b-kide: a framework and a tool for business process-oriented knowledge infrastructure development

& Research Article

B-KIDE: A Framework and a Tool forBusiness Process-Oriented KnowledgeInfrastructure Development

Markus Strohmaier1* and Klaus Tochtermann1,2

1Know-Center, Graz, Austria2Graz University of Technology, Graz, Austria

The need for an effective management of knowledge is gaining increasing recognition intoday’s economy. To acknowledge this fact, new promising and powerful technologies haveemerged from industrial and academic research. With these innovations maturing, organiza-tions are increasingly willing to adapt such new knowledge management technologies toimprove their knowledge-intensive businesses. However, the successful application in givenbusiness contexts is a complex, multidimensional challenge and a current research topic. There-fore, this contribution addresses this challenge and introduces a framework for the develop-ment of business process-supportive, technological knowledge infrastructures. Whilebusiness processes represent the organizational setting for the application of knowledge man-agement technologies, knowledge infrastructures represent a concept that can enable knowl-edge management in organizations. The B-KIDE Framework introduced in this workprovides support for the development of knowledge infrastructures that comprise innovativeknowledge management functionality and are visibly supportive of an organization’s businessprocesses. The developed B-KIDE Tool eases the application of the B-KIDE Framework forknowledge infrastructure developers. Three empirical studies that were conducted with indus-trial partners from heterogeneous industry sectors corroborate the relevance and viability ofthe introduced concepts. Copyright # 2005 John Wiley & Sons, Ltd.

INTRODUCTION

Knowledge in modern economies is increasinglyplaying a key role in achieving organizational suc-cess. Knowledge management (KM) as a conceptand a scientific discipline emerged to acknowledgethis fact. Three main reasons can be identified forthis development (Sivan, 2001): (1) need: today’sinformation technology-enabled organizationshave to process and make use of ever more infor-mation in ever-decreasing time cycles; (2) recogni-tion of need: organizations increasingly recognize

the need for and the importance of conscious man-agement of knowledge (Matzler et al., 2004); (3)availability of KM instruments: past research activ-ities (e.g., Maurer and Tochtermann, 2002; Maierand Remus, 2002; Lehner, 2002; Lindstaedt et al.,2002; Rollett, 2003) and product innovations (e.g.,Hyperwave, 2004; Livelink, 2004; Lotus, 2004) inthe field of knowledge management promise toprovide sound instruments for addressing currentKM challenges and enabling the management ofknowledge in organizational settings. These threeobservations represent insightful explanations forthe emergence of knowledge management.

Practicing knowledge management in organizationscan be achieved through the development andimplementation of knowledge infrastructures (Sivan,

Knowledge and Process Management Volume 12 Number 3 pp 171–189 (2005)

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/kpm.227

Copyright # 2005 John Wiley & Sons, Ltd.

*Correspondence to: Markus Strohmaier, Know-Center, Graz,Austria. E-mail: [email protected]

2001). In this contribution, knowledge infrastructuresare defined as the set of all successfully implemen-ted interventions, measures, institutions and facil-ities that represent a supportive environment forknowledge workers who execute knowledge-inten-sive tasks. These knowledge infrastructures consistof three main dimensions: (1) people; (2) organiza-tional systems; and (3) technological systems;whereas knowledge is defined to be informationthat is relevant for business actions (Strohmaier,2003a). According to a Delphi study on the futureof KM,1 the successful integration of knowledgemanagement into an organization’s business pro-cesses is regarded to be the most pressing and chal-lenging theoretical research issue for theunderstanding and advancement of KM. By takingthe increasing number of organizations certifiedaccording to a process-oriented management stan-dard into account (ISO Survey, 2001, 2002), theimportance of this issue is even more emphasized.Among others, these insights motivated theresearch of this contribution, which aims to enablethe development of technological knowledge infra-structures that are integrated in and supportive ofan organization’s knowledge-intensive businessprocesses. Two main research challenges are ofutmost relevance in the context of this objective:

(1) Support for business process networks. Businessprocess management deals with the manage-ment, continuous improvement and optimiza-tion of business processes (ISO, 2000a). Inknowledge-intensive organizations, businessprocesses are typically increasingly knowl-edge-intensive (Eppler et al., 1999) and inter-connected. Instead of focusing only on theoptimization of isolated business processes, cur-rent standards for business process and qualitymanagement (e.g., ISO, 2000a) suggest thatorganizations should investigate, support andimprove their networks of business processes, espe-cially focusing on interactions between them (ISO,2000c, Section 5.1.2). Knowledge as the keyresource of knowledge-intensive organizationsrepresents a significant cause for interactionsbetween knowledge-intensive business pro-cesses (Strohmaier, 2003a). By failing to focuson such knowledge interactions, an organiza-tion is not able to optimize the sum of its efforts(its business process network); instead it is tar-geting local optima (specific business pro-

cesses) that do not necessarily contribute to anorganization’s overall goals. Although today’sorganizational knowledge management initia-tives already focus on multiple business pro-cesses rather than on a single business process(Maier and Remus, 2002), surprisingly neitherexisting process standards (e.g., ISO, 2000b)nor existing business process modeling techni-ques (e.g., Scheer, 1996) nor knowledge man-agement approaches provide comprehensiveconcepts on how to tackle this identified chal-lenge. Remus and Lehner (2000) strikinglyacknowledge the need for scientific conceptsin this area by stressing that successful supportfor knowledge-intensive business processes is,to a greater extent, a matter of supportingknowledge flows (knowledge interactions thatspan multiple business processes) (Remus,2002) rather than workflows.

