How To Implement a Knowledge Management System:
A Practical Guide for Project Managers
By Russ Wright
A Practical Recommendation for Project Managers to Implement A Knowledge Management System
Implementing a knowledge management system can greatly assist a project manager in their work. A study conducted by White and Fortune (2002) described the most important project success factors mentioned by project managers, which included: (1) having clear goals and objectives, (2) good support from the senior management, and (3) enough funding and resources to complete the tasks. In a paper on the benefits of knowledge management systems, Wiig (1997) explained that knowledge management systems, when properly implemented, could improve communication between departments and provide the users with a history of best practices within the organization. In a study conducted by Alavi and Leidner (1999) the authors described that an effective knowledge management systems assisted project management by providing better communication, shortening the time to find solutions to problems and better estimates of project duration. Thus a knowledge management system can help a project manager in all three of the important areas by providing the information they need to secure the project success factors. This paper will provide a background on the definition of knowledge and knowledge management models. Three knowledge management implementation models are then reviewed to demonstrate a progression of the research. Further, from a synthesis of the literature on knowledge management implementation, this document provides several factors that would help a project manager be successful at implementing a knowledge management system. The conclusion finds that the field of knowledge management and the process of implementation are still evolving.
A Brief Discussion of Knowledge There is much debate among the scholars as to what constitutes knowledge within the context of knowledge management systems. Nonaka and Takeuchi (1995) defined knowledge as beliefs and commitments and not really information. Drawing from Polyanyi (1966), they used the concepts of tacit and explicit knowledge. Tacit knowledge was defined as personal, context specific and difficult to explain, this knowledge gained from experience can be lost if an individual leaves an organization and does not share it. Explicit knowledge was defined as the common knowledge known by a large
group and could be easily codified and shared. Zack (1999) defined codified knowledge as knowledge that is created, located, captured and shared that can be used to solve problems and make opportunities. Accordingly this type of knowledge, because it is captured, can become stale if not regularly revisited and evaluated (Gillingham & Roberts, 2006). Thus, knowledge, for the purpose of this paper, will follow the aforementioned two categories of tacit and explicit.
The knowledge management field is still fairly new, within the past three decades, and
many facets of the field are still unsettled. According to research by Rubenstein-Montano, Liebowitz, Buchwalter, McCaw, Newman & Rebeck (2001a), one of the bigger revelations in the past decade was the realization that knowledge management was far more
than technology for sharing knowledge as it also incorporated individuals, and the culture in which they worked. According to research by Bresnen, Eldman, Newell, Scarbrough and Swan (2003) the sharing of knowledge within and across projects was very difficult and developing the ability to share knowledge both within and across projects was a very important source of
competitive advantage for an organization. Thus the project manager, who wants to improve the quality of knowledge sharing through the implementation of a knowledge management system, needs to consider many factors to find a solution. For the project manager, finding a useful methodology and implementing it requires a good understanding not only of the methodologies, but also the technological constraints of the organization in which they wish to deploy a knowledge management system. Research conducted by Liebowitz and Megbolugbe (2003) identified several high-tech and low-tech solutions for knowledge management. Low cost
solutions included frequent face-to-face meetings between departments, perhaps over working lunches, to share tacit knowledge. If an organization required a low-tech virtual solution because they were spread out over a large distance, which made meeting in person difficult or impossible, they might have used on-line bulletin boards and facebook-like groups to share tacit knowledge in a virtual workspace. Research by Kasvi, Vartianen and Hailikari (2003) showed that these types of interactions, lunch meetings between departments and seminars, were described as some of the most important sources of knowledge. The more high-tech solutions explained by Liebowitz and Megbolugbe (2003) used expert systems to capture and codify knowledge into a repository and data and text mining software that looked for patterns to inductively create knowledge. These solutions were much more difficult to implement and required considerable IT investment and employee training. Kuhn and Abecker (1997) acknowledged the value of these systems and cautioned a balanced approach that flexes with the organization was required to make these systems function well within an organization. Thus, the project manager must soberly consider what models for knowledge management will fit into an organization’s capability and budget before attempting to find and implement a particular model.
