**5.1 Overview**

KM emerged as a scientific discipline in the early 1990s. It was initially supported solely by practitioners, when Scandia hired Leif Edvinsson of Sweden as the world's first Chief Knowledge Officer (CKO). Hubert Saint-Onge started investigating various sides of KM long before that.

The idea of a KMS is to enable employees to have ready access to the organization's documented base of facts, sources of information, and solutions. For example, an engineer could know the metallurgical composition of an alloy that reduces sound in gear systems. Sharing this information organization wide can lead to more effective engine design and it could also lead to ideas for new or improved equipment. (Langton & Robbins, 2006).

### **5.2 Knowledge management systems**

It has been suggested that the term "KMS project" should never be used as if it pertained to the same category as an IT or IM project (Terra & Gordon, 2002). KMS projects should take a holistic or organic view of the enterprise and should encompass different initiatives in many areas: certainly in IM, but also in HR, organizational design, internal communications and so forth. KM is more closely associated with the "act of managing" than IM.

In this sense, KM is never-ending. It is defined by the identification of people's expertise and the interplay of people with people (tacit knowledge-sharing) and people with information systems (two-way road of knowledge capture, reuse and recreation). Given that they are highly dependent on people's previous knowledge, motivation and willingness to create, act, share and or codify their own individual knowledge, KM processes are far more complex than IM projects. However, KMS is increasingly dependent on the support of a solid IT infrastructure.

### **5.3 Activity theory**

Initial large-scale software development efforts were chaotic, often resulting in an explosion of costs and development times which were much larger than originally predicted. The outcome was typically quite different from the original objective of the activity. Many times the object was simply not produced and the effort was abandoned after the investment of considerable resources, (Barthelmess & Anderson, n.d).

As a result, practitioners turned their attention to the development process itself. A new term, software engineering, was coined to represent this endeavour. Software engineering strives to further define techniques, processes, methodologies, and languages to ease the development of large software systems, (Barthelmess & Anderson, n.d).

Software engineering approaches the problem of collective development from a productionoriented viewpoint. While this view allows a certain amount of anticipatory reflection, e.g.,

To ascertain how KMS differ from conventional systems to warrant a different

To propose a roadmap for requirements elicitation for Knowledge Management

KM emerged as a scientific discipline in the early 1990s. It was initially supported solely by practitioners, when Scandia hired Leif Edvinsson of Sweden as the world's first Chief Knowledge Officer (CKO). Hubert Saint-Onge started investigating various sides of KM

The idea of a KMS is to enable employees to have ready access to the organization's documented base of facts, sources of information, and solutions. For example, an engineer could know the metallurgical composition of an alloy that reduces sound in gear systems. Sharing this information organization wide can lead to more effective engine design and it

It has been suggested that the term "KMS project" should never be used as if it pertained to the same category as an IT or IM project (Terra & Gordon, 2002). KMS projects should take a holistic or organic view of the enterprise and should encompass different initiatives in many areas: certainly in IM, but also in HR, organizational design, internal communications and

In this sense, KM is never-ending. It is defined by the identification of people's expertise and the interplay of people with people (tacit knowledge-sharing) and people with information systems (two-way road of knowledge capture, reuse and recreation). Given that they are highly dependent on people's previous knowledge, motivation and willingness to create, act, share and or codify their own individual knowledge, KM processes are far more complex than IM projects. However, KMS is increasingly dependent on the support of a

Initial large-scale software development efforts were chaotic, often resulting in an explosion of costs and development times which were much larger than originally predicted. The outcome was typically quite different from the original objective of the activity. Many times the object was simply not produced and the effort was abandoned after the investment of

As a result, practitioners turned their attention to the development process itself. A new term, software engineering, was coined to represent this endeavour. Software engineering strives to further define techniques, processes, methodologies, and languages to ease the

Software engineering approaches the problem of collective development from a productionoriented viewpoint. While this view allows a certain amount of anticipatory reflection, e.g.,

could also lead to ideas for new or improved equipment. (Langton & Robbins, 2006).

so forth. KM is more closely associated with the "act of managing" than IM.

considerable resources, (Barthelmess & Anderson, n.d).

development of large software systems, (Barthelmess & Anderson, n.d).

