships Four different types of partnerships

Optimization and economy of scale Strategic alliances between non-competitors Coopetition (strategic partnerships between competitors) Reduce risk and uncertainty

Joint-ventures to develop new business

Acquisition of particular resources and activities

Buyer-supplier relationships to assure reliable supplies

Key activities & Key resources (I) Every business model requires a number of Key activities and Key Resources that will make the business model work. These are important actions and assets that the firm needs to take in order to operate successfully. The Key activities and Key resources are required to create and offer the Value proposition, reach the necessary markets, maintain the Customer relationships and activate the Revenue streams. Osterwalder and Pigneur (2010) suggests three categories of Key activities and four categories of Key resources. Table 5 Types of Key activities and Key resources (Osterwalder and Pigneur, 2010)

Key activities Key resources

Production Physical

Intellectual Problem solving

Human

Platform/Network Financial

Value proposition (O) The Value proposition constitutes the foundation for the reason a customer choses the specific solution, service or product presented. This means that the value proposition presents the benefit that the company can offer the customer and the problem that is solved (Osterwalder and Pigneur, 2010). It should not simply be the product or service offered, but the underlying value that this will deliver to the customer (Cantamessa and Montagna, 2016). Customer relationships (C) The type of relationship with the company wants to have with customer should be established and can range from personal to automated depending on the type of offering the business model is examining. The Customer relationships should be structured in a way to optimize customer acquisition, customer retention and upselling. Different types of Customer relationships may co-exist in a particular business model. Channels (C) The Channels refer to the method of which the value is delivered to and communicated to the customers. That is, the customer facing interface of the company. According to Osterwalder and Pigneur (2010), Channels have five distinct phases for which any given Channel can cover some or all. The types of Channels can also be divided into Partner and Own Channels,

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as well as Indirect and Direct Channels. It is crucial for any organization to find the right mix of Channels that will satisfy the customers. The Channel types and Channel phases can be seen in Table 6. Table 6 Channel types and Channel phases (Osterwalder and Pigneur, 2010)

Channel types Channel phases

Ow

n Pa

rtner

Dire

ct

Indi

rect

1. Awareness How do we raise awareness about our company’s products and services?

2. Evaluation How do we help customers evaluate our organization’s Value proposition?

3. Purchase How do we allow customers to purchase specific products and services?

4. Delivery How do we deliver a Value proposition to customer?

5. After sales How do we provide post-purchase customer support?

Customer segments (C) One of the most fundamental parts of a sustainable business models are the customers. In fact, a business model can only be sustainable if it is able to offer something that is deemed valuable to someone else. The customer segment specifies the groups of customers that the business model aims to serve (Cantamessa and Montagna, 2016). In the business model canvas, one or several large or small customer segments should be defined. According to Osterwalder and Pigneur (2010) groups of potential customers represent different segments if:

1. Their needs require and justify a distinct offer 2. They are reached through different Distribution Channels 3. They require different types of relationships 4. They have substantially different profitabilities 5. They are willing to pay for different aspects of the offer

Cost structure (F) The cost structure compounds the most important costs related to operating the business model. As stated earlier, a business model should be considered a conceptual model rather than a financial model (Teece, 2010). This means that when it comes to mapping the cost structure, focus should be to identify the most important cost drivers in the operating model rather than trying to find exact cost levels. Revenue streams (F) According to Osterwalder and Pigneur (2010) a business model can involve two different types of Revenue streams: transactions revenues gathered from a one-time payment or recurring revenues resulting from ongoing payments from delivering continuing value either through a continuous access to the product or service or through post-purchase customer support. As with the Cost structure, focus is on identifying the streams of revenue rather than the exact quantity.

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2.4.1 Opportunity recognition The source of innovation and presumably the first step of any type of innovative process or new business model generation is the idea, creating the base of an opportunity that is recognized. This concept is called Opportunity Recognition. Hills, Shrader and Lumpkin (1999) argues that an often overlooked, however potentially highly valuable source for opportunity recognition is the intuitive approach. The intuitive approach may itself seem counter-intuitive within academics as finding orderly processes and structures is often the goal. Intuition is characterized by non-linear and unsystematic approaches to problem solving. In the intuitive approach of opportunity recognition, the idea will be partly developed in an Incubation phase as a person intuitively considers possibilities and options. This is the process that occurs when a person is thinking about an idea and is according to (Hills, Shrader and Lumpkin, 1999) where ”new combinations” might emerge. Furthermore, (Mosakowski, 1998) suggests four entrepreneurial resources which are likely to contribute to a competitive advantage in the process of recognizing opportunities, these are: creativity, foresight, intuition and alertness. (Osterwalder and Pigneur, 2010a) also argues that what is demanded when generating a new and innovative business model is a creative process. Perhaps more importantly, they argue that business model innovation is not about looking to competitors or the industry “way of doing things”. It instead is about creating new mechanisms to create value and generate revenue through challenging the orthodox and traditional. To do this, they suggest one must “dream and grab” before narrowing down to conceivable options through an innovation funnel. The impact of this is that the ideation step, contains two phases: idea generation, where quantity is key, and synthesis, where the generated ideas are narrowed down. The sources for ideas of innovative business models can come from anywhere, and thus any of the nine business model building blocks can be a starting point (see 2.4). Osterwalder and Pigneur (2010) suggests four epicenters for business model innovation, sourcing from different blocks in the Business Model Canvas: resource-driven, offer-driven, customer-driven, finance-driven and multiple-epicenter driven. The resource-driven business model innovation originates from an organization’s existing infrastructure or partnerships to expand or transform the business model, thus puts most focus on the Infrastructure area of business and thus the building blocks Key partners, Key resources and Key activities.

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3 THE FRAMEWORK In this chapter the framework developed from theory and applied on the case is presented. The purpose is to provide a clear understanding of how the framework is structured in terms of the order of the steps as well as how the theory is connected to each step. In order to thoroughly identify and assess the possible opportunities from utilizing the resources suggested in The Climate Data Project at Telia, a framework for how existing resources can be utilized is transformed to a business case was developed. The process, see Figure 7, consists of four steps and is arranged as a funnel. The process starts with the identification of existing resources that can be utilized in several new ways and is then narrowed down and synthesized into a business case that can be used as basis to decide whether to pursue the project beyond the front-end phase of innovation (see section 2.3.1) or not.

Figure 7 Theoretical framework for the innovation process

In the first step, the potential resources to utilize needs to be identified, this is done aligned with RBV theory, which effectively propose a way to identify and separate valuable resources from non-valuable. In the second step, the resources are transformed into use cases with defined stakeholders. Focusing on addressing the need for open innovation processes and engage stakeholders early in the process, this is done with basis in open innovation theory. In the third step, the feasibility of the produced use-cases is assessed qualitatively. This is done with the TELOS framework in order to evaluate the different risks associated with open innovation, see Table 2, together with reducing the uncertainty of the project. Finally, in the fourth step, the use case will be formulated as a business case, in the form of a business model canvas, a tool common in decision making in this phase. In addition, the process, see Figure 7, aims to be structured enough to make the project manageable, this with a clear theoretical framing in each step. However, it also needs to allow flexible enough to not affect creativity, see section 2.3.1. This to be achieved by designing the

Identify resources Build use cases Feasability analysis Build Business case

RBV/VRIO Lead users TELOS BMC

Front End of Innovation

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empirical phase in a way as open as possible, with workshops and semi-structured interviews. This will be elaborated further in chapter 4.

3.1 Step 1 – Identify resources The purpose of step 1 is to identify valuable resources and capabilities of the firm. Within this step, we find two crucial phases that can increase the likelihood to successfully identify the right resources, in accordance with the ideation process suggested in section 2.4.1 Opportunity recognition. First, it is necessary to thoroughly search and find potential resource candidates that can be examined. Secondly, we need to validate that these resources meet the criteria of being valuable resources. When identifying and assessing the value of resources in the context of a partnership enabled innovation project, we identify two complexities, in addition to the complexity of identifying valuable resources in traditional organizations. Firstly, when following the traditional VRIO-framework, presented in section 2.1.1, to examine the value of the resources, one of the definitions of value suggests the criteria that the resource “enables the firm to exploit the external opportunities and through the combination of the resource and the opportunity create a sustained competitive advantage” must be met. This can be interpreted as being based on the assumption that the value of the resource is only a function of its value to the own firm. As we are in this context instead interested in not only the direct value for the own firm but also the potential value for the partner firm this statement needs to be somewhat further defined. Secondly, the traditional VRIO-framework is also adapted for the competitive advantage that the resource brings in the current context. As mentioned in section 2.1.1, Wernerfelt (1984) suggests that a resource might well be valuable in the context of a new area of utilization. This puts pressure on the capability within the firm to innovate and find and enable new ways of utilizations and benefits of the potential resource. In context of the FFE, the quest to find new ways of utilization is especially important.

