FUNDAMENTALS FOR AN IT-STRATEGY

FUNDAMENTALS FOR AN IT-STRATEGY TOWARDS MANAGING VIABLE KNOWLEDGE-INTENSIVE RESEARCH PROJECTS

PAUL PÖLTNER
Vienna University of Technology; Institute of Computer-Aided Automation
Research Group for Industrial Software (INSO); Wiedner Hauptstraße 76/2, 2nd Floor
Vienna, 1040 Vienna, Austria
E-mail: paul.poeltner@inso.tuwien.ac.at
THOMAS GRECHENIG
Vienna University of Technology; Institute of Computer Aided Automation
Research Group for Industrial Software (INSO); Wiedner Hauptstraße 76/2, 2nd Floor
Vienna, 1040 Vienna, Austria
E-mail: thomas.grechenig@inso.tuwien.ac.at
Based on existing research in the field of viable system modelling, social systems and the corporate genome, this paper presents a framework for the modelling and managing of viable knowledge-intensive research projects, which require the generation of new knowledge within a dynamic and complex world. This framework presents an overall look at the different levels which need to be established in order to implement a new, self-organised and viable system able to realise the defined aims of research projects.
1. Introduction
Current economic developments are driven by two major forces: information and communication. In our so-called information economy, which has existed as such for roughly a century, information is the driving force. Recent developments in internet technology are leading society in a new direction, that of the “networked economy,” where communication is a second major driving force (Benkler, 2006). The implied capitalistic development of this new economy is referred to by (Boltanski & Chiapello, 2006) as networked capitalism; the dominant values in this system are activity, flexibility, communication, creativity and autonomy. In order to cope with these developments, organisations must open their borders and connect with different partners within the value chain (Reichwald & Piller, 2006). As value chains have increased in complexity and flexibility over the last century, current research and development activities are no longer undertaken by a single organisation, but rather by teams of different partners from different organisations.
Interlinked with technological developments in the internet sphere are the new free software (Raymond, 2001) and open source software movements started in the 1990s (Stallman, Lessig, & Gay, 2002). These developments marked the opening of the frontier for universal participation in the creation of competitive software products. Recent technological developments, most notably that of Web 2.0, have established a new force for creating content (O'Reilly, 2005). (Howe, 2008) describes this amateur-created content as “crowdsourcing.” These new technologies allow new kinds of group-forming, where everybody can help in solving bigger problems (Shirky, 2008). These new communities become collectively intelligent and are able to solve complex problems no single individual could cope with. In this sense, collective intelligence is the phenomenon whereby connected people and computers can act more intelligently than a group of experts (Atlee u. a., 2008).
Confronted with these developments, organisations need to adjust their corporate cultures. They must shift from acting as closed source innovation teams to pursuing a so-called open innovation philosophy (Chesbrough, 2005). Ideas for new products and services need not only to come from inside the company but also from the “crowd” outside.
In order to cope with these new developments, organisations need to devise new forms of cooperation and collaboration. In the case of value chains, these new forms are known as collaborative network organisations (or virtual organisations, smart organisations, etc ) (Camarinha-Matos & Afsarmanesh, 2004). Collaboration networks can be as simple as the digitisation of some sort of information (e.g. Amazon), whereby physical processes are substituted by ICT, or as complex as phenomena like virtual organisations, collaboration networks and innovation networks, in which agile networks of partners cooperate in innovative ways. These new forms of collaboration save money and time, reduce the number of steps of interaction, prevent mistakes due to lack of information,and enhance knowledge and trust (Nagel, Walters, Gurevich, & Schmid, 2005).
The first part of Chapter Two of this article presents the theoretical basis for the model, which will be described in Chapter Three. Guidelines for the design of a research project will be discussed in Chapter Four.
2. Literature
2.1. System Theory and Social Systems
The basis of system theory was defined by Bertalanffy and Wiener. Bertalanffy, a biologist, was searching for a way to describe the relationships between different parts of a body. According to him, a system is considered to be open if it interacts with its environment (Heylighen & Joslyn, 1992). Cybernetics, defined by Ashby, provides a model to describe the behaviour of a machine. His Law of Requisite Variety states that “only variety in R can force down the variety due to D; variety can destroy variety” (Ashby, 1957).