(2) Application of knowledge management technologies.Today, a heterogeneous set of KM technologiesis available from industrial vendors (e.g.,Hyperwave, 2004; Livelink, 2004; Lotus, 2004)as well as from academia (e.g., Woitsch andKaragiannis, 2002; Dustdar, 2002; Engelbach,2003; Huth et al., 2003). Failures of technology-driven KM projects in the past that did not takecritical business requirements of organizationsinto account (Rollett, 2003, Chapter 3) urgentlycall for concepts that aid the application andconfiguration of KM technologies to specificbusiness contexts. KM technology itself cantoday be classified according to differentdimensions. The MT2 model introduced byMaurer and Tochtermann (2002) distinctly clas-sifies KM system functionalities based on dif-ferent types of communication betweenpeople and technological systems. Each classis represented through a specific arrow index.One specific class of KM functionality (entitled‘Arrow 3’ in the MT model) describes the abil-ity of technological knowledge infrastructuresto generate new knowledge and autonomously per-form appropriate actions (such as the routing ofinformation between people) based on the implicitinput of data by users without burdening them.The non-intrusive nature of this KM functional-ity combined with its high potential to supportthe execution of knowledge-intensive businessprocesses especially makes this type of KMfunctionality the most promising one to beeffectively applied to specific, operative busi-ness contexts. The scientific question that

1Carried out in 2001/2002 by the Fraunhofer Competence Centerof Knowledge Management, Berlin, and the Institute for Psy-chology at Humboldt University, Berlin (Mertins et al., 2003b,Chapter 8). 2Maurer–Tochtermann.

RESEARCH ARTICLE Knowledge and Process Management

172 M. Strohmaier and K. Tochtermann

emerges from this conclusion is how such abusiness alignment of KM functionality can beachieved. Therefore, research challenge 2 calls forconcepts that support the successful applicationof KM functionality3 to given business contexts.

The two research challenges introduced provide aprofound basis for the definition of the main objec-tive of this contribution, which is to introduce a fra-mework that allows for the development of businessprocess-supportive, technological knowledge infrastruc-tures for knowledge-intensive organizations.

RELATED WORK

This contribution relates to and builds on conceptsfrom areas such as business process-orientedknowledge management (Allweyer, 1998; Heisig,2001; Remus, 2002; Papavassiliou et al., 2002), mod-eling and engineering of business information sys-tems (Sinz, 1995, 1997; Ferstl and Sinz, 2001),requirements engineering (Robertson and Robertson,1999), systems analysis (Yourdon and Constantine,1979), social network analysis (Paier, 2003; Mueller-Prothmann and Finke, 2004; Choy et al., 2004) andknowledge management technologies (Maurerand Tochtermann, 2002; Maier and Remus, 2002;Rollett, 2003). Since business process-orientedknowledge management (BpoKM) represents themost significant area for addressing the identifiedobjective, a model of challenges in this domain isintroduced in Figure 1. Business process analysisfocuses on knowledge-oriented analysis of businessprocesses and represents the basis of most ap-proaches in the field of bpoKM. Business processmodeling deals with the integration of knowledgeaspects into business process models (e.g., Allweyer,

1998; Papavassiliou et al., 2002; Gronau et al., 2003).Business process learning aims to provide supportfor learning in or about business processes (e.g.,Starkloff and Pook, 2001; Papargyris et al., 2002).Business process support focuses on support forknowledge workers in their respective businessprocesses (e.g., Bach et al., 2000; Raimann et al.,2000; Jansen, 2000; Heisig, 2001; Hoffmann et al.,2002; Mertins et al., 2003b). Business process execu-tion deals with knowledge-oriented extensions totraditional workflow management systems (e.g.,Wargitsch et al., 1998; Maurer and Holz, 1999;Reimer et al., 2000; Abecker et al., 2001). Businessprocess improvement deals with improvements ofbusiness processes from a knowledge perspective(e.g., Dammig et al., 2001; Voss and Althoff, 2002).Because the anticipated framework aims to provideguidance in the development of business processsupportive knowledge infrastructures, the contri-bution at hand can well be assigned to the domainof business process support.

The methodological research approach chosen toserve as a basis for this contribution was designresearch. In this contribution, design researchersare considered to create realities through construc-tive intervention, then reflectively become positi-vist observers, recording the behavior of thesystem and comparing it to the predictions (theory)set out during a suggestion phase (Vaishnavi andKuechler, 2004). Other research approaches (suchas case study research (MacNealy, 1997) or actionresearch (Kock, 1997)) were utilized in this workas well—in clearly defined areas of applicationwithin an overall design research approach.

KNOWLEDGE INFRASTRUCTUREDEVELOPMENT

Today, organizational knowledge managementinitiatives such as the development of knowledgeinfrastructures are largely organized as a project(Maier and Remus, 2002). Figure 2 introduces rele-vant roles and respective tasks of knowledge infra-structure development projects.4

The knowledge manager (or CKO—chief knowl-edge officer) is regarded to be the highest rankedrole in KM (Maier, 2002, p. 143). In this steeringposition, his or her main responsibility is to devel-op and implement a KM strategy5 and to initiateand coordinate KM projects. The project manager

3More specifically: ‘Arrow 3’ KM functionality of the MT model.

Figure 1 A model of BpoKM challenges

4The dotted lines in Figure 2 illustrate aspects that are outsidethe scope of this contribution.5Lehner (2000, p. 226); Schreiber et al. (2002, p. 22); Mertins et al.(2003b, p. 107).