Figure 8 Step 1 of the innovation funnel is divided into two phases

Search & find

Assess & value

Valuable resource

Partnership enabled

Innovative utilization

Phas

e 1

Phas

e 2

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The complexities from these phases are illustrated in Figure 8. So, the first phase of Step 1 requires a process that has the potential to identify potentially valuable resource candidates that (1) might only be considered valuable when enabled by the resources of a partner and (2) when used in a new context or for a new purpose. The resource candidates should thus be accompanied with new potential benefits, as explained in section 2.1.3 Core competencies. Finding these potential resources in Phase 1 can be especially complicated due to the difficulty in following a structured and established process when coming up with the potential candidates as is often the case in the FFE. As suggested in section 2.4.1 Opportunity recognition, this needs to be a creative process where possible resources are identified. The findings from Phase 1 is considered the source of innovation. Furthermore, for phase 2, we are interested in assessing the potential value from the identified resource. As stated above, using the VRIO-framework for assessing this value needs further complementing frameworks, however it can work as a guiding framework. And the definition of value does allow for further interpretations and methods of assessment. As in accordance with core competence theory, presented in section 2.1.3 Core competencies, the identified resources should be assessed as potentially valuable in the new context. This means that new Benefits needs to be identified from the existing resource. For instance, in the case of collecting data as a resource. We can look at the frameworks in section 2.1.2 Data and analytics as a resource. These complement the VRIO-frameworks with the value arrived from the complexity of analytics possible from the data. This could be translated into the Benefit-level of analytics. Before moving on to Step 2, the essence of the findings from Step 1 should be summarized. This means synthesizing the benefits and opportunities that the value of the identified resources can lead to. This form the basis for the value proposition used in the Business model canvas in Step 4, presented in section 2.4.

3.2 Step 2 – Build use cases The resources identified in step 1 will in this step be used to find use cases and partners. In order to identify the most interesting and valuable use cases in the FFE phase, earlier studies argues that one focus should be identifying lead users. Involving lead users early will both help select the right product and reduce project time, see section 2.2.2. This is also encouraged by open innovation theory which argues that external involvement, can help firms catalyze innovation. Exchanging ideas openly can help the firm in discovery of new markets, as well as help firms advance their technology, see section 2.2.1. From a traditional view, pursuing RBV would disagree that early stage parterships are benificiary. In traditional RBV, it is argued that focus should be to create value from the resources internally with minimized cooperation between firms. Howevever, strategic partnerships where resources are exchanged between firms are in modern RBV theory also viewed as a resource, so called network resources, which can be important for enhancing competitiveness, achieving strategic goals and finding new market opportunities, see a. Therefore, based in theory on Partnerships and RBV and, the following two focus points should be pursued when selecting use cases in the FFE phase;

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• Focusing on identify lead users as stakeholders with high degree of potential

cooperation in development of the product and high influence on the market. According to empirical studies, two of the characteristics of a lead user are that they are pioneering and innovative, as well as develop their own innovations and applications (see section 2.2.2). In addition, RBV research regarding network resources as well as open innovation theory argues that new market opportunities to be found if the right partnerships is established, but that a high degree of cooperation is needed from the interconnected firms on order to capture the benefits from a parterships (see section 2.2.1 and a)

• Focusing on identify use cases with high scalability and high user benefit.

Lead users should have needs which are reflected by a whole market, but experience the need earlier than the general users. Thus implying the importance of scalability of the use case. It should not be only applicable for one specific need, but relevant for a broader market. Secondly, lead users should expect high level of benefit of the product, both in the future and before the general market. Thus it is of interest to choose use cases where the user benefit is high. This is also an important factor in RBV theory, which argues that it is important that a resource is valuable and able to exploit external opportunities, see section 2.1.1. In order to further validate the value for the use case for the identified lead users. These can be qualified against the five characteristics suggested by Morrison, Roberts and Midgley, (2004) (see section 2.2.2):

• Recognize requirements early • Expect high level of benefits from the product • Develop their own innovations and applications • Perceived to be pioneering and innovative.

3.3 Step 3 – Feasibility analysis Looking again at the main issues of the FFE, reducing uncertainty is key. The aim of a feasibility analysis like the TELOS framework is to function as an early reality check for management to judge probability of success and should be done as soon as possible in the innovation process, see section 2.3.2. The TELOS framework aims to answer two essential questions. • If the customer is ready and if it is possible to provide the right features for the right price.

Due to the characteristics of lead users (see section 2.2.2), they should be expected to be able to specify rather specific requirements, highlighting what would be important components for success, thus allowing for a somewhat accurate answer to those questions.

• If the company have the sufficient technology and resources to meet the customer requirements?

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In this phase of the innovation process, where qualitative, informal decision making is common, see Table 3 this could be investigated by searching for answers to each of the parts of the TELOS framework covered in section 0.

3.4 Step 4 – Build business case The last part of the innovation process funnel is to synthesize the findings in the previous steps and structure them into a business model which clarifies the business case. As stated in section 2.4 Business model generation, this involves structuring the important resources, benefits, value from the use case and technical infrastructure in a holistic way to visualize the potential of the business model. In order for the decision makers to be able to assess the validity of the business case a tool to visualize the business model in a way that is recognizable and familiar is to be preferred. Structuring this into a Business model canvas will give a holistic perspective on the feasibility of the project and thereby a solid ground for determining further developments of the project. The process of structuring a Business model canvas is described in section 2.4 and entails going through the nine building blocks: Key partners, Key activities, Key resources, Value proposition, Customer relationships, Channels, Customer segments, Cost structure, Revenue streams, step-by-step and describing the identified components and aspects from the previous steps in accordance with the framework. In addition to being a tool to be used for basis in a Go/No-go decision, building a business model canvas will also provide a perspective on the gathered information and suggest an indication on whether some aspect might need complementary gathering of data.

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4 METHOD This chapter lays out the research methodology chosen for the study.

4.1 Research strategy The study has been conducted in the form of a qualitative approach, a method where focus lies in testing theory (Bryman and Bell, 2011). This study focused on evaluating a framework based in prior research, for finding business opportunities through utilizing existing resources and new partnerships. The evaluation was done by a case study, investigating a concept on how climate data from Telia’s base stations could be a new revenue stream for Telia. Since this study focused on phase called the front end of innovation, characterized by being unstructured and uncertain (see section 2.3.1), there is little quantifiable data to look at, in line with what Bryman and Bell (2011) argues is why a qualitative study is preferred.

4.1.1 Systematic Combining In research focusing on business aspects, Bryman and Bell, 2011 claims it is important to have both a deductive and inductive approach. The approach put forward by Dubois and Gadde (2002), referred to as systematic combining, suggests that research on an ongoing case is best done through confrontation between the evolving framework and the evolving case. That is, it beneficial for the research allow itself to constantly go “back and forth” between empirical observations and theory, see Figure 9. It is described as a non-linear path-dependent process with the ultimate objective to match theory with reality.

Matching

Direction and redirection

Figure 9 Systematic combining (Dubois and Gadde, 2002)

Empirical world The empirical world in this case consisted of a concept developed at an innovation department with the goal of finding new revenue streams for a large telecom company. This entails two overall characteristics. First, the innovation department is a generally positive environment where new ideas and concepts were embraced up to a certain point. Secondly, the project is in the concept phase. Meaning, when reaching out to potential partners, the broad picture was discussed and not specific details.

