Intensive Service Activities in the Software Business ... describing the software cluster from business models and value network perspective. Phase two consists of ...... Accounts. R&D. Engineering. Finance. Personnel. Production. Distributors.
Risto Rajala, Mika Westerlund, Arto Rajala and Seppo Leminen
Business Models and Value Nets as the Context of KnowledgeIntensive Service Activities in the Software Business
LTT-TUTKIMUS OY • LTT RESEARCH LTD Pohjoinen Rautatiekatu 21 B • FIN -00100 HELSINKI, Finland • tel: +358-9-431 38570 • fax: +358-9-408 417 • www.ltt-tutkimus.fi ISBN 951-774-114-6 • ISSN 1456-4882 • HELSINKI 2004 SERIES B 170
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Executive Summary In this study, we address the innovation systems within the Finnish software cluster by reviewing first the literature of both business models and value nets in the context of software business. We then classify the basic types of software businesses according to their business models and describe concepts for modeling and analyzing their valuecreating networks. Furthermore, we make an attempt to depict the role of knowledge intensive service activities in association with different business models and value nets in the software industry. This study is the first phase of a larger project focusing on the innovation activity and knowledge intensive services in the software industry. The whole project is divided into three phases. This report is conducted on the basis of the first phase and strives for describing the software cluster from business models and value network perspective. Phase two consists of a description and an analysis of innovation activity and innovation processes in the SW cluster and the role of knowledge-intensive services in it. Phase three comprises a synthesis to improve innovations and innovation processes for the SW cluster. This phase of study describes the concepts of business models and value net(work)s as the means of creating and delivering value in different innovation systems within the software cluster. The aim of this phase is to establish the basis on which the knowledge-intensive services, service providers and users, service types and roles can be analyzed. We illustrate software business models and value nets through two cases. Both of them support our preliminary framework. Based on the studies reviewed for this project, it is clear that in the software industry there is a multitude of business models with a great variety of cooperative forms of actors providing or using different services. We point out that the partnerships identified in the product development phases are not the only value nets of innovation activity. In addition to product innovations, there are number of other forms of innovation, e.g. process innovations and organizational innovations. Cooperation in the production and use of knowledge-intensive services influence organizational innovations, which emerge as new forms of creating and delivering value within the value nets in the software industry.
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Tiivistelmä Tässä tutkimuksessa perehdytään ohjelmistoliiketoiminnan innovaatiojärjestelmiin ja analysoidaan niissä esiintyviä tietämysintensiivisiä palveluita ohjelmistoyritysten liiketoimintamallien ja arvoverkostojen näkökulmasta. Kuvailemme ja jäsennämme aluksi ohjelmistoyritysten liiketoimintamalleja ja arvoverkostoja aikaisempien tutkimusten ja kirjallisuuden perusteella. Luokittelemme tässä yhteydessä joitakin liiketoimintamallien perustyyppejä ja kuvailemme niiden arvoverkostoja. Lisäksi kuvaamme eri liiketoimintamalleille tyypillisiä tietämysintensiivisiä palveluita ja niiden roolia osana arvoverkostojen toimintaa. Tämä tutkimus on osa laajempaa projektia, jossa tutkitaan ohjelmistoyritysten innovaatiotoimintaa ja siinä esiintyviä tietämysintensiivisiä palveluita. Koko tutkimus on jaettu kolmeen eri vaiheeseen, josta tämä tutkimus muodostaa ensimmäisen osan. Tutkimuksen ensimmäisen vaiheen tarkoituksena on kuvata ohjelmistoliiketoimintaa liiketoimintamallien ja arvoverkostojen näkökulmasta. Toinen vaihe käsittää ohjelmistoklusterin innovaatiotoiminnan kuvauksen ja analyysin tietämysintensiivisten palveluiden roolin sekä palvelujen (tuottamisen ja) käytön kannalta. Kolmas vaihe sisältää yhteenvedon innovaatioprosessien kehittämiseksi. Tutkimuksen tämä vaihe kuvaa liiketoimintamallien ja arvoverkkojen olemusta arvon tuottamisen ja toimittamisen välineenä ohjelmistoklusterin innovaatiojärjestelmissä. Tämän vaiheen tarkoituksena on luoda perustaa tietämysintensiivisten palvelujen, palveluntarjoajien ja –käyttäjien, palvelutyyppien ja roolien tarkemmalle kuvaukselle ja analyysille. Havainnollistimme ohjelmistoalan liiketoimintamalleja ja arvoverkkoja kahden tapaustutkimuksen avulla. Molemmat niistä tukivat esittämäämme alustavaa viitekehystä. Tässä tutkimuksessa tehdyn kirjallisuuskatsauksen perusteella ohjelmistoalalla on havaittavissa lukuisia erilaisia liiketoimintamalleja ja yhteistoiminnan muotoja palvelujen käyttäjien ja tarjoajien välillä. Osoitamme tässä tutkimuksessa että innovaatiotoiminta ei rajoitu tuotekehitysprosesseihin. Tuoteinnovaatioiden lisäksi tapahtuu prosesseihin ja organisaatiomuotoihin liittyviä innovaatioita. Yhteistoiminta tietämysintensiivisten palveluiden tuottamisessa ja käyttämisessä edistää uusia arvon luomiseen ja jakeluun liittyviä organisaatioinnovaatioita ohjelmistotoimialalla.
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Table of Contents Business Models and Value Nets as the Context of Knowledge-Intensive Service Activities in the Software Business...................................................................................1 1. Introduction....................................................................................................................8 1.1 Background and purpose of study ..........................................................................9 Business Model Perspective on KISA ....................................................................11 Value Net(work)s as the Context for KISA .............................................................11 1.2 Outline of Study.....................................................................................................12 1.3 Objectives of Study and Research Questions......................................................13 The first phase of study (Phase I) ...........................................................................13 Next phases of study (Phases II and III) .................................................................13 1.4 Definition of key terms and concepts....................................................................14 1.5 Research design and methodology ......................................................................15 1.6 Scope and limitations of study ..............................................................................15 1.7 Framework of Study ..............................................................................................16 1.8 Characteristics of the Finnish software cluster.....................................................17 2. Theoretical Background ..............................................................................................19 2.1 The Business Model Context ................................................................................19 2.2 Types and Characteristics of Business Models....................................................20 2.3 Value Production and Business Networks ...........................................................24 The Issue of Value ..................................................................................................25 From Value Chain to Value Systems......................................................................26 What are Networks?................................................................................................27 2.4 Value System and Different Types of Business Nets...........................................30 2.5 Innovation Activity in Different Types of Value Nets in Software Sector .............32 3. Knowledge-Intensive Service Activities in Innovation Net(work)s .............................35 Definition of KIBS ....................................................................................................35 Innovation Networks................................................................................................36 4. Examples of Business Models and Value Nets in the Innovation Systems of the Software Cluster..............................................................................................................43 4.1 Business Models and Value Nets in the Software Service Business ..................43 4.2 Case Examples on System Solution and Software Product Businesses ............45 Akumiitti ...................................................................................................................45 BasWare Group.......................................................................................................49 Conclusion of Cases ...............................................................................................53 5. Summary and Conclusions.........................................................................................55
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6. Further Research........................................................................................................56 7. References ..................................................................................................................57
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List of Figures Figure 1 KISA-LTT as a part of KISA SWC and the KISA Finland and OECD................8 Figure 2 Knowledge-intensive service activities as the catalyst of innovation in the networked business model context.........................................................................10 Figure 3 The Focus of Study in its Three Phases ..........................................................13 Figure 4 Framework of Study..........................................................................................16 Figure 5 Intercompany network relations between North Ostrobothnian software companies – sample of 19 companies. (Pasanen 1999 ref. Alajoutsijärvi et al. 2000) .......................................................................................................................18 Figure 6 The Business Model Context (extended from Linder 2000; Äijö 2001; Pigneur 2002) .......................................................................................................................19 Figure 7 A Business Model Ontology (Pigneur 2002) ....................................................20 Figure 8 Generic Examples of Software Business Models [Adapted from Rajala et al. (2001)] .....................................................................................................................22 Figure 9 An Illustration of Business Models According to Customer Relationships and Standardization of Product/Service Offering ..........................................................24 Figure 10. Value Production Spectrum (Möller and Törrönen, 2003) ............................25 Figure 11. Value Chain and Value Star (Wickström et al., 1994, 112) ..........................26 Figure 12. Company as a Knowledge System for the Creation of Value (Wickström et al., 1994)..................................................................................................................27 Figure 13. An illustration of internal and external networks (web of actors) (Bovet and Martha 2000; Achrol and Kotler 1999)....................................................................28 Figure 14. Actors, Resources, and Activities (ARA-model) (Håkansson and Snehota, 1995) .......................................................................................................................29 Figure 15. Network configuration and the role of software produces and KISA provider .................................................................................................................................30 Figure 16 Value System Characteristics (Möller, Rajala & Svahn 2002) ......................31 Figure 17. Conceptual Tool for Examining Innovation Activity in Different Value Nets .33 Figure 18 KISA clients and suppliers (Forssen et al. 2003) ...........................................36 Figure 19 Classification of KIBS and KISAs ...................................................................36 Figure 20 Potential innovation partners and their contributions (Adapted from Ritter and Gemünden, 2002) ...................................................................................................37 Figure 21 The Importance of KIBS Providers for Software Industry (n=34 of 100, response rate 34%, SPIN evaluation by LTT 2003, Forthcoming) ........................38 Figure 22 Cooperative Partners (n=34 of 100, response rate 34%, SPIN evaluation by LTT 2003, Forthcoming)..........................................................................................39 Figure 23 Pattern of services innovation (den Hertog 2000) .........................................40 Figure 24 Development Areas of Business Services (n=34 of 100, response rate 34%, SPIN evaluation by LTT 2003, Forthcoming) .........................................................42
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Figure 25 Actors in a Software Subscription Business Network (Adapted from Messerschmitt 2000)...............................................................................................44 Figure 26 The ASP value chain (Wainewright 2001) .....................................................45 Figure 27 Akumiitti's distribution and technology partners.............................................46 Figure 28 Akumiitti's partners .........................................................................................47 Figure 29 Emphasis of partners in Akumiitti’s ESC and COSMO Business Models .....48 Figure 30 Decentralized Hub and Node Structure .........................................................48 Figure 31 BasWare’s distribution partners ....................................................................50 Figure 32 BasWare’s distribution and R&D networks ....................................................51 Figure 33 Emphasis of partners in BasWare’s Business models ..................................52 Figure 34 Centralized Hub and Node Structure .............................................................52 Figure 35 Distributed Multiplex Structure .......................................................................52 Figure 36 Cases Positioned in the Study Framework....................................................53
List of Tables Table 1 Characteristics of Generic Business Models (Adapted from Rajala et al. 2001) .................................................................................................................................23 Table 2 Preliminary Classification of Knowledge-intensive Business Services in the Software Industry ....................................................................................................41
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1. Introduction This study is part of the Finnish KISA-SWC (Knowledge-Intensive Service Activities in the Software Cluster). It belongs to a larger KISA Finland project, which is a part of an international KISA OECD project. The KISA project is an initiative of the OECD Working Party on Innovation and Technology Policy, addressing the following three main issues: (OECD, 2003) −
The major lines of provision and use of knowledge-intensive service activities (KISA) in selected industries.
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How firms/organizations use and integrate different sources of KIS A (internal and external) to build their innovation capability?
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How provision of KISA (public or private) can best build innovation capability in the selected industries?
Knowledge-Intensive service activities are studied in four industries as part of the KISA Finland project. These are: entertainment, health care, forest and software industries. The project of the software industry, called Knowledge-Intensive Service Activities in Software Cluster (KISA-SWC), will take care of the tasks allocated to Finland in the KISA OECD project for the part of the Finnish software cluster (See Figure 1).
