SOFT MODELING SUPPORT FOR MANAGING KNOWLEDGE-BASED INFORMATION TECHNOLOGY (IT) PROJECTS

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<ul><li><p>This article was downloaded by: [Selcuk Universitesi]On: 21 December 2014, At: 18:33Publisher: Taylor &amp; FrancisInforma Ltd Registered in England and Wales RegisteredNumber: 1072954 Registered office: Mortimer House, 37-41Mortimer Street, London W1T 3JH, UK</p><p>Cybernetics andSystems: AnInternational JournalPublication details, includinginstructions for authors andsubscription information:http://www.tandfonline.com/loi/ucbs20</p><p>SOFT MODELINGSUPPORT FORMANAGINGKNOWLEDGE-BASEDINFORMATIONTECHNOLOGY (IT)PROJECTSCezary OrlowskiPublished online: 30 Nov 2010.</p><p>To cite this article: Cezary Orlowski (2002) SOFT MODELING SUPPORTFOR MANAGING KNOWLEDGE-BASED INFORMATION TECHNOLOGY (IT)PROJECTS, Cybernetics and Systems: An International Journal, 33:4,401-411, DOI: 10.1080/01969720290040669</p><p>To link to this article: http://dx.doi.org/10.1080/01969720290040669</p><p>PLEASE SCROLL DOWN FOR ARTICLE</p><p>http://www.tandfonline.com/loi/ucbs20http://www.tandfonline.com/loi/ucbs20http://www.tandfonline.com/action/showCitFormats?doi=10.1080/01969720290040669http://dx.doi.org/10.1080/01969720290040669</p></li><li><p>Taylor &amp; Francis makes every effort to ensure the accuracy ofall the information (the Content) contained in the publicationson our platform. However, Taylor &amp; Francis, our agents,and our licensors make no representations or warrantieswhatsoever as to the accuracy, completeness, or suitability forany purpose of the Content. Any opinions and views expressedin this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor &amp; Francis. Theaccuracy of the Content should not be relied upon and shouldbe independently verified with primary sources of information.Taylor and Francis shall not be liable for any losses, actions,claims, proceedings, demands, costs, expenses, damages,and other liabilities whatsoever or howsoever caused arisingdirectly or indirectly in connection with, in relation to or arisingout of the use of the Content.</p><p>This article may be used for research, teaching, and privatestudy purposes. Any substantial or systematic reproduction,redistribution, reselling, loan, sub-licensing, systematic supply,or distribution in any form to anyone is expressly forbidden.Terms &amp; Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p><p>http://www.tandfonline.com/page/terms-and-conditionshttp://www.tandfonline.com/page/terms-and-conditions</p></li><li><p>SOFTMODELINGSUPPORTFORMANAGINGKNOWLEDGE-BASED INFORMATIONTECHNOLOGY (IT) PROJECTS</p><p>CEZARYORLOWSKI</p><p>Faculty of Management and Economics,Technical University of Gdansk, Poland</p><p>The present article aims to present the self-adjusting fuzzymodel of the software</p><p>engineering management, which is going to aid in creating knowledge-based</p><p>systems. Carrying out such systems creates problems for managers of project</p><p>teams, which in turn is connected with a limited knowledge of the subject</p><p>matter, lack of IT tools for the acquisition, and implementation of knowledge</p><p>and the coordination of the cooperation between experts and engineers. Thus,</p><p>the solutions that aid the projectmanagement processes, especially those related</p><p>to the changes, risk and the timeof realization, are sought. The suggestedmodel,</p><p>which is based on the knowledge and theory of regulators and fuzzy sets, might</p><p>offeran answer to theaboveproblems.Whilebuilding the system, theknowledge</p><p>of managing the real software systems was used and created conditions for the</p><p>tuning of the model, building knowledge-base rules and membership functions.</p><p>Managing IT projects is a complex research and utilitarian problem as it</p><p>integrates solutions from a number of areas related to software engineer-</p><p>ing: methods, techniques and tools of information science, management</p><p>science, and system science. Paulk et al. (1995) dene IT project man-</p><p>agement as an organized set of processes designed to deliver a product, i.e.</p><p>an IT system, under specic conditions. Serrano (1987) claims that IT</p><p>project management contains all management functions: leadership,</p><p>control, planning, and organization. According to Beyond-Davies (1999),</p><p>Address correspondence to Cezary Orlowski, Technical University of Gdansk,</p><p>Faculty of Management and Economics, Narutowicza 11=12, 80 952 Gdansk, Poland.E-mail: cor@zie.pg.gda.pl</p><p>Cybernetics and Systems: An InternationalJournal, 33: 401411, 2002Copyright# 2002 Taylor &amp; Francis</p><p>0196-9722/02 $12.00+ .00</p><p>DOI: 10.1080/01969720290040669</p><p>401</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p>IT project management involves three inter-dependent stages: planning,</p><p>organization, and control, all designed to deliver a specied IT system.