knowledge-based approach to business and it ...

A. Lopata, M. Ambraziunas, S. Gudas

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Structural Transformations in Business Development ---------TRANSFORMATIONS IN --------

Lopata, A., Ambraziunas, M., Gudas, S. (2011), “Knowledge-Based Approach to Business and IT Alignment Modelling”, Transformations in Business & Economics, Vol. 10, No 2 (23), pp.60-73.

BUSINESS & ECONOMICS © Vilnius University, 2002-2011 © Brno University of Technology, 2002-2011 © University of Latvia, 2002-2011

KNOWLEDGE-BASED APPROACH TO BUSINESS AND IT ALIGNMENT MODELLING Audrius Lopata1

Martas Ambraziunas2

Saulius Gudas3

Affiliation: 1 Kaunas Faculty of Humanities Vilnius University Muitines g. 8 LT – 44280, Kaunas Lithuania Affiliation: 2 Information Systems Department Kaunas University of Technology Studentu g. 50 LT–51368, Kaunas Lithuania

Kaunas Faculty of Humanities Vilnius University Muitines g. 8 LT – 44280, Kaunas Lithuania

Affiliation: 1 Kaunas Faculty of Humanities Vilnius University Muitines g. 8 LT – 44280, Kaunas Lithuania Affiliation: 1 Department of Information Systems Faculty of Informatics Kaunas University of Technology Studentu g. 50 LT-51368 Kaunas Lithuania Tel.: +370 37 453445 E-mail: [email protected]

E-mail: [email protected]

E-mail: [email protected]

1

Audrius Lopata, PhD, is Assoc. Prof. at Kaunas Faculty of Humanities, Vilnius University (Lithuania) and Kaunas University of Technology (Lithuania). Dr. A. Lopata is the author and co-author of more than 35 research publications in English and Lithuanian languages published in Springer’s Lecture Notes of Computer Science (2004), Business Information Processing (2009, 2010), Lecture Notes in Artificial Intelligence (2010) and other ISI Web of Science indexed and Lithuanian journals. The main fields of scientific research incorporate knowledge based information systems engineering, requirements management techniques, knowledge based CASE tools. Dr. A. Lopata has experience in international (Nordforsk MINE, EUREKA, ERASMUS) as well as in Lithuanian (BPD2004 – ESF – 2.5.0 – 03 – 05/0010, ESF/2004/2.4.0-K02-VS-01/SUT-219, VP2-1.3-ŪM-02-K-01043) projects related activities.

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Structural Transformations in Business Development 2

Martas Ambraziunas, acquired Bachelor Degree from Vytautas Magnus University in 2006, MSc in Business Informatics from Kaunas Faculty of Humanities, Vilnius University in 2008), currently is a PhD student in Informatics at Kaunas Faculty of Humanities, Vilnius University (Lithuania). The main fields of scientific research are knowledge based information systems engineering, requirements management techniques, model driven information systems engineering. Ambraziunas has five-year work experience in developing business information systems. 3

Saulius Gudas, PhD, is Full Professor at the Department of Informatics, Kaunas Faculty of Humanities, Vilnius University (VU KHF), Lithuania. Since 2008, Dean of VU KHF. Education: in 1969–1974, studied at Kaunas University of Technology, Lithuania; in 1982 defended the PhD dissertation on the topic „Synthesis of Algorithmic Structure of Information Systems for Manufacturing Objects”; in 2005, passed the Doctor Habilitation procedure on the topic „Modelling of Knowledge-based Information Systems Engineering Processes“. Research directions are as follows: knowledge-based enterprise modelling, knowledge-based information system engineering and CASE methods. Prof. S. Gudas is the author and co-author of more than 135 research publications. Received: July, 2010 1st Revision: November, 2010 2nd Revision: January, 2011 Accepted: April, 2011

ABSTRACT. The main scope of the research is to improve the alignment between Business and IT domains. The article concerns deployment of Strategic Alignment Model’s Strategy Execution Perspective using Knowledge Based and Model Driven Information System Engineering approaches. It will ensure efficient IT and Business alignment process by reducing impacts of human factor.

KEYWORDS: business and IT alignment model, strategic alignment model, knowledge- based information system engineering, model driven architecture, enterprise Meta-model, UML.

