**2. Concepts of enterprise knowledge management modeling**

A rough overview of the concepts and their dependencies involved for development of the control view-based approach to Enterprise Knowledge Management modeling is given in Fig. 1.

Fig. 1. Dependency map of major concepts involved for development of Enterprise Knowledge Management framework

*Semiotics* and *Control theory*. The top two concepts in Fig. 1 are on the level of theories, namely, "*Semiotics*" and "*Control theory*". Semiotics gives for Enterprise Knowledge Management modeling the concept of *Semiotic tetrahedron* of FRISCO [Falkenberg et al., 1998], which affords a predefined methodological structure for *Organizational System* modeling using *Internal modeling* paradigm.

*The Control theory* gives the concept "*Control System*" for developing the *control view*  approach to *Organizational System management* modeling. The concept "*Control System*" is a background for developing the feed back loop of the *Management Control System*, formally defining the Enterprise *Management* as a hierarchy of *Management Functions* comprised of *Data, Knowledge* and *Goal* components and interactions in the information feedback loop. The internal structure of *Management Function* is information processing framework defined as *Elementary Management Cycle* (Gudas, et al., 2005).

The *External modeling* paradigm. The *External modeling* paradigm denotes the branch of empirical Enterprise modeling methodologies and methods, relevant and formally

Knowledge-Based Enterprise Framework: A Management Control View 183

Fig. 3. The Internal modeling paradigm is relevant to White Box principle

Fig. 4. The semiotic tetrahedron of FRISCO (Falkenberg et al., 1998)

*relation of symbols to reality")* (Falkenberg, et al., 1998).

semantic model of Real World).

The Semiotic tetrahedron of FRISCO. The concept of *semiotic tetrahedron* is a methodological structure for understanding the relation between "model"and "business domain" ("*the* 

The *semiotic tetrahedron* in the Fig.4 (*Domain, Conception, Actor (Interpreter&Representer)*, *Representation*) is key predefined structure for understanding the *internal modeling* paradigm and its application for *Organizational System* management modeling as well as for understanding the concepts *Interpretation* and *Elementary Management Cycle* (Gudas et al, 2005). The Semiotic tetrahedron reflects the view of FRISCO to the relation of reality (*Domain*) and model (*Representation*): there is a *domain* (the Real World) observed by analyst called the *Actor*. As a result of these activities (namely, *perception* and *interpretation*), the *Actor* forms *A Conception* (an internal semantic model of Real World) and *A Representation* (an external

The semiotic triangle is a helpful tool for explaining the enterprise management as a semiotic process – a sequence of steps and transformations of information (data, knowledge and goals).

described by "Black Box" approach (Gudas, 2009]. Enterprise modeling is a well developed field of business process modeling, closely related with Business Process Re-engineering (BPR) and Information System Engineering (ISE), development of CASE methods and tools. Enterprise modeling affords a set of methodologies, enterprise architecture modeling frameworks, methods, standards and languages for manifestation (representation) of empirical information acquired by system analyst in the business domain. Enterprise models developed for BPR and ISE needs correctly empirically represents the identified data (information flows), processes, events, organizational units, workflows or few other component types (constraints, business rules, etc.) of business domain.

The development of Knowledge –Based Modeling methods is related with understanding differences of two modeling paradigms: *an external modeling* paradigm and *internal modeling* paradigm.

An external modeling paradigm is based on the Black Box model of W. Ross Ashby (Fig. 2). A Black Box model highlights the origin of empirical models: components and (functional) behaviour of a system are acquired by external (empirical) analysis and represented by analyst using definite modeling language (notation).

Fig. 2. The External modeling paradigm is relevant to Black Box model

The *Internal modeling* paradigm. The *Internal modeling* paradigm denotes the branch of *Knowledge-based approaches* to modeling, relevant and formally described by "White Box" approach (Gudas, 2009). The *Internal modeling* paradigm gives background to extend Enterprise modeling views and aspects, a set of Enterprise components' types and interactions.