Framework

Theory

The case

The empirical world

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Framework In this thesis, the strategy was to initially suggest a tight framework, based on a theoretical foundation, for examination that will evolve through theoretical and empirical examination simultaneously. The particularity in creating a tight and evolving framework allows for two specific aspects (Dubois and Gadde, 2002). Firstly, the tightness of the framework reflects the degree of understanding behind the preconceptions of the framework, which is important as it is these preconceptions that are tested. Secondly, the reason for the framework to evolve is that it is likely that empirical observations will inspire changes in the framework. This is especially true in a case study focused on an innovation process as it is deemed unstructured and unpredictable by nature. The case Dubois and Gadde, (2002) states that the case should evolve during the course of the study. Case studies is a great tool for developing theory as the interaction between a phenomenon and its context is best understood through in-depth examination. In this study, climate data as a new business opportunity was used. During the development of the project, relevant theory needed together with an extensive set of interviews was used in order to allow for understanding the phenomenon of front end of innovation in the context of the innovation department, division X, at a large telecom company, Telia. Theory In order to get a both comprehensive and balanced perspective of the study, it has been important to both find new and old research about the topics covered in this study, the resource based view, Innovation processes, partnerships and business model generation. In addition, focus lied in triangulating key characteristics within these areas of research to find reliable insights which can be utilized and combined with confidence in a framework. In this study we combined several smaller frameworks: (1) VRIO from resource based view; (2) Lead users as a form of early partnership from partnership research (3) TELOS as a feasibility framework inspired by necessary requirements from the early phases of innovation processes called front end of innovation. in prior research. Although there are much literature discussing each concept and framework; (4) Business model canvas, as an efficient and commonly used framework for creating a business case. There is little prior research on the combination of these framework, thus the qualitative approach will provide a basic understanding on how the frameworks from RBV, lead users, TELOS and business model canvas.

4.2 Research Process By using the approach of systematic combining, the framework was developed from theoretical concept in parallel with the case study. After being presented with the idea of collecting climate data from base stations, the main research question was formulated: “How can a large telecom company catalyze innovation with existing resources and new partnerships?”. Thereafter, a brief literature review was conducted, exploring the relevant theoretical concepts, in this case resource based view, innovation processes, partnerships and business model generation. Thereafter, it was discovered that the main research question needed to be broken down into two sub questions: “How can existing resources be assessed for new areas of utilisation?” and How can new partnerships be found?

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A process was created that could be followed that could answer these questions. As stated in section 2.3.1, a

process in the front end of innovation should focus on allowing flexibility, but also with structure to some extent. To achieve both flexibility and structure, the process was arranged as a funnel, see

Figure 10, where the initial steps (step 1 and 2) were more exploring, allowing flexibility, not limiting ideas to feasibility or business relevance. The idea was to give as much space for creativity as possible. However, in order to give some structure and possibility to value and rank the ideas that were generated in these steps, frameworks originating in the studied theory concepts where used. The two following steps (step 3 and 4) did not focus as much on creativity but rather structuring the ideas and making sure the necessary components of the concept were covered to take the concept to the next phase. This was also done with previously researched frameworks from literature in order to make be able to make it evaluate the result and perform an analysis of the outcome.

4.3 Research Design The research design was done in the form of a case study which followed the framework developed in chapter 3, see Figure 10. According to, Bryman and Bell, (2011) a case study allows to both capture the complexity as well as the certain characteristics of a case which was deemed to be important in this study on climate data for Telia.

Empirical material was collected for each step by interviews both with employees and managers within Telia, but also with the potential external partners. The interviews and workshops were structured in accordance with

the corresponding framework in each step of the process, see

Identify resources Build use cases Feasability

analysisBuild Business

case

RBV/VRIO Lead users TELOS BMC

Empi

rical

wor

ld

Theo

ry

Fram

ewor

k

Workshops and interviews

Workshops and interviews

Validation Expert interviews

32

Figure 10. In order to make the case study manageable, the concept with the best potential of succeeding, when mapped against the frameworks in Step 1 to 3 where then selected to formulate the business case around according to the business model canvas.

Figure 10 Empiric process

4.4 Data Collection Data collection has been done through conducting a comprehensive literature review as well as semi-structured interviews and workshops. For each step, focus has been to ask open, broad questions to be able to locate knowledge within the company, as well as external potential partners. For more information on interviews and workshops, see Appendix A and Appendix B.

4.4.1 Workshops The workshops where held together with 5 experienced managers at Division X who either had expressed an interest, had knowledge that could be of relevance for the project. In the first workshop, the idea that climate

data could a potentially interesting new revenue stream was presented, where after the participants were free to discuss both the idea itself as well as what type of climate data would be of most interest. The results from the

workshop, what data could be of interest, where and insights where then arranged and assessed according to the framework for step 1, see

Figure 10 and chapter 3. The second workshop, held in step 2 consisted of the same participants as workshop 2.. The participants was now familiar with the case and now focused on generating valuable use cases as well as the potential lead users (further elaborated in section 2.2.2), called stakeholders in the empirics chapter. The structure was in this workshop also open where all participants were engaged in discussing and coming up with suggestions without any other limit rather than it should be a business customer (B2B). All the suggestions were during the interview also placed on two graphs after certain characteristics, see section 3.2, by the participants and given a score between low, medium or high. For use cases these were “Perceived Scalability” and Level of Benefit” (how much benefit the user might have of the product). The stakeholders where sorted after perceived “Level of Influence” (meaning the influence the stakeholder have/will have on the market and product) and “level of required cooperation” (meaning how much cooperation is needed of the stakeholder to make the product both developed and successful.

4.4.2 Interviews In total 18 semi-structured interviews were held with 14 interviewees. 7 of those interviews were held with people outside Telia. The case study conducted in this study had the purpose of developing a business opportunity on a conceptual level, therefore the purpose of the interviews was to conceptually validate the necessary stages of the framework suggested in

33

chapter 3. Therefore, it was reasoned that interviews internally in Telia should conducted with managers with long experience within his/her respective field. Thus, being able to provide realistic judgement and insight to the questions asked, as well as the feasibility of the components of the project both from a business and technical perspective. The external interviews were held with the most promising stakeholders from workshop 2. The interviews in step 2 (Build business case) of the framework focused in presenting the ideated product “real time climate data” and thereafter asking questions related to the parameters that the stakeholder and use case was scored on prior in workshop 2. The people interviewed for each of the stakeholders were in managers with both technical and business knowledge about their own company. The purpose here was that this also would ensure that the answers could be deemed to be accurate and representative of what could be expected by the company. Finally, one stakeholder was selected for step 3 in the framework (feasibility analysis). Here, the interviewee, was asked in more detail about specific requirements according to the TELOS framework. These were then reiterated for a technical manager at Telia to verify the possibility of carrying the project through.

4.5 Reliability and validity This study is done through systematic combining where the case study is done by qualitative research. The framework followed to structure the case study is derived from theory, where different research areas have been triangulated in order to create a tight framework. Bryman and Bell (2011) argues that triangulation is an important way of increasing both reliability and validity of a study. The case study in itself was also triangulated, the results from the workshops and interviews within Telia was checked against external stakeholders, and then once again checked against other sources within Telia. The main research question states ask how can a large telecom company catalyze innovation with existing resources and new partnerships. In this study, we primarily focus in the concept phase, front end of innovation. As Tomas Edison said, the hard part is not coming up with ideas, but rather to implement them (see section 2.3). To be able to fully answer the main research question, it can be argued that the project must be followed through all the way to full commercialization. However, the interviews and workshops have been aimed to interview persons that can give as much trustworthiness as possible even if the stage investigated is only the early part of the innovation phase. We suggest a framework from theoretical concepts which is then applied on the empirical world. One can argue about causality, what the relationship is between cause and effect of the study. Can it be assessed if the framework has had an effect in catalyzing innovation from existing resources and new partnerships, or are there other factors which were not investigated that have impact. While this is an important issue to cover, the framework in chapter 3 is merely used in order to understand and put the ideas and insights in theoretical context.

