KEY CHARACTERISTICS IN SELECTING SOFTWARE TOOLS

FOR KNOWLEDGE MANAGEMENT

Hanlie Smuts

, Alta van der Merwe

1,2

and Marianne Loock

School of Computing, P.O. Box 392, UNISA, South Africa

Meraka Institute, P.O. Box 395, Pretoria, South Africa

Keywords: Knowledge management characteristics, Knowledge management system selection.

Abstract: The shift to knowledge as the primary source of value results in the new economy being led by those who

manage knowledge effectively. Today’s organisations are creating and leveraging knowledge, data and

information at an unprecedented pace – a phenomenon that makes the use of technology not an option, but a

necessity. Software tools in knowledge management are a collection of technologies and are not necessarily

acquired as a single software solution. Furthermore, these knowledge management software tools have the

advantage of using the organisation’s existing information technology infrastructure. Organisations and

business decision makers spend a great deal of resources and make significant investments in the latest

technology, systems and infrastructure to support knowledge management. It is imperative that these

investments are validated properly, made wisely and that the most appropriate technologies and software

tools are selected or combined to facilitate knowledge management. In this paper, we propose a set of

characteristics that should support decision makers in the selection of software tools for knowledge

management. These characteristics were derived from both in-depth interviews and existing theory in

publications.

1 INTRODUCTION

Imagine that, in the same way that a disc failure on

your personal computer or laptop erases all

information in the file folders, all intellectual capital

within your organisation is erased from the

employees’ minds and the organisation’s storage

media. There is no doubt that the market value of

such an organisation will be affected severely as

decisions in an organisation are made based on

sufficient, relevant and accurate knowledge (Meyer

and Botha 2000).

Knowledge assets are of much greater value than

any tangible asset, all of which provided

organisations with a competitive edge in the past

(Davenport and Prusak 1998). This knowledge asset

provides the basis for creating sustainable

competitive advantage in the knowledge age (Covey

2004). Furthermore, as new technologies,

innovation, organisational flexibility and new and

better forms of leadership propel the growth and

earnings of knowledge-intensive companies, so the

need to extract wealth from brainpower and

knowledge (individual and organisational) becomes

increasingly pressing. An organisation that kept its

workforce skills and expertise could operate quickly

even though it lost all of its equipment. An

organisation that lost its workforce, while keeping

its equipment, would never recover.

Today’s organisations are creating and

leveraging knowledge, data and information at an

unprecedented pace and the extraordinary growth in

on-line information, makes the use of technology not

an option, but a necessity (Lindvall, Rus et al. 2001;

Abar, Abe et al. 2004). This influence of technology

on the maintenance of knowledge management

actions is widely accepted, as technology adds value

by reducing time, effort and cost in enabling people

to share knowledge and information; especially

when it is closely aligned with organisational

requirements, the way people work and are

supported by and integrated with relevant processes

(Hoffmann, Loser et al. 1999).

A long-term view of fostering the knowledge-

base competence of an organisation is required

when selecting knowledge management software

tools and information technology is needed that aids

an effective and efficient knowledge-conversion

process while increasing the swiftness and ease of

170

Smuts H., der Merwe A. and Loock M. (2009).

KEY CHARACTERISTICS IN SELECTING SOFTWARE TOOLS FOR KNOWLEDGE MANAGEMENT.

In Proceedings of the 11th International Conference on Enterprise Information Systems - Artiﬁcial Intelligence and Decision Support Systems, pages

170-179

DOI: 10.5220/0001991401700179

 SciTePress

switching from one such process to another

(Nonaka, Reinmoller et al. 2001; Yu, Kim et al.

2004). However, the challenge is that there is not

necessarily a blueprint available for this integrated

view or a standard set of characteristics defined that

technology must comply with, to be categorised as a

typical knowledge management system. This

motivates the need for this research where we

provide a set of features toward defining a

characteristic set for a typical knowledge

management solution. Organisation and business

decision makers, who invest in expensive systems

and infrastructure to support knowledge

management, could use this set of features to assist

them during the toolset selection process.