JEL classification: M15, Y80.

Introduction The majority of Information Technology (IT) project failures (about 68% (Asadi et al., 2008, p.419)) are caused by insufficient analysis of problem domain and inconsistent user requirements. One of the reasons is that IT is still thought of as a function that “serves” the business, rather than the one that plays an integral part in the business's operations (Champy, 2006). Often the IT systems are inflexible due to hard-coded business rules as well as business-related constraints. These systems resist change and hinder the business effort to deliver the service or product efficiently and on time (Grigoriu, 2009). Changes in business TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development strategy and infrastructure are common and necessary in order to maintain competitive advantages; therefore, modifications of IT infrastructure should be as fast and accurate as possible to support modified business infrastructure and strategy. The main goal of this research is to efficiently improve the alignment between business and IT domains. Usually, IT infrastructure changes are made by omitting detailed enterprise modeling and user requirements’ analysis stages of Information System Development Life Cycle (SDLC) and directly proceeds to development and testing stages. This leads to serious project problems, such as failures of parallel IS functionalities, logical gaps in project documentation and system architecture and other malfunction cases. In order to improve risk management and avoid these failures, even minor changes in IT infrastructure should go through all stages of SDLC (Development, Testing), although changes performed in this manner are very time and resource consuming. Most medium and large organizations use Enterprise Data Warehouse (EDW) or internal database systems. EDW may be used as the main project data source for IS engineering and IS reengineering process, although in a traditional manner the project data acquisition process is performed in empirical way, when the user directly communicates with the system’s analyst or developer. It means that the problem domain knowledge acquisition process heavily relies on the system’s analyst and the user. The expert plays a pivotal role in the problem domain knowledge acquisition process, and few formalized methods of knowledge acquisition control are taken into consideration (Melnikas, 2008; Gudas, 2010). Currently, despite of the existing system engineering tools, user requirement analysis largely depends on the expertise of the system’s analyst and the user (Chen, 2008; Wegrzyn, 2010). The knowledge stored in repository of IS Development tool is not verified through formalized criteria, thus it is necessary to use advanced data capture techniques that would ensure iterative knowledge acquisition process during which missing or incorrect data elements are obtained and fixed (Kamińska, 2009; Lentner, 2007). Object Management Group (OMG) provides Model Driven Architecture (MDA (OMG, 2003)) approach to information systems engineering where MDA focuses not only on technical details, but also on functional requirements and system architecture. Model Driven Architecture allows a long-term flexibility of implementation, integration, maintenance, testing and simulation. This means that enterprise modeling and user requirements engineering stages of SDLC are yet not enough covered by MDA. There is a lack of formalized problem domain knowledge management and user requirements acquisition techniques for composition and verification of MDA-Based models. In order to solve this problem, enhancement of MDA approach by the best practices (ENV 12 204, 1996), (ENV 40 003, 1990), (Vernadat, 2001) of Knowledge-Based IS engineering (including Enterprise Knowledge repository) can be used. The proposed enhancement will intellectualize MDABased models’ composition process by improving their consistency and decreasing the influence of the empirical information in composition process. Knowledge-Based Subsystem will ensure MDA-Based models’ verification against formal criteria defined by the Enterprise Meta-Model (EMM). It will reduce the risk of project failures caused by inconsistent user requirements and insufficient problem domain knowledge verification (Lopata et al., 2010a, 2010b, 2010c). 1. Businesses and IT Strategic Alignment Model J.C. Henderson and N. Venkatraman were the first to describe in a clear way the interrelationship between business strategies and IT. Strategic Alignment Model (SAM) was TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development created in order to describe these relationships. It consists of four domains: Business Strategy Domain, Business Infrastructure Domain, IT Strategy Domain, IT Infrastructure Domain and relationship between them. Conceptually, the model is based on two building blocks: strategic fit (integration) and functional integration. Strategic fit recognizes that the IT strategy should be articulated in terms of an external domain (how the organization is positioned in the IT environment) and an internal domain (how the IT infrastructure should be configured and managed) (Grembergen, 2004, 2009). Business Domains’ Strategic fit describes same relationships with similar attributes but focused to on the business. There are two types of functional integration (Table 1): “strategic and operational. Strategic integration is the link between the business strategy and IT strategy. Operational integration covers the internal domain and deals with the link between business infrastructure and IT infrastructure. Functional integration considers how choices” made in the IT domain impact those made in the business domain and vice versa (Henderson et al., 1999). Table 1. Relations among Strategic Alignment Model’s elements

Source: created by the authors.