To review weaknesses of present KMS in achieving its intended goal.

**4. Research objectives** 

Systems using Activity Theory

**5.2 Knowledge management systems** 

approach.

**5. Literature review** 

**5.1 Overview** 

long before that.

solid IT infrastructure.

**5.3 Activity theory** 

the ability for subjects to predict important aspects of development prior to initiation and to assess results after completion (Floyd,1992), it blinds software engineers to the communicative aspects of a collaborative software development activity; (Barthelmess & Anderson, n.d).

Activity Theory (AT) is a philosophical and cross-disciplinary framework for studying different forms of human practices as development processes, with both individual and social levels interlinked at the same time, (Nardi, 1996).

AT is a development theory that seeks and explains qualitative changes in human practices over time (Uden, n.d). KMS also involves in qualitative changes in human practices, therefore AT is required in the development of KMS. AT helps to maintain adequately the relationship between the individual and social levels (Uden, n.d). KM Systems also incorporates relationship between the managerial personnel and its co-worker to the benefit of the organization (Nardi, 1996). This further emphasizes how AT can play an important role in the development of KM Systems.

AT helps to maintain adequately the relationship between the individual and social levels (Uden, n.d). KM Systems also incorporates relation between the managerial personnel and its co-worker to the benefit of the organization (Stahl, 2006), this emphasizes AT definitely plays an important role in the development of KM Systems.

#### **5.4 The connection between knowledge management system and software engineering**

KMS is developed in order to convince the need for improving productivity and the potential of employees and the company as a whole. The existing knowledge infrastructure is evaluated so that it can convey the idea that the present ways of doing things are not just sidelined in preference for a new system. KMS is a commercial system, generally IT based, mainly for managing knowledge and experience in organizations supporting creation, capture, storage and dissemination of information (Benbye, 2008).

In essence, KM is a method that simplifies the process of sharing, distributing, creating, capturing and understanding of a company's knowledge (Davenport & Prusak, 1998). KM starts with a problem and ends with a solution.

Software Engineering (SE) concerns methods and techniques to develop large software systems. The engineering metaphor is used to emphasize a systematic approach to develop systems that satisfy organizational requirements and constraints. Since SE is a typical knowledge-intensive discipline that evolves very fast and involves a large number of people, different phases and different activities (Rus & Lindvall, 2002), it is one of the disciplines that can benefits most from KM (Edwards, 2003). Does this mean that KMS follows SE principles?

It can be derived that both practices (KM & SE) start with a problem. For an example, one of the challenges in KM is to change organizational culture, whereby it involves changing the people attitudes and behaviours to ensure that they contribute to the sharing of knowledge to the organization. However to use SE to develop a large software system in the industry, the processes also follow a number of defined steps which are accepted as best practice by the software engineers. The early phase for SE starts with information or requirements gathering while KMS requires knowledge capture in order to kick-start the development phases. Both the software engineers and the knowledge developer need to specify the suitable tools for designing their intended systems. From this discussion, both practices

A Roadmap for Requirements Elicitation of

Knowledge developer gathers knowledge from people with the given knowledge and the developer depends on them for the solution

Knowledge developer deals with the domain expert

oriented (Sornlertlamvanich, n.d).

and irrelevant for most of its users (Straker, 2009).

warrant a different approach:

Knowledge Management Systems: A Delphi Study 59

From the table below, we can see how KM systems differ from conventional systems to

Experts know the solution and problem Users know the problem, not solution Result oriented, incremental, interactive Process driven, sequential Testing phase at the beginning Testing phase at the end

KM team must capture the knowledge requirements for the system to be built so that the end product will be meaningful to the organization and its users. Conventional systems development is primarily sequential, whereas KMS is incremental and interactive. In the case of a conventional system, testing is usually done towards the end of the cycle (after the system has been built), whereas in KMS, the evolving system is verified and validated from the beginning of the cycle. Systems development and systems management is much more extensive for conventional information systems than it is for KMS. The conventional systems life cycle is usually process-driven and documentation-oriented whereas KMS is result-