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5 THE CASE STUDY In this chapter the outcome from applying the framework on the case is presented. This includes the process of applying the framework on the case, results from the empirical world and the output from the framework. Telia Company is the largest telecommunications provider in Sweden with a market share of 40% within mobile telecom, but is operates in a wide range of markets (Telia Company, 2016). With this position and large customer base, the company is usually perceived as an attractive partner for other companies interested in reaching a larger group of potential customers (ID, 2017). This has enabled various partnerships being formed where Telia Company offers exposure to their customer base and the partner in return provides Telia Company with the possibility to provide their customers with value added services. For instance, Telia partnered up with a streaming service in order to appear more appealing to a younger audience, while the streaming service wanted to reach a broader user base (Telia Company, 2009). Since then Telia has done several partnerships with smaller companies where the selling point has been that the smaller companies will reach a large and broad user base if they allow their products to be associated or bundled with Telia’s products. In exchange, Telia gets an upper hand against competition through being able to offer new exciting products at better terms than if they were to be acquired elsewhere. Although these partnerships have proven successful, they are merely a bundle of two brands sold together, rather than a deeper partnership where a new product or service is developed and introduced to the market jointly. (ID, 2017) The firm’s innovation department is called division X with the goal to find new revenue streams for the company’s existing resources. Furthermore, it is expressed that external partnerships are preferred when pursuing new revenue streams, to avoid the need to take resources working Telia’s core business. In this case, an idea was presented that Telia’s base stations might be able to be utilized in new ways. The base stations are scattered across all of Sweden in order to supply the Swedish customers with a competitive level of cellular coverage. Thus, the company owns and operates a highly granular network of base stations which are located to cover >99.9% of the Swedish population and 84.9% of the country’s surface (PTS, 2016). By mounting sensors on base stations to collect climate data, a network of climate data could be created in a way currently not possible, in places where only Telia had access to (HoI, 2017). No prior investigation of the feasibility of the project have been done by the company, therefore, this project starts in the front end of innovation, and in this chapter, the case will be investigated as a project in this phase, following the framework suggested in chapter 3.

5.1 Step 1 – Identify resources As suggested in section 3.1, the initial step of the process is to identify the resources that can be used in new areas of utilization. Furthermore, the initial step includes assessing potential value and level of competitive advantage that can be enabled from exploiting the resource. In The Climate Data Project, Step 1 focuses on taking the initial idea presented by the company, and assessing the resources suggested according to our framework. The expectation of Step 1

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is to be able to give an initial indication on whether the suggested resource should be pursued and examined further.

5.1.1 Phase 1 – search & find The creative process of finding potential resources in Telia Company within the Division X is used as a basis for examining this funnel. Telia proposed the network of base stations as a potential resource that could be utilized for new applications, and the possibility of collecting climate data as a benefit from these was suggested as a new business opportunity (HoI, 2017b). This was the initiation of the project and thus the basis for the funnel examination. The identified potentially valuable resource and its potential new area of utilization is summarized in Table 7 .

Table 7 Initially identified resource and the potentially new area of utilization

Potentially valuable resource: Potentially new utilization: Telia Company’s network of base stations

Granular network of sensors providing real-time climate data

Benefits from utilizing the network of base stations in for real-time climate data could be Trough workshop 1 (workshop 1, 2017), the potential benefits from the network of base stations was further defined, listed in Table 8.

Table 8 Potential benefits from new utilization of base stations

Potential benefits from new utilization: It is suggested that a granular network of sensors can potentially collect climate data on the following: • Rainfall • Temperature • Humidity • Sun radiation • Air quality/pollution • Air particles • Accelerometer • Sound • Pressure • Wind

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5.1.2 Phase 2 – assess & value

The second phase is to assess the identified potentially valuable resources from phase 1 through appropriate frameworks. Telia’s base station network Testing the base stations with the VRIO-framework gives us the following:

Table 9 VRIO-framework applied on Telia’s base station network

Telia’s base station network

Val

uabl

e

The value of Telia’s base station network can be viewed in two ways: (a) It is valuable to the customers as one of the core value propositions

in Telia’s main area of business (Telia, 2017) (b) It might enable Telia to exploit opportunities, this is further

examined in Table 10.

Yes

Rar

e

While the specific network owned by Telia is of course unique in the way that no competitor owns and operates the exact same network, similar network constellations do of course exist within competitors. The main characteristics of Telia’s base station network is similar to that of the competition in terms of national surface coverage and population coverage (PTS, 2016).

No

Impe

rfec

tly

imita

ble

As there are competing firms with similar networks the question of being imperfectly imitable is not relevant, see section 2.1.1. However, it can be worth noting that for new actors to install a base station network of the same magnitude would require tremendous resources and is thus somewhat of an entry barrier.

-

Org

aniz

atio

nal

appr

opria

bilit

y

As a telecom company, the organization of Telia is designed and highly suitable to be the owner and operator of a large base station network. This is due to two factors:

• The historical factor, where Telia has been the operator of this type of network for a long time and thus has built up organizational infrastructures and competencies allowing an efficient organization, see section 2.1.1.

• The economies of scale-factor, Telia Company is the largest telecom company in Sweden and thus has the economies of scale to be a profitable operator, see section 2.1.1.

Yes

This suggests that Telia’s network of base stations in the current context enables Telia to enjoy a competitive parity. As a basis for strategic direction, this gives two implications: (1) the base station network is essential for Telia’s operations, and (2) the network would benefit from seeking new area of utilization as exploiting the resource can potentially create a competitive advantage. However, failing to exploit the resource is more likely to put the firm at a competitive disadvantage, as mentioned in section 2.1.1. As suggested, developing this

38

resource with further resources and capabilities can potentially enable a competitive advantage. New utilization of the base station network with real-time climate data Testing the new utilization for Telia’s base station network with real-time climate data with the VRIO-framework gives us the following:

Table 10 VRIO-framework applied on the climate data project

Real-time granular climate data network

Val

uabl

e

The value of climate data in the daily operations of Telia is low (EM, 2017). However, through intuition, one can easily suggest further firms and industries whom are highly effected by weather, and thus would value this information. It is also important to look at the data through the perspective of the Gartner Analytic ascendancy model where increased complexity results in increased value, as suggested in section 2.1.2. Data that comes from measuring climate etc can result only in building predictive analytics due to the nature of environmental aspects being impossible to alter. What this means in practice is that even though, for instance, you know that you will sell more ice cream when it’s warm and sunny outside, you do not have the option to choose that weather. Knowing that there will be a poor weather for selling ice cream today, however, gives you the ability to change what you’re selling to something that is suitable in that type of weather. Furthermore, it is important to note that the potential value from climate data must be further validated through interaction with potential stakeholders and partners.

Yes

Rar

e

Although real-time climate data exists (Mc, 2017), and climate data covering a large area of Sweden exists, the network enabled by Telia would offer a combination of these. A real-time granular and nation-wide network of climate data with the infrastructure available with the help of Telia’s capabilities does not currently exist and would thus be regarded as a unique attribute to Telia.

Yes

Impe

rfec

tly

imita

ble

Installing sensors to collect climate data from the base station network is initially estimated to not require a substantial investment from a base station network operator, and can thus not be regarded as imperfectly imitable (HoI, 2017a). However, further analysis from the feasibility study will give increased estimation for the assessment of this.

No

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Org

aniz

atio

nal

appr

opria

bilit

y The Telia organization is not currently designed to handle climate data (EM, 2017). However, some key-aspects of the infrastructure needed to do this are in place. Telia, as a telecom company are highly suitable to handle large data streams, implement the needed connectivity and operate the required infrastructure. Furthermore, handling the actual data and applying it in a valuable sense requires experts within meteorology and weather analysis and forecasting.

Maybe

The VRIO-assessment for the real-time climate data network presented in Table 10 suggests that the resource in this context is valuable, rare and organizationally appropriate, however, not imperfectly imitable. This means that the resource would be considered to enable a Temporary competitive advantage, however, also give Telia a first-move advantage. As a first-mover, Telia can potentially put up further entry barriers, thereby enjoying prolonged competitive advantage. In order for Telia to enjoy a sustained competitive advantage, they must discover further use cases. In conclusion, Step 1 leads to a supposed product offering with the following characteristics: Climate data distributed through Telia’s network, both in cities and in rural areas, with much

higher update frequency and higher spatial resolution than current actors.

5.2 Step 2 – Build use cases With the product offering formulated in step 1, step 2 is initiated. The purpose of the step is to find potential new partners who could be early beneficiaries and be able to be involved early in the development phase. This is done by two substeps, similarly to step 1. First, potential parterships, called stakeholders and potential use cases are ideated through workshops with internally. Secondly, the most interesting use cases and stakeholders are selected and are interviewed to assess and value their interest.