KISA OECD KISA Finland Entertainment Forest industry Health care KISA SWC KISA INTO
KISA LTT
Figure 1 KISA-LTT as a part of KISA SWC and the KISA Finland and OECD
The objective of the KISA-SWC project is to study software cluster and its innovation processes and the role of knowledge-intensive services in the innovation processes. The KISA-SWC project started at the beginning of 2003 and finishes at the end of 2003.
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KISA-SWC consists of two subprojects: KISA-INTO (Finnish Knowledge-Intensive Service Activities – Innovative Technologies and Organizations) managed by SoberIT 1 and KISA-LTT (Finnish Knowledge-Intensive Service Activities- Business Models and Networks) managed by LTT Research Ltd. SoberIT also acts as a main coordinator of KISA-SWC project. LTT Research Ltd (LTT) is a research-oriented subsidiary of the Helsinki School of Economics (HSE). Our mission is to generate new information and insights for the development of clients' operations. Our strengths include marketing and international business, electronic commerce, financing, and competence management. LTT leans strongly on the research conducted at HSE and its extensive international co-operation network.
1.1 Background and purpose of study Recent research argues that knowledge-intensive services (KISA), e.g. business consulting, do have a significant influence on the industrial competitiveness and innovation in a number of different ways (Hauknes, 1999; Gadrey and Gallouj, 2002 in Kuusisto 2003): • • •
They act as bridging institutions in distributed knowledge creation system, KISAs can be facilitators, carriers or sources of innovation through co-production of capabilities, and; KISAs have a role in transforming individual firms and nets into learning organizations Service innovations in themselves play an increasingly important role in the knowledge-intensive economy
This project depicts the context where knowledge-intensive services exist in the software business. Our working hypotheses include the basic assumption that different services are emphasized in different business models. This aspect is addressed in this study by describing generic types of software business models and studying the services that are important in association with them. Furthermore, the knowledgeintensity of services is assumed to affect the degree of collaboration between the produces and the user of services. This can be thought to serve as one starting point. The KISA-LTT project will deliver three reports, of which this is the first one addressing the business models and value nets of software businesses as the context of knowledge-intensive service activities. The second report describes the innovation processes and services from the strategic network perspective and the third one proposes a synthesis of improving innovation activity in the SW cluster. Knowledge-intensive service activities have been studied in relation to innovation activity focused on developing technology solutions to be commercialized into products or services. In this study, this kind of an innovation approach is seen as just one form of innovation activity. In addition to this “technology push” approach, other innovation approaches in the Finnish market of software products and services can be seen.
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Software Business research group at the Software Business and Engineering Laboratory. SoberIT is a unit of the Department of Computer Science at Helsinki University of Technology
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These other forms of innovation can be based, for instance, on “market pull” approaches, i.e. for new ways of meeting emerging needs in the market. Organizational innovations appear as new forms of creating and delivering value within different value nets. Innovations based on cooperation forms and partnership approaches are of great importance in establishing new ways of successful bundling and delivery of products and services to customers. Furthermore, there are organizational innovations related to networked collaboration structures aimed at improving the competitive edge and cooperation of business actors. Hence, we are interested in taking a look at the forms and structures of both value creation and value realization in the software business. In this study, we will review the business models and value nets in the (Finnish) software cluster to improve understanding of the different forms of innovation in the software industry, and to obtain a richer view of the context of knowledge-intensive services in various innovation systems. The purpose of studying knowledge-intensive services in the software cluster in association with business models of software companies is to understand the role of services existing in a certain business context. According to our current understanding, different shapes of innovation activity have strong linkages with different business models, which require different services. Thus, we believe that understanding of the role and nature of knowledge-intensive services related to innovation activity is improved by understanding the context of business models, in which the services are produced and used.
Knowledge Intensive Business Services
Business Models
C C C C SS CC C C S SS S C C CC S S S S FC S FC C S C C C C S C S C S S SS C C C SS SS C C C CC
Innovation
Research and Development Networks S S SS C C S SSS S CC S SSSSSS C
FC C C CC
S S
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Strategic Supply and Service Networks
SSSSSSSSSSS S S
SSS
S S S S SS
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Innovation Services and Networks
Figure 2 Knowledge-intensive service activities as the catalyst of innovation in the networked business model context
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On the other hand, the characteristics of services, and knowledge-intensive services in particular, prevent business actors from trading them without cooperation between the parties engaged in the production and use of the services. Hence, services differ from products or other commodities that can in some occurrences be traded without cooperation between vendors and buyers. Furthermore, due to the inherent nature of services, the vendors and buyers of knowledge-intensive services need to cooperate with each other. This is the breeding ground of value nets. In this study, we introduce concepts for studying the value nets of companies to understand the characteristics and structure of cooperation in association with different forms of innovation activity. Business Model Perspective on KISA Today, when many of the companies with “new” and “innovative” business models continue to struggle to next phases in their life-cycles and many of them have failed to grow into profitable businesses it is worth taking a closer look at the viable business models from the perspective of utilizing KISA in the software business. In the fiercely competitive and fluid environment of international software business the companies and their partners need tools that can be used to analyze their situation and possible future strategies including partnering and cooperation in their business networks. Previous research on software business has focused, for instance on software product development, finance and publication cycles, or, on the industry as a whole. This study addresses the concept of business model, and decomposes it into essential elements. Although the term business model is commonly used in both business articles and academic literature dealing with e-commerce and information economy, the definitions used are often either vague or nonexistent (Timmers, 1998; Amit & Zott, 2000). The development towards integrated business networks build up a multi-faceted market for software product and service innovations aimed at enabling electronic business-to-businesses integration. On the other hand, the ways the networked economy operates will shift the mindset from streamlining internal processes of value chains into connecting networked processes across organizational boundaries. This shift incorporates the challenges of both managing the networked processes and capturing new opportunities of networking externalities in various value networks. In addition to developing product strategies to respond to these needs, software product companies (or software vendors) are facing the need to consider new ways to perform their service operations, and manage distribution channel alternatives and revenue logics in their attempt to capturing opportunities that their product propositions potentially provide. Hence, in this study we explore the business models of software businesses participating in business networks. Value Net(work)s as the Context for KISA Recently, as Möller and Svahn (2003) have noted, networks have attained a lot of interest both in academic journals and business magazines. Reason for this is that the way in which economic value is created in a society is fundamentally changing. Increased importance of knowledge, technological complexity, global competition and the availability of digital information technology are driving this change (Castells, 1996). To cope with these challenges companies and other social actors are establishing complex networks consisting of both knowledge and technological bonds.
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The emerging networks of firms are replacing traditional markets structures and vertically integrated companies. Networks seem to adapt well to knowledge-rich environments because of their superior information-processing capacity and flexible governance structures compared to markets and hierarchical organizations (Achrol and Kotler, 1999; Snow et al., 1992). Empowered by the new digital media, network organizations are expected to take the leading role in the creation of economic and social innovations (Castells, 1996; Grabher, 1993; Thompson et al., 1994). Proactive creation and management of business networks and strategic navigation in the network environment form a major challenge to Finnish software providers as well. According to recent studies, software companies are extensively using networks or even other collaborative forms in their business operations (e.g. Leminen, 1999). The role of collaborative forms is claimed to be especially fruitful in innovation context (Tidd et al., 2001; Miettinen et al., 1999). Many companies are not even familiar with the concept of organizational innovation and thus the companies do not invest in that. However, the roles of organizational and process innovations are essential, especially, to the innovativeness of the growing service software segment. Therefore, with reference to these earlier studies, there exists a need to study organizational and process innovations in addition to product innovations. The development and maintenance of value net(work)s incorporate both managerial and system challenges related to knowledge-intensive service activities (KISA). Managers and researchers are likely to face a challenge of identifying what type of organizational arrangements, management capabilities, and managerial systems are needed to improve innovations and innovation processes in the software cluster. Finally, managers face challenges of managing different types of business models and collaborative forms such as strategic partnerships and value networks to effectively support innovations in different market and company life cycle contexts.
1.2 Outline of Study This study is the first phase of a larger project focusing on the innovation activity and knowledge-intensive services in the software industry. The whole project is divided into three phases, of which this study forms the first one. Phase one strives for describing the software cluster from business models and value nets perspective. Phase two consists of a description and analysis of innovation activity and innovation processes in the SW cluster and the role of knowledge-intensive services in it. Phase three comprises a synthesis to improve innovations and innovation processes for the SW cluster. Based on the framework of study presented in Figure 4, the focus of the three phases of this study is illustrated in Figure 3 below.
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Value Nets
Cases
Value Nets
Services
Services
Synthesis
Cases
Business Models
Analysis
Business Models
Survey
Services
Literature
Value Nets
Phase III
Literature
Business Models
Phase II
Literature
Phase I
= Focus of Innovation activity
Figure 3 The Focus of Study in its Three Phases
As illustrated in Figure 3, the study is divided into three phases. The first phase focuses on the business models and value nets in the software industry. The second phase clarifies the services essential to different business models and their roles in different value nets. Finally, the third phase presents a synthesis on the use of knowledgeintensive services to improve innovation activity within different business models and value nets.
1.3 Objectives of Study and Research Questions The first phase of study (Phase I) This study, the first deliverable of the KISA-LTT project, focuses on the business models, cooperative forms and value nets that currently exist in the software cluster and provides theoretical tools and concepts utilized in the next two phases. The research question of this part of the study is posed as follows: RQ 1: What kind of business models, cooperative forms and value nets currently exist in software industry? RQ 1i:
What kind of theoretical perspectives and conceptual models can be used for identifying business models and value nets?
RQ 1ii: What are the typical characteristics of the existing strategic partnerships and value nets? Next phases of study (Phases II and III) The second phase of the study focuses on the description and analysis of innovation processes and services from a strategic network perspective. The tentative research question of the second phase is:
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RQ 2: What aspects of innovation processes and knowledge-intensive services are carried out through (or by using) strategic partnerships and value nets in the software industry? The third phase sums up the study and proposes a synthesis and recommendations to improve innovation activity in the SW cluster. The preliminary research question of the third phase is: RQ 3: How to utililize knowledge intensive services in connection with different business models, strategic partnerships and value nets to enable successful implementation of innovation?