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(or knowledge project manager; Mertins et al.,2003b) is in charge of running KM projects (Schrei-ber et al., 2002, p. 22). He or she focuses on aspectsrelated to project management such as the develop-ment of project goals and plans or the coordinationof project team members (Mertins et al., 2003b,p. 107). Knowledge workers are the primary targetgroup for KM projects (Maier, 2002, p. 150). There-fore, KM projects aim to support and improve thework of knowledge workers (Davenport et al.,1995). Knowledge analysts are responsible for analyz-ing organizational knowledge work executed byknowledge workers. Similar to the concept of sys-tem analysts (Yourden, 1989, p. 56), they investi-gate a complex object system (organizationalknowledge work) and create models that illustratecore aspects of the system under investigation.The knowledge infrastructure designer is responsi-ble for transforming the developed models of orga-nizational work into a design of a knowledgeinfrastructure, which describes a supportive envir-onment for knowledge workers (in analogy toYourdon, 1989, p. 57). Lastly, the developed knowl-edge infrastructure design represents the basis forimplementation (not depicted in Figure 2).

THE B-KIDE FRAMEWORK

In industrial environments, buildings are alreadyplanned and designed based on business processes.

To give an example: in order to design BMW’s6

new development center in Munich, the industrialarchitect in charge, Gunter Henn, analyzed the cen-ter’s targeted product development processes anddeduced impacts on the building’s architecture(Woltron, 2003; Strohmaier, 2003b). What can beconcluded is that business processes obviouslypose implications for the architecture of organiza-tional buildings. Therefore, the fundamentalhypothesis of this contribution is that businessprocesses pose implications for the developmentof organizational knowledge infrastructures as well.

Principle approach

In knowledge-intensive settings, business pro-cesses are typically complex (Eppler et al., 1999)and weakly structured and therefore are not cap-able of being a direct basis for the development ofbusiness process supportive knowledge infrastruc-tures. A commonly used approach to overcome thisproblem is to identify and model organizationalknowledge processes based on business processes7

that visualize relevant, executed knowledge workin different ways. The concept of knowledge pro-cesses (Strohmaier, 2003a) allows for the visualiza-tion of distributed organizational knowledge flows.

Figure 2 Knowledge infrastructure development projects (based on Schreiber et al., 2002)

6BMW: Bayrische Motoren Werke.7See, for example, Strohmaier (2003a); Remus (2002, Chapter11.3); Gronau et al. (2003).



Figure 3 introduces this concept via an accessibleyet abstract example. The depicted knowledge pro-cess visualizes how knowledge of a given knowl-edge domain is generated, stored, transferred andapplied across a set of business processes andinvolved organizational roles in an organization.The question mark in Figure 3 thereby indicatesan improvement potential for the exemplaryknowledge process. By the identification of suchknowledge processes,8 a more profound basisfor knowledge infrastructures that aim to supportthe execution of knowledge intensive business pro-cesses is established.

B-KIDE Framework components

The conceptual B-KIDE9 Framework illustrated inFigure 4 represents an elaboration of the principleapproach and consists of three main components:

(1) the B-KIDE Model Architecture (2) the B-KIDEMethod and (3) the B-KIDE Context. While the B-KIDE Model Architecture deals with aspects ofmodeling knowledge processes, the B-KIDE Meth-od focuses on the development of knowledge infra-structures based on these knowledge processes.The B-KIDE Context describes the environment inwhich the B-KIDE Framework and a complemen-tary supporting software tool, the B-KIDE Tool,can be employed. The B-KIDE Tool represents animplementation of the B-KIDE Model Architectureand supports the application of the B-KIDE Meth-od. It aids knowledge analysts on an operative levelin building models about organizational knowl-edge work and knowledge infrastructure designersin the development of appropriate knowledgeinfrastructures based on these models (similar towhat Tolvanen (1998) defines as method–tool com-panionship).

B-KIDE Context

The B-KIDE Framework and the related B-KIDE Toolaim to provide conceptual as well as operational

Figure 3 Simplified illustration of a knowledge process

8That are considered to run within and/or across business processes.9B-KIDE: Business process-oriented Knowledge InfrastructureDEvelopment.

Figure 4 B-KIDE Framework: principle approach and components


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(tool) support for knowledge analysts and knowl-edge infrastructure designers. Knowledge analystsare aided in modeling organizational knowledgework, while knowledge infrastructure designersare aided in the process of designing business pro-cess supportive knowledge infrastructures. The B-KIDE Framework focuses on the initial, identifica-tion of currently executed knowledge processes inorganizations as a basis for the development ofbusiness process supportive knowledge infrastruc-tures. Dynamic aspects of knowledge processes(e.g., change over time) are not considered. Byrelating the SER10 model introduced by Fischeret al. (1994) to the context of this contributionit becomes clear that the B-KIDE Frameworkcontributes to a seeding phase of knowledge in-frastructure development. The B-KIDE Frameworksupports the development of knowledge infra-structures on an implementation- and vendor-independent level. Thus resulting knowledge infra-structures can be represented through a variety oftechnological options such as organizational intra-nets, file servers, document, content or knowledgemanagement systems.

B-KIDE Model Architecture

The B-KIDE Model Architecture provides direc-tives for creating models of organizational knowl-edge work based on business processes. The mainoutput is a formal representation of knowledgeprocesses identified in an organization. The B-KIDE Model Architecture consists of two main ele-ments: (1) a modeling structure; and (2) a modelingtechnique. These two elements correspond to whatHommes and van Reijswoud (2000) describe, inthe context of modeling object systems, as the‘Way of Modeling’ and the ‘Way of Working’.The modeling structure (the Way of Modeling) intro-duces the conceptualizations that are used in amodeling effort (notations, conceptual structures),while the modeling technique (the Way of Working)describes the procedures by which models aboutan object system are constructed (the process andcorresponding activities). Both are introduced ingreater detail in the following sections.