In section 2 we provide a knowledge

management overview, followed by a synopsis of

the method used to gather the characteristics in

section 3. In section 4 we list the characteristics

derived and the conclusion of the study is reflected

in section 5.

2 THE KNOWLEDGE IN

KNOWLEDGE MANAGEMENT

While some epistemologists spent their lives trying

to understand what it means to know something

(Davenport and Prusak 1998; Clarke and Rollo

2001), Plato first introduced the concept of

knowledge as justified, true belief in 400 B.C.

(Meno, Phaedo and Theaetus as cited by Nonaka and

Takeuchi 1995). Advances in knowledge described

the achievements of the ancient Greek, Roman,

Egyptian and Chinese civilisations and the

transforming impact of the industrial revolution was

characterised by the application of new knowledge

in technology (Clarke and Rollo 2001; Moteleb and

Woodman 2007).

For the purpose of this paper, a more pragmatic

approach has been followed and the following

working description of knowledge has been explored

(Davenport and Prusak 1998 : 5): “Knowledge is a

fluid mix of framed experiences, values, contextual

information and expert insight that provides a

framework for evaluating and incorporating new

experiences and information. It originates and is

applied in the minds of knowers. In organisations, it

often becomes embedded not only in documents or

repositories but also in organisational routines,

processes, practices and norms.”

Knowledge can be categorised as either being

explicit or implicit. Explicit knowledge can be

defined as knowledge that has been articulated in the

form of text, diagrams or product specifications for

example (Clarke and Rollo 2001; Nickols 2001).

Nonaka (1991) refers to explicit knowledge as

formal and systematic, like a computer program. In

organisations today, explicit knowledge resides in

best practices documents, formalised standards by

which goods and services are procured and even

within performance agreements that have been

documented in line with company and divisional

goals and objectives.

Implicit knowledge is far less tangible than

explicit knowledge and refers to knowledge deeply

embedded into an organisation’s operating practices

(Kothuri 2002). Tacit knowledge, as a dimension of

implicit knowledge, includes relationships, norms

and values. It is knowledge that cannot be articulated

and it is much harder to detail, copy or distribute, to

the contrary, the knowing is in the doing in this

instance (Clarke and Rollo 2001). Tacit knowledge

can provide competitive advantage to organisations

as it is protected from competitors (Hahn and

Subramani 2000; Wessels, Grobbelaar et al. 2003).

The management of explicit and implicit

knowledge is a multifaceted subject based on the

dimensions of knowledge and therefore there are

various and varied definitions for it (Newman and

Conrad 1999). McCullough (2005) concludes that,

based on the vast majority of academic research into

knowledge management, there is a general difficulty

for organisations to explain what they mean when

they use the term knowledge management. For the

purpose of this paper the following definition of

knowledge management as suggested by Choo

(1995) will be used: “a framework for designing an

organisation’s goals, structures and processes so that

the organisation can use what it knows to learn and

to create value for its customers and community”.

Technology is a key enabler of knowledge

management and knowledge management processes

as it extends the reach and enhances the speed of

knowledge transfer (Chua 2004). Technology

permits the knowledge of an individual or group to

be structured and codified and allows distribution of

knowledge across the world (Davenport and Prusak

1998; Wessels, Grobbelaar et al. 2003). Knowledge

management technology is a broad concept and

organisations apply a wide variety of technologies to

the objectives of knowledge management

(Davenport and Prusak 1998; Lindvall, Rus et al.

2001).

Explicit knowledge is found in reports,

documents and manuals and can easily be gathered

and stored as a knowledge base (Clarke and Rollo

2001). Organisations use groupware applications to

KEY CHARACTERISTICS IN SELECTING SOFTWARE TOOLS FOR KNOWLEDGE MANAGEMENT

171

collect, store and share their explicit knowledge, and

once this has reached a sufficient level of efficiency,

collaborative technologies such as intranet, the

internet, extranet, e-mail, video-conferencing and

tele-conferencing are used to assist in the growth of

tacit knowledge transfer (Wessels, Grobbelaar et al.