Strategic Alignment Model is conceptual and does not provide a practical framework to implement business and IT alignment, although there are alignment mechanisms developed and used in organizations to achieve the business and IT fusion: the business systems’ planning, critical success factors, the competitive forces’ model, the value chain of M.E. Porter, and business process reengineering (Henderson et al., 1999, p.472). These Mechanisms are oriented to business, not to IT. Strategic Alignment Model describes four basic alignment perspectives: Strategy Execution, Technology Transformation, Competitive Potential, and Service Level. In this article implementation of Strategy Execution Perspective using Knowledge Based MDA method will be discussed. 2. Conceptual Basis for Business & IT Alignment Modeling There are two basic types of IS development Life Cycle (LC) (McKay, 2006) - linear and iterative. All SDLC in one or another way have the following stages: Initiation Phase, System Concept Development Phase, Planning Phase, Requirements Analysis Phase, Design Phase, Development Phase, Integration and Test Phase, Implementation Phase, Operations and Maintenance Phase, Disposition Phase (McKay, 2006). Linear LC (e.g. Waterfall and its modifications) punctuates planning, time schedules, target dates, budgets and implementation of an entire system at one time. This process is heavyweight (includes a lot of documentation and formal procedures), inflexible, slow, costly TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development and cumbersome due to significant structure and tight controls. IS development methodologies of this type can be used when project is large, complex and complicated. Iterative IS development methodologies develop a system through repeated cycles (iterations) and the result of each iteration is more sophisticated than the previous one. There is a great variety of iterative IS development methodologies from heavyweight RUP to lightweight Agile methods. Depending on the project size, problem domain, developers’ and user expertise one of these IS methodologies can be used for a particular project. In 2001 OMG presented MDA (Model Driven Architecture (OMG, 2003)) approach which specifies the appliance of system models in the software development life cycle. System models are often presented as a combination of drawings and a text (OMG, 2003). This approach allows business managers to directly influence IS development process, thus improving IS development process by avoiding logical gaps and communication misconceptions between the user and the developer. The main idea of MDA is to separate the specification of system functionality from the specification of the implementation of that functionality on a specific technology platform (OMG, 2003) (“What” to do from “How” to do). This approach allows business managers to directly influence IS development process. Conceptual MDA structure is presented in Figure 1.

Source: Lopata et al., 2010a, 2010b, 2010c. Figure 1. The Main MDA Components

OMG defines the following key points of MDA: § Definition of Computation Independent Model (CIM) which specifies system requirements of a particular problem domain (it can also be named Business Model); § Transformation of CIM to Platform Independent Model (PIM). User requirements specifications will be converted to systems architecture components and functionality methods during this process; § Transformation of PIM to Platform Specific Model (PSM) where abstract system model (“What” to do) is upgraded with targeted platform’s specific information (“How” to do). PIM provides system’s architecture and functionality without platform’s specific information and technical details. PSM is constructed on the basis of PIM enhancing it with platform’s specific details, e.g. system implementation and deployment information. § Transformation of PSM to a particular platform programming (for example: Java, C# etc.) as well as to other artifacts, such as executable files, direct link libraries, user documentation etc. Furthermore, the above described transformations can be performed backward using reversed engineering (Lopata et al., 2010a, b, c). Three different techniques can be applied to perform the following transformations: TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development § Manual: system’s analyst creates and studies the composition of all types of the defined MDA models and manually performs all the necessary transformations. § Semi-Automatic: system’s analyst uses analysis and design tools that allow performing model creation and transformation process more efficiently. § Automatic: transformation tool completes the transformation process without the system analyst’s interference. Business and technical aspects of an application or integrated system can each evolve at its own pace – business logic responding to business need, and technology taking advantage of new developments – as the business requires (OMG, 2003). An Enterprise Data Warehouse (EDW) is “a subject-oriented, integrated, timevarying, non-volatile collection of data in support of the management’s decision-making process” (W.H. Inmon). It is a centralized repository that stores the data from multiple information sources and transforms them into a common, multidimensional data model for efficient querying and analysis. Enterprise Data Warehouse is a part of a bigger system, which generally consists of an ETL (Extraction, Transformation, and Loading) tool, a Database, a Reporting tool and other facilitating tools, such as a Data modeling tool. The Enterprise Data Warehouse should have multiple subject areas. Most of the data are transactional data (e.g. purchase records) from one or more data sources. In order to ensure integrity and consistency of the enterprise data, an Enterprise Data Warehouse should include all enterprise activity fields, such as marketing, sale, finance, human resources etc. This EDW can be used in decision support systems, trend analysis, logistics and inventory management, as well as in IS Knowledge-Based development process (Figure 2).