*An Internal modeling paradigm* is based on the White Box principle (Fig. 3). *A White Box*  principle highlights the origin of knowledge-based approaches - the representation (model components, structure and the operation of a system) are validated by analyst against some predefined knowledge (theory) related to the internal transformations of *Domain*. For instance, the high level *business model -* Value Chain Model (VCM) (Porter, 1985), as well as the Strategic Business&IT Alignment Model (SAM) (Henderson, Venkatraman, 1990), is classified as internal models of Enterprise. *A Control view-based* approach to Enterprise management and knowledge modeling (Gudas, et al., 2005) fits to *Internal modeling* paradigm based on the White Box principle. The Internal modeling paradigm (Fig. 3) highlights the formal model of *Domain* as the essential component of knowledge-based modeling.

described by "Black Box" approach (Gudas, 2009]. Enterprise modeling is a well developed field of business process modeling, closely related with Business Process Re-engineering (BPR) and Information System Engineering (ISE), development of CASE methods and tools. Enterprise modeling affords a set of methodologies, enterprise architecture modeling frameworks, methods, standards and languages for manifestation (representation) of empirical information acquired by system analyst in the business domain. Enterprise models developed for BPR and ISE needs correctly empirically represents the identified data (information flows), processes, events, organizational units, workflows or few other

The development of Knowledge –Based Modeling methods is related with understanding differences of two modeling paradigms: *an external modeling* paradigm and *internal modeling*

An external modeling paradigm is based on the Black Box model of W. Ross Ashby (Fig. 2). A Black Box model highlights the origin of empirical models: components and (functional) behaviour of a system are acquired by external (empirical) analysis and represented by

The *Internal modeling* paradigm. The *Internal modeling* paradigm denotes the branch of *Knowledge-based approaches* to modeling, relevant and formally described by "White Box" approach (Gudas, 2009). The *Internal modeling* paradigm gives background to extend Enterprise modeling views and aspects, a set of Enterprise components' types and

*An Internal modeling paradigm* is based on the White Box principle (Fig. 3). *A White Box*  principle highlights the origin of knowledge-based approaches - the representation (model components, structure and the operation of a system) are validated by analyst against some predefined knowledge (theory) related to the internal transformations of *Domain*. For instance, the high level *business model -* Value Chain Model (VCM) (Porter, 1985), as well as the Strategic Business&IT Alignment Model (SAM) (Henderson, Venkatraman, 1990), is classified as internal models of Enterprise. *A Control view-based* approach to Enterprise management and knowledge modeling (Gudas, et al., 2005) fits to *Internal modeling* paradigm based on the White Box principle. The Internal modeling paradigm (Fig. 3) highlights the formal model of *Domain* as the essential component of knowledge-based

component types (constraints, business rules, etc.) of business domain.

Fig. 2. The External modeling paradigm is relevant to Black Box model

analyst using definite modeling language (notation).

paradigm.

interactions.

modeling.

Fig. 3. The Internal modeling paradigm is relevant to White Box principle

The Semiotic tetrahedron of FRISCO. The concept of *semiotic tetrahedron* is a methodological structure for understanding the relation between "model"and "business domain" ("*the relation of symbols to reality")* (Falkenberg, et al., 1998).

The *semiotic tetrahedron* in the Fig.4 (*Domain, Conception, Actor (Interpreter&Representer)*, *Representation*) is key predefined structure for understanding the *internal modeling* paradigm and its application for *Organizational System* management modeling as well as for understanding the concepts *Interpretation* and *Elementary Management Cycle* (Gudas et al, 2005). The Semiotic tetrahedron reflects the view of FRISCO to the relation of reality (*Domain*) and model (*Representation*): there is a *domain* (the Real World) observed by analyst called the *Actor*. As a result of these activities (namely, *perception* and *interpretation*), the *Actor* forms *A Conception* (an internal semantic model of Real World) and *A Representation* (an external semantic model of Real World).

The semiotic triangle is a helpful tool for explaining the enterprise management as a semiotic process – a sequence of steps and transformations of information (data, knowledge and goals).