1.4 Definition of key terms and concepts This study emphasizes issues related to software business. There are several ways to classify software business into subcategories. For instance, Nukari and Forsell (1999) have divided software business into software project business (i.e. tailored or customized software) and software product business. Also, some classifications see embedded software as different from these sectors. However, embedded software business is not researched in this study. As with the concept of strategy, there are no dominant definitions of a business model in either the Information Systems (IS) or electronic business literature that would be both consistent and rigorous. This seems to be the case in both e-commerce and software business contexts, although the term has been existent in the e-commerce discussions widely during the past few years. The current semantic confusion related to business models is further complicated by consultants and practitioners that often resort to using the term “business model” to describe any unique aspect of a particular business venture. In this study, we make a distinction between the concepts of business definition, business strategy and business model. We understand the business model as a practical appearance or manifestation of the business derived from strategy and designed to fit into a specific market situation in order to execute strategic plans. We share this view with Osterwalder and Pigneur (2002), who regard business models as the missing link between strategy and business processes. According to them, there is often quite a substantial gap between these two “worlds”. Strategy people position the company, define and formulate objectives and goals, whereas business process and information system designers have to understand and implement this information. A very simple and useful definition has been presented by Rajala et al. (2001); business model spells out how a company makes money by specifying where it is positioned in the value chain, or a value net. Value network is an interconnecting web of value-creating processes that are held together by a unified design and shared values (DeRose 1994). A value network is usually a set of relationships between firms, where companies engage in multiple twoway relationships to bring increasingly complex products and services to the market. (Aldrich 1998) However, value networks are often loosely structured in regard to the number and role of actors, and it makes sense to discuss about intentionally formed groups of companies that have some specific purpose or goal in order to gain competitive advantage. In this study we use definitions of value network and value net by Möller et al. (2002) who take a deeper insight of the terminology by using the
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”network” term to refer to macro networks, and the ”net” to refer to intentional nets of restricted group of actors. We share the definition of Forssen et al. (2003) of innovation as an idea that has been implemented into new product or service, process or organizational elements guiding it to technological, organizational or market change in a value-adding way. This definition captures the crucial importance of implementation; new knowledge has to be successfully implemented before it can be called an innovation. On the other hand, innovation can be understood as a cycle involving interactions between tacit and explicit knowledge, and it can be generated within the firm or be acquired from external sources such as network partners. (Muller and Zenker 2001) The development of the activities of knowledge-intensive business services (KIBS), e.g. IT consulting services, may be interpreted as one of the marking trends of recent economic evolution in industrial countries, and their increasing importance constitutes one of the characteristics of the raise of the so-called knowledge economy. KIBS produce and diffuse knowledge, which is crucial for innovation processes. (Muller and Zenker 2001) Various researches show that KIBS have a clear positive benefit for innovations. In order to understand KIBS and their role in innovation processes, we have to make some definitions. We define KIBS providers in the software industry as actors providing knowledge-intensive services for software companies in order to create and transfer knowledge resources and capabilities. KIBS providers can be public (commercial or non-commercial), private (commercial), or internal actors. Knowledge Intensive Service Activities (KISA) are the actual knowledge transfer activities that occur between KIBS providers and software companies, and facilitate the creation and development of innovations.
1.5 Research design and methodology The study begins with a brief review of earlier research of both business models and value nets. After the concept-centric literature review, we describe some generic examples of business models in the software cluster and illustrate the characteristics of typical value nets in association with them. We have selected two cases to illustrate different business models and value nets in the software industry. The cases were selected on the basis that the case companies have actively developed a value network and engaged in different partnerships. One criteria of selecting these companies was also that there was a fair quantity of information available on their partnerships. The cases selected for this part of the study include Akumiitti Ltd (later Akumiitti) and BasWare Plc (later BasWare). The Akumiitti case illustrates a distribution network of a system solutions business. The BasWare case illustrates a standard product business with both product development and distribution networks.
1.6 Scope and limitations of study This study, as the first phase of the KISA-LTT project, focuses on the review and description of the theoretical background of cooperative forms, value nets and business models to present concepts and tools on studying knowledge-intensive services in the software industry from the perspectives of business models and value nets. This study relies for most parts on previous research and collects new data only to illustrate both
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the business models and strategic nets of selected case businesses and to briefly describe existing (knowledge-intensive) services within them. Software industry encompasses a multitude of business models with a great variety of cooperative forms of actors providing or using different services. However, this study does not describe them all in detail. Instead, this study introduces conceptual tools and perspectives to serve as a foundation to analyze the roles of knowledge-intensive services in various innovation systems within the software cluster.
1.7 Framework of Study The framework for our study is presented in Figure 4, which sums up the key areas of research. Firstly, we describe the concept of business models to characterize different software businesses. Then, we depict the variety of value nets and concepts used to describe them. Finally, we address the knowledge-intensive service partners and types and roles of services within the innovation systems of identified business models and value nets in the software industry. Standardization of product & service
High
Software project business
System solution business
Software/system services business
Standard product/service business
Transactional
Distribution
Business Models
Collaborative
Low
Renewal Nets
Emerging Business Nets
Value Nets
Demand-Supply Nets
Knowledge -intensive services
Efficiency Focused Innovation Activity
Service Partners Providers, users, facilitators, etc.
Efficiency/Effectiveness Focused Innovation Activity
Type of Service Communication service, business service, other
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A
Effectiveness Focused Innovation Activity
Role of Service Informative, Diagnostic, Advisory, Facilitative, Turnkey, Managerial
R
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A
R
A
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Figure 4 Framework of Study
A
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The business model perspective in the framework has been adapted from the earlier works of the researchers (Rajala et al. 2003) and is based on the elements of business models identified in the literature (Amit and Zott 2000, Hedman and Kalling 2003). The value network perspective in our framework is derived from the Industrial Network Approach (INA). The underlying fundamental elements of networks are identified, e.g. by Håkansson and Johansson (1992) as the basis of any industrial network relationships. For the purposes of our study, we have reviewed a multitude of related research on the field, e.g. Axelsson and Easton 1992, Ford et al. 1998, Doz 2001, Håkansson and Ford 2002 and Möller and Svanh 2003. The third level of our framework addresses knowledge-intensive services that have been discussed in the recent literature by, e.g. Bilderbeek et al. 1998, den Hertog 2000 and Muller and Zenker 2001. We analyze them on the basis of the ARA-model (Activities, Resources and Actors) presented by e.g. Håkansson and Snehota (1995) in the industrial network approach.
1.8 Characteristics of the Finnish software cluster Software business is currently one of the fastest growing industries, with a global turnover of 320 billion euros (Nukari and Forsell 1999). Due to the rapid evolvement of software business, the earlier classifications about the software industry are insufficient. New classifications include differentiating software products from the service business as a basis. There has also been discussion about whether the software business should be considered as an industrial business or part of business services (Toivonen 2001). The key factors behind the rapid growth of Finnish software product companies are increasing amount of available venture capital, as well as entrepreneurship and cooperative communities between the companies. The former means, that a successful software company is always based on a good product and business idea, the latter means that regardless of competition software companies use business nets more effectively to strengthen their business and industry compared to other industries. (Spin 2001) There are various reports about the state of the software and software product business in Finland, and results emphasize similar facts (e.g. Nukari and Forsell 1999; Autere et al. 1999; Hietala et al. 2002; Source Code Finland 2002). Software companies are fairly small and employ mainly less than 10 people. Companies are also relatively young and most of them have less than 2 years of activity. Focus of action is generally customer specific projects and tailored software or contracting. Products are usually derived from customer projects, and often represent the so-called spin-offs. Revenues are collected from license fees and support services, but a large number of product-oriented companies are not profitable. Moreover, it is characteristic to especially young software companies that their innovations and business models need continuous specification. Common attributes of software business include high level of networking, the importance of exports and global markets, and strong thrive to grow and enlarge to new markets. As reported in the KISA-INTO part of this KISA-SWC project, the software industry is still relatively small; although it has grown rapidly during the last decade. The total revenue of the industry was estimated at € 1.68 Billion in 1999. The industry employed approximately 20,000 people in 1999 (Nukari and Forsell, 1999; Hietala et al., 2002).
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The estimated shares of different businesses in software industry are as follows: software products 20% and software customized projects 80 %. (Forssén et al. 2003) As stated before, software industry is highly networked area of business. Alajoutsijärvi et al. (2000) refer to Pasanen (1999) in their research about software companies in North Ostrobothia, and claim that the local software companies were having multiple network relations between each other, but only a few customer-supplier relations and nets. This was seen common to the software industry, as software companies utilize the same technology and knowledge resource base.
Figure 5 Intercompany network relations between North Ostrobothnian software companies – sample of 19 companies. (Pasanen 1999 ref. Alajoutsijärvi et al. 2000)
Despite of the highly networked structure of software industry, innovation systems have traditionally been studied from single actor’s perspective. That focus has emphasized firm’s internal value systems in the creation of innovation. However, to understand the current innovation activities within the software industry and the creation and delivering of value within it, we need to address the business models of software companies and depict the value nets they are engaged in.
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2. Theoretical Background In order to depict the context of innovation systems in the software industry, and analyze knowledge-intensive services within them, we briefly review herein the literature of both business models and value nets of software businesses.
2.1 The Business Model Context The purpose of studying the notion of business models in this study is to distinguish different software businesses from each other on the basis of their operation. We aim at dividing software businesses into classificatory groups based on their business models. According to Allee (2002) the key to creating successful business models for the knowledge economy lies in understanding the dynamics of value nets. We can then identify typical value networks of these companies and describe the networking of knowledge-intensive services traded within and between businesses in accordance with different business models. Thus, we do not want to operate at the strategy level and classify companies based on their strategies (i.e. what they aim at being within their planning horizon) nor at the business process level based on how they conduct different business processes. This definition is presented in Figure 6.
Planning level
Strategy
Architectural level
Business model
Implementation level
Business processes
Corporate / Group level Business unit level Functional level
Figure 6 The Business Model Context (extended from Linder 2000; Äijö 2001; Pigneur 2002)
When reading up on the recent academic discussion about business models, we found that it contains few feasible and exact definitions of the term. This seems to be true in the public discussions as well (Eisenmann 2002). In this study, we will define the concept of business model for the purposes of our study, which are, to understand the essential elements of business models, and, to serve as a basis for identifying the value nets and services traded within them in the software business. Amit and Zott (2000) separate business model from the way in which this enables revenue generation, or the revenue model, while Rappa (2000) defines the business model in ecommerce context as a method of turning valid ideas and opportunities into a way of doing business by which a company can sustain itself and generate revenue. In addition, h te business model spells out how a company makes money and specifies where it is positioned in the value chain, or a value network. For example, Mahadevan (2000) has described the business model of an Internet business venture as a unique blend of three streams that are critical to a business: the value stream for the business partners and the buyers, the revenue stream, and the logistical stream.
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To summarize, the main elements of a business model defined by a number of researchers (Timmers 1998; Amit & Zott 2000; Mahadevan 2000; Rappa 2000; Afuah & Tucci 2001; Peterovic et al. 2001; Betz 2002) in different words include value creation processes and capturing the opportunities in the market into revenue through sets of activities, processes and transactions. Common to all of these definitions is that they emphasize the value creation through activities or structures described by a business model. In the context of business model construction, Timmers (2003) states that in comparison between traditional supply chains to dynamic value nets, the focus shifts from increasing value through internal relations to increasing value through external relations, and the amount of relations multiplies. HOW? WHO? Who are customers, how to manage relationships with them?
Customer relationship
Infrastructure logistics
Product innovation WHAT? What is the scope of products and services, its value for the customer, the capabilities to innovation?
How to organize infrastructure, its resources, the knowledge and the structure of costs, manage value chain activities and processes, build partner network to achieve performance?
Financial aspects
HOW MUCH? What is the revenue model / profit model / cost model?
Figure 7 A Business Model Ontology (Pigneur 2002)
On the basis of the studies referred herein, we could say that value creation structures and processes commonly describe the various business actors and their roles whereas value appropriation (capturing) processes describe the sources of revenues and the ways revenue is gathered from these sources. It must be noted, however, that value creation can be accomplished both by the business model and the product/service offering of a firm (Amit & Zott 2000). Based on the studies reviewed above, we can conclude that the focus of business models in software industry is either in the value proposition including product and service offering (software, consulting, etc.) or in the specific method of conducting transactions and capturing the revenue. According to the definitions reviewed herein, we see that a business model refers to a single company, and that it encompasses only a single product/market segment (i.e. single business) at a time. Thus, there can be several business models within one company simultaneously.