Source: created by the authors. Figure 2. Knowledge–Based Enterprise Information Architecture TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development 3. Knowledge-Based IS Development Process Knowledge-Based IS engineering is the process, in which the following equivalent partners – knowledge resources participate: the user, the system analyst, the enterprise knowledge repository and the system architect. Information System in traditional computerized IS engineering is developed empirically, beginning with user requirements acquisition, analysis and specification. In addition, modern scientific management trends, such as Knowledge–Based enterprise management, knowledge management and Knowledge– Based IS engineering, are starting to use IS engineering and development tools – CASE systems for development of Enterprise IS. In this way some time is saved and IS project solutions are qualitatively improved. Knowledge-Based IS development supposes that all stages of IS development life cycle are supported by the Enterprise Knowledge-Based Subsystem. The Enterprise Knowledge-Based Subsystem consists of three parts: the Enterprise Meta–Model (EMM), the Enterprise Model (EM) and model transformation algorithms (Lopata and Ambraziunas, 2010a). EM is a “representation of the structure, activities, processes, information, resources, people, behavior, goals, and constraints of a business, government, or other enterprises” (Fox et al., 1998). EMM is a formal specification that regulates the formation order of EM. Model generation algorithms handle transformations between the third party models and EM. The conceptual scheme of Knowledge-Based Subsystem’s integration in ISE lifecycle is presented in Figure 3.

Source: created by the authors. Figure 3. The Principal Scheme of Knowledge-Based IS Engineering

“The basic feature of the Enterprise Meta-Model is the interaction of Process and Function. A Process is a partially ordered set of steps, which can be executed to achieve the desired material end result. A Process consumes material resources and produces some material output, i.e. a product. Processes are triggered by one or more Event occurrences. Function is a workflow element, which controls processes. Function is a complex construct. The structure of the Function is defined on the basis of the formal definition of management function. At least one Function controls each Process, transforming material input flow into material output flow. Function accomplishes at least one organizational Goal or its subgoal. TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development Process and Function are performed by Actor. Usually, Actor is an employee or organizational unit, but in some cases it can be software or hardware as well. Environment initiates Event and influences enterprise Goals. Some work in this area of research has been done already” (Butleris et al., 2006, p.503), (Skersys, 2008, p.145), (Gudas et al., 2005, p.175), (Gudas et al., 2009, p.417). 4. Enhancement of MDA with Knowledge-Based Engineering Components According to the survey (Asadi et al., 2008, p.419), “leading MDA-Based ISE methodologies should be improved in the following areas: requirements engineering, CIM construction, system models validation and verification against problem domain processes, as most of the methodologies (Asadi et al., 2008, p.419) do not provide sufficient information about which of MDA-Based tools are the most efficient. These problems can be solved by enhancing the MDA approach with Knowledge-Based Subsystem. This subsystem is able to handle MDA models (CIM, PIM) validation process against the Enterprise Meta-Model. EMM ensures completeness and consistency of EM, which is created on the basis of CIM (forward method) or PIM (reverse method)”. Development of Knowledge-Based Approach to Business and IT Alignment Modeling requires definition of formal CIM structure. Although the existing numerous techniques (Ambler, 2009) describe CIM construction procedures, most of them are not formalized enough and this has a negative influence on the EM constructs and composition. The usage of modified workflow diagrams (Lopata et al., 2008, p.456), (Lopata et al., 2009 p.417) can solve such shortcomings and properly support the suggested method. XMI (XML Metadata Interchange) compatible third party tools are able to use Knowledge-Based Subsystem’s data for transformation between particular MDA models. It ensures the availability of wide range of development alternatives for MDA models transformations. Conceptual MDA structure enhanced with Knowledge-Based Subsystem is presented in Figure 4.