2003). In order to enable organisations to retrieve

captured knowledge, knowledge route maps and

directories are developed to create an understanding

of the location of knowledge (Alavi and Leidner

2001; Clarke and Rollo 2001). Knowledge networks

are created using virtual business environments such

as chat rooms, team web sites and learning

communities (Alavi and Leidner 2001; Clarke and

Rollo 2001) with the development of specific

applications of technology such as databases,

workflow systems, personal productivity

applications and enterprise information portals

(Wilson and Snyder 1999; Wessels, Grobbelaar et al.

2003).

“Knowledge management systems [are] more

than just information systems or IT-enabled tools in

support of knowledge management activities”

according to Tsai and Chen (2007 : 258). Instead, a

knowledge management system must be a socio-

technical system as a whole which comprises the

knowledge itself (the intellectual capital of the

organisation), organisational attributes (intangibles

such as trusting culture), policies and procedures, as

well as some form of electronic storage and retrieval

systems.

Different ways of classifying knowledge

management technologies are utilised in the

literature and Antonova, Gourova et al (2006)

categorised technological solutions according to the

following knowledge management processes: (1)

generation of knowledge, (2) storing, codification

and representation of knowledge, (3) knowledge

transformation and knowledge use and (4) transfer,

sharing, retrieval, access and searching of

knowledge.

These specific implications of knowledge and

knowledge management on knowledge management

systems are important as these different views lead

to different perceptions and definitions of

knowledge management systems (Asgarkhani 2004).

3 DATA COLLECTION

The purpose of this paper is to collate a set of

features towards defining a characteristic set for a

typical knowledge management solution. A list of

knowledge management system characteristics was

compiled from the literature and formed the

framework and basis for the research interview

questions. Eight in-depth interviews were conducted

at one of the major mobile telecommunication

providers in South Africa where after the

characteristic set was updated. We used different

criteria, ranging from technical and systems

background to job grade and level, to select research

participants. The rationale for selecting the specific

criterion and the typical profile of an interview

participant complying with the criterion, is depicted

in Table 3-1.

The main criteria that informed the participant

profile were environments where knowledge and

knowledge sharing are key priorities, behaviours

regarding knowledge sharing and some knowledge

on human resource aspects in order to obtain input

on the human-computer interface and related issues.

Furthermore, research participants with a technical

background, who understand systems with broad

business process knowledge, as well as a systems

and business architecture background, informed the

profile. Lastly, these criteria were applied across

different management (job grade) levels and

leadership styles in the organisation. The interviews

were transcribed and the outcome obtained from the

interviews, as well as theory from the literature, was

used to compile a comprehensive list of

characteristics described in section 4.

4 KNOWLEDGE MANAGEMENT

SOLUTION

CHARACTERISTICS

FOR TECHNOLOGY TOOL

SELECTION

The development and evolution of a large number of

software tools have been facilitated based on the

application of technologies to the creation of

knowledge management solutions (Lindvall, Rus et

al. 2001; Xie, Zhang et al. 2006). Although

knowledge management tools are enhancements of

existing technologies, true knowledge management

technologies differ in several important aspects from

the traditional workflow, document management,

intranet and groupware solutions (O'Leary 1998;

Frappaolo and Capshaw July 1999).

Each characteristic is described by means of the

classification of knowledge management

technologies. This description includes the

distinguishing characteristic of a knowledge

management system, a description of the feature and

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Table 3-1: Criteria for defining research participant profile.

Criteria Rationale Typical Participant Profile

1 Technical / technology / systems

background

Utilise their understanding of systems and

systems architecture

Information Systems and Network

Group (engineering) participants

Human resources / behavioral

background

Obtain input on the human computer

interface and any issues around this

interface

Organisational Development (Human

resources) participants

Environments where knowledge and

knowledge sharing are key for success;

environments where key assets go home

every day

Determine issues around knowledge

sharing within the Group and of key

specialist skills and knowledge

System, Business Architecture and

System Architecture specialists

Job grade in Group and in South African

operation

Obtain input from different levels of work

and different operational levels; obtain

input from different management and

leadership styles

Different levels of participants w.r.t.

job grades e.g. Executives, General

managers, Senior Managers, etc.

