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2 Knowledge Archives

July 29, 2007

What is knowledge?

Definitions of knowledge vary greatly. Some are simple, such as “specific information about something” (American Heritage Dictionary). Some are more complex and begin to bring in other elements such as understanding and awareness of objects such as facts, data, and information. There is the question of how knowledge can be gathered or created. And then there is the whole question of what is the value of knowledge if it can’t be applied—which brings us to the need for such topics as knowledge sharing and knowledge transfer.

Philosophers have debated the nature and meaning of knowledge all the way back to Plato and Aristotle. Not being a philosopher myself, I am not able to enter that debate. However, coming from the perspective of helping adults learn and acquire knowledge, I believe that knowledge provides a foundational building block upon which higher-level skills and thinking can flourish. Knowledge can come in many forms (data, information, stories, or even learned physical responses such as that possessed by a surgeon or dancer). Knowledge can be easy to access and well defined (explicit) or it can be elusive and hard to capture (tacit). And, beautifully, knowledge can grow and be the basis of future innovation.

As a doctoral student in Knowledge Management, my own definition of knowledge is evolving and I’ll share its continuing evolution within this blog. For now, I present one definition that comes from the classic Knowledge Management text, Working Knowledge: How Organizations Manage What They Know. In the first chapter of this book, Davenport and Prusak themselves work to define knowledge. They introduce the concepts of data versus information versus knowledge and then present the following definition of knowledge:

“Knowledge is a fluid mix of framed experience, 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 organizations, if often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms.” (Davenport & Prusak, 2000, p. 5)

Having a definition such as this will be helpful as we explore how knowledge, learning, and performance are intertwined. Key ideas in Davenport and Prusak’s definition that are important to point out include the concepts of fluidity or the ever-changing nature of knowledge and how it is often embedded in hard-to-reach places such as “the minds of knowers” and within “organizational routines, processes, practices, and norms.” These two concepts in particular point to the challenges of working with knowledge—it is ever changing and often difficult to access.

However, I believe that by tapping into—or helping individuals and organizations learn ways to tap into their—knowledge in a systematic way, true innovation occurs and maximum potential can be realized. So for my working definition of knowledge, I will say that knowledge feeds learning, learning provides an environment that enables the learner to not only acquire knowledge but also create new knowledge, and performance is the result of what happens when knowledge and learning work in concert with one another. Let us see how this working definition evolves in the coming months and years as I continue my doctoral studies.

References:

Davenport, T., & Prusak, L. (2000). Working knowledge: How organizations manage what they know (Paperback ed.). Boston: Harvard Business School Press. (Original work published 1998)

Knowledge. (n.d.). The American Heritage® Dictionary of the English Language, Fourth Edition. Retrieved July 27, 2007, from Answers.com Web site: http://www.answers.com/topic/knowledge

- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

August 3, 2007

Converting tacit knowledge to explicit

One of the hardest challenges of knowledge work is how to convert tacit knowledge to explicit so that it can be shared. So before we begin with a discussion of how to convert tacit knowledge to explicit, let’s first define what is meant by tacit versus explicit knowledge. Often tacit knowledge is considered knowledge that people carry in their heads or bodies and which is gained through learning or personal experience. For tacit knowledge, think of the things which you are so expert on that it’s difficult to explain them; like breathing, you just do them. On the other hand, explicit knowledge is easy to put your hands on, since it is knowledge which has already been captured and written down. For explicit knowledge, think of all the books on your shelves or the manuals and procedure documents created by your company.

Many of the examples of explicit and tacit knowledge I think of actually can be considered two sides of the same coin, e.g., cooking or repairing an automobile. One can read books and follow instructions on how to do both (explicit knowledge), but true mastery comes through the tacit knowledge built through experience. Skills that are predominantly psychomotor or kinetic (e.g., dance, massage, pottery, etc.) are something that may always remain predominantly in the realm of tacit knowledge. Yes you can read books about these subjects, but to become skilled requires practice of a physical nature. However, tacit knowledge in procedural or task based areas can be much more easily converted into explicit knowledge.

In my work as a workplace learning and performance improvement specialist, I’ve seen and led many projects that did just that—took the tacit knowledge of experts and turned it into explicit knowledge (to then ideally be turned back into tacit knowledge for the new learner). These often will involve the analysis and conversion of the expert’s knowledge into a process flow (complete with decision points), and then further delve into what the expert thinks, does, says, and feels at each step in the process.

Recently, I’ve worked on projects such as this for (1) how to make compensation decisions and (2) for how to lead the construction effort for high-rise office space. In the first case, the compensation department wanted managers to start using better judgment when deciding raises and bonuses so that they could truly differentiate their pay and reward high performers. This had previously been the tacit knowledge belonging to only compensation specialists and occasionally experienced managers. I worked with the compensation department to turn their tacit knowledge (i.e., rules of thumb, personal experience, and decision points not previously articulated) into something any manager making compensation decisions could use. This was then used to create training and an online simulation where the user made the compensation decisions for a small department of employees and received feedback on a number of factors including adherence to budget and guidelines plus how well they differentiated their pay decisions.

In the second example, we worked with the construction management function of a real estate investment trust to develop a consistent process for how they manage the construction and build-out of office space to meet their prospective and current tenant’s needs. Later, when this company chose to eliminate the construction function and train their property managers to take on these responsibilities, I worked with them to capture the remaining tacit knowledge of the experienced construction managers to create a knowledge base and training for the property managers.

- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

August 6, 2007

The knowledge capture process

Expanding on my last post regarding tacit and explicit knowledge, one of the greatest challenges is how to convert tacit knowledge into explicit. The challenge comes in how to access and document that elusive tacit knowledge—knowledge which can often be an individual’s or company’s source of competitive advantage.

Much of my knowledge capture experience to date is related to specific workplace learning and performance improvement projects—for the purpose of ensuring we have the content needed to enable the target audience to meet the desired learning objectives. As such the process often goes like this:

1. Define and confirm the training or information need (and ensure that it is something that can be solved by training), e.g., make sure that it’s not an organizational or motivation issue (because no amount of training can solve that!)

2. Define the target audience and performance expectations, i.e., what is it that you need the audience to be able to DO as a result of completing the training?

3. Work with experts to learn how they have successfully met those performance expectations in the past. This content gathering can take the form of reading the company’s existing materials on the subject, researching how other leading companies have addressed the same problem, interviewing the experts, facilitating work process or other analysis-type sessions with experts, observing the experts at work, etc.

4. Synthesize the results of the content gathering phase. Return to the experts as needed to fill in any content holes until you have adequate information to teach others what the experts know/do.

From there, with the learning objectives as a guide, you can design, develop, and test an appropriate performance improvement session and/or tool that enables the target audience to successfully accomplish the desired learning objectives. (This is where appropriate adult learning theory, interactivity/action learning, media selection, performance support/job aids, e-learning, games, help systems, etc. all come into play depending on the need.)

- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

August 7, 2007

The knowledge capture process (continued)

Yesterday’s post addressed the key process steps for how to capture knowledge to ensure you have the content needed to enable a target audience to meet desired learning objectives. Today, let’s explore the more elusive challenges of how to capture knowledge in those situations when an experienced (expert) individual has serendipitous moments of insight (that they gain only from experience) that lead to a problem solution.

What I’ve found is that, honestly, it depends on the content expert. For example, there are times experts are very aware of their process and are happy to share what they know; gathering content from them is easy. On the other hand, there are times people are less aware of what it is they do so well that has made them the “expert” on a subject. In cases like that, I find it best to get them talking about what they do and have done, i.e., encourage them to tell stories. You can get them started by asking questions like:

- Think about some projects where you were doing XXX (like what we want our target audience to be able to do). Tell me about one of the projects that went extremely well. Why was that so successful? What did you (or others) do (or not do)?

- Now, tell me about a project that went poorly (either from your own experience or one that you observed). Why would you classify that as a being a problem project? What went wrong? What would you do different next time to not make the same mistakes?”

This will get the expert talking and help reveal not only details behind their process, but also war stories and key success factors—all very useful items when trying to teach someone how to “do as the expert does.”

- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

August 16, 2007

Don’t let technology take over your program!

Fahey & Prusak (1998) argue that one of the deadliest sins of knowledge management is “substituting technological contact for human interface.” Unfortunately, many knowledge management programs rely too heavily on technology to the unfortunate minimalization or exclusion of the human side. However, to do this is to spell failure for “…although IT is a wonderful facilitator of data and information transmission and distribution…Knowledge is primarily a function and consequence of the meeting and interaction of minds” (Fahey & Prusak, 1998, p. 273). McDermott echoes this argument further stating that, “Knowing is a human act, whereas information is an object that can be filed, stored, and moved” (1999, p. 110). An important distinction is made here in both articles—that of information and data being objects that can be gathered, sorted, stored, and retrieved versus knowledge which is generated through human interaction via discussing and testing out new ideas and concepts. IT systems can do an outstanding job with information and data; however, true knowledge management is more than just information and data—it also involves elements of culture, change, community, motivation, and trust. Thus to ensure a successful knowledge management program, one must give equal or greater attention to the human component as to the technology component (Davenport & Prusak, 1998/2000).

So what is one to do to mitigate or counteract the effects of potentially relying too heavily on the technological side? First, ensure that equal or greater attention is paid to the human components of any knowledge management initiative. Be sure to consider and provide support for the human elements of culture, change, community, motivation, and trust—for without any one of these it can be difficult if not impossible to create an organization able of generating and sharing knowledge. Then, ensure that technology is considered only in context of how it can support the generation and sharing of knowledge. Do not allow the technology to lead the solution, but rather to let the desired solution lead the technology.

Two specific examples of methods an organization can use to encourage and provide structure to the very important human side of knowledge management are community/corporate yellow pages or expertise location systems and communities of practice. Corporate yellow pages or expertise location systems are quick and relatively easy to implement and can provide a first step in connecting people to the experts and knowledge they seek. Communities of practice, or CoPs, are often cross-functional teams of professionals organized around a common goal such as a problem, practice area, or process (Nickols, 2003); as such, they can be outstanding vehicles for both the creation and sharing of knowledge. In these two examples, it is important to note that technology still plays a role, but that role is a supporting one. Corporate yellow pages may use such tools as Tacit’s ActiveNet or AskMe Enterprise. CoPs can also be aided by technology (especially when it is a virtual CoP); for example, technology may provide a means for virtual meetings via web conferencing, communication via email, document sharing via a web or FTP site, or even collaboration via a Wiki or content management system.