Source: Lopata et al., 2010a, 2010b, 2010c. Figure 4. The Main Knowledge-Based MDA components

The set of modified workflow models (Gudas, 2009, p.417) can be used for CIM construction. “After CIM model is constructed, iterative verification (against EMM) process is started and is repeated until all the incorrect or missing CIM’s elements are updated and TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development corresponds to internal structure of EMM. The process leads to the creation of EM, which can be realized as a relational or object oriented database” (Gudas, 2009, p.417). The following step is the transformation of EM to PIM. The result of this transformation conforms to XMI standard that third party tools can use this model for the next stages of Information Systems Engineering life cycle. Additionally, PIM transformation process can be performed backwards using reverse engineering technique. Every XMI compatible PIM can be validated against Enterprise Meta-Model that helps to update the existing Information Systems with the missing components, as well as remove the unnecessary ones. 5. Guidelines for Using Knowledge-Based MDA Method to Strategic Alignment Model Efficient business and IT alignment is a challenge that not all organizations succeed to achieve. It is a state when business organization is capable to effectively use information technology (IT) in order to achieve business goals. Strategic Alignment Model proposed by J.C. Henderson and N. Venkatraman deals with this issue. 5.1 Strategy execution perspective using knowledge-based-MDA method Strategy Execution Perspective is most common enterprise perspective of Strategic Alignment Model (Henderson et al., 1999, p.472). Usually, implementation of new business strategy results in changes of business infrastructure. That leads to IT infrastructure modifications as well. In most cases changes in IT infrastructure influence only changes in software architecture. Software architecture modifications could also impact hardware and network infrastructure. IT infrastructure domain-related software can be updated regarding to user requirements by using two alternatives: IS engineering and IS reengineering. In traditional manner these updates are performed by experts and the success of business and IT alignment process heavily depends on competence and communication skills among business and IT staff. In that case business and IT infrastructures alignment process becomes a complex issue that often causes the following business and IT alignment problems: · Information system is not implemented on schedule. · Exceeded Information System‘s development costs. · The Information System‘s functionality does not correspond to the user requirements. The usage of Knowledge-Based MDA process can improve implementation of this Business and IT alignment perspective by the following means: · Monitoring of changes alignment between Business and IT domains; · Validation against formal criteria of existing and new business infrastructure; · Automatic or semi-automatic generation of new software elements in response to changes in business infrastructure; · Improved project management by ensuring better quality of communication between Business and IT domains staff. · Software elements are generated using real time data; · Flexibility. Software elements can be generated to many different platforms. In most cases large and medium organizations have Enterprise Data Warehouse which contains data from all four domains of Strategic Alignment Perspective model discussed above. The EDW ensures that all organization units use data from the same data source, thus ensuring real time data availability and integrity. Warehouse internal structure is not TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development standardized and may vary depending on particular organization’s specific processes and goals. EDW is the main data source for Enterprise Knowledge Based Subsystem which ensures quality of Business and IT alignment process. In large organizations Enterprise Data Warehouse (with Strategic Goals Base (Gudas et al., 2006, p.334)) can be sufficient to fulfill Knowledge-Based Subsystems needs. At this case data are transformed and Enterprise Model is created according to the rules and constraints from particular Enterprise Meta-Model. Enterprise Model which is saved in Knowledge-Based Subsystem contains the data only about organizations’ activities and related information. Small organizations can have smaller EDW or do not have it at all. In this case specific data of the domain are acquired directly from Strategic Alignment Model domains using different techniques. Strategy execution perspective and the role of Knowledge-Based Subsystem are presented in Figure 5.