Broad business, people, process and

system knowledge

Obtain input on “big picture” issues /

requirements around business, people and

knowledge management

Generalists in company, participants

required to integrate all management

aspects in order to deal with their

respective departments

an example clarifying the characteristic.

4.1 Classification 1: Generation of

Knowledge

The first classification dimension is generation of

knowledge, which comprises of activities for

knowledge creation, acquisition and capturing as

shown in Table 4-1.

With regard to knowledge content generation,

authoring, knowledge creation, knowledge objects

and content validation are important. Authoring

encompasses sources of explicit knowledge line

documents, manuals, proposals, e-mail messages,

etc., as well as implicit knowledge. Knowledge

creation refers to the generation of new knowledge

through thinking or reasoning and knowledge

objects encompass an object of structured

information, un-structured information, insight,

facts, practical and theoretical experience, as well as

best practice to be stored and manipulated. Content

validation points to the validation and auditing of

knowledge objects when they are captured and

resolves data and information conflicts.

Knowledge discovery allows the generation of

knowledge through knowledge harvesting, content

evolution and ensuring that this is made easily

accessible and available via various distribution

bearers. Knowledge harvesting is the process of pro-

actively facilitating the harvesting and capturing of

ideas. Knowledge, expertise and content evolution

refer to the creation of knowledge by combining

new sources of knowledge, optimising feedback

loops and by re-applying and re-creating knowledge.

Data capturing tools enable the capture of

knowledge and consists of characteristics such as

externalisation, maintenance and update, storing and

content capture. This toolset ensures that knowledge

in the repository is maintained by providing

mechanisms to refresh data and information.

Externalisation refers to the connection of

information source to information source and to

creating interrelationships while maintenance and

update ensure that knowledge objects in the

knowledge management system stays valid and

recent. It includes a formal change process for

captured knowledge and also provides versioning of

content. Storing supports knowledge creation

through exploitation, exploration and codification

and content capture facilitates the capture of

knowledge through mechanisms such as a keyboard,

optical character recognition, bar code identification

and real-time location sensors.

4.2 Classification 2: Storing,

Codification and Representation of

Knowledge

The second classification dimension is storing,

codification and representation of knowledge, which

comprises of activities contributing to effective

storage, human-readable knowledge and the

organisation of knowledge, as depicted in Table 4-2.

This dimension focuses on knowledge

management processes and the quantity, quality,

accessibility and representation of the acquired

knowledge. Several technologies for storage

consisting of several relevant characteristics have

been identified in the literature and obtained from

the research participant interviews. Archiving refers

to archiving ability based on certain criteria and

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Table 4-1: Characteristics for the generation of knowledge.

Generation of knowledge

Dimension Characteristic Description Example

Knowledge

content

generation

Authoring

Encompasses knowledge objects i.e. sources

of explicit (e.g. documents, manuals,

proposals, email messages) or implicit

knowledge (e.g. people)

Supported by standard authoring tools like

word processors and database management

systems (DBMS)

Knowledge

creation

Refers to generation of new knowledge

through thinking or reasoning

Brainstorming

Knowledge

objects

Knowledge is an object of structured

information, un-structured information,

insight, facts, practical and theoretical

experience, as well as best practice to be

stored and manipulated.

KMS will not appear radically different from

existing IS, but will be extended toward

helping in user assimilation of information.

Role of IT involves gathering, storing and

transferring knowledge.