Fig. 4. The semiotic tetrahedron of FRISCO (Falkenberg et al., 1998)

Knowledge-Based Enterprise Framework: A Management Control View 185

and knowledge make rigorous discussions of Knowledge Management difficult" (Hicks, et

One major problem related with enterprise management and knowledge management is a problem of understanding *data, information, knowledge, goals* and their inter-relationships (Muller, Schappert, 1999), (Liew, 2007), (Hicks, et al., 2006). In the classical interpretation (based on the semiotic triangle) the concept "data"is associated with syntax (has no meaning), information corresponds to semantic (*information* is context interpreted *data*) and *knowledge* takes the pragmatic part (*knowledge* is action interpreted information) (Muller,

The definitions of data, information, and knowledge could be concerned as problem, because data and information, as well as information and knowledge are perceived as

And what about one more type of information – a g*oal (an objective)*, representing the key feature of Organizational Systems and management activities – a goal-driven behaviour? The semiotic tetrahedron of FRISCO extends the content of semiotic triangle including *an Actor* (interpreter and representer of percepted (acquired) *Data*) related with *Knowledge* and *Information* components. *An Actor* must be considered as an active component of *Organizational System* (as goal driven component), i.e. an Actor is considered as a goal seeking component of semiotic triangle. Consequently, the modified semiotic triangle that includes a *Goal* component interrelated with *Data, Information* and *Knowledge* components is

The inter-relationships of *Data, Knowledge, Goal, Information* and *Real World (RW)* are presented in the Fig. 7. A Goal is considered as domain interpreted information (pragmatic aspect – RW related). Knowledge is considered as action interpreted information (pragmatic

Enterprise modelling. Enterprise modelling usually involves the definite set of aspects: function, behaviour, information, resource and organization (Vernadat, 2002) (GERAM, 1999). In addition, it is possible to distinguish one more aspect of an Enterprise modelling, defined as *the management point of view*. From this point of view, the new major Enterprise modelling constructs are identified. In the management control systems' literature, similar

aspect – management related, predefined (constrained) by *Goal*)).

interchangeable, it depends on activities and situations (Muller, Schappert, 1999).

al., 2006).

Schappert, 1999).

presented in Fig. 6.

Fig. 6. The modified semiotic triangle

Enterprise management&control as White Box. *A control* is an activity of managing or making control over some another activity. *A control system* is a system for controlling the operation of another system. A feedback control concept is applied to technical, social, economic systems modeling as well as to enterprise management and knowledge management modeling (Gudas, et al., 2005).

Definitions of management mostly include activities as follows: *planning, organizing, directing, and controlling* of the enterprise's operation so that objectives can be economically and efficiently achieved through others. So, the definition of the *management* includes the *control* concept*.* 

Enterprise (Organizational System) is managed by management and control system, which performs a definite set of *Management Functions* {Fj} aimed to control enterprise *Processes* {Pi} (Fig. 5)**.** Any *Management Function* is comprised of two components, namely, *Information Processing* (goal driven data processing and decision making) activity and *Information Feedback loop*.

Enterprise (management and control) modeling is based on the assumption as follows: any Enterprise is under control if each Enterprise *Management Function* includes the closed loop cycle of information transitions: a) takes (makes measurements of) *a Process state attributes*, b) calculates and decides a *Process control attributes* and in that way c) influences the *state of a Process*.

Fig. 5. The White Box model of Enterprise *Management Function* 

According to Firestone (Firestone, 1999), organizational knowledge management activity "is aimed at integrating the various organizational agents, components, and activities of the organizational knowledge management system into a planned, directed process producing, maintaining and enhancing an organization's knowledge base". The enterprise knowledge base along with its organizational and technological components constitutes enterprise knowledge management system (KMS). Knowledge management activity, as any other enterprise activity, is arranged in a hierarchy, which can have some reasonable number of interrelated levels.