2.2 Types and Characteristics of Business Models Sallinen (2002) divides software products and services into four segments; professional software services (production of customized software), enterprise solutions, packaged mass-market software, and embedded software. However, the software industry is changing continuously, with new forms of creating value taking shape all the time. The
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presented classification does not recognize software companies that operate in the area of e-commerce and information content service businesses, such as application service providers (ASP). Also, one of the new businesses expected to be successful in the future within the software industry is the production of component software. Locating these new businesses in traditional categorization is rather difficult, as they overlap and may have both product and service orientations. (Sallinen 2002) Warsta (2001) has researched contracting in the software business, and he divides the software business models as product business including commercial off-the-shelf software (COTS) and pure tailored systems, and project business including modified off-the-shelf software (MOTS). Due to the nature of offering and the wide potential customer base, the commercial and modified off-the-shelf software business models usually emphasize strategic partnership and alliance management building, and channel management, as opposed to pure tailored systems. From the contracting point of view, COTS is fairly short-term oriented but tailored systems and MOTS are longterm oriented. This is directly related to the level of service content (see also Tähtinen 2001). There is a clear shift from tailored software to COTS and MOTS software, and ultimately software as services business, such as application service provision (ASP). Warsta (2001) gives some examples of this, and notes that the companies making such operations must rethink their revenue model, which is an important part of the business model. In addition, he claims that a small COTS software producing company should cooperate with a bigger OEM type channel. According to McHugh (1999), strategic partners of software companies tend to be large companies with impact on markets. According to Warsta (2001), software companies operating in fluctuating environment should move to MOTS markets, and a tailored software producing companies should not just be resource sellers, but utilize projects as learning and know-how building processes. The basic idea of software component production (also known as original component manufacturing, OCM in the context of COTS) is to facilitate software production through integrating available commercial or non-commercial software components. The architectural structure of component-based software is seen to enhance productization of the software, and to provide time and cost savings. Niemelä and Seppänen (2000) claim that software companies have a clear trend to aim at developing software components related to their area of business, and to change the architectural structure of the software products to component-based structure. Additionally, they claim that the development of software component technologies should focus on integration of product-line architectures and software components, and one of the key objectives for software component production is cost-effective operation. Hietala et al. (2002) conducted a survey about the state of the software product business in Finland. They identified four different groups of companies based on the amount of installation and integration work needed, and degree of productization. Instead of productization, we define this dimension of offering as the level of standardization. The identified groups are standard product, enterprise resource planning (ERP), solution provider, and tailoring companies. However, according to their research, majority of the companies lie somewhere in between. Open source and ASP were used only to a small degree, but tailoring companies were seen to often aim for more standardized software product offerings.
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A framework presented by Rajala et al. (2003) for analyzing software business models separates different business models from each other based on the characteristics of the product proposition, services and implementation, revenue logic and the distribution model. The key elements of business models identified in the framework of Rajala et al. (2003) are: •
Product Strategy describes the core product and service proposition of a software business and the way its product development work is organized. The product proposition in this context describes the focus of product development and its outcome, the core product and service offering of a software business. The product development model can be thought as the way the product development work is organized.
•
Revenue logic describes the sources of revenue and the way a software vendor generates its revenue from these sources
•
Distribution model describes the ways the marketing and sales of the product and service offering have been organized and identifies the sellers and marketers of the product and service offering. This element also characterizes the sales process and its outcome, i.e. the agreement between the vendor and a customer about the characteristics of the solution provided.
•
Service and Implementation model describes how the product offering will be dispatched to the customers and deployed as a working solution, including the set of services and actors implementing them, e.g. physical distribution, implementation and maintenance of the product/service offering.
Based on the key dimensions (the product and service proposition and the distribution model) of above-mentioned framework of Rajala et al. (2003), we have classified generic software business models as presented in Figure 8. Level of standardization of product & service offering
Distribution model
Collaborative
Low
Software project business
–
Tailor-made or Customerspecific sw
– –
Embedded sw Component-based games
Software/system services business
Transactional
– –
Transactional services
High
System solution business
– –
Large software solutions
–
Standalone games
Modified off-the-shelf software (MOTS)
Standard product/service business
–
Software subscription (e.g. Application Service Provisioning)
–
Commercial off-the-shelf sw (COTS)
–
Server-based games
Streamed games
Figure 8 Generic Examples of Software Business Models [Adapted from Rajala et al. (2001)]
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The classification of generic software business models presented in Figure 8 can be used to describe the innovation activity and knowledge-intensive services related to different business models. We have divided different software business models into four main categories according to the distribution model and the level of standardization of the product and service offering within them. This tentative classification is to serve illustrative purposes only and is by no means complete. Problems exist, for instance, in classifying businesses offering both embedded software and component-based software with this classificatory scheme. However, the basic types of software business models illustrated by this classification are: software project business, software and system services business, system solution business and standard product or service business. Table 1 summarizes the characteristics of the generic business models presented in Figure 8. Table 1 Characteristics of Generic Business Models (Adapted from Rajala et al. 2001) Software Project Business
System Solution Business
Product Strategy
Tailored solutions. Emphasis on meeting customer’s needs
Customized solutions, sometimes based on a uniform core of several products or customerspecific solutions tailored to a degree, product platform or component-based solution.
Distribution Model
Close collaboration between vendor and customers including direct consultation
Software integrators as a value adding resellers especially in the growth and maturity phases of business
Revenue Logic
Driver: Economies of scope.
Driver: Scalability
Determinant of profitability: Share of wallet Determinant of profitability: Quality and performance of solution Value-based pricing (sometimes also on effort and cost). Pricing based on quality Service and Implementation model
Lots of custom service
Integration services
Culture: Problem solving focused
Culture: Building trust
Examples
IT consulting companies
ERP providers, etc.
Software and System Services Business
Standard Product or Service Business
Product Strategy
Product or service concept based on a set Uniform core product, modular product family or of components, middleware or platform standardized on-line service
Distribution Model
Internal hierarchy
Wide distribution network On-line distribution possible in Software as a Service (SaaS) models (like ASP)
Revenue Logic
Driver: Efficiency of sales processes
Driver: Economies of scale
Determinant of profitability: Speed of development & deployment, efficiency of implementation
Determinant of profitability: Utilization of facilities and low -cost operations
Service and Implementation model
Customer services
Deployment services
Culture: Domain knowledge focused
Culture: Standardization and cost reduction
Examples
New media companies, etc.
Universal product or service providers
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The characteristics of software business models illustrated in Table 1 are based on generic examples. It should be noted also that these examples may exist in parallel with each other in a software business (see e.g. Leminen 1999). For example, software project business can support system solution business or even standardized product business e.g. financially or by diminishing risks of product success. It has in some cases been seen as a path towards more standardized product or service business (Rajala et al. 2001). Due to the problems of dividing all business models into the four generic categories presented above, we examine the dimensions of categorization as continuums. Our preliminary classification of software business models based on the standardization of products and services typical to the business and the relationship between the vendor and customer in trading the software is, then, more like a map used to position different businesses. This view is presented in Figure 9. Low (Complex/tailored services) Collaborative
Software project business − Tailored software solutions
Level of standardization of product/services
Product platform business
Embedded software business
High (Standardized services)
System solution business − Large software solutions − Modified off-the-shelf software (MOTS)
Customer relationship Component-based software
Software/system services business − Transactional services − Streamed games & services
Transactional
Standard product/service business − Subscribed software (e.g. ASP) − Commercial off-the-shelf software (COTS) − Server-based games
Figure 9 An Illustration of Business Models According to Customer Relationships and Standardization of Product/Service Offering
2.3 Value Production and Business Networks In this section we focus on identifying the characteristics of value production and networks. The main argument for choosing the value net perspective is that networks, as such, have been claimed to provide superior information processing capacity and more flexible governance structures compared to markets and hierarchical organizations, especially, in knowledge intensive businesses (e.g. Achrol and Kotler, 1999; Eisenhardt and Martin, 2000). In this sense, our basic argument is that the establishment of network-based cooperative forms between software companies and KISA providers may also enhance innovation activity in the whole Finnish software cluster. On the basis of a review in network studies, our aim is, firstly, to identify the key
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elements in value production, and secondly, to the main characteristics of business networks. The Issue of Value Value is primarily defined in business context in monetary terms. Broader definitions include non-monetary benefits and sacrifices, such as competitive gains, competencies, social relationships, knowledge, and managerial time spent. On the other hand, value can be regarded as a trade-off between the total benefits obtained and the total sacrifices incurred. The assessment of value is a complex task due to the problems in identifying and measuring both the monetary and, especially, the nonmonetary benefits and sacrifices. The business model approach presented in previous section also highlights the ways and practices how value is created and distributed in software cluster. In fact, each business model reflects a unique way of value production. However, we need more specified tools for better understanding the production of value and the establishment of value nets. Möller and Törrönen (2003) have developed a model or a tool, which they call ‘value spectrum’ to describe value production. In this model focus is on the relational aspects of value production. They propose a continuum, which expresses simultaneously the level of complexity involved, and the time horizon of value realization (see Figure 10). Core Value Production Transaction-oriented Relationships
Low Relational Complexity Current Time-orientation
Value-adding Relational Value Production
Future-oriented Value Production Partnering Relationships
High Relational Complexity Future Orientation
Figure 10. Value Production Spectrum (Möller and Törrönen, 2003)
In the left end of the spectrum value production aims at maximizing overall efficiency by focusing on ‘core value production’. It means, for example, that software companies use KISA to enhance their overall productivity by outsourcing the activities which are not in the core of the business. This kind of sub-contracting is traditionally based on contractual agreements done, for example, annually. In the spectrum, the middle range describes ‘value-adding relational value production’ indicating that through mutual investments and adaptations, for example, a KISA provider and a software company can create new product and process solutions that are more effective than the ones that exist in the field. This relation-specific development creates new ‘added’ value in terms of the available solutions. Finally, the right end of the spectrum deals with more radical innovations expected to be realized in the future. Here, the value production is highly dependent on strategic partnering and many networked actors. KISA’s role in this kind of context is also more critical to facilitate new business concepts or models for software providers. It needs to be pointed out that the value of KISA to software providers could be very difficult to assess, at least, in advance with any accuracy, since it depends on many factors affecting the development of the software industry itself, or even other industry sectors, and the whole society. However, the high risk associated with the future value production is partly compensated by the potentially huge revenues to be accrued. To summarize, only the production of core value can be sufficiently estimated in terms of
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costs and benefits. The more we move from the left to the right, the more problematic the evaluation of the value-production potential becomes (Möller and Törrönen, 2003). From Value Chain to Value Systems During the last decade, the way in which economic value is created in a society has dramatically changed. The increasing importance of knowledge intensity, technological complexity, global competition and the availability of digital information technology are driving this change (Castells, 1996). As a result, the pace of innovation has also accelerated, which has led to shorter product life-cycles and the emergence of totally new types of business models. On the other hand, individual companies, even major multinational corporations, such as Microsoft, Nokia, and IBM, cannot internally master, or it is not economically sensible, all the relevant value activities of the supply chain. (Möller and Svahn 2003) The straightforward function-specific value chain (presented by Porter, 1985) describing the value-creating elements for an individual company, its suppliers, other channel members and customers has been, more or less, replaced by value constellations, such as value stars or value systems (see Figure 11), in which network of firms are often replacing traditional markets and vertically-integrated companies. It is also important to note that when a company moves over from value chain to value star thinking in its management, its core processes are shifted from logistical operations to information and knowledge management (Wickström et al., 1994). From innovation management point of view, the notion of value creation, or value production, is closely related to knowledge management.
Figure 11. Value Chain and Value Star (Wickström et al., 1994, 112)
According to Wickström et al. (1994), new knowledge is created largely in activities, which are geared to the solving of problems. Value is created through three interrelated knowledge processes: generative, productive, and representative. In the processes, which in the long run are to generate new business and better customer offerings are called generative processes. The knowledge, which the company successfully accumulates in this way, is then used in productive processes to produce customeradapted knowledge. In the representative processes knowledge is made available to the customer’s own value-creating processes. By combining these three processes and
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incorporating them with the value stars (both supplier’s and customer’s value stars) the authors have developed a model for value creation (see Figure 12 below).