5.2.1 Search and Select In workshop 2 (workshop 2, 2017), the participants, where asked to identify and arrange the stakeholders on a graph, illustrated in Figure 11. 24 potential stakeholders for climate data were identified. The placement for each stakeholder in the graph where purely based on perception and judgements based on previous experience by the workshop participants. The stakeholders where sorted after perceived level of influence on the y-axis, graded low, medium and high. This means the degree the stakeholder had influence on the market if to be involved in a climate data project with Telia. On the x-axis, also graded low, medium and high, the stakeholders where sorted after “required level of cooperation”, meaning how much and how close they would be able to work with Telia to develop a product.

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Figure 11 Identified Stakeholders

Looking at the identified stakeholders, 15 use cases where developed, (workshop 2, 2017), see Figure 12. Like Figure 11, the use cases where arranged in a graph, where the placement is based upon the participant’s previous experience and judgement. The use cases where arranged after “scalability” on the y-axis graded low, medium and high, defined as how capable the case would be able to grow. Furthermore, the use cases were arranged after “level of benefit” graded low, medium and high on the x-axis, referring to how much the user of the product would benefit from a climate data product.

Figure 12 Identified Use Cases

1

23

4 5

0

1

2

3

0 1 2 3

Leve

l of I

nflu

ence

Requiered level of Cooperation

Stakeholders

Low

Med

ium

H

igh

Low Medium High

31 2

0,0

1,0

2,0

3,0

0 1 2 3

Scal

abili

ty

Level of benefit

Use cases

Low Medium High

LowM

edium

High

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5.2.1 Assess and value After looking further into the 24 identified stakeholders and 15 use cases, five of the stakeholders in Figure 11 (marked in green) and three use cases in Figure 12 (marked in purple) where selected as the most realistic and with the highest potential for success, to investigate further. In Figure 13, potential climate data to collect from sensors, identified in Step 1 is represented by the black dots. They reflect the data that is of interest for the corresponding use case. Since the network has been divided up in the two broad categories of “rural” and “City" networks, the figure also illustrate what network type is of interest for each use case (CTS, 2017).

Figure 13 Most plausible stakeholders connected with use case and data of interest

The five identified stakeholders express their own view of their need of real time climate data below: Stakeholder 1 Stakeholder 1 is an agriculture cooperative who sees benefits in aggregating more data to their farmers that can help their day to day work, prevent damages on crop for example. As such, Stakeholder 1 is motivated by optimizing their business model and reducing the risks and uncertainty of the farmers. Therefore, main climate data of interest consist of rainfall, temperature, humidity, sun radiation, wind and pressure, see Figure 13. With Stakeholder 1, Telia could create a strategic alliance as well as a buyer-supplier relationship where the companies can exchange information on targets for product development in parallel with Telia selling the service through a subscription. (PM, 2017) Stakeholder 2 Stakeholder 2 is a company involved with energy trading, where knowledge about data that affects energy use is essential. They see potentially great benefits of receiving some types of climate data in real time. The motivation of Stakeholder 2 for engaging in this project is thus

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to optimize their business model and reduce risk and uncertainty. Contrary to the availability of weather data they have today where data has an update frequency of a couple of times per day and large delay. They find it suitable to form a buyer-supplier relationship where they are provided with the data through a subscription. Furthermore, Stakeholder 2 express that there are needs for real time data both in rural areas and in cities. Being experts in collecting data, the stakeholder had clear requirements in terms of technical aspects of the data quality. Two data types, of the nine which were assessed as possible to collect, where expressed as being of particular interest: sun radiation and temperature. Finally, Stakeholder 2 is open to collaborate in innovative projects that can benefit the company in different ways, which, in combination with Stakeholder 2’s expert status within the field makes Stakeholder 2 suitable for forming a strategic alliance. (HoPMA, 2017) Stakeholder 3 & 4 After interviews with Stakeholder 3 and 4 it was communicated that a real benefit and interest could not be found at this stage. Therefore, these where chosen not to continue discussions with. (VPSD, 2017; VPSBI, 2017) Stakeholder 5 Stakeholder 5 is an air quality analytic department, municipally owned, who have an interest in gathering more climate data, especially in cities, where it today is hard to put measurement systems up on rooftops due to restrictions by, for example real estate owners (HoDe, 2017). The stakeholder expresses that more accurate climate data in cities could improve and verify current prediction models. This is important since the stakeholder also work with monitor and approve real estate and infrastructure projects within the city (HoDe, 2017). Thus, they are interested in all climate data that can be gathered in cities, see Figure 13. As Stakeholder 2 has expert knowledge within the field and previous experiences of partnering with private companies, they could potentially form a strategic alliance with Telia. Continuing down the funnel, the identified stakeholders with its respective use case where evaluated to hone in on one case that could be function as the first pilot study, see Table 11.

Table 11 Stakeholders evaluated after lead user requirements (HoPMA, 2017; HoDe, 2017; PM, 2017)

Stakeholder1 Stakeholder2 Stakeholder5Recognizerequirementsearly

Yes Expressed need of new types of climate data.



Expecthighlevelofbenefitsfromtheproduct

Maybe Some benefit of aggregated climate data is expressed, however need to be combined with other services be useful.

Yes Expressed that there are potentially large gains with faster and more accurate climate data.

Yes Stated that there are many benefits if to be able to access more climate data, especially within cities.

Developtheirowninnovations

Yes Currently on path on helping

Yes Houses large R&D department to be

No Do not the resources to pursue

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andapplications

farmers in new ways through digitalization.

able to be in forefront of their field

innovation. Rather analyses and gives recommendations from data available.

Perceivedtobepioneeringandinnovative

Maybe Historically not known for being innovative, but shows willingness to go towards that direction.

Yes Has historically introduced several innovations in large scale, in need to be in forefront of technology to have upper hand against competitors.

Maybe Function of organization is mainly providing municipality with information and recommendations. Although projects are done in collaboration with universities and researchers.

After conducting further interviews with the three stakeholders of interest, Stakeholder 2 come off as particularly interested. They are in the forefront of gathering and analysing climate data thus, perceived as pioneers in its field. They could have immediate use of the data and would also be interested in an initial pilot study. This leads to a “Yes” for all requirements for lead users, see Table 11 and section 2.2.2. Thus, continuing to Step 3, technical validation, this will be done with basis from Stakeholder 2 and Use case 2.

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5.3 Step 3 – Feasibility analysis In this step, a first feasibility analysis is carried out by interviewing technical managers as well as representatives from the selected stakeholder in step 2. Since stakeholder 2 was assessed to be most fit according to Table 11, this stakeholder was used in step 3. In this step the TELOS framework, covered in section 2.3.2 will be used to assess the feasibility of the project. Interviews were held with stakeholder 2 about their necessary requirements and then interviewing technical managers, innovation managers and product specialists at Telia around the achievability of the expressed requirements.

5.3.1 Technical Feasibility The technical feasibility analysis is structured in two segments. First, looking at the requirements needed from the base stations to allow a network of sensors. Secondly, the requirements expressed by Stakeholder 2. In Table 12, the technical requirements for mounting sensors on the base stations is presented together with an assessment of the technical feasibility made by technical managers and product specialists.

Table 12 Base station requirements

# Requirement Technical Feasibility 1 Power source OK 2 Network Connectivity OK 3 Available base stations located in cities and in rural areas OK

According to a technical manager (EM, 2017), the base stations are designed for simple mounting of hardware. And thus, mounting hardware should not be an issue,. This was also verified by another technical manager who expressed that mounting, power source or network connectivity should not be an issue (EM, 2017; GPS, 2017; CTS, 2017b). Looking at the actual sensors, three types of sensors where discussed with stakeholder 2: temperature, sun radiation and wind sensors, see Table 13. While collecting temperature from weather data should not be a challenge, collecting sun radiation and wind have some technical issues. Placement of sun radiation sensors must be in direct sun light, cannot be covered by shadows from antennas to give accurate data. Wind sensors often have moving parts which entails high risk of breaking. It is expensive to maintain and replace hardware on base stations, thus focus should be on robust sensors with non-movable parts with low maintenance. (EM, 2017) Furthermore, there should be no issue with the other requirements issued by Stakeholder 2, according to Chief of Technical sites (CTS, 2017), the only potential problem is requirement 7, having sensors in close proximity of energy production units, requires base stations to be located close to them which cannot be ensured to be possible.