KMS can be a very complex system which comprises of expensive hardware solutions and complex indexed database. When KMS is completed, the developers of the system need to ensure that KMS is able to store tacit knowledge so that their effort proves to be successful. KMS has a reputation for costing a lot to set up, running into difficulties when trying to get everyone to contribute and ending up with a great deal of information that is inconsistent

Organizations tend to focus more on the technology used in the development of KMS rather than the requirements or extraction of tacit knowledge to be stored in the KMS. Organizations think that investment in expensive technology can provide them with a good KMS. KM involves organizational, human and technical issues, with the advice that the technical should be treated as least important of the three (Davenport & Prusak, 1998). Complex IT infrastructures for KMS prove to be costly because the effort need to maintain, update and develop is huge. Instead of focusing too much on the technical view, the developer should focus more on the human part where the KM team should play their role by dealing with the domain experts, experts that know the solution, problem and also can contribute how to make sure the data inside the KMS is tacit knowledge. Knowledge capturing is crucial in developing KMS because before implementing or designing the

system, the knowledge has to properly assign to the intended user for future usage.

Failing to capture tacit knowledge will result in the KMS just being a normal database system containing data that is not meaningful for the organization. Tacit knowledge is the

Fig. 2. Adapted from Sornlertlamvanich, V. (Sornlertlamvanich, n.d)

**5.5 The weakness of present KMS in achieving its intended goal** 

KM System Conventional System

Systems analyst gathers data and information from the users and the users depend on analysts for the solution

Conventional system developer deals with the user

have the same concept, which is problem solving but the approach and the domain may possibly be different. KM involves organizational, human and technical issues, with the advice that the technical should be treated as least important of the three and the most important part of the KMS is to capture experience which is the knowledge itself (Davenport & Prusak, 1998).

We should see KMS and SE principles differently even though both these practices have the same goal which is to develop a system that help solve problems but the end product of both will not be the same. We use SE principles to develop a conventional system to solve day to day problems such as library system, content management system, point of sales software and other software that are related to our daily use.

The real purpose of the software that has been developed is achieved by looking inside the software as to what does the software or the system contain? Based on simple logic, we can say that the library system contains information about books, names, authors, locations and the ISBN codes and this is what distinguishes a library system from other systems. What then makes a system that is based on SE principles different from KMS?

SE principles may not be sufficient for KMS because to some extent KMS is completely different from a SE system. Both are software, but what goes inside the software might be different as stated earlier. What goes inside the SE system consists of information such as account numbers, stock quantities and others, which are explicit as opposed to KMS, which consist of tacit knowledge which is completely different from information.

Knowledge is distinguished from information by the addition of 'truths, beliefs, perspectives and concepts, judgments and expectations, methodologies and know-how'. Based on opinions, the way we capture information is different than knowledge because knowledge is tacit and from tacit, one can capture experience.

Fig. 1. Adapted from Sornlertlamvanich, V. (Sornlertlamvanich, n.d)

have the same concept, which is problem solving but the approach and the domain may possibly be different. KM involves organizational, human and technical issues, with the advice that the technical should be treated as least important of the three and the most important part of the KMS is to capture experience which is the knowledge itself (Davenport

We should see KMS and SE principles differently even though both these practices have the same goal which is to develop a system that help solve problems but the end product of both will not be the same. We use SE principles to develop a conventional system to solve day to day problems such as library system, content management system, point of sales

The real purpose of the software that has been developed is achieved by looking inside the software as to what does the software or the system contain? Based on simple logic, we can say that the library system contains information about books, names, authors, locations and the ISBN codes and this is what distinguishes a library system from other systems. What

SE principles may not be sufficient for KMS because to some extent KMS is completely different from a SE system. Both are software, but what goes inside the software might be different as stated earlier. What goes inside the SE system consists of information such as account numbers, stock quantities and others, which are explicit as opposed to KMS, which

Knowledge is distinguished from information by the addition of 'truths, beliefs, perspectives and concepts, judgments and expectations, methodologies and know-how'. Based on opinions, the way we capture information is different than knowledge because

software and other software that are related to our daily use.

knowledge is tacit and from tacit, one can capture experience.