Systems generally consist of two parts: an element (or node) and a relation (the node can also be a system in and of itself). Variety in a social system describes the system’s complexity, which encompasses its connectivity and dynamic (Schuh, Friedli, & Kurr, 2005). In order to control such a system, the variety must be changed, because according to Ashby’s Law of Requisite Variety, the variety of the control system must match the variety of the system (Masak, 2007).
The social system was first defined by Luhmann. He defines a system as a difference within the environment; the differentiation in a social system is made through communication. One of his key points is that social systems are self-referential: they can observe themselves as a system and define what it is that differentiates them from the environment. He calls this phenomenon “re-entry”. In his model, he differentiates between social systems. Society is a special social system which encompasses all other social systems and does not know any social system out of its borders. Society consists in this context only of communication. Luhmann defines an organisation as a social system which controls access to work. Developments such as education (school and university levels) as well as monetary and law systems prepare the environment for organisations. He notes that entry and acceptance to an organisation is a sort of membership, whereby one must agree to follow its rules and guidelines for observation of and communication with the environment. In other words, the organisation defines one’s worldview (Luhmann, 2009).
2.2. Management cybernetics
The founder of management cybernetics was Stafford Beer, who researched in the field of living systems and defined the Viable System Model (VSM). In this model, a system is viable if its identity is sustainable. In order to be viable according to the VSM, a system needs to have five subsystems: System 1 is the operative element, which is responsible for daily business interactions with the environment. System 1 can consist recursively of subsystems, which need to have the same structure as the upper system (p.e. business unit, subsidiary, etc,). System 2 is responsible for coordination between the different subsystems of System 1; following the guidelines of Ashby’s system theory, it balances complexity through variety management. System 3 controls and regulates the whole system, and tries to optimise resources. System 4 interconnects with the environment, defines the overall vision, and models the system’s organisation and environment. Finally, System 5 defines the identity of the system (Masak, 2007).
In order for an organisation to cope with complexity, Beer suggests variety engineering (management), which assumes that a system is self-organised and therefore has the ability to control and regulate itself. Any business activity can be split into three systems: the management, the organisation and the environment. The management reduces or increases the organisation’s complexity according to the needs dictated by its environment. The management of the system receives data from the environment and, using a model, evaluates their potential for viability of the organisation. Therefore, a management process cannot be better than that model it is based upon. The management process itself is split into three parts: the operative level, which guarantees efficiency (productivity and quality), the strategic level, which guarantees effectiveness, and the normative level, which guarantees that all stakeholders’ requirements are fulfilled. Intelligent organisations fulfil all these management requirements recursively at every level, which implicates that they are also self-organised at every level (Schwaninger, 1999).

According to Kruse, the problem with self-organised systems is that people have the tendency to stick with a certain strategy and try to optimise this (Theory of Best Practice). This theory of self-organised systems can be applied to organisation forms in environments which are unstable (dynamic) and complex, where at some point in time best practice has stopped working (Kruse, 2004). At some point of instability, known as a bifurcation point, self-organised systems have the ability to reach a new, unpredicted level of stability. This can only be realised in an unstable environment (Heylighen, 1999). In order to cope with a dynamic market, the management needs to find a balance between stability and instability.
One of the central elements of self-organised systems is the theory of iterations, which states that complex systems can be built up by means of several recursive iterations. In a social system, simple rules and stable corporate cultures are the mechanisms necessary to build complex systems. These rules create a reality which limits the complexity of the problem space. Thus, the corporate culture defines the set of rules for a complex, self-organised system to evolve (Kruse, 2004).
2.3. (Knowledge) Management model
Any self-organised system needs a model to proof its concepts. The definition of the corporate strategy necessary for the model’s development hinges on a specific view the environment. Porter’s “The Five Competitive Forces That Shape Strategy” is useful for defining this strategy and orienting companies on the market (Porter, 2008). Porter’s so-called market-based view presents different strategic business units, which are in compliance with the requirements of the segmented markets.