Modeling StructureThe B-KIDE Modeling Structure defines how orga-nizational knowledge work is being modeled withthe B-KIDE Framework. Figure 5 depicts the essen-tial elements and relationships of the modeling

structure illustrated by a conceptual UML11

diagram.Knowledge domains represent topical fields of

knowledge which are relevant in the context ofundertaking certain business actions. Specific knowl-edge activities are basic knowledge-processing activ-ities executed by individuals, groups of people ortechnological systems. They represent qualifiedassociations (such as the generation, storage, trans-fer and application) between knowledge work andknowledge domains. In the B-KIDE Modeling Struc-ture, the specific knowledge activities generation,storage, transfer and application (Heisig, 2001) areutilized since they adequately12 describe knowl-edge work on an operative (or knowledge object)level.13 Specific knowledge activities are furthersemantically refined through additional associationobjects, represented by generation, storage, transferand application objects. An example of a transferobject would be a specific ‘newsletter’ or ‘voicechat tool’. These objects are organized in hier-archical reference models14 to ensure their uniqueexistence in B-KIDE models of organizationalknowledge work (similar to the ARIS-House con-cept of Scheer (2000)). Beneath that, knowledgedomains, business processes and organizational rolesas well are organized in hierarchical referencemodels for the same reason. Knowledge work is per-formed whenever knowledge of a certain knowledgedomain is being processed (generated, stored, trans-ferred or applied) by an organizational role in a busi-ness action. A business action is either a businessprocess for an undefined work activity. Business pro-cesses represent an organizational environment inwhich knowledge work is performed. Undefinedwork activities represent the complement set to busi-ness processes. They contain all business actions thatare not modeled in business processes.

Modeling TechniqueModeling with the B-KIDE Framework is based onstructured, process-oriented interviews withknowledge workers of a target organization. Theknowledge analyst is responsible for performingthese interviews with selected organizational roles.The main instrument for that purpose is the B-KIDE Tool. The B-KIDE Modeling Technique in

10SER: Seeding–Evolutionary growth–Reseeding.

11UML: Unified Modeling Language.12With respect to the identified challenges of this contribution.13Here, a necessary distinction between specific knowledge activ-ities (on a knowledge object level (Schreiber et al., 2002)) and spe-cific knowledge management activities (on a knowledgemanagement level (Schreiber et al., 2002)—such as knowledgeplanning, identification or assessment) has been made.14So-called B-KIDE reference models.



Figure 6 describes the method of modeling organi-zational knowledge work with the B-KIDE Frame-work. The process is divided into the followingfour main sub-activities:

� Scope definition. During scope definition, a deci-sion concerning the targeted business area hasto be made. This includes the determination ofbusiness processes and organizational roles thatshould be supported by the anticipated knowl-edge infrastructure. Based on this scope, intervie-wees and a related interview plan need to bedeveloped.

� Pre-modeling. In order to prepare for the actualmodeling, existing documentation about organi-zational structures can be gathered and ana-lyzed. This includes material such as existingbusiness process models, knowledge structure

diagrams, hierarchical organization charts, busi-ness strategies, existing technological systems,filing structures and communication channels.Based on this documentation, the introduced B-KIDE reference models can be prepared tosome extent before actually starting to modelthe object system of organizational knowledgework through interviews. Thereby, pre-modelingsignificantly lowers the burden of work forknowledge analysts during interview situations.

� Object system modeling. This activity is concernedwith the actual process of interviewing in orderto develop an inter-subjective model of organiza-tional knowledge work. The knowledge analystprepares the interview by utilizing available B-KIDE interview guidelines and employs the B-KIDE Tool to raise questions and documentsanswers given in accordance with the B-KIDE

Figure 5 The B-KIDE Modeling Structure

Figure 6 The B-KIDE Modeling Technique


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Modeling Structure. He uses (provisional) refer-ence models of past interviews for current inter-view situations, following an iterative approachof modeling reference models (as for examplepursued by Schreiber et al., 2002, p. 206 aswell). At the end of each interview, the knowl-edge analyst together with the interviewee cor-rect and validate the gathered data.15

� Model system refinement. After finishing eachinterview, the knowledge analyst reorganizesand refines the hierarchical reference modelsaccording to his understanding gained aboutthe object system. Although the knowledge ana-lyst (the modeler) thereby slightly influences themodel system, this activity supports the knowl-edge analyst in subsequent interview situations.

The application of the B-KIDE Modeling Struc-ture and Technique, together with the B-KIDETool (introduced in greater detail below), resultsin visualizations of knowledge processes as illu-strated in Figure 7.16 The exemplary knowledgeprocess depicted is interpreted in the followingway: the knowledge domain ‘knowledge aboutpotential customers’ is generated in the businessprocess ‘market analysis’ by the organizationalrole ‘marketing’. The knowledge is transferred viasales meetings (in the ‘market analysis’ businessprocess) to sales agents, who need to apply it intheir respective business process ‘Acquisition’.Such formal knowledge process visualizationsrepresent the basis for the development of business

process supportive knowledge infrastructuredesigns with the B-KIDE Framework.

B-KIDE Method

The B-KIDE Method provides a set of directives forthe development of knowledge infrastructuredesigns based on knowledge processes and consistsof two main elements: a knowledge infrastructure tem-plate architecture and a normative design process.

Knowledge infrastructure template architectureThe knowledge infrastructure template architec-ture in Figure 8 represents a system architecture,which describes the basic layers of technologicalsolutions that are capable of tackling the challengesof this contribution. The basic layers are: (1)contents; (2) taxonomies and meta-knowledge;17 and(3) access. Existing research provides comprehensiveconcepts for these layers. For example, extensive

Figure 7 The B-KIDE Tool report ‘Knowledge Process Landscape’

15Aspects of validation include checks for (1) self-consistency, (2)uniqueness of model elements and (3) model accuracy (based onKotonya and Sommerville, 1998, pp. 103–104).16The screenshot of Figure 7 was graphically revised in order toincrease comprehensibility of the concepts to be communicated.