Data, information, and knowledge. The analysis of *knowledge management* area requires well defined conceptual basis – relevant definitions at least for *management, data, information, knowledge, goal/objective* concepts*.* "The lack of consistent definitions for data, information,

Enterprise management&control as White Box. *A control* is an activity of managing or making control over some another activity. *A control system* is a system for controlling the operation of another system. A feedback control concept is applied to technical, social, economic systems modeling as well as to enterprise management and knowledge

Definitions of management mostly include activities as follows: *planning, organizing, directing, and controlling* of the enterprise's operation so that objectives can be economically and efficiently achieved through others. So, the definition of the *management* includes the

Enterprise (Organizational System) is managed by management and control system, which performs a definite set of *Management Functions* {Fj} aimed to control enterprise *Processes* {Pi} (Fig. 5)**.** Any *Management Function* is comprised of two components, namely, *Information Processing* (goal driven data processing and decision making) activity and *Information* 

Enterprise (management and control) modeling is based on the assumption as follows: any Enterprise is under control if each Enterprise *Management Function* includes the closed loop cycle of information transitions: a) takes (makes measurements of) *a Process state attributes*, b) calculates and decides a *Process control attributes* and in that way c) influences the *state of a* 

According to Firestone (Firestone, 1999), organizational knowledge management activity "is aimed at integrating the various organizational agents, components, and activities of the organizational knowledge management system into a planned, directed process producing, maintaining and enhancing an organization's knowledge base". The enterprise knowledge base along with its organizational and technological components constitutes enterprise knowledge management system (KMS). Knowledge management activity, as any other enterprise activity, is arranged in a hierarchy, which can have some reasonable number of

Data, information, and knowledge. The analysis of *knowledge management* area requires well defined conceptual basis – relevant definitions at least for *management, data, information, knowledge, goal/objective* concepts*.* "The lack of consistent definitions for data, information,

Fig. 5. The White Box model of Enterprise *Management Function* 

management modeling (Gudas, et al., 2005).

*control* concept*.* 

*Feedback loop*.

*Process*.

interrelated levels.

and knowledge make rigorous discussions of Knowledge Management difficult" (Hicks, et al., 2006).

One major problem related with enterprise management and knowledge management is a problem of understanding *data, information, knowledge, goals* and their inter-relationships (Muller, Schappert, 1999), (Liew, 2007), (Hicks, et al., 2006). In the classical interpretation (based on the semiotic triangle) the concept "data"is associated with syntax (has no meaning), information corresponds to semantic (*information* is context interpreted *data*) and *knowledge* takes the pragmatic part (*knowledge* is action interpreted information) (Muller, Schappert, 1999).

The definitions of data, information, and knowledge could be concerned as problem, because data and information, as well as information and knowledge are perceived as interchangeable, it depends on activities and situations (Muller, Schappert, 1999).

And what about one more type of information – a g*oal (an objective)*, representing the key feature of Organizational Systems and management activities – a goal-driven behaviour? The semiotic tetrahedron of FRISCO extends the content of semiotic triangle including *an Actor* (interpreter and representer of percepted (acquired) *Data*) related with *Knowledge* and *Information* components. *An Actor* must be considered as an active component of *Organizational System* (as goal driven component), i.e. an Actor is considered as a goal seeking component of semiotic triangle. Consequently, the modified semiotic triangle that includes a *Goal* component interrelated with *Data, Information* and *Knowledge* components is presented in Fig. 6.

#### Fig. 6. The modified semiotic triangle

The inter-relationships of *Data, Knowledge, Goal, Information* and *Real World (RW)* are presented in the Fig. 7. A Goal is considered as domain interpreted information (pragmatic aspect – RW related). Knowledge is considered as action interpreted information (pragmatic aspect – management related, predefined (constrained) by *Goal*)).

Enterprise modelling. Enterprise modelling usually involves the definite set of aspects: function, behaviour, information, resource and organization (Vernadat, 2002) (GERAM, 1999). In addition, it is possible to distinguish one more aspect of an Enterprise modelling, defined as *the management point of view*. From this point of view, the new major Enterprise modelling constructs are identified. In the management control systems' literature, similar

Knowledge-Based Enterprise Framework: A Management Control View 187

Fig. 8. Domains of Enterprise in the Strategic Alignment Model (SAM) (Henderson,

classified as internal model of Organizational System (Fig. 8).

c) aligns its knowledge management activity with its strategy.

support of the management of its business processes.