Content validation

Validation and auditing of knowledge

objects when they are captured and

resolution data and information conflicts

Knowledge object auditor validates

submissions for knowledge repository before it

is published

Knowledge

discovery

Knowledge

harvesting

Pro-active facilitation of harvesting and

capturing of ideas, knowledge, expertise

Knowledge harvesting workshops and focus

groups, defining tangible knowledge and

capturing it

Content evolution

Knowledge creation, combining new sources

of knowledge, optimise feedback loops and

re-apply, re-create

Data mining and learning tools

Various

distribution

bearers

Ease of access and availability SMS knowledge source to knowledge seeker

Data

capturing

tools

Externalisation

Refers to the connection of information

source to information source and creating

interrelationships; integration of

organisational interdependencies

Focuses on explicit knowledge and provides a

means to capture and organise this knowledge

into a knowledge repository

Maintenance and

update

Ensures that knowledge objects stay valid

and recent

Workflow enabled review indicator

Storing

Support knowledge creation through

exploitation, exploration and codification

Technology enabled store or knowledge

repository that can support less structured

information

Content capture

Facilitates the capture of knowledge through

different mechanisms

Keyboard, optical character recognition, bar

code identification and real-time location

sensors

business rules specified by knowledge base

administrators, while capability is the characteristics

indicating the potential to influence action,

processing, decision-making and application.

Customisation points to the configuration and set up

of the system reflecting the specific organisation or

user context (personalisation). Flexibility refers to

the characteristic regarding the handling of various

media. Security is an important characteristic that

addresses physical and logical security, since

knowledge is such a valuable asset, while storing in

this context refers to the commitment of knowledge

to the data warehouse, knowledge warehouse,

lessons learnt knowledge base or the data mart.

Some characteristics like application scalability,

back-up and housekeeping and hardware platform

independence ensure that the knowledge

management application can be adapted to the size,

application and hardware configuration of an

organisation while ensuring accessibility and proper

housekeeping of the physical infrastructure.

Human-readable knowledge consists of the

characteristic set including heuristic and content

capture. Heuristic means that the solution should

constantly learn about its users and the knowledge it

possesses as it is used. Its ability to provide a

knowledge seeker with relevant knowledge should

therefore improve over time. Content capture refers

to the characteristics that ensure that knowledge is

committed to the knowledge repository based on

certain rules.

Knowledge organisation includes classification,

indexing, internalisation, taxonomy and content

upload. Classification handles content management

according to the context of the organisation,

Indexing means content management according to

the context of organisation. Corporate taxonomy

refers to the definition of how the knowledge is

stored, where internalisation involves the extraction

of knowledge from the external repository and

subsequent filtering ensuring greater relevance and

appropriateness to the knowledge seeker.

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Table 4-2: Characteristics for storing, codification and representation of knowledge.

Storing, codification and representation of knowledge

Dimension Characteristic Description Example

Technologie

s for storage

Archiving

Encompasses knowledge objects i.e. sources of

explicit (e.g. documents, manuals, proposals, email

messages) or implicit knowledge (e.g. people)

Supported by standard authoring tools like

word processors and database management

systems (DBMS)

Capability

Knowledge is the potential to influence action,

processing, decision-making, application.

Role of IT is to enhance intellectual capital

by supporting development of individual

and organisational competencies.

Customisation

Configuration and set up of the system reflecting

the specific organisation or user context

Organogram of organisation

Flexibility

Solution should be able to handle knowledge of any

form as well as different subjects, structures,

taxonomies and media

If knowledge seeker wants to learn about

gramophone records, it should supply

knowledge on the technology as well as

purchasing trends and examples of famous

recordings

Security

Have to address physical and logical security since

knowledge is such a valuable asset

Implemented using inherent mechanisms in

each tool or by using specific tools in

addition to the existing system

Hardware

platform

independent

Allows application setup to size and infrastructure

of organisation

SMME applications

Storing

Support knowledge creation through exploitation,

exploration and codification

Technology enabled store or knowledge

repository that can support less structured

information

Application

scalability

Allows application setup to size of organisation SMME applications

Back-up and

housekeeping

Handles all backups and housekeeping around

knowledge repository

Relevant backup cycles

Human-

readable

knowledge

Heuristic

Solution should constantly learn about its users and

the knowledge it possesses as it is used i.e.