Figure 8 The Knowledge infrastructure template architecture

17Both taxonomies and meta-knowledge represent concepts forknowledge organization and are therefore grouped together.



classifications of contents of technological knowl-edge management systems are available (Maier,2002, Chapter 7). The development of taxonomyand meta-knowledge concepts is aided, for example,by available standards (Dublin Core MetadataInitiative, 2003; Association for Computing Machin-ery, 2002), procedures (Dutra and Busch, 2003),methods (Mertins et al., 2003a), best practices(Ramos and Rasmus, 2003) or the concept of ontol-ogies (Abecker et al., 2001; Kim et al., 2003). On theaccess layer, instruments such as hierarchical tree orlist navigation, catalogues (Netscape Communica-tion Corporation, 2004), retrieval systems, complexvisualizations (Kienreich et al., 2003), standards(American National Standard for Information Tech-nology, 2003) as well as portals (Dias, 2001; Nohr,2002; Lindstaedt et al., 2003) aid developmentefforts. Based on identified knowledge processes,the knowledge infrastructure template architectureis instantiated per knowledge infrastructure devel-opment project by utilizing the B-KIDE Methodand existing concepts (as briefly listed above) forthe design of business process supportive knowl-edge infrastructures for organizations. By applyingthe B-KIDE Method, knowledge processes becomereified in knowledge infrastructures.

Design processTo aid the design of knowledge infrastructures thatsupport an organization’s knowledge-intensivebusiness processes, a normative design process isintroduced. Based on knowledge processes identi-fied by knowledge analysts, this design processaids knowledge infrastructure designers in inte-grating identified (knowledge) requirements intoknowledge infrastructure designs. Typically,design is perceived either as a product or a process.Because of the emergent field of knowledge man-agement systems and vendors and the lack of com-mon conceptualizations, this work predominatelyfocuses on a process approach to design. Thus theresulting approach can be applied across differentknowledge management system vendors and con-ceptualizations. In this contribution, the followingdefinition of design by Yourdon and Constantineis applied:

Design means to plan or mark out the form andmethod of a solution. It is the process whichdetermines the major characteristics of the finalsystem . . . . (Yourdon and Constantine, 1979, p. 8)

The design process is divided into the followingthree main sub activities:

� Knowledge process definition. Identified knowledgeprocesses represent the major imperative for the

design process. By integrating requirementsfrom knowledge processes into knowledge infra-structure designs, the resulting knowledge infra-structures are able to provide comprehensivesupport for knowledge-intensive business pro-cesses. For specifying these requirements, theknowledge infrastructure designer uses the iden-tified as-is knowledge processes and, togetherwith knowledge workers and representatives ofthe management, defines to-be knowledge pro-cesses based on them. In addition to that, fit cri-teria (Robertson and Robertson, 1999) need to bedeveloped. Fit criteria allow to check the devel-oped knowledge infrastructure design18 for inte-gration of appropriate knowledge processsupport. While the fit criteria are developed inthis design activity, the check is performed lateron—in the design activity ‘design validation’.

Fork A in Figure 9 illustrates the two principalways the B-KIDE Method can be applied:option 1 represents a way to evaluate existingknowledge infrastructures and knowledge infra-structure designs for improvement potentials,while option 2 specifies new knowledge infra-structure designs.

� Preliminary knowledge infrastructure design. In thisactivity, the introduced template architecture isinstantiated according to the constraints of speci-fic knowledge infrastructure development pro-jects. In each reference architecture layer theknowledge infrastructure designer considers therequirements specified by the knowledge processdefinitions. Thus the knowledge infrastructuredesigner either designs and introduces a newtechnological infrastructure, or alters existinginfrastructures to enhance technological environ-ments of knowledge workers. The fit criteriadeveloped in design activity 1 (which are appliedin design activity 3) already guide the KI designerin his design efforts. This not only allows him toperform the design process in a more efficientway, it also reduces the complexity of this task.

� Knowledge infrastructure design validation. Thisdesign activity validates the developed knowl-edge infrastructure design in terms of its supportfor the defined knowledge processes. The fit cri-teria developed in design activity 1 now fulfillthe purpose of an objective instrument that is uti-lized for validating the preliminary knowledgeinfrastructure design. By checking each fit criter-ia against 1) every defined knowledge process

18Here, knowledge infrastructure design is understood as a pro-duct (vs. a process); e.g., a design document that marks out theform of the final solution.


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and 2) against the knowledge infrastructuredesign, the knowledge infrastructure designercan identify fits as well as deficits in the currentdesign. A lack of sufficient fits leads to iteratingthrough design activities 2 and 3 (as depictedby fork B in Figure 9).

To summarize: the application of the B-KIDEMethod yields to a design space that is quantita-tively open (in terms of the number of possibledesigns) but qualitatively closed (in terms of therequirements supported).

In other words, the application of the B-KIDEMethod in knowledge infrastructure developmentprojects prescribes what needs to be implementedin the targeted knowledge infrastructure designs(in the sense of functional requirements—in orderto support the defined knowledge processes), butnot how this functionality is provided.