One additional and very important method is to have corporate policy that supports the knowledge creation and sharing process. Unfortunately, too many corporate cultures do not give people the most valuable resource needed to create and share knowledge—that is, time. However, if corporate policy (and upper management) clearly state and support these processes, then greater success can be had. For example, 3M has a program called the “Fifteen-Percent Rule” that supports employees spending up to 15% of their time in individual learning and knowledge-building pursuits that benefit not only them as individuals but also the organization in innovation and new product development—and a healthy bottom line (McElroy, 2003).


References

Davenport, T. & Prusak, L. (2000). Working knowledge: How organizations manage what they know (Paperback ed.). Boston: Harvard Business School Press. (Original work published 1998)

Distance Consulting. (2003). Communities of practice: A start-up kit [Brochure]. Fred Nickols.

Fahey, L. & Prusak, L. (1998). The eleven deadliest sins of knowledge management. California Management Review, 40(3), 265-276.

McDermott, R. (1999). Why information technology inspired but cannot deliver knowledge management. California Management Review, 41(4), 103-117.

McElroy, M. (2003). The new knowledge management: complexity, learning, and sustainable innovation. Burlington, MA: Elsevier Butterworth-Heinemann.


- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

September 6, 2007

Expertise Locators: Part 1 (Benefits)

Appropriately-selected knowledge management initiatives can help companies in many ways. They can help people access the information they need, support a learning organization culture, and even assist in facilitating change. This paper addresses how an expertise locator system can assist a company during a period of significant organizational change and create the foundation for future knowledge sharing and innovation.

To provide better perspective, we’ll take a look at the use of an expertise locator with a particular company in mind. The company for which this initiative is recommended has recently been acquired and is about to incorporate another recently-acquired company within their operating platform. There has been significant change and unrest for both organizations, and efforts need to be made as soon as possible to get them talking and sharing with one another to help them operate as one. With all these organizational changes, there are also a lot of questions about who to call for what (and in many cases who even still works for the company as significant layoffs are occurring). It is the desire of upper management to return the company to its previous levels of productivity, plus prepare them for future collaboration and further operational improvements. Since awareness and expertise management are core functions in achieving integration, collaboration, and innovation (Maybury, D'Amore, & House, 2002, p. 201), the recommendation is for this company to implement an expertise locator system as an introductory knowledge management initiative. From a timing perspective, updates will need to be made to the corporate directory and this could be an excellent opportunity to capitalize upon to concurrently capture the employees’ area(s) of expertise.

Many other companies have experienced operational benefits from implementing an expertise locator and management system. Some relevant benefits include being able to:

1. “Help people in large, often widely geographically dispersed organizations find out who has subject matter expertise or who knows how and where to get at important know-how.” (Smith & McKeen, 2006, p. 44)

2. “Cultivate a culture of collaboration” (Maybury, D'Amore, & House, 2000, p. 12)

3. “Enable users to create expert profiles and submit questions to be answered by the pros…[and thus] tap into expertise and tacit knowledge.” (Kaplan-Leiserson, 2003, p. 19)

4. Ease the formation of cross-functional teams by facilitating “quick identification of potential skill matches for teams based on employees' backgrounds” (Becerra-Fernandez, 2001, p. 34)

Implementing an expertise locator system will enable this company to experience similar benefits; it will help solve the immediate need for employees to know who they can contact and also begin to build a foundation for sharing knowledge. Thus it will help them through this period of organizational change, return them to their previous levels of productivity, and prepare them for future collaboration and further operational improvements.


References

Becerra-Fernandez, I. (2001). Locating expertise at NASA. Knowledge Management Review, 4(4), 34-37.

Kaplan-Leiserson, E. (2003). Do you know. Training and Development, 57(5), 18-19.

Maybury, M., D'Amore, R., & House, D. (2000). Automating the finding of experts. Research Technology Management, 43(6), 12-15.

Maybury, M., D'Amore, R., & House, D. (2002). Awareness of organizational expertise. International Journal of Human-Computer Interaction, 14(2), 199-217.

Smith, H. & McKeen, J. (2006). Development in practice XXII: Expertise location and management: Hope or hype? Communications of AIS, 18, 44-54.


- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

September 9, 2007

Expertise Locators: Part 2 (Process Approach)

Today we’ll begin exploring the process, people, and technology considerations for implementing an expertise locator system—first with a look into the key process considerations. Each recommendation is supported by research into the experiences of other companies as they implemented similar expertise locator and management systems. In addition to the experiences gleaned from such organizations as the St. Paul Companies, the MITRE Corporation, and NASA, of particular note is the information gained from BP Amoco’s experience (Collison, 1999). BP Amoco’s experience is very relevant as much of their expertise locator experience comes after the merger of British Petroleum and Amoco—similar to the upheaval and change occurring in the company for which this initiative is recommended.

In determining the process for implementing an expertise locator system, it is helpful to consider three main phases—up-front design, initial rollout and implementation, and ongoing maintenance.

During up-front design, it will be critical for the company to first link the use of the system to a business process, work process, or other defined purpose (Harney, 2002, p. 6; Thompson, 2003, p. 12; Smith & McKeen, 2006, p. 50). Experience at other companies has shown that if the problem to be solved is not clearly known—and a corresponding strategy developed to specifically solve that problem—“the level of usage and value of usage is going to be compromised significantly” (Harney, 2002, p. 6). It is also important to be aware of how the principles and perceptions of expertise can present some challenges for manually-populated expertise locator systems. For example, expertise changes and evolves over time, expertise is often distributed across a group of people, and some may be hesitant to provide access to their expertise (Maybury, D'Amore, & House, 2002, p. 214). Thus, the system needs to be designed to address these considerations. In addition, it will be important to the design and success of the system to eliminate self-assessment issues of overstating or understating capabilities, define a required minimum level of information required on each employee, and determine how to solve the issue of employees with the same last name (Becerra-Fernandez, 2001, p. 35). As possible, it would also be desirable to consider having a “humanware solution to expertise location that is really closer to solution resolution” by allowing for questioning of the experts and archiving of the resulting answers (Harney, 2002, p. 6).

During the initial rollout and implementation phase, it is recommended to do a pilot program and include mechanisms for feedback and revisions (Smith & McKeen, 2006, p. 51). In addition, utilizing techniques from the rollout of BP Amoco’s expertise locator system (Connect) would be encouraged:

In order to build momentum, an awareness campaign was mounted by a group of “Connect champions” from a variety of backgrounds… who each believe strongly in the benefits of a connected organization. Posters, competitions, deskdrops, learning fairs and lunchtime publicity booths with digital cameras have all been used to great effect. As token recognition, promotional pens are awarded to good examples with a personal thank you from the program director. The note concludes with a request to encourage their peers to use Connect, and invariably results in a series of conversions in the office of the pen recipient. (Collison, 1999, p. 14)

For ongoing maintenance of the expertise locator system, it will be important for the company to design the process considering both how to maintain expertise information after it has been initially collected and the social factors that go into selecting who someone may ask for assistance (e.g., ability to understand the context of a problem, skill at sharing knowledge, willingness to share, and time available) (Smith & McKeen, 2006, p. 48). The former may be solved through the Technology approach, and the latter solved through the People approach (both described later in this paper). Experience from BP Amoco’s rollout of Connect also shows that to maintain the expertise locator system it can be desirable to appeal to people’s egos and encourage their natural competitive natures:

Among the engaging features of Connect is the “Fifteen minutes of fame” that an employee gains when updating their details. A post-itTM icon on the front screen displays their name and photograph until another employee supplants them by updating their own details. Occasionally staff can even be seen to duel for prominence on the front screen, frivolous perhaps, but the end result is an increased likelihood of current, relevant information – the lifeblood of any knowledge directory. (Collison, 1999, p. 15)


References

Becerra-Fernandez, I. (2001). Locating expertise at NASA. Knowledge Management Review, 4(4), 34-37.

Collison, C. (1999). Connecting the new organization: How BP Amoco encourages post-merger collaboration. Knowledge Management Review, 2(1), 12-15.

Harney, J. (2002). An innovative take on expertise location. Knowledge Management, 6.

Maybury, M., D'Amore, R., & House, D. (2002). Awareness of organizational expertise. International Journal of Human-Computer Interaction, 14(2), 199-217.

Smith, H. & McKeen, J. (2006). Development in practice XXII: Expertise location and management: Hope or hype? Communications of AIS, 18, 44-54.

Thompson, E. (2003). Effective knowledge management in a cost-cutting environment. Knowledge Management Review, 6(1), 12-15.


- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

September 11, 2007

Expertise Locators: Part 3 (People Approach)

Today we’ll continue exploring the process, people, and technology considerations for implementing an expertise locator system—now with a look into the key people considerations. Research shows that when considering the people component of implementing an expertise locator system, it is important to understand the underlying philosophies and organization principles so as to be prepared for the human elements that could otherwise cause an expertise locator initiative to fail.

Being sensitive to what participation in an expertise locator system represents to the individual employee and the organization is an important first step. For example, participation in BP Amoco’s Connect system:

…not only represents a way to locate expertise, it also demonstrates the participants’ willingness to be contacted, therefore making all users more collaborative – and approachable. In this sense, the existence and high profile of a product such as Connect reinforces the importance of knowledge-sharing and encourages staff to think consciously about why others may want to contact them and how they can help people find them. This thought process prompts a knowledge-sharing culture at a critical time for the newly-merged organization. (Collison, 1999, p. 13)

In addition, to encourage a culture of trust, it is recommended to “establish employee ownership” and not require participation (Collison, 1999, p. 13). Also realize that expertise location can suffer from a lack of participation due to people not wanting to share their contact information and/or self-identify themselves as experts (potentially increasing their workload when asked to share their knowledge) (Smith & McKeen, 2006, p. 45). To address each of these concerns that the employees may have, it will be important for this company to consider these issues when creating the communication plan for the initiative as well as the overall change management strategy being pursued to address the recent and future organizational changes.