continually refine itself as a user’s pattern of

research is tracked by the system. Its ability to

provide a knowledge seeker with relevant

knowledge should therefore improve over time

If the solution responds to many requests on

a particular subject, it should learn how to

assist multiple users in more depth on that

subject

Content capture

Ensures that knowledge is committed to the

knowledge repository based on certain rules

Organisation knowledge map and taxonomy

Knowledge

organisation

Classification

Handles content management according to context

of organisation

Corporate taxonomy as knowledge map

supported by classifying and indexing tools

Date and time

stamp

Refers to the tagging of knowledge objects to track

recency

Date and time linked to knowledge objects

Indexing

Handles content management according to context

of organisation, corporate taxonomy

Corporate taxonomy as knowledge map

supported by classifying and indexing tools

Internalisation

Refers to the connection of explicit knowledge to

people or knowledge seekers

Involves extraction of knowledge from the

external repository and subsequent filtering

ensuring greater relevance to knowledge

seeker

Knowledge gap

identification

Allows a knowledge user to identify areas of the

knowledge repository that is utilised significantly

vs. underutilisation, as well as to identify areas

where more content can be uploaded and populated

in the knowledge repository

Knowledge repository usage report

Content upload

Identifies areas where more content can be

uploaded and populated in the knowledge

repository

Taxonomy elements without any references

Taxonomy Refers to the definition of how the knowledge is

stored

Organisation knowledge map and taxonomy

Knowledge gap identification is a feature that allows

a knowledge user to identify areas of the knowledge

repository that is utilised significantly vs.

underutilisation, as well as to identify areas where

more content can be uploaded and populated in the

knowledge repository. Date and time stamp refers to

the tagging of knowledge to track recency and the

mechanism to add more knowledge areas

respectively.

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Table 4-3: Characteristics for knowledge transformation and knowledge use.

Knowledge transformation and knowledge use

Dimension Characteristic Description Example

Knowledge

transformation

Search and retrieval

Primarily concerned with enhancing the

interface between the user and information /

knowledge sources, user-friendliness and

learning agility

Help users better understand the

information and knowledge available

by providing subject-based browsing

and easy navigation

Access to information

Encompasses the transformation of end-user

collected data and information before it is

committed to the knowledge repository

Knowledge object auditor validates

submissions for knowledge repository

before it is published

Knowledge

reconstruction

User sensitive

Solution should be able to organise the

knowledge in the way most useful to the

specific knowledge seeker

Should give knowledge relevant to

knowledge seeker’s current knowledge

level, facilitating easier understanding

Knowledge use

and retrieval

Application

Timeous availability of organisational and

individual memory, just in time learning.

Inter-group knowledge access

Expert systems, rapid application of

new knowledge through workflow

systems

System learning agility

Refers to the ease of learning and teaching

how to utilise the knowledge management

system

Guided e-learning and assessment

module

4.3 Classification 3: Knowledge

Transformation

and Knowledge Use

Classification dimension three is depicted in Table

4-3 consisting of knowledge transformation,

knowledge reconstruction and knowledge use. This

refers to the fact that once knowledge has been

acquired it cannot be used in its raw form and must

be transformed in order to become a valuable

knowledge asset.

Knowledge transformation ensures that the

knowledge conforms to the format of the target

repository and consists of two allocated

characteristics namely search and retrieval and

access to information, encompassing the

transformation of end-user collected data and

information before it is committed to the knowledge

repository.

Knowledge reconstruction ensures that

knowledge is presented in the particular reasoning

method that is used by the knowledge management

system, e.g. editing into case formats to support

case-based reasoning or a business intelligence

dashboard.

Knowledge use and retrieval encompasses expert

systems, decision support systems, visualisation

tools and knowledge simulation. This classification

dimension consists of processes of applying

expertise to knowledge, the ease of learning and

teaching how to utilise the knowledge management

system through a user-friendly user interface.

Application includes the timeous availability of

organisational and individual memory and just in

time learning, as well as inter-group knowledge

access.

4.4 Classification 4: Transfer, Sharing,

Retrieval, Access and Searching of

Knowledge

The fourth classification dimension is transfer,

sharing, retrieval, access and searching of

knowledge, which comprises of knowledge access,

searching, collaboration and sharing characteristics,

as shown in Table 4-4.