Table 13 Technical requirements from stakeholder 2

# Requirement Technical Feasibility

1 Collect Temperature OK

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5.3.2 Economic Feasibility

The project is not core business to Telia, as a mobile network operator. Priority lies in fulfilling demands from the sales department. Funding is often prioritized for projects or changes directly connected to increasing sales of their existing products (EM, 2017; HoI, 2017). However, while a project for rolling out sensors on all Telia’s 15 000 is unlikely in this phase, a pilot project for proof of concept of one targeted use case, like Use Case 2, would be feasible to fund within the scope of Division X (HoIM, 2017). Furthermore, maintenance costs of the sensors is deemed to be possible in conjunction to maintenance work already in place and is thus not estimated to require any considerable extra costs according to a manager involved in the (CTS, 2017).

5.3.3 Legal Feasibility One manager (CTS, 2017b) involved with managing the base stations expressed that there could be an issue mounting additional objects on base stations located on rooftops. If too large, or obscure, it might not be allowed by the rental agreement signed with the owner of the real estate in question. Another senior at the firm however argued that the agreement with the real estate owners did not regulate this particular topic (EM, 2017)

5.3.4 Operational Feasibility The project requires Telia to execute three key activites: place the requested climate sensors on relevant locations, gather the data in real-time and distribute the data through an appropriate platform or protocol. According to one innovation manager (HoIM, 2017) the project is similar to other cases the firm have pursued. Knowledge and skills for pursuing the project is not estimated to be an issue. In addition, this is confirmed by a product specialist involved in project surrounding IoT (Internet of Things). Projects with sensors has previously been done within Telia as well as building platforms for distributing the data. In addition, Telia has in place a dialogue with a Sensor equipment manufacturer to produce sensors for industrial and commercial use (GPS, 2017).

5.3.5 Schedule Feasibility Stakeholder 2 expressed that a pilot project in one urban area where sun radiation and temperature is collected would be of interest if requirement 4,5 and 6 in Table 13. As an initial scope for this project, this was voiced as reasonable by an innovation manager at Telia. (HoIM, 2017)

2 Collect Sun radiation Maybe

3 Collect Wind Maybe 4 Speed rather than quality, approx. 1 min update frequency OK 5 In cities, spatial resolution of around 5 sensors per 50 000 habitants (a

smaller city) OK

6 In Urban areas, favour sensors located on rooftops on buildings OK 7 In Rural areas, favours sensors in close proximity of energy

production units

Maybe

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Looking at resources, most of the projects at division X are developed together with external partners. Due to the experimental nature, they are often outside Telia’s core business and require flexibility. If this project the climate data project is taken to the next, external resources are likely to be used ( HoI, 2017e). In summary, a pilot project should be deemed feasible according to the TELOS framework, although the feasibility of a full scale project is still uncertain, see Table 14.

Table 14 Summary of feasibility analysis

Aspect Feasibility Comment

Technical Yes A pilot project is deemed feasible with the requirements stated by stakeholder 2

Economic Yes/Maybe Cost and benefit difficult to estimate at this stage, but a pilot project is feasible.

Legal Yes/Maybe Different opinions with the company but should not be a challenge.

Operational Yes Similar projects have been carried out previously, knowledge and resources exists

Scheduling Yes/Maybe Feasible with external consultants. Might be difficult to allocate enough internal resources since project currently is far outside core business for Telia.

5.4 Step 4 – Build business case From the previous steps of the process, the Business model canvas is synthesized. The purpose of the business is to provide a holistic perspective of the validity of the business model. In sections 5.4.1, 0, 5.4.3 and 5.4.4 the building blocks within each of the four areas of business is constructed. This is primarily done by synthesizing the findings from the previous steps in the context and framework of the Business model canvas. In section 0 the full Business model canvas based on the construction is presented.

5.4.1 Infrastructure

As a first step in building the business model canvas, the business area of infrastructure is constructed. First, the identified partners from Step 2 and Step 3 are added to the building block Key partners and listed with corresponding type and motivation, see Table 15.

Table 15 Building block for Key partners in the Climate Data project

Key partners Type Motivation

Stakeholder 2 Strategic alliance and buyer-supplier

Optimization of business model and reducing risk and uncertainty

• Increase Telias level of resource utilization as well as provides Telia with pointers in product specification and expert knowledge within the field of climate data

• Reduce risk and uncertainty for Stakeholder 2 in their

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core operations

Sensor equipment manufacturer

Buyer-supplier relationship

Acquisition of particular resources and activities

Furthermore, the capabilities and resources as well as the required activities identified in Step 1 and Step 3 are synthesized in the building blocks Key activities and Key resources, see Table 16.

Table 16 Building blocks for Key activities and Key resources in the Climate Data project

Key activities Key resource

1. Positioning relevant climate sensors on base stations

2. Gathering climate data from in real-time 3. Distribute collected data through appropriate

platform, also in real-time

The key resources are both physical, intellectual as well as human.

1. The granular network sensors themselves are physical resources

2. The network infrastructure for collecting and delivering data is a physical resource

3. The data gathered from the sensors is an intellectual resource

4. The competence within Telia Company to structure this type of network and implement the system required to gather the data is a human resource

5.4.2 Offering The suggested value proposition from Step 1 is added to the building block Value proposition, see Table 17.

Table 17 Building block for Value proposition in the Climate Data project

Value proposition Climate data distributed through Telia’s network, both in cities and in rural areas, with much higher update frequency and higher spatial resolution than current actors.

5.4.3 Customers

The content for the customer area of business is mostly gathered from Step 2 as the main customer is the partners.

Table 18 Building block for Customer relationship in the Climate Data project

Customer relationships

Customer acquisition The customers are acquired through building partnerships where the partner has the ability to be involved early in the product development process and thereby make sure that

Customer retention Through initiating partnerships with partners who benefit highly of the use of the service as well as allowing them to be involved in the future of developing

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the product, it is more likely that the partners will return. As is presented with Stakeholder 2.

Upselling Continuous collaboration on development of product will allow further features in the future adding additional value to the user.

Furthermore, the insights from stakeholder 2 (HoPMA, 2017b) in Step 2 has provided basis for constructing the Channels building block, see Table 19.

Table 19 Building block for Channels in the Climate Data project

Channels

Channel types Channel phases

Own Direct

1. Awareness

The customers will be made aware through involvement in early stages of product development as proposed in Step 2.

2. Evaluation

Continuous collaboration with the partners will ensure feedback and evaluation on product development and quality of delivery.

3. Purchase

Purchases will be ongoing with value delivery following a subscription model. Amount is rather agreed with partner and corresponds value of delivery.

4. Delivery

Value will be delivered through platforms or relevant protocol (HoIM, 2017)

5. After sales

Further services in conjunction with the value proposition will be developed in collaboration with the partners.

Customer segments

The customer segments are pursued through the frameworks suggested in Step 2. These are initially corporations with a high level of benefit from the collected data and which have the ability to collaborate in the development process. Stakeholder 2, as stated in Step 2, fits these criteria.

Further customers are developed through continuingly building partnerships for mutual planning and development of offering to make sure that the implementation of further sensors meets the demanded requirements and provides valuable data.

5.4.4 Financial viability The financial viability of the business model is summarized conceptually with the purpose to allow for a ballpark assessment of revenue vs. costs from the running operations.

Table 20 Building blocks for Cost structure and Revenue streams in the Climate Data project

Cost structure Revenue streams

Primarily, costs of the project will be related to two parts of the operations (HoI, 2017b):

• Installing the sensors, implementing the

The revenue stream structure is suggested to be a subscription type from the ongoing delivery of value. (HoI, 2017b)

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sensor network infrastructure and expanding the network with demand

• Maintenance of the sensors and network infrastructure to make sure that the value delivery is of high quality

5.4.5 Business model canvas The building blocks presented in the business areas in sections 5.4.1, 0, 5.4.3 and 5.4.4 are synthesized into a complete business model canvas, see Figure 14.