Figure 12. Company as a Knowledge System for the Creation of Value (Wickström et al., 1994)
In knowledge-intensive businesses, value is often produced or created simultaneously by several participating actors (customer, service providers, sub-contractors, and other partners), thus the traditional value chain is incomplete to describe the complexity of the process. Therefore, we believe that identifying the ways and practices how knowledge is created and understanding interaction between the different knowledge processes helps us to better capture the nature and characteristics of innovation activity in a specific industry. In case of software providers, this approach also helps companies to better understand the potential of different actors, such as KISA, and their potential to enhance innovation activity. As the model indicates, networking is an essential part of knowledge-intensive businesses. To study these issues we need conceptual tools for better understanding the establishment and management of value-creating nets or networks. What are Networks? As Möller et al. (2002) and Möller and Svahn (2003) point out, the term network is currently being used to refer to large range of phenomena ensuing ambiguity (e.g., Dyer and Nobeoka, 2000; Jones et al., 1997; Håkansson and Ford, 2002; Nohria, 1992). Thus, it is essential to establish what we mean by value network. First, it is important to distinguish between a “network of organizations” and a “network organization”. The former refers to any group of organizations or actors that are interconnected with direct or indirect exchange relationships. According to INA (Industrial Network Approach), any market can be described as this kind of macro network, or network of firms (Axelsson and Easton, 1992). In many cases, companies have been seen to form extended enterprises which are part of a business design (or model) that consist of different cooperative forms, negotiate responsibilities and utilize mediating technology and share resources to achieve superior customer satisfaction and profitability of all members participating value creation. This so-called value creating network model emphasizes the central role of customer, and in general, builds up around him. As a result, every participant contributes and receives value in ways that sustain both their success and the success of the value net as a whole. (DeRose 1994; Stabell and Fjeldstadt 1998; Bovet and Martha 2000; Germany and Muralidharan 2001; Reingoldt 2001; Allee 2002) As a
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consequence, firms and other social actors are creating increasingly complex internal and external webs of knowledge and technological bonds (see Figure 13). Internal Networks
External Networks
Vertical networks Technology sales to non-competing manufacturers
SUPPLIERS
Customers of components
Sub-providers Providers
Purchasing Production
Engineering
Research consortia
Contract manufacturers
Companies Customers
Personnel
R&D
Horizontal networks Strategic alliances Consulting services Accounts
Finance Investors
Marketing
Marketing alliances Distributors
CUSTOMERS
Tighter cooperation (e.g. partnerships, alliances) Looser cooperation (e.g. joint ventures, preferred suppliers)
Figure 13. An illustration of internal and external networks (web of actors) (Bovet and Martha 2000; Achrol and Kotler 1999)
As the industrial network approach suggests, companies in a network are economic actors, which are inter-related through a web of resources and activities (see Figure 14). Value is created in a network by actors who perform and control activities that are based on control over critical resources, and include social content by developing relationships with each other through exchange processes (Håkansson and Johansson, 1992; Axelsson and Easton 1992). Critical resources can be physical, but especially, in software business they are mainly knowledge-intensive intangibles. Resource ties between the companies are essential in order to innovate in using resources and to develop new ones (Ford at al. 1998; Ford et al. 2002). Actors also have differential knowledge about activities, resources and other actors in the network, and act as information sources providing new opportunities and alternatives, thus enhancing the potential for innovation activity of the focal network. Furthermore, actors are goal-oriented and continuously have efforts to increase their control and to achieve better position in a network. Increasing the control over the network leads ultimately to the position presented by Jarillo (1988) where a company becomes the firm that sets up the network and takes pro-active attitude in the care of it. In the context of value nets, this is called the hub company. However, Möller et al. (2002) claim that full control of another actor’s resources and activities cannot be acquired in value networks, but opportunities and challenges of control and coordination vary considerably in terms of novelty and complexity as expressed along the value-system continuum.
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Resources Ties
Network Value Creation Actor Bonds
Activity Links
Figure 14. Actors, Resources, and Activities (ARA -model) (Håkansson and Snehota, 1995)
Networks between business organizations are not monoliths but serve several purposes. During the 1990’s supply networks provided a solution for the rapid growth in the ICT field. In high-tech and knowledge-intensive industries R&D partnerships/coalitions are employed for creating new technological platforms and dominant solutions. In the ICT cluster business networks are often the best and only way to integrate the value activities of several players for creating mobile and digital customer services (Paija, 2001). Networks are also formed to enhance members’ competitive position as the alliances in the airline business demonstrate. Finally, large corporations are themselves starting to resemble network organizations (Möller and Rajala 1999, Snow 1992). The role of the focal actors (in our case software producers and KISA providers) in a business network can be classified according to the firm’s position in the net and the configuration of the net itself (Doz, 2001). The company may act as the engine, or hub, in the focal business network, or it is one of the many actors having a minor role as a partner with whom the hub company cooperates. The configuration of a network is traditionally classified into two or three groups. According to Barbasi (2002, ref. Möller and Svahn, 2003) networks are either centralized, decentralized of distributed. Typical of a centralized network is that one company controls activities and resources in this network. Doz (2001) labels this configuration a hub-and-spoke structure. The hub company also decides which companies are selected as partners into the network. In a decentralized network the hub company is not directly controlling over each actor. Typical of this configuration is that it consists of several node companies which might have their own hub-and-spoke structures. This means that the focal hub company is neither able to select all partners into the network nor to decide the distribution of resources. Decentralized structure produce a portfolio of 1st , 2nd, and even 3rd tier relationships. However, it is important that the hub company make clear for itself which are the relationships the company needs to control, influence, and be aware of. We label this configuration a hub-and-node structure.
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Network Configuration
Distributed Multiplex structure
Distributed Hub & node structure
Centralized Hub & spoke structure
Hub
Partner
Firm’s Position Figure 15. Network configuration and the role of software produces and KISA provider
The third type of network configurations differs from the decentralized one in two aspects. Firstly, it does not have a clear structure, or ties, since activities are distributed to and carried out by partners that do not have any control over each other’s business operations. Secondly, most of the partners are at the same level and can, for example, freely cooperate with the most suitable partner in each separate business case. However, these kinds of multiplex network structures, as Doz (2001) calls them, may still need one actor who coordinates and facilitates networking between the members. As the previous discussion indicates, there exist different types of value systems and network configurations. The distinction between these value systems and business networks originates from the fundamental purpose, or goal set, for creating and delivering value to customers and other stakeholders of the focal company. In the next section, we focus on constructing a framework that provides guidelines and tools for studying the role of KISA to improve innovation activity in software industry.
2.4 Value System and Different Types of Business Nets Since we are interested in intentionally formed networks, we call them hereafter ‘value nets’ to distinguish them from more general ‘networks of firms’. These nets come in many forms and with many purposes; in the literature and business press one can, for example, identify supplier nets, distribution nets, technology development or R&D nets, competitive coalitions, technology coalitions, etc. Möller et al. (2002) have developed a conceptual tool for analyzing value nets. This tool or model, labeled as value system continuum, is based on the notion that each product or service requires a set of value activities performed by a number of actors forming a value-creating and value-delivering system. This model comprises the typical
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characteristics of both (1) stable, well defined value systems, (2) established value systems with incremental improvements, and (3) emerging value systems with radical changes in the way the network is operating for creating value. The value continuum is based on three factors which have core roles in promoting understanding of the nature of value net and its management. 1.
The level of determination of the value activities and the actors forming the net, i.e., the nature of the value-system embraced by the net. This indicates how wellknown the value activities of the net and the capabilities of the actors performing them are, and to what extent can they be explicitly specified. The greater the level of determination of the value-system underlying the net, the less uncertainty there is and the less demanding its management, all other things being equal.
2.
The goal of the strategic net, or its hub firm. This answers the question of what outcomes are pursued through the net. Examples include increasing the operative efficiency of an established value-system, product or process innovation, and setting up a completely new business requiring partly new value activities or even a new value-system.
3.
The structure of the net, as described through the vertical and horizontal dimensions and through the numbers and different types of actors constructing the net. Scope and relative complexity versus simplicity have a direct impact on the managerial requirements.
By combining these three factors a model of value system continuum can be constructed (Figure 16). The value-system and its level of determination have a central role in the understanding of the characteristics of a specific net. Accordingly, value systems vary from fully determined systems to emerging systems.
• Well-known and specified value activities • Well-known actors • Well-known technologies • Well-known business processes • Stable value systems
Stable, well -defined values system
• Well-known valuesystems • Change trough local and incremental modifications within the existing value system
Established value system, incremental improvements
• Emerging new value systems • Old and new actors • Radical changes in old value activities • Creation of new value activities • Uncertainty about both value activities and actors • Radical system -wide change
Emerging value system, radical changes
= Describes ideal types of the values systems and their overlapping characteristics
Figure 16 Value System Characteristics (Möller, Rajala & Svahn 2002)
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The value system continuum of Möller et al. (2002) is composed of three ideal value systems. The left end describes clearly specified and relatively stable systems. The actors producing and delivering specific products and their value activities and capabilities are basically known. The right end of the continuum describes emerging value systems. The constructors of this aim at creating nets through which new technologies, products or business concepts can be developed and commercialized. These future-oriented strategic nets often involve radical changes in the existing value-systems and the creation of new value activities. For example, Internet portals and emerging mobile services are generally created through a strategic net. Emerging value-systems involve dynamic and complex learning processes and an inter-organizational relationship formation that cannot be specified in advance. Uncertainty related to value activities and to actors and their capabilities is an inherent feature of the system. (Möller et al. 2002) In their extreme forms, the value systems outlined are ideal types. In reality, we will never find completely determined or undetermined systems. Local development activities exist even in the most established and well-specified nets producing incremental local change. On the other hand, even in the most radical emergence, some actors have visions of the end goals that can be achieved through shaping new technologies and new actors. These views, although uncertain and vague, guide the actions of firms, and it is through these actions that the new strategic nets take shape. It is a very probabilistic world well described by the birth of commercial Internet and mobile telephony and mobile services, involving both old and new actors and old and new value activities. (Möller et al. 2002) According to Möller et al. (2002), the middle of the continuum describes value systems that are relatively well determined, but that are being modified through incremental and local improvements. Most multi-actor R&D projects, as well as business-process modifications, exemplify these kinds of incremental changes within an existing valuesystem. This value system continuum provides us a conceptual tool for examining the different roles of actors, critical resources, and activity sets that are typical for each value system constellation. In the next section we will further develop the framework by combining the elements of value spectrum and ARA-model into the value system continuum. The aim of this framework is to give us guidelines for examining the role knowledge-intensive service activities and their impact on the innovation activity of software providers.
2.5 Innovation Activity in Different Types of Value Nets in Software Sector The enhancement of innovation activity is considered as one of the key development areas for software providers. For this purpose, we propose a conceptual tool (Figure 17) according to which we are able to identify key elements for successful use of knowledge-intensive services in the software sector. As for constructing the tool, we have borrowed elements from value system continuum developed by Möller et al. (2002), value spectrum (Möller and Törrönen, 2003), and network configuration defined by Doz (2001) and Barabasi (2002). The underlying logic in this model is that the creation of value through innovation activity in software business needs the participation of several actors, such as knowledge-intensive service providers, to provide invaluable resources to carry out innovation activities (cf. ARA-model, Håkansson and Snehota, 1995).