Fig. 1. Adapted from Sornlertlamvanich, V. (Sornlertlamvanich, n.d)

then makes a system that is based on SE principles different from KMS?

consist of tacit knowledge which is completely different from information.

& Prusak, 1998).

From the table below, we can see how KM systems differ from conventional systems to warrant a different approach:


Fig. 2. Adapted from Sornlertlamvanich, V. (Sornlertlamvanich, n.d)

KM team must capture the knowledge requirements for the system to be built so that the end product will be meaningful to the organization and its users. Conventional systems development is primarily sequential, whereas KMS is incremental and interactive. In the case of a conventional system, testing is usually done towards the end of the cycle (after the system has been built), whereas in KMS, the evolving system is verified and validated from the beginning of the cycle. Systems development and systems management is much more extensive for conventional information systems than it is for KMS. The conventional systems life cycle is usually process-driven and documentation-oriented whereas KMS is resultoriented (Sornlertlamvanich, n.d).

#### **5.5 The weakness of present KMS in achieving its intended goal**

KMS can be a very complex system which comprises of expensive hardware solutions and complex indexed database. When KMS is completed, the developers of the system need to ensure that KMS is able to store tacit knowledge so that their effort proves to be successful. KMS has a reputation for costing a lot to set up, running into difficulties when trying to get everyone to contribute and ending up with a great deal of information that is inconsistent and irrelevant for most of its users (Straker, 2009).

Organizations tend to focus more on the technology used in the development of KMS rather than the requirements or extraction of tacit knowledge to be stored in the KMS. Organizations think that investment in expensive technology can provide them with a good KMS. KM involves organizational, human and technical issues, with the advice that the technical should be treated as least important of the three (Davenport & Prusak, 1998). Complex IT infrastructures for KMS prove to be costly because the effort need to maintain, update and develop is huge. Instead of focusing too much on the technical view, the developer should focus more on the human part where the KM team should play their role by dealing with the domain experts, experts that know the solution, problem and also can contribute how to make sure the data inside the KMS is tacit knowledge. Knowledge capturing is crucial in developing KMS because before implementing or designing the system, the knowledge has to properly assign to the intended user for future usage.

Failing to capture tacit knowledge will result in the KMS just being a normal database system containing data that is not meaningful for the organization. Tacit knowledge is the

A Roadmap for Requirements Elicitation of

information (Straker, 2009).

**5.6 Research gaps** 

**6. Research method** 

pressures getting in the way.

**7. Scenario** 

Knowledge Management Systems: A Delphi Study 61

the years to their organization. They may feel they are 'giving away the shop', deskilling their job and reducing their employability or potential to earn higher wages. Experts, in particular, live and die on what they know. Where knowledge is power, to give freely what you know to others can seem like professional suicide. It may also be work that is rewarded relatively poorly and can lead to people following up and asking you for further

KM approaches should include methods to overcome impediments to knowledge transfer. Implementing effective methods to counteract impediments in this way may not always be possible (Szulanski, 1996). For example, it may be too much to expect that contributors describe a knowledge artifact, including the factors that associate the strategy with the original context, and how the strategy should change when applied to different contexts. KM approaches may fail when they attempt to create a monolithic organization memory. Organizations that have tried to develop a massive organization memory as a whole have failed (Ackerman, M. S. and Halverson, C. A. (2000)). Among other reasons, such

Such organizations may fail when they do not incorporate with humans, processes, and technology (Ackerman & Halverson, 2000). This is justified by the limitations and importance of each of these components. Humans alone are slow and have limited capacities. Processes are the main component in delivering organizational goals. Thus, any approach that is not associated with processes will tend to fail or be perceived as failures.