With regard to knowledge access and transfer,

allocation of characteristics and features consisting

of content delivery, access to information, multi-

language support and user-friendly user interface

were concluded. Access to information is facilitated

via a user-friendly user interface and the delivery of

content consisting of the gathering of user-

information and delivering appropriate content to

meet specific user needs.

Collaboration includes person to person as well

as team collaboration features encompassing the

support of the knowledge sharing process through a

social network analysis and collaborative tools, as

well as collective insights across operations and

different geographical locations. Workflow

enablement connects people in different ways

supporting increased work performance and

productivity.

Knowledge sharing includes intermediation - the

connection of people to people, i.e. bring together

those who are looking for a certain piece of

knowledge and those who are able to provide this

piece of knowledge.

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Table 4-4: Characteristics for transfer, sharing, retrieval, access and searching of knowledge.

Transfer, sharing, retrieval, access and searching of knowledge

Dimension Characteristic Description Example

Knowledge

access and

transfer

Content delivery

Personalisation involves gathering of user-

information and delivering appropriate content

to meet specific user needs aligned to user

profile

Electronic bulletin boards, through portals

is knowledge distributed as needed by

different applications

Access to

information

Encompasses the transformation of end-user

collected data and information before it is

committed to the knowledge repository

Knowledge object auditor validates

submissions for knowledge repository

before it is published

Multi-language

support

Refers to language setting of user interface or

translation feature to support knowledge seeker

User interface language configuration

User-friendly user

interface

Encompass ease of use of user interface Context-sensitive in-line help facility

Person to

person and team

collaboration

Collaboration

Support the knowledge sharing process through

a social network analysis and collaborative

tools; collective insights across operations and

different geographical locations; multi-

dimensional collaboration

Facilitate communication between users,

collaboration among users and workflow

management

Expertise applying

process

Knowledge is a process of applying expertise.

Role of IT is to provide link among sources

of knowledge to create wider breadth and

depth of knowledge flows.

Workflow enabled

Encompasses workflow enablement of

knowledge requests, content update notification

and knowledge object validation requests

Email information knowledge seeker that

knowledge object has been updated

Knowledge

sharing

Intermediation

Refers to the connection of people to people i.e.

bring together those who are looking for a

certain piece of knowledge and those who are

able to provide this piece of knowledge

Primarily positioned in the area of tacit

knowledge based on its interpersonal focus

Search and find

Accessibility

Knowledge is a condition of access to

information via different mechanisms (e.g. web

based) and locations.

Role of IT is to provide effective search

and retrieval mechanisms for locating

relevant information.

Appropriateness

Refers to display of suitability indicator based

on keywords specified by knowledge seeker

Appropriateness scale 1-15where 1 is very

relevant and 5 least relevant

Context sensitivity

Solution should be able to understand the

context of the knowledge requirement and

tailor response accordingly

Should be able to understand and respond

differently between animal reproduction

and document reproduction

Heuristic

Solution should constantly learn about its users

and the knowledge it possesses as it is used i.e.

continually refine itself as a user’s pattern of

research is tracked by the system. Its ability to

provide a knowledge seeker with relevant

knowledge should therefore improve over time

If the solution responds to many requests

on a particular subject, it should learn how

to assist multiple users in more depth on

that subject

Suggestive

Solution should be able to deduce what the

knowledge seeker’s knowledge needs are

Suggest knowledge associations the user is

not able to do

Relevance

Indicates the significance of knowledge objects

retrieved

Result set includes direct keyword retrieval

and well as context specific retrieval set

Search and retrieval

Primarily concerned with enhancing the

interface between the user and information /

knowledge sources, user-friendliness and

learning agility

Help users better understand the

information and knowledge available by

providing subject-based browsing and easy

navigation

Timeliness Knowledge is available whenever it is needed.

Eliminates time-wasting distribution of

information just in case it might be

required

Responsiveness

Encompasses almost immediate retrieval and

presentation cycles

Query response time

For the search and find dimension accessibility,

appropriateness, context-sensitivity, heuristic,

suggestive, relevance, search and retrieval,

timeliness and responsiveness are important.