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Demand -Supply Nets
Core Value Production Transaction -oriented Relationships
Efficiency Focused Innovation Activity
Renewal Nets
Emerging Business Nets
Value-adding Relational Value Production
Future-oriented Value Production Partnering Relationships
Efficiency/Effectiveness Focused Innovation Activity
Effectiveness Focused Innovation Activity
Figure 17. Conceptual Tool for Examining Innovation Activity in Different Value Nets
We label the more stable types of value systems as demand-supply nets because these focus on enhancing the core value production by, for example, streamlining business processes both in upstream (supply nets) and downstream (demand nets). Renewal nets, on the other hand, aim to add value through incremental changes to existing value systems. Good examples of these kinds of nets are, for example, cooperation in R&D activities to add new elements in existing products, services, or systems. Also, strategic alliances that complement existing offerings, for example, by providing better market coverage or access to customer interface may remarkably renew, or enhance. Finally, as emerging business networks are characterized by future-oriented value production, they embody a high level of complexity and uncertainty. For this reason, the number and roles of participating actors may change all the time. We also expect that in demand-supply nets the network configurations are mainly following the hub-and-spoke, or to some extent also hub-and-node, structures where the central company has a dominating role in the net management. On the contrary, in emerging business networks multiplex structures are expected to dominate, although hub-and-node types are used to some extent as well. Here, it may be difficult to manage the net in traditional meaning but rather the actors jointly agree of the goals for the net. In renewal nets used structures may vary and we expect all the three different types to be possible. Which one is used may depend on whether the goal of the net is to increase efficiency or effectiveness. The focus in this research project is to examine how innovation activity among software providers can be improved by using knowledge-intensive activities (KISA). Our conceptual tool suggests that in the case of ‘demand-supply’ type of nets, the focus of innovation activity should be on enhancing efficiency of the existing value system. This means that there is, for example, a need to outsource activities that cannot be carried out efficiently enough inside the company to KISA providers. On the contrary, in emerging business nets, the focus should be more on effectiveness than efficiency meaning that the company is searching for new business opportunities and models.
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Here, the role of KISA providers can be more critical because it is not only the question of carrying out transactions-related activities, but also to help the focal company to build up the whole new value system. This needs more long-term perspective on the establishment of relationships and collaboration between actors. In the renewal nets, KISA providers may either help the focal company to increase its efficiency or effectiveness.
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3. Knowledge-Intensive Net(work)s
Service
Activities
in
Innovation
Earlier studies of innovation (e.g. Palmberg et al. 2000; Toivanen 2000) have showed the importance of software innovations in the Finnish economy. Software has become perhaps the most innovative sector of the economy, in accordance to the rapid growth of the software business. The share of software innovations in earlier studies has been almost 15% percent of all innovations. Therefore, the software innovation has become also a very interesting research topic. Due to the rapid growth and role of software innovations it is important to research actors and activities supporting innovation creation and development. Definition of KIBS We share the definition of Forssén et al. (2003) of innovation as an idea that has been implemented into new product or service, process or organizational elements guiding it to technological, organizational or market change in a value-adding way. This definition captures the crucial importance of implementation; new knowledge has to be successfully implemented before it can be called an innovation. On the other hand, innovation can be understood as a cycle involving interactions between tacit and explicit knowledge, and it can be generated within the firm or be acquired from external sources such as network partners. (Muller and Zenker 2001) Innovations can occur not only as products or services, but also as new ways of actions, e.g. distribution or collecting revenue. These are often the basic elements of a business model, and innovations can therefore also occur as new business models. In regard to this we share the definition by Forssen et al. (2003) of innovations as product innovations, process innovations and organizational innovations. On the other hand, product innovations can also be divided as product innovations and service innovations. (see Kuusisto and Meyer 2002) The development of the activities of knowledge-intensive business services (KIBS) may be interpreted as one of the marking trends of recent economics evolution in industrial countries, and their increasing importance constitutes one of the characteristics of the raise of the so-called knowledge economy. KIBS providers produce and diffuse knowledge, which is crucial for innovation processes. (Muller and Zenker 2001) Earlier research shows that KIBS have a clear positive benefit for innovations. Therefore, it is reasonable to examine KIBS, their roles and activities in innovation creation. In order to understand KIBS and their role in innovation processes, we have to make some definitions. KIBS providers may be defined as consultancy firms in a broad sense, more generally KIBS providers can be described as firms performing, mainly for other firms, services encompassing a high intellectual value-added. (Muller and Zenker 2001) However, KIBS are not provided only by firms, but can also be provided by public organizations or in-house services. Forssen et al. (2003) classify knowledgeintensive services as commercial knowledge-intensive business services KIBS, public knowledge-intensive service activities P-KISA, and companies’ internal knowledgeintensive service activities I-KISA. Their classification is presented in Figure 18.
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Figure 18 KISA clients and suppliers (Forssen et al. 2003) However, we separate the service actors and the activities they create, and define KIBS providers in software industry as actors providing knowledge-intensive services for software companies in order to create and transfer knowledge resources and capabilities. KIBS can be public (commercial or non-commercial), private (commercial), or internal actors. Public KIBS include governmental or municipal knowledge-intensive services and universities. Knowledge-Intensive Service Activities (KISA) are the actual knowledge transfer activities that occur between KIBS and software companies, and facilitate the creation and development of innovations. Our classification is presented in Figure 19. KIBS provider
Software Company
NonCommercial
NonCommercial
KISA
Public KIBS
KISA Commercial
KIBS provider
Internal KIBS
Private KIBS
KISA Commercial
Figure 19 Classification of KIBS and KISAs
Innovation Networks Various nets of actors have become the primary context for innovation creation. (Miettinen et al. 1999) Innovation network is a net of actors that participate in the development of a new product or process, and whose resources and competences are complementary to each other. In addition, innovation networks tend to change during the innovation process. (Miettinen et al. 1999) Gemünden et al. (1996) have studied the effect of technology-oriented relationships on company’s product and process innovation success. Their study clearly points out that business nets have significant importance in innovation success. In addition, Gemünden and Heydebreck (1995) have demonstrated the relationship between business strategy and technological network activities, thus addressing the impact of business strategy or business model on company’s network configuration.
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External resources and competencies have a great impact on successful innovations. (Miettinen et al. 1999, 16) According to Gemünden and Heydebreck (1995) companies that have close relationships with customers, suppliers, research institutions and competitors are more likely to have higher product and process innovation success. They present a revised model of innovation partners and their contributions, and suggest that the management of a firm’s innovation network becomes a critical task in order to achieve competitive advantage. (Ritter and Gemünden, 2001) The innovation partners and their contribution are presented in Figure 20.
Administration -Subsidy -Political support - Mediations, transfer
Suppliers Producers of means of productions
- Laws, (de-) regulations
- New technologies of material, components and systems
Co-suppliers
Research and training institutes -Research -Training - Qualified personnel
Focal Company
Competitors
-Complementary know-how
Own competencies
-Joint basic research
-Solving interface problems
Own Authority
-Establishing standards - Getting subsidies
Consultants -Innovative concepts -Structuring of processes - Financial, legal and insurance services
Buyers -Defining new requirements -Solving problems of implementation and market acceptance
Distributors -Changing and weighting of demands -Gathering information about development of competitors
-Reference function
Figure 20 Potential innovation partners and their contributions (Adapted from Ritter and Gemünden, 2002)
Hauknes and Antonelli (1999) refer to Bessant and Rush (1995) and present another approach to innovation partners and their contributions. They divide the potential contribution of innovation agents to six characteristics, which are capability building, institution building, failure avoiding, lower cost, support functions, and decentralized operations. However, they emphasize the role of innovation agents in capability building, and provide advice and information support via consultancy as an illustrative example of developing key management capabilities in identifying needs, exploring and selecting innovations, and planning and implementing them. Sallinen (2002) points out a clear tendency in high-technology industries, according to which firms increasingly outsource innovative activities that typically have been considered as their core capability. The literature widely uses the concept of firm’s “core competence” proposed by Prahalad and Hamel (1990) in context of competitiveness. In modern business environment this can also be seen as network competence. Ritter and Gemünden (2002) claim that the degree of a company’s innovation success is positively correlated
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with its level of network competence. The term competence often describes resources and preconditions, i.e. qualifications, skills or knowledge that are necessary to perform by the company. However, competence has also been defined as a process of activities (see e.g. Day 1994). We suggest that these competencies can be facilitated by external knowledge-intensive service activities discussed in the next chapters. KIBS and their clients are often in what might be characterized as a symbiotic relationship. (Bilderbeek et al. 1998) Earlier studies have showed that interacting and cooperating SMEs and KIBS are more oriented towards innovation than non-interacting firms. It can be assumed that KIBS play an important role in innovation systems through not only by transmitting knowledge, but also through knowledge reengineering. (Muller and Zenker 2001) Most KIBS contact and co-operate with numerous client firms and their employees, constantly diffusing and absorbing knowledge, reprocessing it, and diffusing it again. Therefore, through their activities they act as bridging institutions in innovation systems. (Bilderbeek et al. 1998) Importance of KIBS Providers for the Software Industry Large corporations Tekes Technology Centres Venture capitalistst International partners SMEs
KIBS Providers
Universities Customers Local public authorities Finpro Trade associations Other research institutions Business facility providers Private investors Other financial institutions Ministries Local entrepreneurial associations Cities or municipalities Trade unions 0%
Very important
10 %
20 %
Important
30 %
40 %
50 %
60 %
70 %
Not important
80 %
90 %
100 %
N/A
Figure 21 The Importance of KIBS Providers for Software Industry (n=34 of 100, response rate 34%, SPIN evaluation by LTT 2003, Forthcoming)
We analyzed the importance of different KIBS providers from the perspective of software businesses. The analysis was carried out in collaboration with a research group evaluating the SPIN technology programme of Tekes (The National Technology Agency of Finland). The data in Figure 21 is based on a survey directed to approximately 100 SPIN participants, of which 34 responded to the query. In the interpretation of the results of this analysis it should be noted that the data can be biased for the part of Tekes as a KIBS, because Tekes has been a key financier and
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partner for the SPIN participants. Matching evidence was, however, obtained from 10 interviewees representing other actors in software business. Cooperative Partners
Customer Subcontractor University / Research institution Intra-organizational unit Business service provider Industrial association Other company within industry Other Other company in province / area 0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
Figure 22 Cooperative Partners (n=34 of 100, response rate 34%, SPIN evaluation by LTT 2003, Forthcoming)
The survey of participants in SPIN technology programme indicates that business services were utilized by only about 20% of the companies studied (see Figure 22). However, it did not explain the reasons for low degree of usage. Potential explanations include: services are not available, companies are not aware of them, companies do not have dedicated resources to use them, or they are not satisfied with the supplied services. This sets forth the need for further research on knowledge-intensive business services. Innovation Services KIBS that derive their intermediate function primarily from the production and transfer of technology-related knowledge are called T-KIBS. They are particularly relevant for examination of service-mediated innovation, and can be shown to be highly innovative users of technology for their own process. (Bilderbeek et al. 1998) On the other hand, Nählinder and Hommen (2002) claim that in addition to T-KIBS there are also servicesrelated innovations, and they call these as professional services P-KIBS. Mostly service innovations coincide e.g. with new ways of distributing the product, new ways of interacting with the client, new ways of making sure that the product is produced according to a certain standard. In practice, most innovations are mixtures of major and minor changes and adaptations. However, the case of a completely new product or service innovation differs from offering an existing service using new distribution channel. Service innovations include also e.g. conceptual innovations, client-interface innovations, delivery system and organization innovations, and technological innovations. (Bilderbeek et al. 1998)
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Bilderbeek et al. (1998) and den Hertog (2000) have mapped services innovation patterns and the role of KIBS, and found various distinctive patterns. In supplierdominated innovation pattern (focused on technological innovation) innovation is derived from hardware industries in particular. In the innovation within services pattern, the actual innovation and implementation take place in the service firm itself (often combined technological and non-technological innovation). The client-led innovation pattern aims at responding to needs clearly articulated by clients, and in the innovation through services pattern, the service firms can influence the actual innovation process in client firm by providing inputs to the innovation process. Paradigmatic innovations are complex and pervasive innovations that affect all actors in a value chain in a very profound way. Innovation may be required to take place in all subsequent elements of the value system. This type of innovation implies completely new infrastructures, new types of knowledge and adaptation on the part of intermediate and final users. (Bilderbeek et al. 1998)
Figure 23 Pattern of services innovation (den Hertog 2000)
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Further innovation patterns can be drawn consequently, but it is crucial to notice that the role of service firms in innovation process can vary considerably, and the way service providers and client firms interact is central to the process of service innovation. (Bilderbeek et al. 1998) KIBS typically perform a catalytic role in knowledge-creating or innovation processes of client firms. Their role varies from adding innovative knowledge originating from the KIBS itself (KIBS as a source of innovation), originating innovative knowledge from another source to the client firm (KIBS as carrier of innovation) or helping out a client in implementing new knowledge mostly developed in house (KIBS as a facilitator of innovation). (Bilderbeek et al. 1998) Bilderbeek et al. (1998) also divide KIBS into supply side and demand side services. Many KIBS are providing services that are intensively tailored to their specific clients. However, this varies in different sectors; some KIBS companies produce very standardized products, while others supply very unique products. There is a different incidence of standardized versus specialized service products across the sectors. In earlier studies software business is seen to have less standardized knowledgeintensive services. On demand side the question of outsourcing and externalization becomes relevant. Coombs and Battaglia (1998) researched outsourcing of business services from collaboration and capabilities point of view, and emphasized the variety of length of relationships in different kind of governance forms. These governance forms involved levels from internal firm governance to alliances and outsourcing. Alliances were seen to be more appropriate to acquire new or changing capabilities or to coordinate new and existing ones, and outsourcing more appropriate for existing capabilities. The fundamental issues of networks are clearly identifiable in this context. Table 2 Preliminary Classification of Knowledge-intensive Business Services in the Software Industry Strategic Consulting Business Consulting IT Consulting Research Services Marketing & Communication Services Software Development Services Sales & Distribution Services After-Sales & Support Services Legal Services Human Resource Development Services Financing services IT Support Services
The KIBS identified at this phase of Study are presented in Table 2. The classification of these business services is based on literature and will be studied further in the next phase of the study.