Most KMS are so diverse, spanning across industries. In order to obtain necessary data to answer the research question, it is imperative that the research method employed is flexible enough to cater the needs of a variety of situations and to a wide range of complex problems, for which there is often no other suitable means of analysis. The Delphi technique is a systematic method of collecting opinions from a group of experts through a series of questionnaires. The iterative approach espoused in Delphi allows KM experts to reconsider their judgements in the light of feedback from peers. The anonymity of the approach enables experts to express their opinions freely, without institutional loyalties or peer group

The aforementioned iterative approach also gives KM experts more time to think through their ideas before committing themselves to them, leading to a better quality of response. Since AT emphasises on human activity as the basic unit of analysis, the research is able to uses human activities (supervision of projects) to analyse responses garnered from Delphi.

The Five-Year Strategic Plan of University X has made teaching and learning a major priority. Under the said target plan, technology is identified as one of the drivers that will shape the future direction of the University's learning experience. Hence, the gradual adoption of e-Learning tools and strategies is currently being investigated. On that note, the critical success factor and challenges for the implementation of e-Learning at the University is the willingness and ability of existing faculty members to adopt technology into their

organizations are distributed and may have conflicting goals.

result of the human brain processing, analyzing and filtering information to reach conclusions. Information is not knowledge. Yet many organizations fail to understand the difference and are disappointed when a huge investment in technology does not deliver the expected results (Hurley, 2010). Organizations need tacit knowledge because it can drive the organization forward and increase the efficiency on how the organization can operate and be more competitive. In an organization, workers come and go and some of them might have ten to fifteen years of working experience. Their invaluable experience in handling certain practices is important for the organization to expand its potential and knowledge capabilities.

Building a system for KM is thoroughly different from building a system for conventional purpose. As discussed earlier, abandoning social, cultural and organizational issues may interrupt the development process of a good KMS. The character of learning and sharing needs to be cultivated in the foundation of any given organization. Workforces that are willing to learn and share their ideas and experiences in an organization can enable the KMS to perform better. When a knowledge management initiative is seen as the exclusive mandate of the technological department it can become an exercise in information and document storage and retrieval. Successful knowledge management is about fostering an environment in which knowledge is shared and questions asked and answered across the internal barriers of departments and teams.

Most organizations are still structured along hierarchical lines that are not conducive to interdepartmental collaboration or cooperation and yet this collaboration is essential to knowledge management. Finding and managing the flow of knowledge in an organization requires a very different approach to managing information. Creating an organizational culture where knowledge sharing is the norm is the most important and most difficult part of implementing knowledge management within a business. As with all organizational change, technology can and does play an important and integral part but it cannot alone be the driver (Hurley, 2010).

KMS approach without input from all stakeholders can interrupt KMS intended goal. Current knowledge management technologies cannot yet handle uncertainties with inadequate information. They cannot deliver the right information to the right person at the right time because companies cannot predict what the right information to distribute is and who the right people to distribute it to are (Lang, 2001). Stakeholders need to anticipate the prospect of building the KMS and also to identify the experts needed to collaborate with the developers of KMS. Besides, inadequate knowledge or data in the KMS may perhaps be one of the weaknesses of the current KMS available. The quality of information can also be a turn-off. If the first item the user opens is unexpectedly scrappy, then the user will not look further (Straker, 2009). The user's experience is important when navigating the KMS in order to look for specific knowledge. If the experience is not worth a visit due to the poor quality of data stored, then the user might not consider using the system again.

Other than the quality of the data in KMS, a complex user interface and a complex operation can also be an obstacle for the user to use the KMS. When the users only want a simple system and do not have the time to learn how to use it fully then such systems are liable to fall into disuse (Straker, 2009).

Another strong reason why KMS fails in achieving its intended goal is because people are unwilling to cooperate during requirement elicitation for KMS. Apart from that, when the KMS is completed, there is no valuable knowledge input to the KMS itself. People are reluctant to share their invaluable experience and knowledge that they have acquired over the years to their organization. They may feel they are 'giving away the shop', deskilling their job and reducing their employability or potential to earn higher wages. Experts, in particular, live and die on what they know. Where knowledge is power, to give freely what you know to others can seem like professional suicide. It may also be work that is rewarded relatively poorly and can lead to people following up and asking you for further information (Straker, 2009).