</p><p>The term ``knowledge-based system is often associated with IT</p><p>projects, and has different meaning for different authors (Baborski 1994;</p><p>Ceri and Fraternali 1997; Ullman 1988). In this paper it represents a class</p><p>of IT systems with a rule-object knowledge representation and mixed</p><p>(forward and backward) type of deduction. The IT knowledge-based</p><p>systems have an increasingly important effect on the global economy and</p><p>call for comprehensive research, technical analysis of implementation</p><p>cases, and involvement of specialists from various areas. This means</p><p>substantial expenditure for companies involved in IT systems develop-</p><p>ment and implementation, high risk, and equally high expectations of</p><p>signicant benets by making the businesses more attractive in our</p><p>increasingly competitive market (Laudon and Laudon 1991).</p><p>The IT project management approach as presented in the paper</p><p>attempts to use qualitative (soft) modeling support in the process of</p><p>systems development. This approach looks at project management as the</p><p>management of a group of pre-dened design processes which have to be</p><p>completed within the assumed time and by using the available resources.</p><p>MODELOFAKNOWLEDGE-BASED IT PROJECTMANAGEMENTSYSTEM</p><p>The paper presents a systems approach to the problem of planning and</p><p>control of IT projects. The approach is based on the theory of modeling</p><p>and process simulation (Zeigler 1984), design theory (Braha and Maimon</p><p>1998), and the concurrent approach to systems analysis and development</p><p>(Szczerbicki 1997; Szczerbicki and Punch 2001). The proposed solution</p><p>was integrated through the use of IT and Articial Intelligence (AI) tools</p><p>and techniques.</p><p>IT projects that include knowledge management require a result-</p><p>oriented approach, organizationa l and project risk assessment, control</p><p>over how design work proceeds, and full consideration of how new meth-</p><p>odological and qualitative types of solutions are developed (Go rski 1999).</p><p>The solutions presented use empirical data gathered by project teams.</p><p>For the purpose of this paper, an IT project is dened in multiple</p><p>scopes, levels, and platforms using the concept of state space. The proposed</p><p>approach to project management involves four main stages as depicted</p><p>in Figure 1.</p><p>402 C. ORLOWSKI</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p>In stage one a description of the real life system is given. Stage two</p><p>presents hierarchical structure of project management model. Stage three</p><p>describes the structural model, and stage four provides characteristics of</p><p>the integrated model. The integrated model combines components</p><p>of fuzzy models of analysis and synthesis processes, non-fuzzy processes</p><p>of formal control requirements, control of planning processes, and con-</p><p>trol of IT project management.</p><p>The real life system consists of a team working in IT environment</p><p>and using available techniques and tools to develop a specied end</p><p>product a software package. This system is presented using observable</p><p>and non-observable variables. Measurable variables include input and</p><p>output data. According to Zeigler (1984), an experimental framework</p><p>presents a nite set of conditions for observing the real system or</p><p>implementing the experiment. For the implementation reasons a sub-set</p><p>of the real life systems input-output responses was dened in the adopted</p><p>approach. A comparative criterion was developed and used to dene</p><p>input-output pairs corresponding to the structure of the real life system.</p><p>The hierarchical architecture of stage two and structural model of</p><p>stage three are depicted in Figure 2 and Figure 3, respectively. Relations</p><p>Figure 1. The integrated IT project management model: development stages.</p><p>MANAGING KNOWLEDGE-BASED IT PROJECTS 403</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p>Figure 2. Hierarchical model of IT project management.</p><p>Figure 3. Structural model of IT project management.</p><p>404 C. ORLOWSKI</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p>between input and output data of the structural model are dened using</p><p>the concept of state space (Figure 4).</p><p>THE INTEGRATEDMODELOF IT PROJECTMANAGEMENTSYSTEM</p><p>The integrated model that was developed focuses on project planning and</p><p>control using the well-known concept of feedback controller (Yager and</p><p>Filew 1995). Fuzzy models were applied for control mechanism</p><p>description. Two mechanisms developed by Zeigler (1984) were used:</p><p>homogeneity, which is dened as having identical structures within a</p><p>block, and uniformity, which is dened as having identical effects for</p><p>superior and secondary elements. Also, the concepts of parallel and serial</p><p>decomposition with feedback were used (Szczerbicki and Orlowski in</p><p>press). As the result, to verify the integrated model its INPUT=OUTPUT</p><p>responses can be compared with the responses of the real life system.</p><p>Project platforms within the model are functional sections, developed</p><p>by following the descending systemic approach. The concept of platforms</p><p>allows for a multi-level decomposition of the organizationa l and IT</p><p>Figure 4. The state space concept applied in stage three of the IT project management model</p><p>development.