THE B-KIDE TOOL

Introduction

The B-KIDE Tool supports knowledge analysts andknowledge infrastructure designers in applying theB-KIDE Framework. The tool implements the B-KIDE Modeling Structure to provide a formal, sup-portive instrument that reduces the complexity ofthe B-KIDE Framework application. The B-KIDETool represents an instrument for structured,business process-oriented interviews betweenknowledge analysts and knowledge workers

(employees) of an organization. The gathered inter-view data is utilized by knowledge infrastructuredesigners to lay out the design of business processsupportive knowledge infrastructures.

Figure 10 illustrates the principle approach of theB-KIDE Tool. Front-end interview forms, appliedby knowledge analysts during interview situations,provide means to map gathered interview data onthe B-KIDE Modeling Structure. This ensures thatgathered interview data conforms to the B-KIDEModeling Structure. On top of the interview data,a set of B-KIDE Tool Reports19 allows for generat-ing a broad range of different model perspectives(such as a Knowledge Process Landscape) andthereby allows for generating different models oforganizational knowledge work as a basis for pro-found analysis.

Tool structure

The B-KIDE Tool is based on the object-orientedstructure depicted in the UML diagram inFigure 11. Thus, a B-KIDE project consists ofmultiple interviews and a set of reference models.Each interview contains information about the inter-view context as well as the actual interview data.Interview context contains information about therelevant interviewee, his organizational role, andthe analyst who performs the interview. Interview

Figure 10 B-KIDE Tool principle approach

19As already exemplarily introduced in Figure 7.

Figure 9 Design process: designing knowledge infrastructures



data contains all elicited, interviewee-specific inter-view information gathered through a series of inter-view forms. In addition to that, reference models,which exist in parallel to interview data, representmodels of specific dimensions of organizationalsystems and provide the basis for modeling organi-zational knowledge work with the B-KIDE Tool.These dimensions are based on the five referencemodels20 from the B-KIDE Model Architecture,which are: (1) Knowledge Domain Reference Mod-el; (2) Business Process Reference Model; (3) Orga-nizational Roles Reference Model; (4) TransferObject Reference Model; and (5) Storage ObjectReference Model. With the B-KIDE Tool, thesedimensions are modeled in a collaborative effortbetween knowledge analysts and interviewees.

Figure 12 depicts the implementation of the mainelements in the B-KIDE Tool user interface. Whilethe area containing the reference models remainsthe same across different interviews of the sameproject, the interview context depicts informationspecific to certain interviews. The interview dataarea, which changes with changing interviewees,represents the central area for analysts to gatherinformation during interviews. Knowledge ana-lysts raise questions provided by the B-KIDE Tool(Situation ‘A’ in figure 12) and document answersthrough, for example, dragging and dropping ele-ments from the reference model area up to theinterview data area (Situation ‘B’ in figure 12).The application of the B-KIDE Tool on an operative

level is illustrated by the following accessible appli-cation scenario.

Application scenario: knowledge analyst Arthur,utilizing the B-KIDE Tool, asks interviewee Billwhat information he needs in order to be able toexecute the business process ‘Acquisition’, inwhich he is involved. Bill replies that informationabout potential customers is necessary for him inorder to successfully execute this process. Arthurdrags the already existing knowledge domain‘knowledge about customers’ from the knowledgedomain reference model up to the respectiveanswer field within the interview data area. TheB-KIDE Tool notices this action and translatesthe established relation21 to the B-KIDE modelingstructure. In doing that, knowledge work in busi-ness processes is modeled in a way that wasdepicted and introduced in Figure 5.

Interview data within the B-KIDE Tool is struc-tured according to the UML diagram depicted inFigure 13. Here, the mapping of interview dataonto the B-KIDE Modeling Structure takes place.An Interview Form consists of two Interview DataPanels (which focus on the generation and applica-tion of knowledge by a knowledge worker throughthe utilization of request/respond patterns), whichthemselves contain multiple interview lines. EachInterview Line is concerned with a specific Knowl-edge Domain that is either applied or generated bythe interviewed knowledge worker. For eachknowledge domain, communication partners

Figure 11 Simplified illustration of the B-KIDE Tool’s main structure

20The Generation and Application Reference Models were notimplemented in the B-KIDE Tool because of the foci of the antici-pated case/pilot studies.

21In prose, this relation can be described in the following way: InBusiness Process ‘Acquisition’, knowledge about customers is appliedby the organizational role ‘sales agent’.


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(Organizational Roles in corresponding Business Pro-cesses) and aspects of storage/transfer can be docu-mented. The structure provided by the B-KIDETool to document that information ensures theappropriate mapping of the gathered data ontothe B-KIDE Modeling Structure.

B-KIDE Tool reports

The B-KIDE Tool supports the generation of twomain model perspectives on the B-KIDE ModelingStructure. First, a Business Process Landscape visua-lizes organizational business processes and related

Figure 12 Main user interface of the B-KIDE Tool

Figure 13 B-KIDE Tool interview data area



knowledge work. The main structuring elements ofthis perspective are business processes. This per-spective is similar to traditional approaches of busi-ness process-oriented modeling of knowledgework as introduced, for example, by Gronau et al.(2003) and Allweyer (1998). Secondly, a KnowledgeProcess Landscape visualizes organizational knowl-edge domains and related business process. Thisrepresents an orthogonal (knowledge-oriented)view on business processes and a novel approachto knowledge process modeling. As already intro-duced in Figure 3, the main structuring elementshere are not business processes but knowledgedomains. Figure 14 illustrates how B-KIDE Toolreports can be generated with the B-KIDE Tool.

B-KIDE Tool implementation

The B-KIDE Tool implementation is based onMicrosoft’s .NET Framework # and the program-ming language VB.NET in combination withadvanced technology such as the Extensible MarkupLanguage (XML) (Bray et al., 2004) or Scalable VectorGraphics (SVG Working Group, 2003) utilizingsophisticated programming techniques such asobject-oriented application and data design andobject persistence.