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Business Service Development Areas Technological competencies Specialization and networking Existing competence centres Cooperation capabilities University research activities Local cooperative networks Local uncompelled development Research & education networks Product development culture and competencies Business competencies International competitiveness New competence centres Broad development programs Industry structures and strategies Knowledge on customer business Internal methods Knowledge on international demand
Program improved Significance
Cooperation of large and small companies Knowledge on dist ribution and exports
Low
Significance
High
Figure 24 Development Areas of Business Services (n=34 of 100, response rate 34%, SPIN evaluation by LTT 2003, Forthcoming) The evaluation study of the SPIN Technology programme (SPIN evaluation by LTT 2003, forthcoming) provides some indication about the existence of product development-related business services, but pointed out the lack of business services related to managerial business competence. Although the study was concluded within software product business, many of the companies actually had multiple business models of varied types. This gives some suggestions of the generalization of the results within software industry.
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4. Examples of Business Models and Value Nets in the Innovation Systems of the Software Cluster As the industrial network approach suggests, companies in a network are economic actors, which are inter-related through a web of resource ties and activity links (Håkansson and Johansson, 1992; Axelsson and Easton 1992). Actors perform and control activities that are based on control over critical resources, and include social content by developing relationships with each other through exchange processes. Resources can be physical, but more commonly, and especially in knowledge-intensive software business it is the knowledge resources of companies that are adapted to each other. Resource-ties between the companies are essential in order to innovate in using resources and to develop new ones. (Ford et al. 1998; Ford et al. 2002) Actors also have differential knowledge about activities, resources and other actors in the network. They act as information sources providing new opportunities and alternatives for other actors. However, they are goal-oriented and continuously have efforts to increase their control and to achieve better position in a network. Increasing the control over the network leads ultimately to the position presented by Jarillo (1988) where a company becomes the firm that sets up the network and takes pro-active attitude in the care of it. In the context of value nets this is called the hub company. However, Möller et al. (2002) claim that full control of other actor’s resources and activities cannot be acquired, but opportunities and challenges of control and coordination vary considerably in terms of novelty and complexity as expressed along the value-system continuum. What actors are engaged in a net for a given service? What roles and relationships do these actors have in their nets? Identification of value-creating nets is not straightforward. The firms have not necessarily identified their nets and roles in them. The search of value nets could, however, begin by studying individual business actors, their business models and partners they are cooperating with, and continue with depicting the actors of the network they are members of.
4.1 Business Models and Value Nets in the Software Service Business An example of the software as a service (SaaS) approach is presented by Messerschmitt (2000), who has described some value nets for digital services and use Application Service Provisioning (ASP) as an example of it. A typical ASP value network is depicted in Figure 25.
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Service supplier
Application software supplier System Service Integrator
Infrastructure software supplier
End user organization
Application service provider (ASP)
Infrastructure service provider (ISP)
Figure 25 Actors in a Software Subscription Business Network (Adapted from Messerschmitt 2000)
Wainewright (2001) has provided another approach to the ASP value chain. He emphasizes the relationships and cooperative forms in service provisioning business in order to create value. Many different types of providers work together to create each ASP solution, and there are many types of solution on offer. The circles in Figure 25 represent areas where the innovation activity potentially changes network configuration. Service integrators are the actors that end-user businesses recognize as ASPs. They bring together services for delivery as complete, managed solutions. Application providers create the software and applications from which solutions are assembled. This category encompasses the software developers and independent software vendors (ISVs), whose products ASPs and service integrators deliver. Access providers, in turn, take care of the last mile connection that allows users to access the network. Infrastructure operators look after the physical “backbone” elements of the network, and infrastructure service providers make up the software and services layer of the Internet computing infrastructure. They include application and ASP infrastructure providers (AIPs), who operate hosting centers that are specially equipped for application hosting.
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Figure 26 The ASP value chain (Wainewright 2001)
Figure 26 illustrates a theoretical value network in a standardized software services business.
4.2 Case Examples on System Solution and Software Product Businesses The cases selected for this part of the study include Akumiitti and BasWare. The Akumiitti case illustrates a distribution network of a system solutions business. The BasWare case illustrates a standard product business with both product development and distribution networks. Akumiitti Akumiitti is a mobile entertainment software provider with a number of mobile services delivered around the world via telecom operators. The company was founded in 1993 and has been emphasizing applications development for network environment since 1996. Akumiitti is owned by employees and international investors, and headquartered in Helsinki. The company established subsidiary in Singapore in 2001, and in 2002 the group had about 50 employees. The company has also caught attention of the Tornado Insider, which included the company in among its pick of Europe’s top 100 private IT companies in 2001. Akumiitti operates in global markets, and has customers on three continents. Products Akumiitti specializes in total mobile entertainment solutions to telecom operators, brandbuilders, and the entertainment industry. The clients are provided with mobile entertainment content through an Akumiitti Entertainment Service Center (ESC), which is a mobile entertainment software solution that enables service providers to offer their subscribers innovative entertainment services. The services include MMS multimedia
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content, Java games, EMS, polyphonic ringtones and a vast array of other content types and services via general web and mobile media interfaces. The other solution is Content Stream for Mobiles (COSMO), which creates a one-stop shop for a total Mobile Entertainment offering. The company’s solutions are used in more than 30 organizations serving 70 million subscribers. Akumiitti’s partners Akumiitti provides mainly platform products, e.g. “ESC platform” to mobile operators for the delivery of mobile content and services, such as ring tones and multimedia messages to the subscribers. Because of the nature of the products, Akumiitti’s direct customers are in fact distribution partners, which include both mobile operators and music producers globally. Product distribution is also supported by international value added resellers (VARs), who sell the solutions to operators and providers, and complementary technology partners (CTPs), who integrate the product as a part of their original product or service offering.
Akumiitti Distribution partners
Technology partners
(Customers)
(VARs, CTPs)
Content partners
Mobile operators Quam Germany
StarMedia
RadioMobil T-Mobile Czech Republic Motorola O2 Ireland
Starhome
Orange, UK & Denmark
WAP Portal
Radiolinja Finland
Newpalm
Telefonica Moviles Spain
Soundonweb Norway Moving Entertainment Finland HMM Finland Santatelevision.com Finland PowerFX Sweden
NetCom Norway
Nokia
Telemig Celular Brazil
Sony Ericsson
Amaztnia Celular Brazil
Motorola
CTBC Celular Brazil
Siemens
ComCel Colombia
Comverse
Blu Italia
Logica
Telia Finland
CMG
Movilnet Venezuela
SchlumbergerSema
Music producers
Setec
Universal Music UK
HP
Island Records UK
SmartTrust
Espresso Entertainment
Polydor UK BMG UK Sony Music Nordic EMI Finland
Figure 27 Akumiitti's distribution and technology partners
In addition to these partners, the company has technology partners, whom they cooperate with in order to provide new solutions. The above-mentioned three groups of actors can be combined as technology partners. The company has also content producer partners, who operate as content providers by utilizing Akumiitti’s products. The partners are listed in Figure 27.
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Distribution partners (Operators)
End customers (Subscribers)
VARs
Akumiitti
Distribution partners (Music producers) CTPs
Technology partners
Figure 28 Akumiitti's partners
Emphasis of partners in different product related business models Akumiitti has two main products, which have clearly different emphasis on the partners in business model context. The Entertainment Service Center (ESC) is mainly aimed at mobile operators and entertainment providers, such as music producers, and stresses the importance of distribution partners in delivering content to ultimate customers. Complementary technology partners and resellers are also of importance in this business model. Technology partners facilitate development of the products. The other product, the Content Stream for Mobiles (COSMO), in turn emphasizes content partners in providing content to the end users. Emphasis of partners in different product related business models is presented in Figure 29.
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End users (Subscribers)
Distribution partners
CTPs, VARs
ESC
Technology partners
Content partners
COSMO
Technology partners
Figure 29 Emphasis of partners in Akumiitti’s ESC and COSMO Business Models
The two lines of product offering comprise a quite different delivery partnership models. The ESC product offering is delivered more or less like a product through VAR’s and distribution partners. On the other hand, the COSMO delivery is based on more collaborative approach for the creation of content to mobile devices. Note that the number of actors in the illustration (see Figure 29) does not reflect reality. Interpretation of the Case The Akumiitti case illustrates an example of distribution networks in a system solutions business. The case indicates that the relationship between the vendor and its clients is more intensive in content production business compared to content delivery business. This indicates that the degree of collaboration is subject to the standardization of product offering as presented in our business model framework.
Figure 30 Decentralized Hub and Node Structure
The network configuration in the case of both Akumiitti’s solutions (ESC and COSMO) is interpreted as decentralised hub and node structure, where the case company itself is not the hub of the network (see Figure 30).