“Human facilitation [of the process also] is essential” (Smith & McKeen, 2006, p. 51). One approach to doing this would be to define groups of experts with identified leads. At first these leads would take a visible role in promoting and participating in the expertise locator system; the leads could also be the initial point of contact for any requests for experts and/or questions on that area of expert knowledge. As the company matures in its move toward a knowledge-sharing culture, these groups of experts could also form the basis of future communities of practice. Another benefit of having expert groups and leads identified would be a reduction in the potential “cold-start problem.”

Systems often suffer from the cold-start problem where there is a mismatch between the number of experts and users. In some cases, experts out number users, discouraging experts' participation or affecting revenue. In other cases, there is a dearth of experts (or qualified experts), and users become frustrated because of poor response times or low-quality answers. (Maybury, D'Amore, & House, 2002, p. 203)

To further counteract this issue, as well as help with some of the previously-stated people concerns, it will also be important to secure participation from senior management and key individuals across the organization. Management’s leading by example will help with the initial and ongoing acceptance and usage of the system.

Despite these efforts, it is important to know that some people will hold tenaciously to the belief that their personal networks are enough (Smith & McKeen, 2006, p. 51). Thus, work may need to be done to help employees realize the potential limitations in their personal networks. For example, short training sessions could demonstrate the potential of the system by comparing examples of who their personal network would identify to solve a problem versus who the system points them to (Cullen & Rumizen, as cited in Smith & McKeen, 2006). Examples such as this will likely show that the system can point the employee to many more (and perhaps better) resources in the new, combined organization rather than what their old (and perhaps now outdated) personal networks would have.


References

Collison, C. (1999). Connecting the new organization: How BP Amoco encourages post-merger collaboration. Knowledge Management Review, 2(1), 12-15.

Maybury, M., D'Amore, R., & House, D. (2002). Awareness of organizational expertise. International Journal of Human-Computer Interaction, 14(2), 199-217.

Smith, H. & McKeen, J. (2006). Development in practice XXII: Expertise location and management: Hope or hype? Communications of AIS, 18, 44-54.

- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

September 13, 2007

Expertise Locators: Part 4 (Technology Approach)

Today we’ll continue exploring the process, people, and technology considerations for implementing an expertise locator system—now with a look into the key technology considerations. In defining and selecting the technology for implementing an expertise locator system, it is important to consider the following features:

1. Select technology that is compatible with and “integrated into…legacy information systems” (Thompson, 2003, p. 14).

2. Like NASA’s Expert Seeker system, “provide a unified interface to access competencies within the organization, such as completed academic and non-academic courses, past projects and other relevant knowledge” (Becerra-Fernandez, 2001, p. 34).

3. At a minimum, select a tool that helps people locate one another’s expertise. Ideally, select a tool that can also expand to provide question and answer functionality (including archiving of those answers) to provide support for the growth of future expert communities.

4. Select a product that has a flexible and robust search engine, e.g., select one that “uses text fields to search for employees based on their fields of expertise, names, or other applicable search fields…[such as] intellectual property, skills, competencies and proficiency levels” (Becerra-Fernandez, 2001, p. 35).

5. Have a taxonomy or thesaurus developed from the beginning to help organize the areas of expertise and thus the system. In doing so, also aim to strike a “balance between a structured taxonomy of expertise areas and the anarchy of a free-form entry…[because] if there is too much structure staff feel constrained by ‘box-ticking’” (Collison, 1999, p. 12). At the same time, be careful to not let the taxonomy structure be so limited as to hurt the precision of the system and its search results (Dooley, Corman, & McPhee, 2002, p. 227).

6. Give the users the ability to “build it themselves” without having to rely on programmers or system experts (Thompson, 2003, p. 14). Consider a technology approach that utilizes personal home pages employees can easily create themselves. For example, employees could “upload photographs and resumes; choose from an evolving list of expertise categories; note their contracts and network affiliations; write as much as they need to; and link to other Web-based items of relevance – both intranet and Internet” (Collison, 1999, p. 12).

While some researchers (Maybury, D'Amore, & House, 2000, p. 13; Becerra-Fernandez, 2001, p. 35) indicate it would be preferable to select a system that has data mining and other automation features to keep the expert database current, for speed and ease of implementation it is recommended that this company start with a manually-populated system at first. To enable easier migration to a data mining approach in the future, it will be helpful to have the company’s intranet team ensure that they are gathering authorship meta-data (e.g., who developed and who else contributed) for all documents and tools posted on the intranet. Once data mining is added, it will aid in keeping the information contained in the system current (e.g., through mining for contributions to the company intranet and/or documents on shared drives).

References

Becerra-Fernandez, I. (2001). Locating expertise at NASA. Knowledge Management Review, 4(4), 34-37.

Collison, C. (1999). Connecting the new organization: How BP Amoco encourages post-merger collaboration. Knowledge Management Review, 2(1), 12-15.

Dooley, K., Corman, S., & McPhee, R. (2002). A knowledge directory for identifying experts and areas of expertise. Human Systems Management, 21(4), 217-227.

Maybury, M., D'Amore, R., & House, D. (2000). Automating the finding of experts. Research Technology Management, 43(6), 12-15.

Thompson, E. (2003). Effective knowledge management in a cost-cutting environment. Knowledge Management Review, 6(1), 12-15.

- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

September 14, 2007

Expertise Locators: Part 5 (Ensuring Success)

To wrap up our discussion of how to implement an expertise locator system, today we’ll turn our attention to what needs to be done to ensure the success of such an initiative.
To ensure the ultimate success of this expertise locator initiative, many factors needs to be considered in selecting the previous process, people, and technology approaches.

Referring to Davenport and Prusak’s (2000) critical success factors, it is clear that one critical success factor that will benefit this project is having a highly-accessible and consistent technology infrastructure. Fortunately, the target company has already invested heavily in their corporate intranet and it is well-accepted by employees as an important source of information and knowledge.

In a comparison of different authors’ critical success factors for knowledge management, it is interesting to note that both technology infrastructure and willingness to share are the top two items listed (Alazmi & Zairi, 2003). This [combined with other points made during the People portion of this paper] illustrates that the willingness of employees to enter their information in the expertise locator system will be equally important to the success of the project. As this company has recently undergone a period of re-organization, layoffs, and now a merger, there pre-exists a strong corporate need for people to know who they can now contact to answer their questions. The new organization is also much leaner than the previous, making access to individuals with the desired area(s) of expertise more challenging for employees. Thus, there will be a strong pull encouraging use of the system. In addition, it would be recommended to undertake efforts to encourage individual participation by maximizing the key variables that encourage individual participation such as perceived support from colleagues and supervisors, availability and quality of the system, and the perception of rewards and positive outcome from participation (Cabrera, Collins, & Salgado, 2006).

To further ensure the success of the project, the two critical success factors of technology and sharing—as well as supporting factors that bridge the two—must be maximized (Hariharan & Cellular, 2005). For example, the technology and processes must be simple. The relevance of this initiative to the business must be explicitly stated. Senior management must publicly support the initiative (verbally and with active participation). Those who participate should be rewarded and recognized. Sharing of benefits or anecdotal success stories should be featured informally and in intranet articles so as to further drive current and future participation.

Conclusion and Next Steps

An expertise locator system designed and built with careful consideration of the various process, people, and technology considerations outlined herein will help this company solve the immediate need for employees to know who they can contact—as well as begin to build a foundation for sharing knowledge.

It will also be important that this knowledge management initiative is the first in a series of efforts to encourage this newly restructured company to adopt a more knowledge-sharing culture (Davenport & Prusak, 2000). In fact, the need for multiple processes to make the overall strategy work was cited as important to the success of a number of expertise locator and management systems (Mayburry, D’Amore, & House, 2002; Thompson, 2003; “Sharing Knowledge,” 1997). Potential next steps for this company would include conducting a knowledge fair, building an organization-wide base of knowledge champions, completing a knowledge audit, and developing a formal knowledge strategy.

Thus, by making the expertise locator system a first step toward having a knowledge and learning strategy in place that meets the needs of this newer and leaner company, they will be able to help ease the challenges of the recent series of organizational changes as well as ensure a quick return to operational efficiencies and future innovations.


References

Alazmi, M. & Zairi, M. (2003). Knowledge management critical success factors. Total Quality Management & Business Excellence, 14(2), 199-204.

Cabrera, A., Collins, W., & Salgado, J. (2006). Determinants of individual engagement in knowledge sharing. International Journal of Human Resource Management, 17(2), 245-264.

Davenport, T. & Prusak, L. (2000). Working knowledge: How organizations manage what they know (Paperback ed.). Boston: Harvard Business School Press. (Original work published 1998)

Hariharan, A. & Cellular, B. (2005). Critical success factors for knowledge management. Knowledge Management Review, 8(2), 16-19.

Maybury, M., D'Amore, R., & House, D. (2002). Awareness of organizational expertise. International Journal of Human-Computer Interaction, 14(2), 199-217.

Sharing knowledge through BP's virtual team network. (1997). Harvard Business Review, 75(5), 152-153.

Thompson, E. (2003). Effective knowledge management in a cost-cutting environment. Knowledge Management Review, 6(1), 12-15.

- Robin

Copyright Robin Donnan 2007. All Rights Reserved.
Performance Associates, Inc.

December 1, 2007

Guiding Principles of Knowledge, part 1

Epistemology is defined as “the branch of philosophy that studies the nature of knowledge, its presuppositions and foundations, and its extent and validity” (epistemology, n.d.). In the exploration of epistemology, many philosophers have attempted to define what knowledge is, how it is acquired, and what is truth. My next three posts will be a synthesis of what these many philosophers have taught us over the ages, resulting in the formation of five guiding principles that can be applied to the modern application of learning and knowledge management.

Guiding Principle 1: Knowledge involves aspects of both the mind (thinking) and the body (senses and experience)

In the early days of epistemology, there was a strong separation between mind and body. Plato and Descartes believed that knowledge was of the mind. Plato (360BC/1968) argued that knowledge is innate and need only be brought forth. Descartes (1644) coined the phrase “cogito, ergo sum”—I think, therefore I am—and argued our senses should not be trusted, and that thought proceeds and is more certain and clearer than the body. On the other hand, Aristotle and Locke believed that knowledge focuses on the body and what is learned through our senses and experience. Aristotle (350BC/1993) argued that knowledge is created via mental processes based on what our senses perceive of the world around us. Locke (1689) developed the concept of the mind as a “tabula rasa” (white paper or blank tablet) upon which experience writes.