Another approach is the resource-based view (Grant, 1991), which concentrates on the strengths and weaknesses of the company’s resources and capabilities. A strategy based on this view identifies resource gaps in order to fulfil customer requirements more effectively than competitors do. Grant views resources and capabilities as the primary sources of profit for a firm. Resources are the basic units, and can be seen as the input to processes (capital equipment, skills, employees, etc.). Capabilities are the result of a sum of resources; they can be described as complex patterns of coordination between people and between people and other resources.
In the information economy, knowledge can be seen as the most important strategic resource (Zack, 1999). Zack therefore suggests linking knowledge of strategic opportunity with the SWOT (strength, weakness, opportunities, and threats) analysis. He separates the knowledge resource into core knowledge, advanced knowledge and innovative knowledge. Innovative knowledge is the knowledge required to lead the industry. The knowledge-based view can be seen as the link between strategic management and knowledge management.
Maier presents an integrated concept of a process-oriented knowledge management strategy, which focuses on the market and on internal resources (Maier, 2007). The first step in this strategy should be the identification of resources related to knowledge management. The second step evaluates these resources against the market. Next, the resources deemed to be strategically relevant are combined to form capabilities. Finally, looking to the market, strategic business fields are defined. Knowledge management in this context supports the integration of resources into capabilities. Dynamic capabilities are comprised here of organisational and managerial processes (Teece, Gary Pisano, & Amy Shuen, 1997). With his process-oriented view, Maier integrates the resource-based and market-based views into one framework. Business processes are defined in accordance with customer requirements along a value chain, while the knowledge management process helps to evolve new core competences to implement business processes (Maier, 2007).
Knowledge management itself is an interdisciplinary field, which can be divided into many layers, each of which can be isolated and studied independently. At the heart of knowledge management is a core theory, which incorporates a specific knowledge process and organisational, social and managerial elements (Schwartz, 2007). The bare minimum necessary for an efficient knowledge management strategy is a technical system. Knowledge networks provide an efficient means to manage knowledge sharing and creation. In order for these networks to evolve, they again need facilitating conditions, a knowledge process and an architecture (Back, Enkel, & Krogh, 2006).
This article will draw on the theories of Scharmer (Scharmer, 2007), which will be discussed in Chapter 4. One of Scharmer’s key concepts is that of a five-movement process to collectively generate new knowledge. The first movement, called co-initialing, involves forming a group (project team) and creating a common sense of purpose for the upcoming project. The second movement, called co-sensing, entails the observation of the environment and the collective gauging of its potential. In the third movement, co-presencing, everything is let go and is opened up to a possible future and defined goal. In the fourth movement, this goal is prototyped, and in the fifth and final movement it is implemented in an evolving ecosystem. Open innovation can help to create such a future in a larger environment within the internet.
2.4. The capability-driven organisation
(Aurik, Jonk, & Willen, 2002) present the concept of the capability-driven organisation, which goes a step further than Meier’s knowledge management strategy. At the core of this concept is the idea that the company consists of a sum of capabilities. Each capability is represented as a gene of the company, and the sum of an organisation’s capabilities is represented as the corporate DNA. (Aurik u. a., 2002) write: “Just as each human gene is a piece of DNA working as an instruction manual for a particular human characteristic, each business capability is a component of the value chain that makes a unique contribution to a company’s output.” The sum of all corporate DNAs is the corporate genome. A capability is an element of a value chain and consists of a set of activities and assets. Capabilities on which the company has some edge will help business excel. These capabilities can be capitalised on through coordination with other organisations in the creation of agile value chains. At the same time, capabilities with low business value can be bought in. In the end, every value chain will be separated into a sum of capabilities, with each organisation responsible for one capability, and one organisation responsible for the orchestration of all the different capabilities. A value chain can be broken up into three layers of chains: the physical value chain, which can be seen as the real production chain, the transaction value chain, which defines the transaction and control processes, and the knowledge value chain, the highest layer (Aurik u. a., 2002).
3. A model for self-organised viable collaborative networked organisations
As previously discussed, collaborative networked organisations (CNO) will become more and more relevant in the near future. Companies need to cooperate with different partners, both internal and external, in order to work agilely in accordance with market requirements. The model to be presented provides a means to manage such a structure.