</p><p>MANAGING KNOWLEDGE-BASED IT PROJECTS 405</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p>infrastructure, design processes, and project management. The integrated</p><p>model developed allows for the distinction of any number of platforms</p><p>depending on the type of the IT project analyzed. Four different man-</p><p>agement spaces were proposed: team management, design management,</p><p>knowledge management, and supporting techniques management space.</p><p>Designmanagement space consists of design processes. To dene design</p><p>processes a qualitative solution was developed using the phenomenologica l</p><p>approach to knowledge-based systems development. An attempt was made</p><p>to adopt the deductive approach based on Mesarovic and Takahara (1989).</p><p>Design synthesis and analysis both occur on parallel platforms.</p><p>A parallel design solution was also proposed for concurrent team and</p><p>project management allowing for independent and parallel indirect</p><p>acquisition of knowledge. The design and management processes are</p><p>conducted in a network software environment supported with selected IT</p><p>CASE tools.</p><p>In the knowledge management space the following takes place:</p><p> Experts knowledge is used to dene the scope of the system, determineits function, and the structure of the informal model;</p><p> The experience of knowledge engineers is combined with that of ex-perts creating a formal model to implement it as knowledge bases;</p><p> The system designers tools are matched with design objects in areassuch as knowledge acquisition, decision-making support, and network</p><p>representation;</p><p> IT solutions are developed for project management, design process,and product evaluation.</p><p>The space of management support consists of knowledge codied as</p><p>production rules in the following form:</p><p>IF uk is B10 AND u(k 1) is B11 AND . . .AND y(k n) is Aln THEN y(k) = Aln</p><p>(1)</p><p>where Aij;Bij are linguistic labels, uk-input values, and y(k) output values.</p><p>An example of the rule description is given in Figure 5.</p><p>FINE-TUNINGOF THE INTEGRATED (FUZZY)MODEL</p><p>The process of ne-tuning of the fuzzy model consists of three stages. In</p><p>stage one the measurement data from the three research projects used in</p><p>406 C. ORLOWSKI</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p>our case study were converted into production rules. Stage two was</p><p>concerned with building the membership function and stage three</p><p>involved model self-tuning and self-organizing.</p><p>The rst stage was basically a knowledge acquisition one. Building</p><p>the required knowledge base involved data gathering from three IT</p><p>research projects. The most important project in this case study was</p><p>ECOSIM (Ecological and Environmental Monitoring and Simulation</p><p>System for Management Decision Support in Urban Areas) which</p><p>involved 13 partners. The objective of the project was to develop an</p><p>environmental computer decision-support system working with interna-</p><p>tional monitoring networks and using simulation models of air, soil, and</p><p>water. The conceptual architecture of the project is depicted in Figure 6.</p><p>The above concept was the basis of the system development in re</p><p>steps as illustrated in Figure 7. Data from all stages were used in</p><p>knowledge acquisition and knowledge base development.</p><p>In the second stage membership functions were built using data on</p><p>management methods and IT tools gathered in stage one. Figure 8 shows</p><p>an example of how membership functions were computed.</p><p>The stage of self-tuning and self-organizing involves the following:</p><p> addition of new rules, determination of data clusters,</p><p>Figure 5. Production rules used to describe the integrated model: an example.</p><p>MANAGING KNOWLEDGE-BASED IT PROJECTS 407</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p> checking membership functions for the dened clusters, computation of the degree of rule conrmation.</p><p>Model self-tuning was performed using measurement data on IT</p><p>project management in some additional projects taking part in the case</p><p>Figure 6. The concept of the ECOSIM system.</p><p>Figure 7. ECOSIM system development steps.</p><p>408 C. ORLOWSKI</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Selc</p><p>uk U</p><p>nive</p><p>rsite</p><p>si] </p><p>at 1</p><p>8:33</p><p> 21 </p><p>Dec</p><p>embe</p><p>r 20</p><p>14 </p></li><li><p>studies that were performed. Fully developed and tuned integrated model</p><p>was veried and validated using historical data from a number of soft-</p><p>ware development projects.</p><p>DISCUSSIONREMARKSANDCONCLUSION</p><p>This paper signals a very important challenge in information society,</p><p>namely the problem of how to effectively manage and support the devel-</p><p>opment and implementation of a knowledge-based IT system. As some</p><p>contribution to the ways this challenge can be addressed, a system</p><p>approach was applied to the development of an IT project management</p><p>model. The modeling assumptions were provided by the use of deductive</p><p>and inductive approaches as well as deterministic and forecasting techni-</p><p>ques. The integrated model was implemented in knowledge-based system</p><p>development for the Environmental Department of Gdansk City Council,</p><p>Gdansk, Poland. Integration process involved design integration, man-</p><p>agement techniques, and knowledge source integra...</p></li></ul>