As we move into the 18th century through the mid-20th century, a separation between mind and body was still evident, yet some synthesis of the two began. Rousseau (1762/1957), James (1907), and Dewey (1938/1998) emphasized experience and the senses. On the other hand, Kant (1803/1960) argued that we need both sense and understanding. He believed that the body and senses help form self-sufficiency, strength, skill, quickness, self-confidence, discipline, and individuality plus enable one to become a contributing or working member of society. At the same time, Kant believed that the mind helps with the development of understanding, judgment, reason, and morality.

Looking now to the turn of the last century, a more holistic view of knowledge emerged. Schon argued for both ‘knowledge-in-action’ and ‘reflection-in-action’ (1987, pp. 23-29). Senge introduced the concept of systems thinking which “integrates [his five] disciplines [for learning] into a coherent body of theory and practice” (2006, p. 12). Nonaka and Takeuchi encouraged Western companies to embrace more holistic concepts of knowledge characterized in the Japanese intellectual tradition that emphasizes “the ‘whole personality’… [where] knowledge means wisdom that is acquired from the perspective of the entire personality… [resulting in a] valuing of personal and physical experience over indirect, intellectual abstraction” (1995, p. 29). They further argued that tacit knowledge in particular involves both physical skills (or ‘know-how’) as well as a cognitive aspect that “reflects our image of reality (what is) and our vision for the future (what ought to be)” (Nonaka & Takeuchi, 1995, p. 8).

Guiding Principle 2: Knowledge is acquired through a combination of methods

The ancient philosophers provided many enduring truisms related to understanding how knowledge is acquired. For example, Plato (360BC/1968) introduced his sun metaphor—where the light of good helps us to see the ideas of the mental world—which is the basis of the concepts we hear today with such words and phrases as "enlightenment," "seeing the light," "bright ideas," and "dawning on us.”

Many philosophers believed that knowledge was acquired through the senses. Both Aristotle and Locke contended that one can acquire new knowledge only through the senses and accumulating those experiences to form knowledge and skill. For them, knowledge is inductive by nature. Aristotle (350BC/1993), who laid the foundation for the scientific method, argued that we use our sensory perception to take in particulars and then use reasoning powers to understand what our senses perceived. Locke (1689) argued that the only knowledge humans can have is based on experience (‘a posteriori’). In Book I of Locke’s Essay Concerning Human Understanding, he argued against innate knowledge and the Cartesian split between mind and body. In Book II, Locke presented his theory of knowledge being one where all knowledge is acquired through either our senses or from reflecting on our experiences in the physical world. Interestingly, Locke still did support the Cartesian Dualism of the mind/body split; even though the mind gathers data from the sensory world, Locke argued that knowledge is an intellectual event in a world separate from the physical one. In the 18th century, Rousseau offered a four-step approach for acquiring knowledge where we “let the senses be the only guide for the first workings of reason” (1762/1957, p. 131). He argued that knowledge should be acquired first through the senses, observation, and experience; second, gradually gain the ability to focus on one thing for a long time (as driven by the learners’ interest—not an external mandate); third, apply these to ‘an honest trade’ (ensuring that one does not acquire the prejudices of one’s social and/or economic position); and then, finally, develop judgment and reasoning.

Many philosophers also believed that knowledge is acquired through the mind. Plato and Descartes were proponents of knowledge being acquired through the intellect alone—they both believed that we are born with innate ‘a priori’ knowledge and can deduce truths through mental reasoning. Proponents of rationalist philosophy, they believed that the intellect could be used to acquire knowledge about everything there is to know—that one merely needs to apply adequate intellectual reflection and study to a subject in order to deduce the truth. Plato (360BC/1968) argued that ideas are perfect, eternal, and found in the soul and that knowledge is innate and needs only be brought forth. Descartes (1644) argued that reason alone determines knowledge and this can be done independently of the senses. He further asserted that since conscious sense experience can be the cause of illusions, all sense experience should be doubted. Instead, Descartes argues, the thinking mind can operate under its own rules of logic to come to conclusions about that ‘other world’—the physical world.
More recently, the belief has emerged that knowledge is acquired through multiple means. Kant (1803/1960) argued that two kinds of judgment are needed—a priori (deductive reasoning) and a posteriori (inductive reasoning). Echoing Kant’s belief that “no mental faculty is to be cultivated by itself, but always in relation to others” (1907, p. 71), James also taught that we acquire new beliefs and ideas through the linking or ‘grafting’ of new knowledge onto previous.

As new knowledge is acquired it is done so in relation to what we already know, and in forming these new truths our old ideas and beliefs are forever changed (James, 1907, p. 24). Furthermore, Nonaka and Takeuchi have cautioned Western managers to let go of knowledge acquisition as something that occurs through books and classrooms, but rather through a “less formal and systematic side of knowledge… [that focuses] on highly subjective insights, intuitions, and hunches that are gained through the use of metaphors, picture, or experiences” (1995, p. 11).

To be continued...

- Robin
Performance Associates, Inc.

December 2, 2007

Guiding Principles of Knowledge, part 2

Let's continue our exploration of five guiding principles of knowledge by exploring principles 3 and 4.

Guiding Principle 3: Truth is subjective

Throughout the study of epistemology, there is one concept that the philosophers have debated heatedly—and that is the concept of truth. Some—like Descartes (1644)—strove for certainty in truth, while others took a more accommodating stance.

Some philosophers’ beliefs of truth were characterized by absolutes. Plato (360BC/1968) asserted that only ideas are perfect, eternal, and permanent—unlike all things in the physical world that always become corrupted and die. Descartes (1644) argued that knowledge of eternal truths can be attained by reason alone. He asserted that truths are attained by reason and are broken down into elements that intuition can grasp through a purely deductive process resulting in clear truths about reality. Descartes also argued that everything we know is either a thing, an affection of a thing, or an eternal truth (1644, p. XLVIII). Furthermore, he believed that we can conceive of physical substance without the actual object, but the opposite is not true—thus the truth lies only in the mind (Descartes, 1644, p. LIII). And relatively recently, Skinner (1971) argued that truth can be found only in directly observable behaviors.

Fortunately these rigid definitions have yielded to a more accommodating and subjective view of truth. Locke believed that in "searches after truth...the very pursuit makes a great part of the pleasure. Every step the mind takes in its progress towards knowledge makes some discovery, which is not only new, but the best too, for the time at least” (1689, p. 1). James presented his view of instrumental truth, or “the view that truth in our ideas means their power to ‘work’” (1907, p. 43). He also supported the subjectivity of truth in citing the ideas of Schiller and Dewey who argued that “…ideas become true just in so far as they help us to get into satisfactory relation with other parts of our experience” (James, 1907, p. 23). Women’s perspective on knowing, as described by Belenky, Goldberger, Clinchy, and Tarule (1986), presented the concept of subjective knowledge which encourages the development of one’s instinct and intuition as a means of being able to define one’s own truth. “Truth, for subjective knowers, is an intuitive reaction [where one is] not...part of the process, as constructor of truth, but as conduit through which truth emerges” (Belenky et al., 1986, p. 69). Subjective knowledge means less reliance on restrictive dualistic thinking of absolutes, and embraces what the authors call “connected knowing, an orientation toward understanding and truth that emphasizes not autonomy and independence of judgment, but a joining of minds” (Belenky et al., 1986, p. 55). Nonaka and Takeuchi asserted that “organizational intention provides the most important criterion for judging the truthfulness of a given piece of knowledge…intention is often expressed by organizational standards or visions that can be used to evaluate and justify the created knowledge” (1995, p. 74). Drucker also took an accommodating view of truth, stating “All knowledges are equally valuable; all knowledges, in the words of the great medieval saint and philosopher St. Bonaventura, lead equally to the truth” (1993, p. 218).

Guiding Principle 4: Learning is most effective when it involves elements of both practice/doing and theory/thinking

Through their study of knowledge, the epistemological philosophers also contributed their beliefs about how learning can be most effective—and many argued for including elements of both practice/doing and theory/thinking. Descartes (1644) argued for steps to educate oneself that included both intellectual pursuits and practice as a means to apply morals and logic. Kant (1803/1960) argued for methods designed to train both the mind and the body. He believed the mind should be trained (1) through both physical and moral training, (2) with an eye to the end goal—is it for work (scholastic culture) or play (free culture); (3) to maximize memory skills early and cultivate understanding; and (4) with rules alongside application and examples. Kant also believed that the body should be trained through (1) active doing to combine skill and senses; (2) developing a photographic memory (to be used in nature as well as in books and music); and (3) using childhood games to prepare children for the future and condition them to remain busy and work toward an end goal (1803/1960). Rousseau (1762/1957) argued for learning through experience first and then proceeding to mental reasoning. He believed that it is best to teach through doing whenever possible, and only fall back upon words when doing is out of the question. Rousseau also emphasized the need for experienced-based self-directed learning stating:

Let the senses be the only guide for the first workings of reason… The child who reads ceases to think, he only reads. He is acquiring words not knowledge. [Rather] teach the scholar to observe the phenomena of nature… Put the problems before him and let him solve them himself. Let him know nothing because you have told him, but because he has learnt it for himself. (1762/1957, p. 131)

Late 20th century philosophers continued to support the idea of effective learning needing both practice/doing and thinking/theory. Rogers encouraged us to remember that learning is both intellectual and behavioral by stating, “It is not simply an intellectual value choice, but seems to be the description of the…behaviors by which [the learner] moves exploringly toward what he wants to be” (1961, p. 176). Skinner’s operant conditioning involved the breaking down of learning into small pieces, and then providing both instruction and practice (along with reinforcement) on each piece (1971). Schon stated, “rigorous professional practitioners solve well-formed instrumental problems by applying [both] theory and technique” (1987, pp. 3-4). He argued for practical knowledge providing experience and skill in problem solving—resulting in the artistry by which the seasoned professional practices a trade. Practical knowledge also provides the opportunity to build what Schon termed ‘knowledge-in-action’—the ability to apply tacit knowledge and make wise judgments in the light of new problems and situations (1987, pp. 23-25). He also recommended the use of practical experience that can provide the opportunity for ‘reflection in action’—a series of evaluations, learnings, and modifications that are made in the midst of practice (Schon, 1987, pp. 26-29). Schwab (1971) also argued in support of the need for both theory and practical application. He asserted that theory knowledge provides the legitimacy of facts, rules, and concepts founded upon research; however, theory alone—with its inherent generality—is not enough for today’s professionals since practice requires the concrete and particular.