3.1. The model

Fig. 1: Viable collaborative networked organisation
Figure 1 represents the whole model. At its core, every organisation consists of a corporate DNA. This corporate DNA is the sum of the organisation’s capabilities, or “genes” (e.g. forecasting, manufacturing, accounting). For this model, a capability is considered to be a combination of different resources (Grant, 1991), which are the result of a process of organisational learning (Maier, 2007) and produce some business value. Every company is viable in the sense of the viable system model and therefore consists of five subsystems (as described in Chapter 2.2) (Masak, 2007). Following the theory of Luhmann, every organisation is a social system which differentiates itself by communication from its environment (as presented by the bubble in Figure 1). Knowledge management (itself another capability of the organization) is responsible for the development and enhancement of these capabilities. The model assumes an organisation which is viable and self-organised. Therefore, the viable organisation contains a management level, which is responsible for the normative and strategic management of the system itself (Schwaninger, 1999).
It is crucial to define the rules and the vision of the company from the outset in order for the whole system to be manageable in dynamic and unstable environments. Depending on the complexity and strategy of the organisation, Subsystems 1 to 5 may comprise one or more capabilities (described as S1 to S5 in Figure 1), with several Systems 1 for different operational activities. Using the theory of the corporate genome, the whole corporation can be described both in terms of capabilities and in terms of resources. Resources can include processes, learning cycles, management methods, know-how, skills, etc.
After defining company vision and taking stock of resources, the next step is to create a viable collaboratively networked organisation. (Aurik u. a., 2002) emphasise that there are two kinds of strategies: those focused on single capabilities, and those focused on capabilities along a value-chain. The organisations in this model are single capability-focused, and therefore provide only for some specific parts of a value chain. When two or more separate companies agree on forming a collaborative organisation, however, each organisation can provide for some specific part of that newly formed organisation with its own capabilities. In other words, the DNA of the different organisations will be mixed, creating a value chain to realise defined customer requirements at the market level. Ultimately, a new system, which is a subsystem the other companies will be created. This system is able to recreate itself if necessary and is responsible for the implementation of a specific value chain. This value chain can be separated into three different layers: the knowledge value chain, the transactional value chain and the physical value chain (as described in Chapter 2.4). Furthermore, the newly created viable organisation must be able to communicate with the crowd and therefore open its borders for new innovations.
3.2. Strategic management
The strategic management process itself must be performed recursively at every level in the system (System 4 in the VSM and S4 in Figure 1). The management process is again based on the rules and policy (the identity and corporate culture) of the system, which must once again be defined (System 5 and S5 in Figure 1). On a strategic level, the first step is an identification of the company resources and an analysis of the completive environment with a SWOT analysis. In the next step, the capabilities are crystallised (Maier, 2007) and the core strategic products and services of the organisation are defined. This type of forming leads to a sort of matrix organisation. This is differentiated by the fact that capabilities themselves are customer-focused, since every capability can be integrated into another value chain. Additionally, if the capability of one organisation is not strong enough, it can be replaced by the capability of another organisation (Aurik u. a., 2002). The value chain, defined by the market manager in System 4, will lead the strategic orientation, thus focusing on customer requirements and combining the different capabilities into value chains.
In order to create a viable collaboratively networked organisation, System 4, or the market manager, starts with a SWOT analysis, evaluating strengths, weaknesses, opportunities and threats. Next, the network can be initiated through an analysis of its market possibilities and an identification of possible partners. The next step involves the planning of the new system itself: the different corporate DNAs are brought together and combined along the three value chain layers to form a new, stronger value chain. During the creation of the organisation, the system is self-optimised through the five systems of the viable system model. In the initiation phase, the identity and corporate culture of the different organisations are combined and implemented in System 5. As this newly formed organisation is part of the other systems as well, it will also be coordinated and controlled by Systems 2 and 3 (Schubert, 2008).

4. Implementation of a collaboratively networked organisation for research projects

Fig. 2: Viable collaborative networked research organisation

The requirements for the implementation of research projects in the European environment are particularly high, as public research organizations are unable to fulfil all the needed capabilities themselves. David and Metcalfe note that “knowledge of markets and organisations and factor input availability are key aspects for innovation and not the specialisation of public research organisations. So a division of labour exists between public research organisations and companies.” (European Communities, 2008) In the following, a viable collaboratively networked organization will be developed in accordance with the five steps of Theory U (Scharmer, 2007).