Enterprise Architecture methodologies and frameworks (see Table 1).

The model is aimed to support the integration of information technology (IT) into business strategy by advocating alignment between and within four enterprise domains and is

The major constructs of SAM - enterprise domains (namely, *Business domain* and *IT domain*) and views (*Business strategy*, *Business infrastructure, IT strategy, IT infrastructure)* are selected as criterions for the analysis of the major concepts of various Enterprise Modeling and

The interactions of Business and IT domains and views, namely *functional integration* and *strategic fit* are considered as knowledge manipulation processes, supported or not supported by enterprise information systems (data bases and knowledge bases). Alignment of business strategy and IT strategy is an intensive knowledge process, it requires particular knowledge about at least four views: *Business strategy*, *Business infrastructure, IT strategy, IT* 

Knowledge -Centric Enterprise Structure. The knowledge-centric organization, regardless of whether its products are tangible or not, here is defined according to the concept of knowledge-based organization, presented by M.H.Zack (Zack, 2003) and is based on the resource-based view of the firm; namely, knowledge-centric organization: a) recognizes knowledge as a key strategic resource, b) rethinks their business processes in the knowledge-oriented sense (i.e. "it takes knowledge into account in every aspect of its operation and treats every activity as a potentially knowledge-enhancing act." (Zack, 2003),

Even if the definition of the knowledge-centric enterprise do not emphasizes the use of the information technologies (IT) in the enterprise, it should be noted, that research presented here is concerned with the contemporary enterprise, which extensively uses IT for the

Contemporary organizations use the integrated data repositories which have to be identified

within the enterprise model (the *Data Base* and *Data Warehouse* components in Fig. 9). In order to illustrate the conception of the contemporary enterprise, which is knowledgecentric enterprise, the SAM model has to be complemented by additional components. According to the definition of the knowledge-centric organization, it rethinks its processes in the knowledge-oriented sense and aligns its *knowledge management activity* with its strategy. Consequently, in the knowledge-centric enterprise there exist some infrastructure for the knowledge management – the knowledge management (KM) layer; thus SAM model

Venkatraman, 1990)

*infrastructure* of enterprise.

aspect is called *the management control perspective* (Anthony, Govindarajan, 2003), (Merchant, 1999). The management control perspective focuses on the organisation management and control issues; meanwhile the particularity of *the management-control point of view* is the refinement of information processing constructs and their interactions in the Enterprise. Some business systems are able to choose their own behaviour. Business processes in such systems are guided by the *decision-making mechanism*. That is why the modelling of *management process* and *management information flows* must be taken into account as mandatory aspects of Enterprise modelling. The scope of management process modelling is the internal structure of management information (Enterprise knowledge, data, objectives) and the management information processing as well.

Fig. 7. Inter-relationships of data, information, knowledge, goal, and reality (domain)

It is claimed in Systems and Control Theory that a system can be controlled effectively only if some *feedback loops* (also called *control loops*) are implemented. Consequently, the components of the control loop should be included into Enterprise model.

It should be pointed out that the term *Control flow* (in the sense of *workflow*) is associated with the concept *Activity* in the UEML 1.0 (Vernadat, 2001). However, the earlier version of UEML core (UEML, 1999) includes separate modelling constructs *Function* and *Process,* and that makes this UEML core closer to the Enterprise modelling from the management point of view.

Further, the Control Theory defines the typical structure of a *System* – a real world System with internal "mechanism" of control. *A System* involves the following mandatory (complex) constructs: a real world *Process*, a *Control System* and a *Feedback Loop* which creates *an Information flow* (*Control flow*) between a *Process* and a *Control System* (Gupta and Sinha, 1996). *A Control System* performs a definite set of activities (*Functions,* related to a definite *criterion)* aimed to control *a Process*. Any *Function* takes (makes measurements of) *a Process state attributes*, calculates a *Process control attributes,* in this way makinginfluence on the state of a *Process.* 

Before we go further, let us define that any item (structural unit) of *a System* is named *an object. An object* could be conceptualised as *an entity* or *a class* (of the UML), or in some other way in accordance with particular modelling methodology.