More recent philosophers have brought the concept of learning through both practice/doing and thinking/theory into the mainstream. Drucker himself criticized the traditional liberal arts education (typically grounded in theory), stating that this form of education “does not enable [students] to understand reality, let alone to master it” (1993, p. 213). He argued that what is needed instead is a blending of theory and doing, being able to live and work in both the worlds “of the ‘intellectual’ who focuses on words and ideas, and that of the ‘manager’ who focuses on people and work;” by having both, “there can be creativity and order, fulfillment and mission” (Drucker, 1993, p. 215). Senge introduced “the five disciplines [that] represent approaches (theories) and methods [practices] for developing three core learning capabilities: fostering aspiration, developing reflective conversation, and understanding complexity” resulting in what he calls ‘generative learning’ or enhancing the capacity to create (2006, pp. xiii, 14). Furthermore, Senge cautioned that “we learn best from experience, but [if] we never directly experience the consequences of our most important decisions” we will be limited in what can be learned from that experience (2006, p. 23). Nonaka and Takeuchi (1995) also embraced a holistic method of learning, believing that learning provides an opportunity to internalize knowledge and convert from explicit to tacit knowledge. They argued that sometimes learning by doing is the best method—what they termed ‘re-experiencing’ others’ experiences—and believed that other times hearing or reading of others’ experiences works equally well (Nonaka & Takeuchi, 1995, pp. 69-70).

To be continued...

- Robin
Performance Associates, Inc.

December 3, 2007

Guiding Principles of Knowledge, part 3

Let's now complete our exploration of five guiding principles of knowledge.

Guiding Principle 5: Today’s knowledge managers need to remain flexible, willing to adapt their approaches and adopt new perspectives/techniques

Epistemology has much to offer to today’s knowledge managers. It is interesting to note that the advice is varied. When considered together the solution appears to be adopting a flexible mindset and being willing to adapt one’s approach based on what epistemology teaches us from the past, as well as what we will learn in the future.

From the ancients, we gather suggestions for how to maximize knowledge acquired through the mind or body. Plato’s assertions suggest the need to provide opportunities for each individual’s innate knowledge to spring forth (360BC/1968). He argued that the relation between the knower and what is known is that the knower already possesses the knowledge or can acquire it through mental effort. Therefore, the role of the knowledge manager is to help individuals tap into what they know. Aristotle, on the other hand, argued that the knower has the ability to gather knowledge through mental processes applied to information (i.e., gathered via their senses) based on the world around us (350BC/1993). This gathered knowledge can then be used to increase what the knower knows. The implications of this for knowledge managers is to encourage searching and exploration to find explanations, applying each person’s ability to perceive and thus learn or acquire knowledge, using these perceptions to form memories which can then become experience, and maximizing this experience to create mastery of new skills or understanding. Overall, that means as a knowledge manager it would be important to utilize methods that will help individuals to explore, remember, and then amass experiences to achieve deeper levels of skill or understanding.

Even though Rousseau addressed the education of an adolescent in Emile, he brought forth many ideas that are followed today in the methods of experiential and discovery learning that work for children and adults alike. Rousseau’s gathering sea shells analogy (1762/1957, p. 134) also has a parallel to today’s Internet-based processes for gathering ideas and information. With the vast number of sources available today, ideas and information—just like Rousseau’s sea shells—run the risk of being gathered, tossed here and there as they fit our interests, and then being thrown away once we become overwhelmed. Thus conscious work must be done to ensure that ideas and information have the opportunity to be converted into knowledge before they are thrown away and lost.

Moving forward to the 20th century, Schwab (1971) asserts the need to apply multiple theories to get a more accurate understanding or assessment of a situation, and that people need to be taught how to critically consider and evaluate multiple theories. Schon’s (1987) teachings remind us that for a good learning environment in either academic or corporate institutions, the artist-practitioner needs to be able to convert his/her tacit knowledge into knowledge and activities that can be conveyed and then practiced or applied by students. The artist-practitioner also needs to share his/her experiences of theory in practice; the implication is that if the instructor lacks that experience, it would be helpful to bring in others as guest speakers to provide that and/or (in the case of adult learners) elicit students’ experience to aid in applying the theory. Belenky et al. (1986) cited the importance of trusted experts who can offer their experience and provide guidance when developing one’s subjective knowledge. “By sharing reactions and solutions ...by being given the opportunity to talk things over with a sympathetic, nonjudgmental person with similar experience... [one can see that one] has experience that may be valuable to others” (Belenky et al., 1986, p. 61). This, in essence, is similar to the concept of having a mentor to whom one can turn for reassurance and advice.

Our most recent knowledge experts provide additional recommendations for how today’s knowledge manager can maximize workplace knowledge sharing and learning. Drucker recommended that knowledge managers help facilitate how to best apply knowledge to produce business results (the improvement, exploitation, and innovation that he speaks of as the three kinds of new knowledge) in order “to make knowledge productive” (1993, pp. 185, 191). Senge argued that “the organizations that will truly excel in the future will be the organizations that discover how to tap people’s commitment and capacity to learn at all levels in an organization” (2006, p. 4). He encouraged knowledge managers to maximize the increased connection and networked nature of organizations, thus leading to “new capacity for continual learning, innovation, and adaptation” (Senge, 2006, p. xvi). He recommended companies create a structure that fosters learning and continuous improvement, encouraging the five disciplines and blending them into the organization’s culture. This could be done through developing a shared vision, providing opportunities for reflection, and aligning the reward system to encourage learning and sharing. Senge also encouraged working to create a positive learning environment and being willing to invest in the long-term and not be distracted by short-term gains; thus the implication for the knowledge manager is to help organizations balance their need for short-term results with the desire for sustainability and achievement of lasting and long-term goals. Nonaka and Takeuchi argued that to maximize the knowledge creation capability of an organization, the knowledge manager needs to provide opportunities for individual knowledge to be converted into organizational knowledge “through dialogue, discussion, experience sharing, and observation” (1995, p. 13). They also encouraged the involvement of all levels to create new knowledge—from front-line employees, to middle managers, to senior management (Nonaka & Takeuchi, 1995, p. 15). Furthermore, they asserted the value of using a rugby team approach to teamwork. This involves having overlapping project phases taken on by a multi-disciplinary team who has shared responsibility throughout the development process and takes turns in contributing what their specialization offers to the task at hand (Takeuchi & Nonaka, 1986).

Summary

Reflecting on the history of epistemological thought results in five guiding principles that can be applied to the modern disciplines of learning and knowledge management:
1. Knowledge involves aspects of both the mind (thinking) and the body (senses and experience).
2. Knowledge is acquired through a combination of methods.
3. Truth is subjective.
4. Learning is most effective when it involves elements of both practice/doing and theory/thinking.
5. Today’s knowledge managers need to remain flexible, willing to adapt their approaches and adopt new perspectives/techniques.

The implication is that today’s learning and knowledge management professionals need to use these principles to respect both thinking and experience, and to provide opportunities and methods in the workplace that maximize both the mind and body. Learning and knowledge management professionals are encouraged to model openness and discourage the tendency to seek ‘the’ right answer or truth; instead, they need to encourage the consideration of multiple perspectives and ensure different viewpoints are heard. Learning management professionals in particular need to build in ample opportunities for both theory and practice during workplace learning events. And, finally, learning and knowledge management professionals themselves must be lifelong learners possessing a long-term view. They need to educate themselves and stay current on the methods for effective learning plus knowledge acquisition, sharing, and creation. They must also be able to weigh these methods in light of an organization’s culture and business goals—being willing to recommend incremental solutions that will lead to accomplishing the long-term vision. They must also be flexible, willing to change their approach as needed and help the workforce realize that learning and knowledge is everyone’s job.

References

Aristotle. (350BC/1993). Posterior analytics (J. Barnes, Trans.). London: Clarendon Press.

Belenky, M. F., Goldberger, N. R., Clinchy, B. M., & Tarule, J. M. (1986). Subjective knowledge: The inner voice. In Women's way of knowing: The development of self, voice and mind, New York: Basic Books, Inc.

DeCastell, S. & Bryson, M. (1997). Querying pedagogy. In D. P. Britsman & J. L. Miller (Eds.), Radical interventions: Identity, politics, and differences in educational praxis (pp. 60-80). Albany, NY: State University of New York Press.

Descartes, R. (1644). Principles of philosophy. Retrieved September 3, 2007 from http://www.classicallibrary.org/descartes/principles/index.htm

Dewey, J. (1938/1998). Experience and education (60th anniversary ed.). Kappa Delta Pi International Honor Society.

Drucker, P. (1993). Post-capitalist society. New York: Harper Collins Publishers, Inc.

epistemology. (n.d.). The American Heritage Dictionary of the English Language, Fourth Edition. Retrieved November 18, 2007 from http://dictionary.reference.com/browse/epistemology

James, W. (1907). Pragmatism: A new name for some old ways of thinking. In The matter of belief: Selected works of William James. Retrieved October 1, 2007 from http://www.brocku.ca/MeadProject

Kant, I. (1803/1960). Education. Ann Arbor, MI: University of Michigan Press.

Locke, J. (1689). Essay concerning human understanding. Retrieved September 3, 2007 from http://www.ilt.columbia.edu/publications/locke_understanding.html

Nonaka, I. & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. New York: Oxford University Press.

Plato. (360BC/1968). Republic (B. Jowett, Trans.). Public Domain.

Rogers, C. (1961). On becoming a person: A therapist's view of psychotherapy. Boston: Houghton-Mifflin Company.

Rousseau, J. J. (1762/1957). Emile (B. Foxley, Trans.). London: JM Dent and Sons.