4.1. Co-Initiation
The first phase for the implementation of a new complex research project is the formation of the new system. The lead partner, who takes the initial steps, needs to define a starting vision for the new project.
Once the first idea has been defined for the project, a socioeconomic analysis will define the baseline for further investigations (European Chemicals Agency, 2008). This socioeconomic analysis investigates the society, the culture and the people that the new project might have an impact on. Next, the lead partner must undertake a SWOT analysis to investigate its own capabilities in relation to the identified environment (Schubert, 2008).
Following this analysis, possible partners with specific capabilities need to be identified. In this phase, it is important to evaluate a core group of people (organisations) who share a common (Scharmer, 2007). At this stage, the research proposal should be created and the general conditions (in terms of intellectual property, time and money) defined. If this step goes wrong, the whole new system cannot evolve.
4.2. Co-Sensing
In the second phase, the new viable collaboratively networked research organization will be born. In this step, the corporate DNA (the sum of capabilities) of the different participating partners will be brought together and orchestrated into a new organisation. The value chain for this research model will be defined according to the Theory U process. The new system identity and strategy must be defined based on the genes of some partners in Systems 4 and 5 (Schwaninger, 1999) of the viable system. The rules and the vision for the system will help the system to be self-organised so that every participating party can work independently toward the overall aim of the project.
In the next step, a chain of “Systems 1 – 2 – 3” will be created in order to bring the system to life. Starting with the physical value chain, the different partners will provide different research facilities with different capabilities. In the second layer, a integrated knowledge management process needs to put into action. Based on the concepts of service-oriented architecture, this layer can be divided into different levels. The lowest level is the IT Infrastructure of the different partners. Within these IT Systems, different knowledge services are provided, which can be orchestrated to form an overall virtual ba (Pulier, 2005) (Krafzig, Banke, & Slama, 2004) (Maier, 2007). In the knowledge value chain, different capabilities like patents, licenses, developing methods, sharing experiences and the embedding of the crowd will be implemented in the overall system.
The described system must be open to its environment in order to communicate and exchange information. This will lead to higher viability, which will in turn help to solve more complex socioeconomic problems.
In the next step, the system will be able to start to operate. In this step, observation, listening, and dialogue are crucial to gain a sense of the problem space (Scharmer, 2007).
4.3. Co-Presencing
The creative part of the process takes part in the co-presencing phase. At this point, the system needs to investigate possible future outcomes, and open its heart, its mind and its will. At this stage, after several rounds of observation, listening and dialogue, the system is ready to greet the new possible future (Scharmer, 2007).
4.4. Co-creating
After the future has come (Scharmer, 2007), the precise project vision must be defined and the strategic steps distributed to the different participating partners in the project. The coordination of activities will be led by System 2 in accordance with the overall rules and culture of the system. Starting with a core team and an open policy, the new project can evolve in an open ecosystem. The aim is to develop a prototype of the possible future. This needs to be done in several iterations and must incorporate feedback from the stakeholders (Scharmer, 2007). The viable organisation must support this process by through self-organisation and open exchange with its environment. New technologies from different fields of research can also support this process, depending on the required complexity.
4.5. Co-evolving
The last step of the viable collaborative network research organisation is to implement the newly created reality into a supporting infrastructure (Scharmer, 2007). At this point, the viable system can launch its newly created capabilities into an evolving ecosystem by creating new subsystems which will keep on working. In addition to capabilities, the viable system will have also created resources (artefacts), which can flow back to the different mother systems and be used to realise new capabilities beneficial to the system’s overall aim, identity and strategy.
5. Conclusion and outlook
The theoretical framework presented here is a starting point for further discussions in the field of management of collaboratively networked organizations. Many different disciplines factor into the setting up of such a system; knowledge management (which again depends on a wide variety of scientific fields) is just one of these important fields. Technology is also crucial, and a great deal of emphasis must be placed on the technological implementation of such an agile system. The flexible combination of different capabilities in the technological layer requires a high level of standardisation and interoperability, for which service-oriented architecture is just one starting point for further investigation.
On a management level, the theories of Stafford and the Corporate Genome Theory present yet another perspective on the corporate structure. As in other modern management theories, companies need to be flat and flexible and focus on their core capabilities.
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