Knowledge Management Models
The knowledge management models presented below are only a sample of the many
models found in the research literature. These models are representative of many of the other models as many share similar features and processes. The three presented below are an attempt to show the progression of the research as the models take on more complexity and at the same time attempt to explain and simplify the implementation process. The model presented by Wiig (1997), had four basic iterative steps: (1) review, (2) conceptualize, (3) reflect, (4) act as depicted in figure 1 below. The review process called for monitoring the internal performance of the organization against other organizations in the same industry to determine how well they are doing. The conceptualize step in the process began by organizing the knowledge by different levels. The author provided several examples of survey instruments that identified the knowledge assets and in turn associated them with the particular business
process that used them. Also at this step strengths and weaknesses in the knowledge inventory were identified. The reflectstep involved creating plans to improve the strengths and weaknesses previously discovered. And finally the act step was the implementation of the plan, which might be carried out by individuals in different parts of the organization. This process would be repeated to assist in the capture of knowledge.
Figure 1 Wiig’s knowledge management model
A much more sophisticated model was presented by Rubenstein-Montano, Leibowitz, Buchwalter, McCaw Newman and Rebek (2001b) which according to the authors addressed several of the shortcomings of the other models. The authors argued that the
existing models lacked detail, did not include an overarching framework, and failed to address the entire knowledge management process. The model presented by the authors consisted of five phases: (1) strategize, (2) model, (3) act, (4) revise and (5) transfer as depicted in figure 2 below. Each phase of the model could loop back to the previous if it was determined that further work within a particular phase was required. The strategize phase covered the strategic planning; business needs analysis and a cultural assessment of the organization.
The model phase involved conceptual planning that covered knowledge audits and planning and a design of the plan to store and distribute the knowledge. The act phase focused on capturing, organizing, creating and sharing the knowledge. The revise phase consisted of implementing the system, reviewing the knowledge, and evaluating the achieved results. The
transferphase published the knowledge so it could be used to create value for the organization and consider expansion of the knowledge base.
Figure 2 Rubenstein-Montano et al. Model
A later model presented by Chalmeta and Grangel (2008) tried to simplify the existing systems and provided a generic knowledge management implementation model. The authors argued that all knowledge management systems used some sort of computer system and therefore the implementation methodology should reflect the need for it. This model also consisted of five phases: (1) identification, (2) extraction, (3) representation, (4) processing and (5) utilization as depicted in figure 3 below. The identification phase focused on identifying the knowledge to be stored, and classified it into categories. The extraction phase involved transforming the knowledge from its existing state and putting it into the format used in the
knowledge management system. The representation phase created a model or diagram that showed a map of the knowledge in the system. The processing phase involved defining what technology platform was used to display and share the knowledge. The utilization phase involved deploying the knowledge portal and trained the members of the organization to use the system.
Figure 3 The Chalmeta and Grangel model
The models presented here are a sampling from the literature. The Wiig (1997) model for constructing a knowledge management system seemed very simple. Yet, Diakoulakis (2004) explained that this model was deceptive in the simplicity it portrayed because the model could “build, transform, organize, deploy and use knowledge” (p. 37). The Rubenstein-Montano et
al. (2001b) model tried to fix the shortcomings of models that came before it. In an attempt to generalize and simplify a knowledge management implementation model, Chalmeta and Grangel (2008) created another model, which included elements from both of the aforementioned models and attempted to create a much more generic and complete framework for the implementation of a knowledge management system. Regardless of which model is chosen to implement a knowledge management system within an organization, there are many factors that contribute to the success of the project.