EMPIRICAL WORK

Overview of studies conducted

The concept of case and pilot studies wasemployed to assess the ability of the B-KIDE Fra-mework to achieve reasonable results in complex,

real-world scenarios. The selection of appropriatestudies was driven by the ambition to apply theB-KIDE Framework in the most heterogeneousenvironment available in order to determine thesupported degree of generality. Table 122 gives anoverview of the main contents of the three studiesconducted with partners from the software, auto-motive and consulting industries. Subsequentlyone conducted study is introduced in greater detail(Case Study 1), while the remaining studies (PilotStudies 1 and 2) are only briefly discussed.

Case Study 1

Case Study 1 was concerned with the developmentof a knowledge infrastructure comprising role-oriented and business process supportive knowl-edge portals for a software developing company.These knowledge portals were supposed to (1) pro-vide the targeted roles with information relevant totheir respective business processes and (2) be inter-linked with each other, to effectively transportinformation from/to involved knowledge workers.In this explorative case study, a tentative B-KIDEFramework was applied. On one hand, the tenta-tive framework was utilized to analyze the givenbusiness context and layout the final design of theanticipated technological knowledge infrastruc-ture, while, on the other hand, the case study aimedto improve the quality of the tentative B-KIDEFramework.

Figure 14 Knowledge Process Landscape generation with the B-KIDE Tool

22EDM: Engineering data management; KI: knowledge infra-structure.


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By applying the B-KIDE method to the identifiedas-is knowledge processes, to-be knowledge pro-cesses were defined that need to be supported bythe anticipated knowledge infrastructure. Beneaththat, a set of four fit criteria was developed (suchas ‘All defined roles shall be able to provide knowl-edge they generate within the defined knowledgeprocesses to the anticipated knowledge infrastruc-ture in a fast and easily comprehensible way’). Byutilizing the fit criteria in the knowledge infrastruc-ture design process, the defined to-be knowledgeprocesses (KP) were integrated into the knowledgeinfrastructure design (as schematically depicted inFigure 15). This procedure led to an implementa-tion of a technological knowledge infrastructurethat contained four strongly interconnected, role-oriented and business process supportive knowl-edge portals based on Hyperwave, a knowledgemanagement software that provides ‘Arrow 3’KM functionality (Maurer and Tochtermann,2002). Beneath the (visible) results of Figure 15, aset of concepts (including an access, structure andcontent concept) derived from the knowledgeinfrastructure reference architecture was devel-oped. The implemented knowledge infrastructuresuccessfully provides support for the definedknowledge processes and, thereby, for the respec-tive targeted knowledge-intensive business processnetwork.

Pilot studies

In subsequent pilot studies, the concept of actionresearch was utilized. Action research here wasregarded to pursue a dual goal (Kock, 1997): (1)improving the organization participating in theresearch through so-called positive interventions(pilot studies); and (2) rigorously generating validand consistent knowledge with respect to thedefined B-KIDE Framework objective. Two justifi-

cative pilot studies were conducted that bothapplied (through instantiation and utilization) theB-KIDE Framework and the B-KIDE Tool devel-oped. Pilot Study 1, conducted in cooperationwith a company from the automotive industry,focused on the evaluation of an existing knowledgeinfrastructure (a technological engineering datamanagement system). Based on the delta betweendefined and identified knowledge processes, a setof improvement potentials could be generated.These improvement potentials led to increasedsupport of the EDM system for the pilot study com-pany’s business processes. In Pilot Study 2, theorganizational intranet of a study partner fromthe consulting industry was improved to bettersupport the existing business process ‘Acquisition’.By applying the B-KIDE Framework in this pilot, aknowledge infrastructure design (based on thecompany’s intranet) was developed that traceablysupported knowledge work of the targeted rolesin their respective business processes.

Lessons learned

The application of the B-KIDE Framework in thethree conducted studies generated valuable inputfor framework improvements. One issue thatemerged from applying the B-KIDE Frameworkto real-world scenarios was the introduction andlabeling of knowledge domains during modeling.Knowledge analysts struggled with heterogeneousvocabulary and term boundaries in organizations.To overcome this issue, two major measures weretaken: (1) the element knowledge domain wasextended with an attribute buzzwords to allow forthe assignment of multiple labels to a single knowl-edge domain; (2) pre-modeling of knowledgedomains was introduced to the pre-modeling activ-ity of the B-KIDE modeling technique. Thereby,together with domain experts, an initial prototype

Table 1 Overview of studies conducted

Case Study 1 Pilot Study 1 Pilot Study 2

Project context Software industry,ISO 9001:2000 certified

Automotive industry,formally defined businessprocesses

Consulting industry, noformally designed businessprocesses

Project goals Knowledge portal design EDM system improvement Intranet improvementHypothesis tested B-KIDE Framework B-KIDE Framework and B-KIDE ToolFramework application Design Evaluation DesignProject results Design and implementation

of four knowledge portalsEDM system improvementpotentials

Design of a KI to supportthe acquisition process

Study style Explorative Justificative JustificativePrimary actor Authors A 3rd person A 3rd personEvaluation concerning B-KIDE Framework Objective



of a knowledge domain reference model is devel-oped in order to ease the process of interviewing.Experiences in one pilot study indicate that withsuch a procedure approximately 50% of all identi-fied knowledge domains can be pre-modeled.