#### **3. Four domains of enterprise strategic alignment**

Henderson and Venkatraman have analysed business-IT alignment issue and proposed a Strategic Alignment Model (SAM) (Henderson, J., Venkatraman, N., 1990).

aspect is called *the management control perspective* (Anthony, Govindarajan, 2003), (Merchant, 1999). The management control perspective focuses on the organisation management and control issues; meanwhile the particularity of *the management-control point of view* is the refinement of information processing constructs and their interactions in the Enterprise. Some business systems are able to choose their own behaviour. Business processes in such systems are guided by the *decision-making mechanism*. That is why the modelling of *management process* and *management information flows* must be taken into account as mandatory aspects of Enterprise modelling. The scope of management process modelling is the internal structure of management information (Enterprise knowledge, data, objectives)

Fig. 7. Inter-relationships of data, information, knowledge, goal, and reality (domain)

components of the control loop should be included into Enterprise model.

way in accordance with particular modelling methodology.

**3. Four domains of enterprise strategic alignment** 

Strategic Alignment Model (SAM) (Henderson, J., Venkatraman, N., 1990).

It is claimed in Systems and Control Theory that a system can be controlled effectively only if some *feedback loops* (also called *control loops*) are implemented. Consequently, the

It should be pointed out that the term *Control flow* (in the sense of *workflow*) is associated with the concept *Activity* in the UEML 1.0 (Vernadat, 2001). However, the earlier version of UEML core (UEML, 1999) includes separate modelling constructs *Function* and *Process,* and that makes this UEML core closer to the Enterprise modelling from the management point

Further, the Control Theory defines the typical structure of a *System* – a real world System with internal "mechanism" of control. *A System* involves the following mandatory (complex) constructs: a real world *Process*, a *Control System* and a *Feedback Loop* which creates *an Information flow* (*Control flow*) between a *Process* and a *Control System* (Gupta and Sinha, 1996). *A Control System* performs a definite set of activities (*Functions,* related to a definite *criterion)* aimed to control *a Process*. Any *Function* takes (makes measurements of) *a Process state attributes*, calculates a *Process control attributes,* in this way makinginfluence on the

Before we go further, let us define that any item (structural unit) of *a System* is named *an object. An object* could be conceptualised as *an entity* or *a class* (of the UML), or in some other

Henderson and Venkatraman have analysed business-IT alignment issue and proposed a

and the management information processing as well.

of view.

state of a *Process.* 

Fig. 8. Domains of Enterprise in the Strategic Alignment Model (SAM) (Henderson, Venkatraman, 1990)

The model is aimed to support the integration of information technology (IT) into business strategy by advocating alignment between and within four enterprise domains and is classified as internal model of Organizational System (Fig. 8).

The major constructs of SAM - enterprise domains (namely, *Business domain* and *IT domain*) and views (*Business strategy*, *Business infrastructure, IT strategy, IT infrastructure)* are selected as criterions for the analysis of the major concepts of various Enterprise Modeling and Enterprise Architecture methodologies and frameworks (see Table 1).

The interactions of Business and IT domains and views, namely *functional integration* and *strategic fit* are considered as knowledge manipulation processes, supported or not supported by enterprise information systems (data bases and knowledge bases). Alignment of business strategy and IT strategy is an intensive knowledge process, it requires particular knowledge about at least four views: *Business strategy*, *Business infrastructure, IT strategy, IT infrastructure* of enterprise.

Knowledge -Centric Enterprise Structure. The knowledge-centric organization, regardless of whether its products are tangible or not, here is defined according to the concept of knowledge-based organization, presented by M.H.Zack (Zack, 2003) and is based on the resource-based view of the firm; namely, knowledge-centric organization: a) recognizes knowledge as a key strategic resource, b) rethinks their business processes in the knowledge-oriented sense (i.e. "it takes knowledge into account in every aspect of its operation and treats every activity as a potentially knowledge-enhancing act." (Zack, 2003), c) aligns its knowledge management activity with its strategy.