Source: created by the authors. Figure 5. Strategy Execution Perspective Supported by Knowledge Based MDA Method

Data flows among Strategic Alignment Model domains and Enterprise storage elements are presented in Table 2. Table 2. Data flows among Strategy Alignment Model domains and Enterprise Knowledge storage elements Enterprise Warehouse Business Strategy Business Infrastructure

Data

Domain output: Business goals. Domain output: Business rules, existing business infrastructure data.

Knowledge-Based Subsystem

Strategic Goals Base

-

Goals

Domain input: Model of recommended business infrastructure.

-

IT strategy

Domain output: IT goals Goals Domain output: Domain input: Existing IT infrastructure Recommended IS infrastructure IT infrastructure data, updates, IT platform data working software Relationship between EDW (uses Strategic Goals Base) and Knowledge-Based Subsystem. Acquires particular data that are needed for reengineering and alignment process like: business processes, functions, actors, goals. Source: created by the authors. TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development In order to use Knowledge-Based Subsystem in Business and IT alignment process some specific data (e.g. actors, functions, processes) are needed. The data are acquired in indirect manner through the Enterprise Data Warehouse. Business strategy domain provides business goals to data warehouse. Business goals are defined by the top level business managers and are initiated by business environment. IT goals are defined by the top level IT managers. Business infrastructure domain provides business rules, existing business constraints, processes, functions, and actors’ related data. IT infrastructure domain provides information about existing IT infrastructure including current software and hardware platform, software artifacts and working system. Using mappings, KBS can extract this data to create Enterprise Model and then validate it according to the Enterprise Meta-Model. 5.2 The main steps of knowledge-based strategy execution perspective The process is started when the top business manager creates a new business strategy and defines the business goals. The next step is to evaluate the existing Business Infrastructure in order to define whether Business Infrastructure can support a new strategy, or there are any necessary changes. If changes are mandatory, new Business Infrastructure is created. At this time some major processes are performed automatically by Knowledge-Based Subsystem. It ensures that new Business Infrastructure is correct against formal criteria. Detailed activity diagram of Strategy Execution Perspective implementation using Knowledge Based-MDA technique is presented in Figure 6.

Source: created by the authors. Figure 6. Activity Diagram of the Main Steps of Strategy Execution Perspective Supported by KnowledgeBased MDA Process TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development Changes to IT infrastructure are made using Model Driven Architecture approach. This software systems development method can efficiently transfer Business Infrastructure changes to IT Infrastructure e.g. real time changes in business infrastructure can immediately affect the IT infrastructure. Knowledge-Based implementation of the Strategy Execution Perspective shown in Table 3. Table 3. Knowledge-Based implementation of the Strategy Execution Perspective Step No. 1

Step name

Description

Actor

Create strategy

Top Business management creates a new strategy or updates the existing one. Top Business management sets Goals (from environment) which can be monitored by some parameters. Top Business management evaluates the existing Business Infrastructure and processes. Reports if it can support new strategy. Creates project/model of new Business Infrastructure, which can have new actors, processes, functions etc. New business process model is evaluated against formal criteria. If changes are necessary, business model is updated and checked again. This process is iterative Changes to Business Infrastructure are implemented

Top business manager

Set Goals 2 Evaluate business strategy 3

4

5

6 7

Create model of new Business Infrastructure Evaluation of business infrastructure using formal criteria defined by the Enterprise Meta-Model Update existing Business Infrastructure according validated model. Evaluate IT infrastructure

Design and implementation of required IS changes Source: created by the authors. 8

IT infrastructure is evaluated whether it can support new Business Infrastructure. Knowledge-Based process using MDA approach.