Factors for Success
For the project manager, there are many factors to consider when deciding to implement a
knowledge management system. Below is a synthesis of many of the factors from existing research that will affect the ability of an organization to successfully implement a knowledge management system. They are: (1) managerial support, (2) a supportive culture, (3) incentives for motivation, (4) technology that matches the strategy, (5) ways to assess the value of the process, (6) specialists and processes, and (7) training. Each of these factors for success is discussed in detail below.
The Support of Management
Without the support of management the implementation of a knowledge management
system will not work. According to a study conducted by Holsapple and Joshi (2000) a major factor that contributed to the successful implementation of a knowledge management system were the behaviors of the management team who provided the impetus and the model of behavior that demonstrated a desire to use a knowledge management system. Another study by Massey Montoya-Weiss, and O’Driscoll (2002), who studied the implementation of a knowledge management system at Nortel Networks, explained that the managerial leadership provided control and coordination and most importantly they ensured that the knowledge management strategy was aligned with the business strategy. A similar study conducted by Sharp (2003) explained that the way employees acted in the implementation of the knowledge management system was a direct reflection on the behavior of management. Therefore the support of management not only provides the push to make it happen, it also requires them to set the tone which helps define the culture and acceptance of a knowledge management system.
The Proper Culture of Collaboration
The culture created by management will greatly influence the success of
an implementation of knowledge management system. In a recent paper by Anklam (2002) the author explained that knowledge management and creation requires collaboration on a much greater level. Individuals within the organization must develop a sense of trustworthiness between them that facilitates the sharing of knowledge. According to research by Ruggles (1999) knowledge management without a culture of collaboration will not succeed as collaboration is “strongly conducive to knowledge generation and transfer” (p. 300). Gold Malhorta and Segars (2001) explained that collaboration is important for the transfer of tacit
knowledge between individuals within an organization. The research conducted by Chourides, Longbottom and Murphy (2003) found that a coaching leadership style that established a learning culture was among the most significant factors for a successful knowledge management system implementation. Thus, the vision of management, which includes a vision of the organizational culture of collaboration, is required for the implementation of a knowledge management system to succeed.
Incentives for Motivation
Also included within the culture of an organization is motivation for the individuals in the form of incentives. According to research by Yahya and Goh (2002), the connection of rewards and compensation to an individual’s performance appraisals can have a positive impact on the motivation of an individual towards using a knowledge management system. Huber (2001) explained that to motivate individuals to share knowledge, the policies of the organization, in regards to rewards, must promote sharing. He further explained that the organization should publicize and celebrate instances of knowledge sharing that benefited the organization. The research conducted by Darroch (2005) seems to validate these earlier works as the author explained that the findings of his research showed that the knowledge sharing culture
of an organization was directly affected by performance incentives. Therefore, if management offers incentives, the workers within the organization will be motivated to share knowledge.
Technology That Matches the Strategy
Information and communication technology when matched to the business strategy for knowledge management plays an integral role in a successful implementation of a knowledge management system. The two major strategies for knowledge management are classified as codification and personalization. According to Zack (1999) codification is a process whereby tacit knowledge is captured in some electronic form and then shared about the organization thus making it explicit. He further explained that in this model, information technology is used like a pipeline to move knowledge around the organization. Because this model uses extensive technology and knowledge specialists to capture and store the knowledge, the monetary investment is very high. The second strategy for knowledge management, personalization, according to Hansen, Nohria and Tierney (1999), used information and communication technology to facilitate conversation from person to person where the participants transfered tacit knowledge. This model used much less technology and therefore the costs were much lower. It is important to note here that many scholars, (Alavi & Leidner, 1999; Borghoff & Pareschi, 1997; Wong, 2005), all stated that information and communication technology should not be considered an end unto itself and only considered a tool, as the wrong attitude towards technology can cause the entire knowledge management process to stagnate. Thus, matching the knowledge management strategy to the information technology budget of the organization will have significant impact on the successful implementation of a knowledge management system.