Schon, D. A. (1987). Educating the reflective practitioner: Toward a new design for teaching and learning in the professions. Hoboken, NJ: John Wiley & Sons, Inc.

Schwab, J. J. (1971). The practical: Arts of eclectic. In School review (pp. 493-542). Chicago: University of Chicago Press Journals.

Senge, P. M. (2006). The fifth discipline: The art and practice of the learning organization. New York: Doubleday. (Original work published 1990)

Skinner, B. F. (1971). Chapter 1: A technology of behavior. In Beyond freedom and dignity. Retrieved August 25, 2007 from http://www.xanedu.com

Skinner, B. F. (1971). Chapter 2: Freedom. In Beyond freedom and dignity. Retrieved August 25, 2007 from http://www.xanedu.com

Skinner, B. F. (1971). Chapter 3: Dignity. In Beyond freedom and dignity. Retrieved August 25, 2007 from http://www.xanedu.com

Takeuchi, H. & Nonaka, I. (1986). The new new product development game. Harvard Business Review, Jan-Feb 1986(86116), 2-11.


- Robin
Performance Associates, Inc.

December 8, 2007

What is knowledge management?

Indicative of a relatively new field, there has been much debate in trying to define knowledge management. In the introductory chapter of Dalkir’s book, he references many potential definitions for knowledge management, pulling from such classic knowledge management authors as Davenport and Prusak, Nonaka and Takeuchi, and Wiig. Dalkir also defines common elements found in many, but certainly not all, definitions of knowledge management. Chun Wei Choo, in the forward to Dalkir’s book, offers the definition of “knowledge management as a framework for designing an organization’s goals, structures, and processes so that the organization can use what it knows to learn and to create value for its customers and community” (2005, p. xiii). What is compelling about this definition is that it addresses the synthesizing potential of knowledge management, as well as its valued output. Implied are the people considerations; but what is missing is the technology vehicle often used to accomplish the potential and output to which Choo refers.

Unfortunately, there remains the challenge of developing a commonly accepted definition accepted by academics, practitioners, and the layperson. To develop a definition for knowledge management, considering the people, process, and technology components is a good place to start. Knowledge is captured, codified, shared, and (ideally) created by people for the benefit of people and their organizations. Knowledge management efforts can also live or die on the ability to capture people’s support, both of initial implementation efforts as well as long-term use and support. Knowledge processes can vary from highly structured content management systems with standardized taxonomies and meta-data to the creation of physical spaces that encourage the free flow of knowledge (without imposing any formal structure or process). Technology is indeed an important aspect of knowledge management, for it enables knowledge processes on behalf of the people that knowledge aids. As Davenport and Prusak state, “Technology’s most valuable role in knowledge management is extending the reach and enhancing the speed of knowledge transfer” (2000, p. 125). But technology should not be the only, nor the most important element. As they did in their classic text, Working Knowledge, Davenport and Prusak have continued to “caution against a technology-centered KM approach, but argue that a technology ingredient is a necessary ingredient for successful KM projects” (Davenport & Prusak, 2000; Rao, 2005, p. 22).

People, process, and technology—all are critical elements. None can make a knowledge management initiative successful on its own. The best-intentioned and motivated people without supporting processes or technology may have initial success, but they’ll likely not experience long-term success. Well-designed processes without people’s support or the technologies to enable them are destined to languish on paper. And the best technology will suffer from little or no use if it is not woven into the business processes and supported by all levels of people in the organization.


References

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Elsevier Butterworth-Heinemann.

Davenport, T. H., & Prusak, L. (2000). Working knowledge: How organizations manage what they know (Paperback ed.). Boston: Harvard Business School Press. (Original work published 1998)

Rao, M. (Ed.). (2005). Knowledge management tools and techniques. Burlington, MA: Elsevier Butterworth-Heinemann.


- Robin Donnan
Performance Associates, Inc.

December 27, 2007

Adult Cognitive Development

In considering the cognitive development of adults, two major perspectives have emerged—dialectical and contextual. Dialectical thinking is characterized by discussion and reasoning to make sense of the contradictions and complexities that adults must continually deal with. It argues that “thinking in a dialectical sense allows for the acceptance of alternative truths or ways of thinking about similar phenomena that abound in everyday adult life” (Merriam, Caffarella, & Baumgartner, 2007, p. 342). Dialectical thinking is a logical thought process by which adults can reasonably take what may on the surface seem like contradictory positions. In quoting Kegan’s work on dialectical thinking, Merriam et al. (2007, p. 344) point out that one important method for resolving these contradictions and complexities is to move away from trying to “win” one’s position but rather to recognize that “the other side will not go away, [and] probably should not.”

The contextual approach considers “how social, cultural, economic, and political forces shape the development of adult thinking” (Merriam et al., 2007, p. 347). It argues that these contextual factors may be what influences an adult’s cognitive development. To take on a contextual perspective involves considering these social, cultural, economic, and political factors rather than chronological ones as guideposts for comparison. For example, in comparing adults’ beliefs on DNR (Do Not Resuscitate) orders, the contextual approach would argue for exploring a group of people who have had loved ones involved in a serious medical emergency (where resuscitation was needed) versus those who have not; it might also argue for considering those who have the economic means to sustain someone on life support versus those who do not. Contextual approaches would also argue not to evaluate behavior on its surface, but rather to consider the contextual factors that have influenced and/or may lend meaning to those behaviors. Goldberger’s examples of silence in different cultures are an excellent example of contextual factors in action (as referenced in Merriam et al., 2007, pp. 348-349).

Dialectical and contextual thinking are similar in that they both attempt to explain how adults process the complexities of decision-making and belief formation. As adults, we must come to accept “that all knowledge is incomplete and subjective. However, [we also] recognize that [we] must act despite the limits of [our] knowledge” (Merriam et al., 2007, p. 327). On the other hand, dialectical and contextual thinking differ significantly in how dialectical thinking takes a linear progression with the end result being dialectical thought process, versus contextual thinking that encourages a more cyclic and fluid process of reflection and subjectivity. Dialectical thinking weighs in strongly on logic and reasoning versus contextual thinking that favors relative, affective considerations.

Focusing on the contextual approach, epistemology teaches us that truth is subjective (Locke, 1689; James, 1907; Belenky, Goldberger, Clinchy, and Tarule (1986); Nonaka and Takeuchi (1995)). So to is knowledge. As Davenport and Prusak argued in providing their definition of knowledge, “Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information” (1998/2000, p. 5). As adults, we are often faced with needing to take action even though we may not know everything we would like to about the subject. Think about when we are confronted with a new challenge at work our must act quickly to respond to a child’s or loved one’s needs. We act based on our knowledge at that given time. But, how many times does further life experience show that another course of action would have been better? Our beliefs (and our actions) are also influenced by our previous life experiences—the contextual factors of our previous social, cultural, economic, and political experiences. Think about how the knowledge and beliefs held by young adults often change in one’s middle and later adult years—that’s the contextual factors of social, cultural, economic, and political influences at play.

In reflecting upon my own learning experiences, I believe that contextual approaches have had more impact. While dialectical thinking has had a role—and certainly more so when I was younger—my tendency is to approach complex questions with “it all depends” and “what if.” Perhaps acknowledging dialectical thinking’s role is reflective of my own experience of contextual thinking—as Merriam et al. (2007, p. 349) argue, “contextual factors [can] limit or expand our ways of knowing and allow us to speak of different uses or even meanings of each of the ways of knowing.” My personal aim is to ensure that I employ these contextual considerations in an expanding, and not limiting, way.

References

Belenky, M. F., Goldberger, N. R., Clinchy, B. M., & Tarule, J. M. (1986). Subjective knowledge: The inner voice. In Women's way of knowing: The development of self, voice and mind, New York: Basic Books, Inc.

Davenport, T. H., & Prusak, L. (2000). Working knowledge: How organizations manage what they know (Paperback ed.). Boston: Harvard Business School Press. (Original work published 1998)

James, W. (1907). Pragmatism: A new name for some old ways of thinking. In The matter of belief: Selected works of William James. Retrieved October 1, 2007 from http://www.brocku.ca/MeadProject

Locke, J. (1689). Essay concerning human understanding. Retrieved September 3, 2007 from http://www.ilt.columbia.edu/publications/locke_understanding.html

Merriam, S.B., Caffarella, R.S., & Baumgartner, L.M. (2007). Learning in adulthood (3rd ed.). San Francisco: John Wiley & Sons.

Nonaka, I. & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. New York: Oxford University Press.

- Robin
http://www.perfassocinc.com

January 26, 2008

Critical Analysis of the Research on Communities of Practice

Beginning with its roots in anthropology, communities of practice (CoPs) have been studied by many since Wenger and Lave first introduced the concept in 1991. CoPs can be defined as “a group of people having common identity [and] professional interests and that undertake to share, participate and establish a fellowship” (Pickett as cited in Dalkir, 2005, p. 112). Dalkir (2005) describes CoPs as typically informally-created groups centered around a common focus or goal, whether a profession, work function, problem, topic, or industry; furthermore, members’ commitment is driven by trust and professional behaviors/practices (p. 124) and they typically possess a virtual workspace in which “to store stories, artifacts, tools, discussions, glossaries, [and] historical events” (p. 125). The study of CoPs began with predominantly ethnographic studies, progressed through to qualitative studies, and then more recently has expanded into quantitative studies that are attempting to display a link between CoPs and improvements in organizational performance. This paper will take a chronological look at these developments, ending with a critical analysis of the major theorists and their contributions.

Theoretical Works

Wenger is considered by many to be the seminal theorist on CoPs and has published much on the subject. Through an impressive ethnographic study in his dissertation, Wenger (1990) began his investigation into the characteristics of communities and the people and practices that make up those communities. In 1991, Wenger first published on the subject of CoPs. His article introduced the idea of “learning as a social phenomenon… [where] information only takes meaning in the context of the social practices of the communities that give it cultural life… [Furthermore,] through our membership in their communities…we come to know—and be empowered by what we know” (Wenger, 1991, p. 83). This concept was further reinforced in Wenger’s work that year with Lave where they first identified the CoP concept in their “research toward a ‘social theory of learning’” (Zboralski, Salomo, & Gemuendon, 2006, p. 535). In addition to learning as a social phenomenon, Wenger (1991) provided recommendations for “managers who want to leverage the power of the social communities within their corporations” (p. 83-84). He also introduced his organization, the Institute for Research on Learning (IRL), as a CoP that would be exploring these concepts. Interestingly, IRL was a not-for-profit initially funded by the Xerox Corporation that resulted in the development of the concepts of distributed intelligence, cognitive apprenticeships, communities of learners, and—most significantly—communities of practice (Pea, n.d.). Wenger was a research scientist at IRL from 1987 to 1997 (Wenger, n.d.).