Figure 14 The business model canvas of the Climate data project

Customer segmentsKey activities Customer relationships

Key resources

Key partners

• Stakeholder 2

• Meterology expert

• Sensor equipmentmanufacturer

Cost structure

• Installing sensors

• Expanding network on demand

• Maintenance

Revenue streams

• Subscription model

Channels

Value proposition

Climate data distributed throughTelia’s network, both in cities and in rural areas, with much higherupdate frequency and higher spatial resolution than currentactors.

• Climate sensor positioning

• Real-time data gathering

• Data distribution

• Sensors• Infrastructure• Data• Competence

• Partnerships• Early

involvement• Continuous

collaboration

• Data deliveredthrough ownchannels

• Continuouscollaborationensures evaluation

• Partners builtfrom evaluationof use cases

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6 DISCUSSION AND ANALYSIS In this section, the findings in the previous chapter are analysed critically and a discussion of the results are presented . In this chapter we will first discuss the empirical results for each step of the framework, we will thereafter continue to discuss the impact of the framework as a whole. Finally, some learnings that where found during the study and final conclusions We have investigated if climate data can be a new revenue stream for Telia through utilizing existing resources together new partnerships. This has been done by following a framework derived in theory regarding RBV, innovation processes, partnerships as well as business model generation.

6.1 Step 1 – Identify resources The goal of step 1 was to identify valuable resources and capabilities within the firm with the potential to be utilized in a new context. The result of Step 1 was that one valuable resource within Telia was identified. The base station network within Telia was identified as a potential resource candidate and it was suggested that these could potentially be utilized in a new area as a granular network of sensors providing real-time climate data, as seen in The identified potentially valuable resource and its potential new area of utilization is summarized in Table 7 . Table 7. The potential benefits from this this was identified in Workshop 1. Furthermore, the result from the assessment of the identified resources, capabilities and benefits with the VRIO-framework, indicated that the initially proposed resource would benefit from innovation. With added support from additional frameworks there was also indication that the new area of utilization would be valuable and could enable an enhanced competitive advantage albeit temporary, as seen in Table 10. The first phase of Step 1 proved, as expected and suggested by theory, difficult to execute. While the goal of the step was successfully met, it is hard to estimate whether this can be easily repeated. This is primarily due to the basis for finding potential resource candidates which is done through a creative process. The second phase of Step 1 successfully executed returned useful pointers as to the potential value of the resource in the new context. The initial ideas suggested in phase one could thereby earn at least an indicative validation. And provided support for progress into Step 2.

6.2 Step 2 – Build use case The goal of step 2 was to be able to identify the most interesting use cases together with the most suitable lead users with ability of engaging in an early stage partnership during the development phase.

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At the end of step 2, stakeholder 2, a company involved with energy trading was identified fulfilling all requirements for a lead user with benefit of use case 2, see Table 11 and Figure 13. However, looking at Figure 11 we can see that stakeholder 2 where first perceived to be medium in both influence and cooperation, essentially off less interest than both stakeholder 1,4 and 5. However, this initial classification was done in workshops with managers and employees at Division X, before any external verification was done with the identified stakeholders. In that sense, it could be argued that arranging stakeholders after level of influence and cooperation functioned will in this case. The analysis done in step 2 to sort use cases and stakeholders has been done in a qualitative way, through workshops within Telia and interviews with relevant personnel at the concerned stakeholders. Thus, the conclusions drawn rely greatly on the industry knowledge and competence by those interviewed. Although interviews have been focused on capture those with the most knowledge, this still impose a risk that some valuable use cases and stakeholders have been overlooked.

6.3 Step 3 – Feasibility analysis In step 3, with the stakeholder qualified as a lead user it was expected that clear requirements could be formulated. Then, effectively validated against technical personnel in a qualitative feasibility analysis based on the TELOS framework. This would then be able to function as a way for managers to assess the probability of success of the project. This was based in answers to the main questions from the TELOS framework:

• If the customer is ready and if it is possible to provide the right features for the right price?

The result shows that stakeholder 2 could specify technical requirements which could then be validated against relevant personnel at Telia, see Table 13. Interviewing stakeholder 2, most focus, in terms of requirements laid in the technical aspects. Interviews within Telia showed however, some concern regarding the collection of sun radiation and wind. Although not implied to be impossible, further investigation was expressed to be needed within the area.

• Does the company have the sufficient technology and resources to meet the customer requirements?

Interviewing with managers within Telia, resulted in that a pilot project with a small number of sensors collecting temperature, and potentially sun radiation and wind in one selected urban environment was of reach. Although, further investigation was needed in order to decide the feasibility of a full scale climate data network. Previous theory about the TELOS framework stated that the technical feasibility often is not of issue. In terms of this case, this seemed to be accurate as well. It proved to be difficult to get any definitive answers on every aspect of the feasibility study, but it can be argued that the

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information received was enough to make a judgement of taking the case to the next step by managers. As stated, support for an initial pilot project was expressed.

6.4 Step 4 – Build business case The goal of step 4 was to synthesize the findings from the previous steps in a Business model canvas and provide a holistic perspective on the business model that would be enabled with the innovative utilization of the valuable resources and capabilities. The purpose is to provide visualized basis for decision to decide whether the project should be initiated or not. The result was a business model canvas illustrating the new utilization of the resource in combination with the suggested partnership, and validated. As a basis for decision, it is hard to estimate how promising the suggested business model is objectively.

6.5 A successful framework? Through following the framework, the project gave successful output in the form of a defined business opportunity by the business model canvas. The stakeholder expressed interest in what was suggested and a pilot project was also deemed feasible by managers within Telia. However, this doesn’t necessarily mean that the framework itself is a success. At least two aspects can be considered when suggesting level of success of the framework. First of all, the risks suggested in theory in section 2.2.1, might not have been thoroughly taken into account and thus whether the framework appropriately meets these risks is not measured. In section 2.2.1, 8 major risk drivers for open innovation projects are presented to consider. A successful framework or process would suggest appropriate methods of risk minimization, mitigation or avoidance. When it comes to analysing the efficiency of a framework on an ongoing case, it is difficult to ascertain to what degree the suggested framework has met this demand. As the case studied will likely be under influence of some of the mentioned risks but not others, the study will miss assessing the quality of the framework in the context of mitigating risks which the case did not suffer. It is also hard to assess to what level the success of the case can be attributed to the framework. As the first step of the framework is partially based on a creative process that is ongoing within the organization. It is difficult to ascertain the quality of the input from creative processes and thus difficult to assess level of generalizability. Similarly, input for evaluation in the second step of the process was gathered from workshops executed in accordance with It could also be that the case presented in this thesis is simply the exception that proves the rule. This means that while theoretically, the framework was could be adapted in further use cases, the way it is used in this context can simply not be repeated. That would implicate that the success of this case is due to casual ambiguity.

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6.5.1 Generalizability and validity According to (Dubois and Gadde, 2002), systematic combining does not have an emphasis on verification and checking accuracy of the data. Instead having several sources can potentially reveal new dimensions of a research problem to the researcher. Role of framework Dubois and Gadde (2002) argues that a tight framework could make the researcher blind of important features of the case or misinterpret information. However, too lose framework could lead to overload of data and arbitrary data collection Of the two alternatives, Dubois and Gadde (2002) argues that a tight and evolving framework is preferred. The tightness reflects that well-articulated preconceptions are in place, and evolving reflects that the researcher should evolve and change the framework and view of theory as empirical observations are made. In this study a tight framework was developed where each step was defined by characteristics of a certain theory. Since the FFE phase of innovation is unstructured to begin with, a tight framework helped in sorting and prioritizing what information was interesting and what should be of less focus. For example, a business model canvas of all 15 use cases in section 5.2 would not have been feasible for the scope of this project. Instead, we could qualify stakeholders and use cases, leaning on theory on RBV, partnerships and innovation processes. Thus allowing an overview of which cases entailed the highest potential. Role of case In systematic combining, the case should be evolving during the study and viewed as a tool as well as a product. A tool, in terms of that it is used to test the theory on through the framework. A product as the result of how it has been affected by the study. (Dubois and Gadde, 2002) Aligned with Dubois and Gadde (2002) view that the case is both the tool and end product. The climate project was introduced as an idea, then shaped and developed by the framework where each step was an interaction between empirics and literature. Finally, a clearly defined business case has emerged as the product. Role of theory According to Strauss and Corbin (1990), literature help propose theoretical frameworks as well as define variables and relationships between them. However, Dubois and Gadde (2002) argues that literature in systematic combining is of less importance. Instead, the researcher should not be constrained by too much theory, other variables and relationships are more important. In this project, relying on theoretical concepts when approach each step of the process was helpful rather than imposing a feeling of being constrained. Having that said, some opportunities might be missed by relying too heavily on the theoretical concepts.