Even if the definition of the knowledge-centric enterprise do not emphasizes the use of the information technologies (IT) in the enterprise, it should be noted, that research presented here is concerned with the contemporary enterprise, which extensively uses IT for the support of the management of its business processes.

Contemporary organizations use the integrated data repositories which have to be identified within the enterprise model (the *Data Base* and *Data Warehouse* components in Fig. 9).

In order to illustrate the conception of the contemporary enterprise, which is knowledgecentric enterprise, the SAM model has to be complemented by additional components. According to the definition of the knowledge-centric organization, it rethinks its processes in the knowledge-oriented sense and aligns its *knowledge management activity* with its strategy. Consequently, in the knowledge-centric enterprise there exist some infrastructure for the knowledge management – the knowledge management (KM) layer; thus SAM model

Knowledge-Based Enterprise Framework: A Management Control View 189

when transforming business enterprise into Knowledge-Based Business Enterprise (Gudas,

The scheme presented in Fig. 10 sums up findings made in the chapter. The peculiarity of this abstraction is that it clearly separates the Knowledge domain from Data domain, in contrast to other conceptual enterprise models (e.g. presented in (Hettinger, 2003) or (Iyer, Gottlieb, 2004). For instance, the well-known ISA framework (Zachman, Sowa, 1992) does not concern knowledge domain at all. Though comparing ISA model with the presented abstraction of the Knowledge-Based Enterprise domains, different purposes and tasks of the

The concept of the *knowledge base* is also used in the sense of computerized meta-data repository when implementing large-scale data management and business intelligence systems in the contemporary organizations. Meta-data repository helps to provide business data as well as data about data for business and for IT departments and to make adequate decisions regarding data management in organizations. Contemporary organizations need to manage not only data, but the whole data-information-knowledge continuum; this is why the role and structure of the enterprise repository or enterprise knowledge base have to

The concept of computerized knowledge base become important with the emergence of such intensively computer-based organizational forms as supply chains, virtual organizations etc. Organizations require for having not only shared data bases in virtual environment, but also knowledge about those data, as well as about the data structure and semantics; knowledge about its infrastructure and processes; process management up to

The solid lines in Fig. 10 represent the knowledge management activities which are used to assure integration of the enterprise knowledge base into overall enterprise management and development framework, as well as support of inter-domain alignment tasks. Knowledge management activity has to be managed and explicitly modelled either (Gudas, Brundzaite,

The scope and structure of the organizational knowledge in the knowledge management literature is investigated. This structure has the name of *organizational memory* or *corporate* 

ISA and Enterprise Knowledge Modelling framework should be noted.

change adequately too (Gudas, Brundzaite, 2006a)**.** 

Fig. 10. Two worlds of the knowledge-based enterprise

**5. Knowledge-based enterprise structure** 

Brundzaite, 2006a)**.**

strategic intentions.

2006a).

is complemented with additional structural elements – business *knowledge and IT knowledge management components* (see Fig. 9).

Fig. 9. The Knowledge-Centric Enterprise structure

To sum up, business and IT domains of SAM can be decomposed into three levels of management hierarchy: strategic management level, knowledge management level, and business management&control level.

The management processes on the strategic level and knowledge management level are *knowledge –driven* because these top level management activities require particular knowledge about strategies and management methods, and etc. The management processes on the business and IT management and control level require definite (time related) data about the state of business and IT processes, thus this level of management essentially is *data-driven.*

Knowledge-centric enterprise, as any other contemporary organization, possibly uses the integrated data repositories which are presented in the SAM as the Enterprise *Data repositories* component (Fig.9).

Even if knowledge management activities of Knowledge-Centric Enterprise are under control, there is a possibility for the knowledge flow bottlenecks left, because the valuable knowledge two interrelated enterprise domains required for the management solutions about *(i.e. Business domain, IT domain*) typically resides in the heads of the managers and employees, in the unstructured documents etc. As the business-IT alignment is continuous decision making process, it should be supported with reliable information (*Real World d*ata and *digital* data) and knowledge (*Real World* knowledge only) accessible across the enterprise.