In 1997, Snyder built on Wenger’s and others’ early work by identifying CoPs as a tool for enhancing organizational learning, building organizational competencies, and improving organizational performance. To support this claim, Snyder (1997) argued that “competencies in the current environment are rarely static, so high-performance [CoPs] engage in continuous learning activities to ensure that competencies are built, shared, and applied effectively” (p. 8-9). Furthermore, CoPs:

…are aligned with competencies…they both enact competencies…and develop and renew competencies through a variety of learning activities. [They] “also constitute influential organization conditions…that influence communication and coordination… [and] are aligned, therefore, with several of the factors associated with a performance-based model of organizational learning. (Snyder, 1997, p. 9)

Snyder’s most important contribution in his 1997 article was the introduction of a “set of [33] testable hypotheses about how communities of practice influence performance, how they learn competence, and what conditions facilitate competence development” (p. 14). These 33 hypotheses can be used to test the interrelation between CoPs and organizational learning, organizational competence, and organizational performance. In fact, this set of hypotheses for testing the interrelation between CoPs and organizational learning, organizational competence, and organizational performance went on to encourage many research efforts including those by Lesser & Prusak; Dove; Lorenz; Smith & McKeen; Webb, Wunram, Lettice & Klein; Lucas; and more.

In 2002, Snyder and Wenger collaborated (along with McDermott) on the writing of the seminal book Cultivating Communities of Practice: A Guide to Managing Knowledge. In it, they introduced seven design principles for CoPs:

1. Design for evolution
2. Open a dialogue between inside and outside perspectives
3. Invite different levels of participation View image
4. Develop both public and private community spaces
5. Focus on value
6. Combine familiarity and excitement
7. Create a rhythm for the community
(Wenger, McDermott, & Snyder, 2002, p. 51)

This work also led to the creation of Wenger’s quick start-up guide that succinctly presented the major concepts related to CoPs (View image) (Wenger, 2002). Then in 2004, Wenger reinforced his earlier proposition of the social nature of knowledge by arguing that “communities of practice [are] the social fabric of knowledge” (p. 1). He further described the three elements of a community of practice (domain, community, and practice) and defined the role of management sponsorship to “enable communities to thrive and have an impact on the performance of the organization” (Wenger, 2004, p. 7).

Applied Research

Where the previous theoretical works helped to define what a CoP is and how one should be designed and managed, applied research aided in identifying what problems CoPs can solve. Snyder (1997) referred to the role of early CoP case studies completed by Brown & Gray, Cook & Yanow, Orr, Snyder, and Wenger in demonstrating “that learning occurs most effectively within communities that have developed trust, shared understanding of problems, and a language to communicate new and old solutions” (p. 9). Ever since, CoPs have been identified as an effective knowledge management application in numerous case studies, providing useful examples and best practices for how to design and foster CoPs in organizations. For example, DaimlerChrysler found CoPs “to be an efficient means to achieve business process improvement and manage complexity” by improving the flow and sharing of knowledge throughout the organization (Kannan, Aulbur, & Haas, 2005, p. 138). Ericsson Research Canada used online CoPs, finding them to be “a complete KM concept anchored in the people domain and supported by suitable technology” (Hemre, 2005, p. 157). Baria (2005) shared that Rolls-Royce has seen CoPs provide numerous benefits to “both the business and the individual” (p. 253) and have found that having a corporate CoP leader strengthens CoP activity (p. 246). And New Zealand has used predominantly virtual CoPs as an effective means of encouraging “inter-organizational knowledge networking on a national scale” (Rao, 2005, p. 206; Spence, 2005).

In additional applied research, Choi (2006) examined the potential of CoPs as an alternative learning model for knowledge creation and performance training in corporations; Choi also acknowledged CoPs as a key engine for creating and sharing both tacit and explicit knowledge. Choi (2006) also identified factors that facilitate or encourage CoP activity including “learning motivation and desire for learning, creation of work-related knowledge and sharing of expertise in CoP participation, relationship between theme and outcome of CoP and performance, trust among members, and the leadership trait of the team leader” (p. 144-145). Later in 2006, Zboralski et al. defined potential positive performance effects of CoPs including knowledge, business performance, and socialization (View image). They also developed a measurement model to evaluate the CoP constructs of information exchange, networking, network position, knowledge effect, business performance effect, and socialization (View image). Importantly, Zboralski et al. (2006) demonstrated “that CoPs have a close connection and positive direct impact on business performance” (p. 547) by quantitatively proving CoP members with a strong network position due to their involvement in a CoP have a positive effect on the knowledge base, the business performance, and the socialization between staff.

Critical Analysis

As we turn now to a critical analysis of the theoretical works and applied research, let us focus on Wenger’s contributions from the theoretical perspective and Zboralski et al.’s contributions from an applied research perspective.

Wenger

Bearing in mind that the scope of this paper did not allow for a detailed review of all of Wenger’s work, the materials reviewed were somewhat disappointing. Strong points of Wenger’s work included his solid work to conceptualize CoPs and emphasize the need for them to be very flexible, organic, and evolving in nature. In addition, his writing is approachable and appealing to readers, with many statements possessing good face validity, e.g., “intuitively, everybody knows what knowledge is. When you have it, you are likely to understand situations and do the right thing; when you don’t, you are in trouble” (Wenger, 2004, p. 1). However, his published work (including the materials cited in this paper) focuses more on the practitioner than the scholar; thus some of Wenger’s materials are sometimes lacking in scholarly rigor. For example, much of his published work is targeted to practitioners and most of his articles and materials were not published in peer-reviewed journals. (A search for peer-reviewed CoP articles that Wenger authored revealed only one article that he co-wrote with Eckert in 2005, and reading his detailed CV revealed that a very small percentage of his articles and papers have been published in peer-reviewed journals.) Despite this, Wenger’s material has become the seminal work on CoPs—as supported by the number of citations of Wenger’s work in CoP research articles plus Wenger’s own biography that claims “Communities of Practice: Learning, Meaning, and Identity, [is] a seminal book that lays out the theory of communities of practice” (Wenger, n.d.).

Wenger’s 2004 article was particularly disappointing. While the “doughnut” analogy for his model (View image) may make it feel more accessible to practitioners, he may be doing a disservice to the discipline of knowledge management—made all the worse by the fact that he begins the article stating that the field has had to deal with numerous skeptics and detractors. But then he goes on to state, “I will argue that when it comes to knowledge, management is a doughnut…and noting that the center of the doughnut is empty, I will argue that knowledge management is primarily the business of those who actually make the dough—the practitioners” (Wenger, 2004, p. 1). Again, perhaps this is an approachable analogy, but the light-heartedness of its description may make the reader question if knowledge management is a respectable discipline. Then in looking more closely at the writing of this article, the model is not directly linked to the structure of the paper, causing significant confusion and further making the doughnut model questionable. Further, Wenger (2004) missed opportunities to reinforce the model by not illustrating such statements as “this defines two paths between strategy and performance: business processes and communities of practices” on the model itself (p. 8). Ensuring the article’s structure directly followed the model (e.g., with consistent terminology and labeling of sub-sections) and illustrating all the concepts on the model would have greatly improved the quality and coherence of Wenger’s article and model. A final problem area is that Wenger lists key issues and questions at the end of each sub-section, yet does not address what actions should be taken to address these issues.

Zboralski et al.

In contrast, Zboralski et al.’s (2006) article was particularly impressive for not only its contribution to quantitatively proving a relationship between CoPs and organizational performance, but also in its thorough scholarly approach. The article begins with a very thorough literature review, establishing a strong relation between Zboralski et al.’s research and the existing body of knowledge. However, like most research projects in the social sciences, there were some weaker areas. For example, Zboralski et al.’s sampling is somewhat problematic. Within the selected multinational company, there were 220 CoPs that met the researchers’ criteria; yet over a four month timeframe they were only able to get questionnaire responses representing 36 of those CoPs. The researchers claimed that their coverage of “about 31% of all active community members…can be considered a valid representation of the overall population” (Zboralski et al., 2006, p. 542). However, it is not entirely clear by what objective criteria this claim can be made. The questionnaire for their measurement model was pre-tested, resulting in revisions prior to releasing the questionnaire to the sample population. However, the authors did acknowledge that a common method bias could not be ruled out. In addition, the study is somewhat limited in that it was based on one German multinational company with an extensive number of CoPs, and the measures were based on the CoP members’ perception of the CoPs’ effects on organizational performance. Overall, Zboralski et al.’s conclusions were justified by the results; however, they could be strengthened further by replicating the research with other companies plus comparing the results to the perceptions of non-members of CoPs or to objective performance measures that could not be influenced by the participants’ perception.

Conclusion

In completing this review and critical analysis of the literature on CoPs, it has been intriguing to see the different roles and contributions of the early theoretical works and the later applied research works. It is also fascinating to see the evolution of CoPs from an ethnographic dissertation to one of the most common knowledge management applications utilized by organizations today. Most significantly, it is encouraging to see the efforts of researchers to move from a theoretical base to quantifiable proof, thereby strengthening the professional discipline of knowledge management.


References:

Baria, D. (2005). A day in the life of a Rolls-Royce knowledge manager. In M. Rao (Ed.), Knowledge management tools and techniques (pp. 246-254). Burlington, MA: Elsevier Butterworth-Heinemann.

Choi, M. (2006). Communities of practice: An alternative learning model for knowledge creation. British Journal of Educational Technology, 37(1), 143-146.

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Elsevier Butterworth-Heinemann.

Hemre, A. (2005). Building and sustaining communities of practice at Ericsson Research Canada. In M. Rao (Ed.), Knowledge management tools and techniques (pp. 155-165). Burlington, MA: Elsevier Butterworth-Heinemann.