6.5.2 Learnings from an innovation project at a large telecom company

During the course of the climate data project, a few interesting learnings, or challenges when operating new innovation projects at a large telecom company. First of all, while the project

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seemed to be far outside the company’s core business, specific knowledge and skills needed always existed somewhere in the company. The challenge was to find it. Even though there exists a wide used internal network, the most effective way to find specific competences and knowledge was to ask somebody, who in turn communicated the request further until the right person was found. It is evident that this is an issue that large company struggle with and likely needs to be sorted if the aim is to drive innovation projects effectively. Secondly, people tend to have very busy schedules, focusing on activities related to core business. Thus, little time is left for sharing knowledge with project groups engaged in experimental projects, even though expert insights often is key and can save a lot of time.

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7 CONCLUSION AND RECOMMENDATIONS The conclusions are based from the analysis with the intention to answer the formulation of questions that is presented in Chapter 1.

7.1 Conclusion The purpose of this thesis is to investigate if climate data can be a new revenue stream for Telia through utilizing existing resources together with new partnerships. By addressing this case, the aim is to show how large companies can work with finding and evaluating new business opportunities when searching for new revenue streams. In this study we have suggested that climate data could be a new revenue stream for Telia and that one partner, stakeholder 2 can be used for partnership in a first pilot project to further validate cost and benefits. With the suggested framework used to find and assess this business opportunity, this study shows how a large company can work to find and evaluate new business opportunities in a more structured manner. This was investigated by answering the main research question: How can a large telecom company catalyze innovation with existing resources and new partnerships? To answer all elements of the main research question, three sub-research questions where formulated. We will below present our findings of these questions which will then collectively answer the main research question. SQ1: How can existing resources be assessed for new areas of utilisation? In this study, findings from literature suggested that existing resources could be identified by the VRIO framework. In the case study, collecting climate data from base stations where assessed as a resource in two steps. First, using the VRIO to assess the value of base stations, secondly to assess the value of utilizing the base station as a climate data network. Although the value was not judged valuable by all aspects of VRIO, it showed to be useful enough at this stage to provide material to formulate a product offering to assess further with stakeholders and use cases. Thus, concluding that VRIO can function as a tool for assessing resources for new areas of utilization. However, it should be noted that the framework was only tested on this particular resource and it could have different outcome in different cases. SQ2: How can new partnerships be found? Two workshops were internally held where potential partnerships and potential use cases where ideated. Based on literature regarding how valuable partnerships and use cases can be identified and categorized. Partnerships where categorized after level of influence on its market and required level of cooperation. Use cases where categorized after level of scalability and level of benefit.

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After five stakeholders were found to fit the three use cases with highest score in level of scalability and benefit. These where interviewed with questions aimed to qualify them against the characteristics of lead users. One stood out and could be selected to continue discussions with around details of a pilot project which was aligned with what could be offered by Telia at an early stage. In summary, the partnerships were found by first coming up with potential partners and use cases internally. Then, after sorting and qualifying them against different parameters, the most interesting ones where investigated further by external interviews with relevant personnel from each of the firms. This showed to be an effective process founding a potential partnership early in the innovation process. It could be argued that either all the potential use cases and partnerships needs to be analyzed thoroughly to determine exactly which one posed the greatest benefit. However, this was not the scope of the question, which was to find new partnerships which can be used in catalyzing innovation, which we argue that we found.

MRQ: How can a large telecom company catalyze innovation with existing resources and new partnerships?

Combining the findings from the two sub questions, we can conclude that a large telecom company can catalyze innovation with existing resources and new partnerships by:

• Using frameworks such as VRIO to find and assess value of the identified resources • Finding use cases with high potential scalability and benefits. • Finding partners characterized by having early needs of the innovation, expect high

level of benefits, involved in own development of innovations and perceived as being innovative and pioneering.

• Assessing feasibility early from the potential partner’s requirements. • Using a framework such as business model canvas to summarize and visualize the

business opportunity.

7.1 Contribution and future work In this study we wanted to gain further understanding in how an abstract idea could be transformed into a business case. One of the main contributions this report has is to give a new perspective on how old and new theory and frameworks can be combined and used in an empirical case study to effectively navigate through the often unstructured and uncertain front end of innovation. We show that with combining an exploratory approach, allowing for initial creativity and then in an early stage involving early potential partners is an effective approach. For future work, we propose that other case studies should be carried out with a similar approach and framework, but in other businesses and industries. This is needed in order to be able to thoroughly analyse if the framework followed in this report is effective or if other aspects are of greater importance.

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A second topic of interest would be a follow up on the case investigated in this study, which could be done by two angles. First, it would be of interest to investigate to which degree the business case suggested in this study is able to be carried through to the next phase. Also, how long it would take and what effects the work done in the early stages have had. Secondly, by conducting more case at Telia Division X with the our approach and compare outcomes, which would allow for more deep insights in challenges and opportunities with the suggested framework. In extension, it can contribute to the front end of innovation research where much is still to be uncovered.

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9 APPENDIX APPENDIXA:TableofinterviewsDate Interview

ref # Interviewee reference

Title Company Department Relation to study Method Type

2017-01-27 a HoI, 2017 Head of Innovation

Telia Company

- Ideation and project initiation

Face-to-face

Unstructured

2017-02-06 b HoI, 2017 Head of Innovation

Telia Company

. Empirical support for suggested framework

Face-to-face

Semi--structured

2017-02-09 c HoI, 2017 Head of Innovation

Telia Company

. Empirical support for suggested framework

Face-to-face

Semi--structured

2017-02-17 a ID, 2017 Investment Director

Telia Company

Division X Empirical support for suggested framework

Face-to-face

Semi--structured

2017-02-28 a Mc, 2017 Meterology consultant

SMHI Various Provide potential partners point of view

Face-to-face

Semi--structured

2017-03-06 a EM, 2017 Environmental Manager

Telia Comapny

Technology Input for feasibility analysis

Face-to-face

Semi--structured

2017-03-09 a VPSD, 2017 VP Strategy & Development

Stakeholder 4 - Provide potential partners point of view

Face-to-face

Semi--structured

2017-03-23 a HoIM, 2017 Head of Innovation Management

Telia Company

Purple+ Benchmark against other innovation project within Telia

Skype Semi--structured

2017-04-20 e HoI, 2017 Head of Innovation

Telia Company

- Input for technical feasibility and use case search

Face-to-face

Unstructured

2017-04-21 b HoI, 2017 Head of Innovation Management

Telia Company

Purple+ Input for use case search

Face-to-face

Semi--structured

2017-04-25 a HoD, 2017 Head of Data analytics

Telia Company

Division X Input for use case search and value of analytics

Face-to-face

Semi--structured

2017-04-25 a VPSBI, 2017 VP Strategy & Business Innovation

Stakeholder 3 - Provide potential partners point of view

Face-to-face

Semi--structured

2017-05-11 a HoPMA, 2017 Head of Power Market Analysis

Stakeholder 2 Energy Trading

Provide potential partners point of view


2017-05-12 a HoDe, 2017 Head of Department

Stakeholder 5 Miljöförvaltning


Face-to-face

Semi--structured

2017-05-12 a GPS, 2017 Global Product Specialist

Telia Company

Division X Input for feasibility analysis

Face-to-face

Semi--structured

2017-05-12 a PM, 2017 Product Manager

Stakeholder 1 Provide potential partners point of view


2017-05-16 a CTS, 2017 Chief of Technical Sites

Telia Company

Technology Input for feasibility analysis


2017-05-17 b HoPMA, 2017 Head of Power Market Analysis

Stakeholder 2 Energy Trading



65

APPENDIXB:TableofworkshopsDate Reference Present Relation to study Type

2017-03-07 Workshop 1, 2017 Innovation managers within Telia, Division X

Ideation and assessment Focus group

2017-03-07 Workshop 2, 2017 Innovation managers within Telia, Division X

Ideation and assessment Focus group

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