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BasWare Group BasWare is an international software company that develops, markets and sells packaged software applications for e-Business and financial management. Their headquarters is located in Espoo, and they also have an R&D unit in Tampere. The company has expanded rapidly and currently operates in global market area directly or through a partnership network. BasWare was originally founded in 1985, and the management buy-out occurred in 1990. The corporation has been listed on the Helsinki Stock Exchange HEX NM-list since the early 2000, and became famous for the numerous private investors and households interested in and investing in the company. Despite of the recent problems within high technology companies, and especially in ICT sector, the corporation has been fairly profitable and showed remarkable continuous organic growth of around 40%. As to their product and service offering, this growth is mainly generated by BasWare’s e-Business operations. Also, the company aims at global success and emphasizes the global markets. As a consequence, the growth of the international business operations exceeds 100%. BasWare has almost 250 employees at the moment, of which 60 are working in research and development units. Products BasWare produces software packages and solutions that can be rapidly implemented and operate on many platforms. A profound feature of the solutions is the interoperability and compatibility with major financial administration and ERP solutions. Products are targeted mainly at large corporations. They are separated into distinctive software product lines, which complement each other. The Electronic Business product family includes solutions for electronic purchase management, invoice processing, document archiving, and business transactions. The Financial Management product family includes solutions for business planning, group consolidation, and international accounting system (IAS) models. BasWare Electronic Business solutions are in use in more than one thousand organizations, and the aim is the global markets. The Electronic Market solutions include also ASP-based business in Finland related to electronic invoicing. The BasWare Financial Management solutions are in use in around two hundred Finnish organizations, and the company’s package software has been the market leader in its field in Finland for many years. Distribution network At the moment BasWare has subsidiaries in Sweden, Denmark, Germany, the Netherlands, France, UK, and US. The partnership network has lately undergone some change. In their latest interim report of January-March 2003 BasWare reported having a total of seven value-added resellers (VAR’s) providing full service in six different countries. The company is currently constructing a value added reseller network in France, and signed a new partner agreement in the mid-April 2003. In addition, the company has multiple sales and marketing, implementation and technology partners in various countries. In the context of business models, these partners can be defined as channel partners, as they clearly operate in and facilitate the distribution side of the business model concept. Ultimately, the channel partners compound the distribution network of the company, by offering products and services, and implementation and support related to them. They also act as third party actors, such as consultants, in order to facilitate sales. BasWare’s distribution network partners are listed in Figure 31.
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BasWare Oyj (Finland) BasWare AB (Sweden)
BasWare B.V. (Netherlands)
BasWare France (France)
BasWare GmbH (Germany)
BasWare A/S (Denmark)
Sweden:
Netherlands:
Xerox SAS
Germany:
WM-data eSolutions A/S
WM-data eApplicati ons AB
Canon Nederland N.V. Momentum B.V.
Inform. Consult GmbH
IXOS Danmark
ReadSoft Swets Farrington Sverige AB B.V. Norway:
IoCore B.V. I-Creative B.V.
Iocore AS
BasWare UK Ltd. (UK)
Finland: Proha Oyj Elisa Oyj Iocore Emce Solution Partner Oy Australia:
Austria: Infodesign GmbH
BasWare Inc. (USA)
ReadSoft A/S
TAG Services Pty Ltd
Excelleration B.V. e-Biz Consulting: Belgium: Iocore Belux
Andersen Business Consulting
BSG BVGA
IXOS Nordic
Figure 31 BasWare’s distribution partners
The vast majority of resellers and VARs operate in international markets, and act as local providers in new market areas. They are generally related to packaged eBusiness solutions, but some companies offer products and services in a variety of ways. Service Providers (ASPs) are companies that offer software as service hosting basis. However, they can also sell standardized products. EmCe Solution Partner Oy is an example of a service provider, that in addition to service hosting offers traditional packaged versions of BasWare Electronic Business solutions to customers. Service hosting has opened new market possibilities for BasWare in the SME sector, e.g. through EmCe’s strong market position in that sector. The hosted business concept has been in the interest of BasWare in Finnish market area, but the company also aims at global markets with this concept. As a specialty for the hosted business, partners also include service operators (e.g. Iocore) and infrastructure providers (e.g. Posti eKirje). Consulting and training services are generally accomplished by BasWare, but their consulting partners, e.g. Ixos Nordic offer e-Business consulting including BasWare products. In addition, the parties practice marketing co-operation and technical integration of their systems. Ixos Nordic can therefore be listed as a complementary technology partner (CTP) as it offers the solutions as a complementary extension to the original product and service offering. R&D Network The product development networks of BasWare include a set of companies, which act as technology partners (e.g. Oracle, Microsoft), application tool providers (e.g. Microsoft), subcontractors or component suppliers (e.g. ReadSoft), and localization partners. In order to find the best and the most compatible solutions, and to lessen the dependability on any suppliers, the partners have been changed during the years. BasWare has own quality assurance unit, but also incorporates external actors, such as technical universities of Helsinki and Tampere for the purpose. The combined set of
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BasWare’s distribution and R&D networks is presented in Figure 32. For the simplicity of presentation any second-tier relationships, e.g. activity or resource bonds between the BasWare’s partners are not presented. The company is presented as a hub company of the value net relating to their whole product and service offering. BasWare VARs and resellers, SMPs, Implementation partners
Service and Infrastructure Operators
BasWare Subsidiaries
Consulting partners
ASPs, CTPs Distribution Networks
BasWare
R&D Networks Localisation partners Technology partners Quality Management partners
Subcontractors
Component suppliers
Application development partners
Figure 32 BasWare’s distribution and R&D networks
Emphasis of partners in different product or services related business models According to the definition presented by Rajala (2003) earlier, a business model encompasses only a single product or product portfolio, and refers to a single company. If a company has multiple products or product portfolios, the amount of business models increases respectively. There is a considerable difference in the amount and emphasis of value network actors in the business models of different products. The Electronic Invoice Processing solution of Electronic Business solutions is identified as the spearhead product, and the internationalization and building of BasWare’s indirect distribution channels are largely related to it. Thus, the business model of Electronic Business solutions was discovered to include most actors in the distribution network. Generally, the current international VARs and SMPs are mainly offering the packaged Electronic Business solutions. Various actors can be identified also as ASPs and CTPs. The business model of Financial Management solutions is less rich in regard to the actors and activities by partners. However, also this business model has recently included applications hosting partner. Finally, the Business Transactions part of Electronic Business solutions has an interesting business model. As this business area is still emerging and does not have structured and wellestablished practices, in regard to the business models and value networks it is still dynamically changing. There are numerous hosting partners and CTPs related to this model, and some of them are also directly related to the research and development as members in R&D nets. The emphasis of partners in BasWare’s different business models is presented in Figure 33.
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CUSTOMERS
Hosting and service providers
VARs, CTPs, SMPs
Service providers
Service providers
Electronic Business
Financial Management
Business Transactions
BasWare
BasWare
BasWare
R&D
R&D
R&D
partners
partners
partners
Figure 33 Emphasis of partners in BasWare’s Business models
Interpretation of the Case The BasWare case illustrates a standard product business with both product development and distribution networks. The case comprises close collaboration in some business models and transactional relationships in other business models within the same company. This indicates that the degree of collaboration may vary in different business models depending on the standardization of product offering as presented in our business model framework.
Figure 34 Centralized Hub and Node Structure
The network configuration in the case of standardized software products (BasWare Financial Management and BasWare Electronic Business) is interpreted as centralized hub and node structure, where the case company is the hub of the network (see Figure 30). In the case of standardized software services (BasWare Business Transactions) the network configuration is interpreted as distributed multiplex structure, where the case company is not the hub of the network (see Figure 35).
Figure 35 Distributed Multiplex Structure
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The network in this case is forming around a facilitator, which is promoting the development of the emerging business. Conclusion of Cases The cases illustrated examples of business models and associated value nets that were identified in the businesses of the case companies. The cases are positioned to our framework and presented in Figure 36. Standardization of product & service
High
Akumiitti Software project business
System solution business
Distribution
Business Models
Collaborative
Low
BasWare Standard product/service business
Transactional
Software/system services business
Demand-Supply Nets
Renewal Nets
Emerging Business Nets
Value Nets
BasWare Business Transactions
Knowledge -intensive services
Efficiency Focused Innovation Activity
Efficiency/Effectiveness Focused Innovation Activity
Effectiveness Focused Innovation Activity
BasWare Electronic Business & Financial Management
Akumiitti Service Partners Providers, users, facilitators, etc.
Type of Service Communication service, business service, other
R
A
Role of Service Informative, Diagnostic, Advisory, Facilitative, Turnkey, Managerial
R
A
A
ESC & COSMO
R
A
A
A
Figure 36 Cases Positioned in the Study Framework
It should be noted that one company may have several business models simultaneously, as stated in the business model discussion in section two of this report. For example, the case of BasWare contains three different business models (Electronic Business, Financial Management and Business Transactions) all of them fitting into the category of standard products/services of our business model classification. Types of networks vary in these business models, and the roles and positions of the companies vary accordingly. The business models of Electronic Business and Financial Management are positioned in our analysis into the category of incrementally improved value system, because they emphasize the distribution partners in the value system. Instead, the Business Transactions business model was considered to improve the value system quite
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radically and was, thus, positioned into the category of emerging value systems. The role of the company in its value net varies for many reasons. In the case of the Business Transactions business model, we found out that the position of the business depends on that the company is participating as an equal actor in a network aiming at setting mutual standards for the business in an emerging business area. In the cases of Electronic Business and Financial Management businesses the company operates as a hub of a value network of several actors and aims at enhancing the distribution. Our study framework suggests that the knowledge-intensive services needed in the businesses vary according to the business models, state of the value system and the role and position of a company in the value network. At this phase of Study we did not enter into the analysis of the types and roles of knowledge-intensive services of the cases. These aspects will be covered in the next phases of the Study.
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5. Summary and Conclusions This report serves as a starting point for our further analysis of knowledge-intensive service activities KISAs for the software business sector from the perspective of business models and networks. KISAs are important for software companies in several ways. In many cases, small and medium-sized software companies do not have enough time, resources and skills to develop all needed competencies inhouse. Utilizing the surrounding network of KIBS providers, software companies can obtain necessary services in order to focus on core competencies and acquire lacking competencies. Therefore, network of KIBS providers can be argued to help and fasten the development of businesses within the ICT cluster. In this paper we have addressed the innovation networks within the Finnish software cluster by reviewing first the literature of both business models and value nets in the context of software business. We have also classified the basic types of software businesses utilizing a preliminary framework for categorizing business models. Furthermore, we have described concepts for modeling and analyzing the value nets of these software businesses. The purpose of this study was to establish a preliminary framework, conceptual tools and perspectives to serve as a foundation to analyze the roles of knowledge-intensive services in various innovation systems within the software cluster. This report is the first deliverable of the KISA-LTT project. The described models, frameworks, key terminology and scope will be used during the subsequent research phases. The evaluation of Spin technology program of Tekes (the National Technology Agency of Finland) indicated numerous KIBS providers that are of importance for software businesses. This points out the importance of identifying the roles of KIBS providers in different business models and networks. Based on the studies reviewed for this project, it is clear that in the software industry there is a multitude of business models with a great variety of cooperative forms of actors providing or using different services. In this report we have indicated that the partnerships identified in the product development phases are not the only value nets of innovation activity. In addition to product innovations, there are number of other forms of innovation, e.g. process innovations and organizational innovations. Especially organizational innovations emerge as new forms of creating and delivering value within the different value nets in the software industry. Partnerships identified in the product development phases are not the only value nets of innovation activity. Innovative nets can be facilitated in both research and development, and marketing, delivery and service side of the business model framework.
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6. Further Research In this study we have made an attempt to present a foundation for describing the role of knowledge-intensive service activities in association with different business models and value nets in the software industry. This report describes innovation processes and knowledge-intensive services from the value net and strategic network perspectives. The next phases of research in this project will encompass the description of knowledge-intensive services within the innovation systems of the software business. Phase two consists of a description and analysis of innovation activity and innovation processes in the SW cluster and the role of knowledge-intensive services in it. Phase three comprises a synthesis to improve innovations and innovation processes for the SW cluster. Questions of interest in the next phases of study include: −
Identification of KISA in the business model context (What knowledge-intensive services exist?)
−
What knowledge-intensive services are important in particular business models?)
−
Description of innovation processes and knowledge-intensive services from the value net and strategic network perspectives
In addition to this, the task of the third phase of study is to conclude a synthesis on the improvement of innovation activity through business models and strategic nets utilizing KISAs. Also, one interesting aspect to be kept in mind in the next phases of study is the effect of national technology programmes (like SPIN) in improving innovation activity through supporting development partnerships.
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