Top business manager Top business manager

Top business manager KB Subsystem

Top business manager, lower executives Top IT manager Knowledge-Based Subsystem

The main difference between the traditional and Knowledge-Based implementation of Strategy Execution Perspective is that in traditional manner all decisions are made by business and IT executives – it means, in empirical way. As we have mentioned before, this brings risk to the whole process. Conclusions Changes in Business domain must correctly correspond to IT domain otherwise Information Systems become outdated, resist changes, and do not correspond properly to business needs and user requirements. Strategy Execution Perspective is the most common Business and IT alignment way, although Strategic Alignment Model specifies only theoretical background of this perspective. Implementation guidelines of Knowledge-Based strategy execution perspective using MDA approach are proposed in the paper. The core element of Knowledge-Based MDA process is Knowledge-Based Subsystem, which improves traditional MDA conception with best practices of enterprise modeling and user requirements acquisition methods. It ensures the Business domains knowledge verification against EMM internal structure. Such usage of KnowledgeTRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development Based Subsystem together with MDA will improve the consistency of software artifacts and will reduce IT projects’ dependence on empirical processes. This solution will improve business and IT alignment process in the following ways: · Business requirements will be validated against formal criteria. It will ensure that developed IS elements will efficiently correspond to business needs. · IS elements will be developed in automatic or semi automatic way. It will save time and resources. · IS elements can be generated for various IT platforms without a need of additional resources (human, financial, time etc.). It allows changing IT infrastructure and aligning it to Business infrastructure more efficiently than in a traditional manner. · The usage of EMM in Knowledge-Based MDA method will reduce the amount of human related problems because traditional IS development methods heavily depend on the IT experts and users’ skills and competence. · There is a possibility to use organizations EDW to make the process even more sophisticated and less resource consuming. The final result of this survey will be extra module to CASE tool which will ensure additional functionality for system analysts, IS architects and developers. References Ambler, S.W. (2009), Agile Modeling, available at, http://www.agilemodeling.com/essays/inclusiveModels.htm, referred on 30/11/2010. Asadi, M., Ramsin, R. (2008), “MDA-based Methodologies: An Analytic Survey”, in the 4th European conference on Model Driven Architecture in: Foundations and Applications, pp.419-431. Champy, J. (2006), Four steps to successful IT/business alignment, available at, http://searchcio.techtarget.com/news/1187634/Four-steps-to-successful-IT-business-alignment, referred on 12/11/2010. Chen, C.-K. (2008), “Construct Model of the Knowledge-based Economy Indicators”, Transformations in Business & Economics, Vol. 7, No 2(14), pp.21-31. ENV 12 204 (1996), Advanced Manufacturing Technology Systems Architecture - Constructs for Enterprise Modelling, CEN TC 310/WG1. ENV 40 003 (1990), Computer Integrated Manufacturing Systems Architecture - Framework for Enterprise Modelling, CEN/CENELEC. Fox, M.S., Gruninger, M. (1998), Enterprise Modeling. American Association for Artificial Intelligence, available at, http://www.eil.utoronto.ca/enterprise-modelling/papers/fox-aimag98.pdf, referred on 30/11/2010. Grembergen, W.V. (2004), Strategies for information technology governance, IDEA Group Publishing, ISBN 159140-284-0. Grembergen, W.V., De Haes, S. (2009), Enterprise Governance of Information Technology: Achieving Strategic Alignment and Value, Springer, ISBN: 978-0-387-84881-5. Grigoriu, A. (2009), The Business and IT alignment issue, available at, http://it.toolbox.com/blogs/eamatters/the-business-and-it-alignment-issue-34379, referred on 28/10/2010. Gudas, S. (2010), “Two-Dimensional Decomposition of Business Enterprise Goals”, Transformations in Business & Economics, Vol. 9, No 2(20), Supplement B, pp.447-460. Gudas, S., Brundzaite, R. (2006), “Knowledge-Based Enterprise Modeling Framework”, Advances in Information Systems (ADVIS), pp.334-343. Gudas, S., Lopata, A., Skersys T. (2005), “Approach to Enterprise Modeling for Information Systems Engineering”, Informatica, Vol. 16, No 2, pp.175-192. Gudas, S., Pakalnickas, E. (2009), “Enterprise Management view based Specification of Business Components”, 15th International conference on Information and software technologies, IT’2009, pp. 417-426. Henderson, J., Venkatraman, N. (1999), „Strategic Alignment: Leveraging Information Technology for Transforming Organizations“, IBM Systems Journal, Vol. 38, No 2,3, pp.472-484. Kamińska, T. (2009), “The ICT Usage as an Attribute of the Knowledge-Based Economy – Poland’s Case”, Transformations in Business & Economics, Vol. 8, No 3(18), Supplement B, pp.166-183. TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011