The utilization of the B-KIDE Tool in knowledgeinfrastructure development projects allowedknowledge analysts that were mainly unfamiliarwith the B-KIDE Framework to easily conduct pro-cess-oriented interviews that conform to the B-KIDE Modeling Structure. Experiences in the threestudies showed that the application of the B-KIDETool significantly lowered the work burden forknowledge analysts. Yet, users needed someamount of training to be able to apply the B-KIDETool appropriately. Therefore, interview guidelinesfor knowledge analysts were provided and witheach knowledge analyst a set of supervised testinterviews (two to three) was conducted in orderto enhance the performance of subsequent inter-views.

OUTLOOK AND CONCLUSIONS

This contribution successfully meets its twoaddressed research challenges. The B-KIDE Frame-

work is able to identify and support relevantknowledge interactions in complex business pro-cess networks. This was successfully achieved inthree studies conducted with industrial partners.By applying the B-KIDE Method for the develop-ment of technological knowledge infrastructures,an agreed-upon degree of support for knowledgeinteractions (knowledge processes) could beensured and achieved. Research challenge 2 wassuccessfully addressed as well: the B-KIDE Frame-work provides comprehensive guidelines on howto employ ‘Arrow 3’ KM functionality (routing ofrelevant information) in given business contextsin a way that suits both organizations and employ-ees. Two23 of the three studies performed actuallyintegrated ‘Arrow 3’ KM functionality in theirrespective knowledge infrastructure designs forthe support of knowledge intensive business pro-cesses.

In the process of performing this research, anumber of issues were identified but notaddressed. First, the B-KIDE Framework deals

Figure 15 Case Study 1 results: four role-oriented knowledge portals

23These two studies were those where the B-KIDE Method wasapplied in a design (vs. evaluation) mode: Case Study 1 and PilotStudy 2.


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with how KM functionality can be applied in spe-cific business contexts to support the execution ofcomplex business process networks. However,when it comes to detailed questions of knowledgeinfrastructure designs24 the B-KIDE Frameworkrefers to available design approaches. While thisis a reasonable approach because of the heteroge-neous set of available KM technologies, it bearsan interesting starting point for future research.Future work on this topic should focus on thedevelopment of KM functionality-specific designapproaches based on available concepts to furtherease the process of developing knowledge infra-structures for knowledge infrastructure designers.Secondly, the developed B-KIDE Tool only indir-ectly supports knowledge infrastructure designersin defining knowledge processes through XML-based B-KIDE Tool reports. Future developmentof the B-KIDE Tool should focus on that issue byproviding a user interface that allows for the defini-tion of to-be knowledge processes based on identi-fied ones. This would further lower the workburden for knowledge infrastructure designersand would lead to a more comprehensively tool-supported B-KIDE Framework.

To conclude, this work contributes to a series ofcurrent scientific topics, including the following:

� This contribution provides a generic frameworkfor the development of business process-suppor-tive, technological knowledge infrastructures.The B-KIDE Framework leads to knowledgeinfrastructure designs that ensure a certaindegree of support for knowledge-intensive busi-ness processes and corresponding knowledgeworkers in a traceable and repeatable way.Thereby, it ensures quality and reduces arbitrari-ness of the developed knowledge infrastructuredesigns across various application domains.The B-KIDE Framework therefore represents auniversally applicable theory for knowledgeinfrastructure development projects in organiza-tions that is easily testable by the principle ofinstantionation.

� Although the identification of knowledge pro-cesses has received attention from currentresearch, this contribution introduces a noveland suitable concept for the identification andvisualization of complex knowledge processesand interactions that span a multitude of busi-ness processes and related knowledge workers.The introduced concept of knowledge processes

allows for the identification, visualization andmodeling of greatly distributed knowledgework in organizations. Thereby, it enablesdetailed investigations of organizational knowl-edge work by taking the complex nature ofknowledge into account.

� This contribution uniquely integrates organiza-tional and technological dimensions of knowl-edge infrastructure development efforts. Byintroducing an integrative concept, which con-nects knowledge requirements of business pro-cesses to technological KM functionality, the B-KIDE Framework significantly contributes tocurrent research focusing on closing the gapbetween business process management andinformation systems design approaches (Giaglis,1999; Weerakkody and Currie, 2003).

� This contribution introduces a novel modelarchitecture and a supportive software tool thatenable the development of inter-subjective mod-els of organizational knowledge work. Analyzingcomplex, combined social and technological sys-tems such as organizations is not typicallyaccomplished through direct interventions inthe system, but indirectly through appropriatemodels of the system in question (Ferstl andSinz 2001). The B-KIDE Framework introducesa model architecture for modeling organizationalknowledge work that specifies model elements,relationships, rules and semantics and thusenables modelers to check structural and beha-vioral consistency as well as completeness oftheir models. The innovative B-KIDE Tool repre-sents an implementation of the B-KIDE ModelArchitecture that eases the application of theintroduced concepts. Applying the B-KIDE Fra-mework together with the accompanying B-KIDE Tool reduces complexity found in knowl-edge-intensive organizations (with respect to amodeling goal) and leads to the development ofinter-subjective models of organizational knowl-edge work.

� This contribution answers the question of howcertain maturity levels of existing KM maturitymodels (e.g., Paulzen and Perc, 2002; Oberweisand Paulzen, 2003) can be achieved. The applica-tion of the B-KIDE Framework in knowledgeinfrastructure development projects enablesorganizations to raise their knowledge manage-ment maturity level and to significantly increasetheir ability to appropriately deal with the criticalresource knowledge.

More comprehensive details and backgroundinformation about the B-KIDE Framework andthe B-KIDE Tool can be found in Strohmaier (2004).

24Here, again, knowledge infrastructure design is understood asa product (vs. a process).



ACKNOWLEDGEMENTS

The Know-Center is a Competence Center fundedwithin the Austrian Competence Center programK plus under the auspices of the Austrian Ministryof Transport, Innovation and Technology (www.kplus.at).

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