Assigning Value to the Process
Once a knowledge management system is in place, it will be important to express to management how well the system enhances the business strategy. This can be difficult as many of the benefits created from a knowledge management system are intangible, such as the good will and customer loyalty generated by the extra attention, and were very difficult to measure (Snowden, 2002). In research conducted by Park, Ribiere and Schulte (2004), management only
considered the implementation successful when there was some concrete way of measuring the positive impact of the implementation. This same attitude is echoed in the research conducted by Bose (2004), when he explained that the ability to measure the value of
a knowledge management system is critical to sustaining management’s support. He further explained that only with some way to measure the results could management assist in solving problems in the system. Jennex and Olfman (2008) further added that a successful implementation of a knowledge management system requires the ability to measure several factors of success, among them are: (1) information quality, (2) user satisfaction, and (3) system quality. They further explained that each of these factors add to the measurement of the benefits of implementing the system. Therefore defining method to measure the success of the knowledge management system implementation, although somewhat difficult to define, not only informs management, but also helps the project manager to garner their continued support and sustained use of the system.
People and Processes
Special roles are needed to maintain the knowledge management system. According to Zack
(1999) there were specific roles required to maintain the knowledge management system within an organization, which included people to gather, refine and distribute the explicit knowledge throughout the organization, and IT support for the technology that held the repository. Grover and Davenport (2001) took this notion further and suggested a role of chief knowledge officer
that fulfilled many purposes including an indicator that an organization was serious about knowledge management. This role also served as the chief designer of the knowledge architecture. According to Coombs and Hull (1998) their research explained that
there also must be many knowledge managers within an organization that were familiar with knowledge management and facilitated the sharing of knowledge among different departments. Therefore these roles and responsibilities help to maintain the system and
show the support of the executive management.
Individuals within an organization need to be trained, not only on the technology used to share
knowledge, but also to raise awareness of how to manage knowledge and see it as a valuable resource for the organization. Because the knowledge existed within the minds of individuals within the organization, without proper training an employee was not motivated to use a knowledge management system and share their knowledge (Bhatt, 2001). Research conducted by Hung, Huang, Lin and Tsai (2005) into critical factors for the adoption of a knowledge management system found that one of the biggest factors for successful implementation and increasing an organization’s competitiveness was the effective training of the employees to
recognize the importance of the knowledge management system. Another important factor for training employees was to give them a common language and perception of how they thought about and defined knowledge (Liebowitz, 1999). Therefore, training is a key success factor not only because they need to know how to use the knowledge management system, but also because it teaches the individual to recognize knowledge and understand the value that it represents to the organization. The seven factors for successful implementation of a knowledge management system within an organization outlined here give the project manager a
starting point for assessing the readiness of the particular organization. The project manager must consider how much support management, and especially senior management will give to the project. Another aspect requiring consideration is the culture of the organization. The project manager will have to reflect upon the culture of the organization and note if management is promoting a culture conducive to the plan. The culture created by management will also need to provide incentives to help foster sharing of knowledge among the members. A big consideration the project manager will have to undertake is the availability of
technology, and the people to support it. Some plans can be really expensive and a good review of the organizations technological infrastructure is needed before a serious plan can be made. Also of great importance is the training for the individuals who will use the system. Not only will they need to know how to use the system, but also how to recognize when something is knowledge worth storing.
Knowledge Management Implementation Is Still Evolving
It is clear from this research that a project manager who wants to improve the sharing of knowledge both within and across projects can benefit from a knowledge management system.
From the progression of knowledge management models demonstrated above, it is clear to see that researcher’s understanding ofhow to implement a knowledge management system is still evolving. The research presented on the factors for success demonstrates that research is still ongoing to understand the critical success factors for knowledge management system implementation. A core set of knowledge on how to successfully implement a knowledge management systems seems to exist, yet the constant evolution of technology seems to continue to change how a system might be implemented.
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