Accessibility provides an effective search and

retrieval mechanism for locating relevant

information, while appropriateness indicates the

appropriateness level based on the filtering of

multiple inputs for the same knowledge object.

Context-sensitivity refers to the feature that the

solution should be able to understand the context of

the knowledge requirement and tailor responses

accordingly. Heuristic indicates that as the solution

responds to many requests on a particular subject, it

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should learn how to assist multiple users in more

depth on that subject, while suggestive deduces what

the knowledge seeker’s knowledge needs are.

Relevance indicates the significance of knowledge

objects retrieved, and search and retrieval are

primarily concerned with enhancing the interface

between the user and information, knowledge

sources, user-friendliness and learning agility.

Timeliness and responsiveness refer to the feature

that knowledge must be available whenever it is

needed with almost immediate retrieval and

presentation cycles.

4.5 Knowledge Management Solution

Selection

The characteristics defined in sections 4.1 to 4.4

were compiled based on the nature of knowledge

and knowledge management and may be applied in

different ways. One option is as a requirement

specification of a knowledge management system

before technology is acquired. Another option is to

use it as a checklist to evaluate existing technologies

for compliance to knowledge management solutions,

to identify gaps in existing technologies and to

assess suitability before purchasing new technology

to close the gaps.

Table 4-5: Knowledge management system characteristics

evaluation checklist (illustration only).

KMS characteristic

checklist

Technology

Dimension Characteristic

eGain

Knowledge

Sharepoint

Video-

conferencing

Person to

person and

team

collaboration

Collaboration

D D D

Expertise

applying

process

Workflow

enabled

Such a typical checklist is depicted in Table 4-5,

where one dimension, namely person to person and

team collaboration, with the characteristics

collaboration, user-sensitivity, expertise applying

process, refreshing of data and information and

workflow enablement, was used as a requirement of

a knowledge management solution. Three

technology solutions, namely eGain Knowledge,

Sharepoint and video-conferencing, were evaluated

against these characteristics to establish whether it

complies with requirements for a knowledge

management solution. From the result of the

evaluation reflected in Table 4-5, a combination of

eGain Knowledge and video-conferencing will

comply with all the requirements listed for person to

person and team collaboration, and a combination of

these two technologies can then facilitate knowledge

management in this example.

5 CONCLUSIONS

Knowledge assets are of much greater value than

any tangible asset within a company and provide an

organisation with a competitive edge, which

ultimately results in higher profits for the company.

A company with poor knowledge management

systems risk financial losses when losing its skills

and knowledge encapsulated within its workforce.

Leadership and management considering the

different management systems available to capture

its knowledge, is faced with numerous options as a

plethora of software tools are available.

The literature study emphasised that knowledge

is an organisational asset. Organisations today are

creating and leveraging knowledge, data and

information at an extraordinary rate and it makes the

use of technology not an option, but a necessity.

However, technology aimed at knowledge

management is not the only answer, as it is also

about the way knowledge workers create,

disseminate and manage information. The

development of a comprehensive knowledge

management system that supports all phases of

knowledge management is both a technological and

organisational solution and is not necessarily

available as a single technology. In order to ensure

that the technology and software tools fulfill

knowledge management requirements, organisations

must consider the definition of knowledge,

knowledge management principles, knowledge

management processes and the organisation’s

particular knowledge management requirements.

In this paper, we identified a set of

characteristics for decision makers in selecting

software tools that will comply with most of the

knowledge management solution characteristics in

supporting knowledge management within a

company. The main categories to be considered

include generation of knowledge, storing,

codification and representation of knowledge,

knowledge transformation and knowledge use and

transfer, sharing, retrieval, access and searching of

knowledge.

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The study was conducted at a mobile

telecommunication organisation within the South

African context, in an environment with a great

demand for skills and an extremely competitive

industry where innovation and value proposition are

key differentiators to increasing market share. The

characteristics were derived from a qualitative study

and further research is needed to generalise the list

of characteristics. However, according to informal

discussions with key decision makers within

different companies in South Africa, there is strong

evidence that these may also be appropriate for

smaller companies.

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