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Structural Transformations in Business Development Kapocius, K., Butleris, R. (2006), “Repository for business rules based IS requirements”, Informatica, Vol. 17, No 4. pp503-518. Lentner, C. (2007), “The Competitiveness of Hungarian University-Based Knowledge Centres in European Economic and Higher Education Area”, Transformations in Business & Economics, Vol. 6, No 2(12), Supplement B, pp.87-99. Lopata, A. Gudas, S. (2009), “Workflow- Based Acquisition and Specification of Functional Requirements”, 15th International Conference on Information and Software Technologies IT2009, pp.417- 426. Lopata, A., Ambraziunas, M. (2010a), “MDA Compatible Knowledge Based IS Development Process”, in: BIS 2010 International Workshop, pp.324, ISBN: 978-3-642-15401-0. Lopata, A., Ambraziunas, M. (2010b), “Knowledge Subsystem’s Integration into MDA Based Forward and Reverse IS Engineering”, in: Proceedings of 16th International Conference on Information and Software Technologies “Information Technologies 2010”, pp.205-210, ISSN 2029-0020. Lopata, A., Ambraziūnas, M. (2010c) “MDA Compatible Knowledge- Based IS Engineering Approach”, in: International Conference, AICI 2010, pp.386, ISBN: 978-3-642-16526-9. Lopata, A., Gudas, S. (2008), “Enterprise model based computerized specification method of user functional requirements”, International conference 20th EURO mini conference Continuous optimization and Knowledge-based Technologies (EuroOpt-2008), pp.456-461, ISBN 978-9955-28-283-9. McKay, R. (2006), National Institutes of Health Systems Development Life Cycle Framework, v 1.1, 39p., available online at: http://enterprisearchitecture.nih.gov/NR/rdonlyres/53F3D49A-51DB-4F0E-929744C64B74352E/0/NIHRFC0004SystemDevelopmentLifeCycleSDLCFramework.pdf, referred on 04/04/2011. Melnikas, B. (2008), “The Knowledge-based Economy in the European Union: Innovations, Networking and Transformation Strategies”, Transformations in Business & Economics, Vol. 7, No 3(15), Supplement C, pp.170-192. OMG (2003), OMG: MDA Guide Version 1.0.1, available at, www.omg.com, referred on 15/09/2009. Skersys, T. (2008), “Business Knowledge-Based Generation of the System Class Model”, Informatica, Vol. 37, No 2, pp.145-153. Vernadat, F. (2001), “UEML: Towards a Unified Enterprise modeling language”, International Conference on Industrial Systems Design, Analysis and Management (MOSIM’01), available at, http://www.univtroyes.fr/mosim01, referred on 18/12/2010. Wegrzyn, G. (2010),”Service Sector as a Stimulus of Knowledge-Based Economy Development”, Transformations in Business & Economics, Vol. 9, No 2(20), Supplement B, pp.362-381. ŽINIOMIS GRINDŽIAMAS VEIKLOS IR IT STRATEGINIO SUDERINIMO METODAS Audrius Lopata, Martas Ambraziunas, Saulius Gudas SANTRAUKA Straipsnyje analizuojamas organizacijos procesų bei juos aptarnaujančios informacijos sistemos suderinamumo klausimas. Kintant verslo strategijai arba verslo infrastruktūrai bei siekiant užtikrinti efektyvią organizacijos veiklą, būtina, operatyviai atsižvelgiant į šiuos pokyčius organizacijos, adaptuoti informacinių technologijų infrastruktūrą. Deja, dažnai organizacijoje egzistuoja didelis atotrūkis tarp verslo ir informacinių technologijų infrastruktūrų. J.C. Henderson ir N. Venkatraman sukurtas Strateginio verslo ir informacinių technologijų suderinamumo modelis apibrėžia keturias pagrindines suderinamumo strategijas, kuriomis grindžiant galima sumažinti šį atotrūkį. Šiame straipsnyje pateikiamas žinių inžinerijos principais grindžiamas strategijos vykdymo prioriteto technologinis sprendimas. REIKŠMINIAI ŽODŽIAI: veiklos ir IT suderinamumo modelis, strateginio suderinamumo modelis, žiniomis grindžiama IS inžinerija, modeliais grindžiama architektūra, veiklos metamodelis, UML.

TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 10, No 2 (23), 2011