Kannan, G., Aulbur, W., & Haas, R. (2005). Knowledge management in practice: Making technology work at DaimlerChrysler. In M. Rao (Ed.), Knowledge management tools and techniques, Burlington, MA: Elsevier Butterworth-Heinemann.

Pea, R. (n.d.). IRL. Retrieved January 19, 2008 from http://www.stanford.edu/~roypea/HTML1%20Folder/irl.html

Rao, M. (Ed.). (2005). Knowledge management tools and techniques. Burlington, MA: Elsevier Butterworth-Heinemann.

Snyder, W. (1997). Communities of practice: Combining organizational learning and strategy insights to create a bridge to the 21st century. Retrieved December 15, 2007 from http://www.co-i-l.com/coil/knowledge-garden/cop/cols.shtml

Spence, P. (2005). Knowledge networking on a national scale: A New Zealand case study. In M. Rao (Ed.), Knowledge management tools and techniques (pp. 206-213). Burlington, MA: Elsevier Butterworth-Heinemann.

Wenger, E. (1990). Toward a theory of cultural transparency: Elements of a social discourse of the visible and the invisible. Unpublished doctoral dissertation, University of California.

Wenger, E. (1991, Fall). Communities of practice: Where learning happens. Benchmark, pp. 82-84.

Wenger, E. (2002). Cultivating communities of practice: A quick start-up guide. Retrieved January 9, 2008 from http://www.entreculturas.pt/Media/start-up_guide_PDF.pdf

Wenger, E. (2004). Knowledge management as a doughnut: Shaping your knowledge strategy through communities of practice. Ivey Business Journal, 68(3), 1-8.

Wenger, E. (n.d.). Full CV. Retrieved January 19, 2008 from http://www.ewenger.com/bio/biocv.htm

Wenger, E., McDermott, R., & Snyder, W. (2002). Seven principles for cultivating communities of practice. In Cultivating communities of practice: A guide to managing knowledge (chap. 3). Retrieved January 9, 2008 from http://www.askmecorp.com/pdf/7Principles_CoP.pdf

Zboralski, K., Salomo, S., & Gemuendon, H.G. (2006). Organizational benefits of communities of practice: A two-stage information processing model. Cybernetics & Systems, 37(6), 533-552.

- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

February 18, 2008

Knowledge Management and the Learning Organization

In the past decade, more and more researchers and practitioners have begun to acknowledge the potential synergies and interrelationships between knowledge and learning. This is particularly evident in the convergence of the concepts of the learning organization (LO) and knowledge management (KM). Senge (1990/2006) first introduced the concept of the learning organization as a set of core learning capabilities that enable an organization to innovate (i.e., to create new knowledge) and create sustainable advantage. In 1999, Senge shared that he saw KM addressing “the same critical issues [that the Society of Organizational Learning] members have been struggling with—the sustainable creation, transfer, and dissipation of organizational knowledge” (Karlenzig as cited in McElroy, 2003). In studying the areas of organizational forgetting, organizational memory, and how knowledge transfer is a key to creating organizational learning, Argote (2005/1999) posits that “patterns of knowledge creation, retention, and transfer contribute to differences in the rates at which organizations learn” (p. 203). Loermans (2002) defines the relationship between KM and LO by stating that the LO focuses on the learning process and generating new knowledge while KM “takes the output from the LO, manages it and ensures that an appropriate environment to perpetuate the generation and management of knowledge capital is being properly maintained” (p. 292). Loermans (2002) also cites the research of Brown and Woodland, Wikstrom and Norman, and Allee, observing that organizational learning claims “that learning is the process of acquiring knowledge” while KM claims “that each aspect of knowledge has a corresponding learning activity that supports it” (p. 290). McElroy (2003) argues that “second-generation KM [is] a management discipline that focuses on enhancing organizational learning…[and that] KM is an implementation strategy for organizational learning” (p. 19). Mason (2005) also argues that “learning and knowledge have a symbiotic relationship; they depend upon each other” (p. 321).

So what are the implications of this convergence between knowledge and learning for practitioners? Loermans (2002) recommends that “a corporate architecture [be created] to facilitate learning at the organization level and to create knowledge sharing and dissemination mechanisms across the organization” (p. 290). Mason (2005) recommends considering the use of e-learning as important “knowledge scaffolding” and that “much of the infrastructure development that supports e-learning [is] convergent with systems developed to support knowledge management” (p. 321) —for example, enterprise knowledge portals and Learning Content Management Systems (LCMS). Furthermore, while “content may have been king at the peak of the dot-com boom, [we now know] that context will always shape its usage” (Mason, 2005, p. 322)—and learning is where context and meaning are formed. In addition, any KM, OL, and e-learning initiative must be “designed with...[an] understanding of [how to] sustain online culture…[and an] appreciation that “e” also stands for engagement” (Mason, 2005, p. 322). Thus people, cultural, and infrastructure considerations must always come first for the success of any KM, OL, and e-learning initiative.

In closing, practitioners should consider this final piece of advice from Loermans (2002):

If the discipline of KM operates in such a way as to improve an organization’s learning capability, it therefore improves the capacity for the organization to generate new knowledge and thus systematically expand the knowledge base of the organization. For this cycle to operate effectively, organizational learning and knowledge generation need to be fully integrated into every mission critical business process that the organization is involved in. This is more a cultural than a technological challenge. (p. 292) [Therefore], organizations should focus on the total inter-organization learning process (i.e., the creation of new corporate knowledge from the total environment within which the organization operates) and the nurturing of the cultural environment that supports it and ensures its continuing development. (p. 293)

References

Argote, L. (2005/1999). Organizational learning: Creating, retaining, and transferring knowledge. New York: Springer.

Loermans, J. (2002). Synergizing the learning organization and knowledge management. Journal of Knowledge Management, 6(3), 285-294.

Mason, J. (2005). From e-learning to e-knowledge. In M. Rao (Ed.), Knowledge management tools and techniques (pp. 320-328). Burlington, MA: Butterworth-Heinemann.

McElroy, M. (2003). The new knowledge management. Burlington, MA: Butterworht-Heinemann.

Senge, P. M. (1990/2006). The fifth discipline: The art and practice of the learning organization. New York: Doubleday.

- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

March 9, 2008

CLO and CKO Roles

While the roles of a CLO and CKO often have similar elements, there are unique responsibilities that each one holds. The role of a CLO is to “leverage learning through the culture of an organization, the type of knowledge and learning it wants to emphasize, and how technologically focused it is” (Dalkir, 2005, p. 292). The CKO, on the other hand, is responsible for “formulating [a] knowledge management strategy, handling knowledge management operations, influencing change in the organization, and managing knowledge management staff” (Rusonow as cited in Dalkir, 2005, p. 290). This brief will examine the strategic planning role of CLOs and CKOs, compare their roles and responsibilities, and provide a profile of the individuals in these roles at a national nonprofit organization.

Strategic Planning Role of CLOs

The strategic planning role of CLOs revolves around establishing the strategic importance of learning, leveraging learning as a key linkage within the organization, and managing learning as a business. It is critical that CLOs demonstrate the strategic importance of learning in the organization. This can be done through efforts targeted to both the senior leadership team as well as within the learning function. With the senior leadership team, Baldwin & Danielson (2000) encourage CLOs to raise the level of inquiry and work with the senior leadership team to craft the business strategy rather than play a support role of only helping to rollout or implement new business strategies. Jones (2007) encourages CLOs to work with the senior leadership team to help “leaders to take a look at the talent implications of the strategies and initiatives that they have going on” and to integrate “development into conversations about corporate objectives…[plus] show senior line management how learning relates to their strategic goals and teach them their role in the development process” (p. 52). Within the learning function, Phillips (2004) encourages CLOs to develop a strategic plan including determining the mission, vision, values, and strategic objectives for the learning organization plus “identifying stakeholders, audiences, services, and scope of the [learning] function” (p. 50).

The second key strategic planning role of CLOs is leveraging learning as a key linkage within the organization. In fulfilling the strategic role of CLO, Baldwin & Danielson (2000) argue that this position needs to ensure that there is a strong strategic linkage and business case established for all initiatives and to link “directly to the strategic direction of the firm” (p. 12). Phillips (2004) recommends linking learning “to the business issues to ensure that learning requests are not based on faulty assumptions or inadequate analyses” (p. 52). Finally, the third key strategic planning role of CLOs is managing learning as a business. This begins by working with the senior leadership team to set the preferred investment level and strategy that can include any of the following options: “[1] let others do it…[2] invest only the minimum…[3] invest [the same as] the rest…[4] invest until it hurts…[or 5] invest as long as there is a payoff” (Phillips, 2004, p. 50). Once the investment level is set, the CLO needs to “produce tangible value for the investment” in learning through tracking and managing by critical performance measures (Baldwin & Danielson, 2000, p. 13).

Strategic Planning Role of CKOs

Turning now to CKOs, Awaza & Desouza (2004) argue that CKOs are responsible for “[1] institutionalizing knowledge sharing incentives, [2] breaking knowledge bottlenecks in the organization that impede smooth knowledge flows, [and 3] embedding knowledge into the work practices and processes” (p. 343). Bonner recommends that CKOs work to “locate knowledge within a company and find ways to capture, distribute, and create more of it” (p. 37). Furthermore, CKOs are responsible to:

1. Leverage the technical infrastructure to better manager the transfer and flow of explicit knowledge assets.
2. Foster and develop social mechanisms to enable the exchange of tacit know-how, skills, and abilities.
3. Manage the flow of knowledge between an organization and its business partners…
4. …set the direction, structure, and give direction as [to] how to manage the content in [knowledge] repositories, from a logical point of view. (Awaza & Desouza, 2004, p. 341)

Comparison of CLO and CKO Roles and Responsibilities

To compare the responsibilities of the CLO and CKO, Awaza & Desouza (2004) do an excellent job of simplifying the differences by arguing:

CKOs are mainly responsible for leveraging existing knowledge resources in the firm [and] CLOs are mainly responsible for managing the knowledge generating agents of the organization…[by] infusing them with new training and development so that they can create knowledge to be managed. (p. 342)

In other words, the CLO and the learning function should focus on functional skill development and creating capacity to create knowledge while the CKO and knowledge function takes the output of learning and focuses on dissemination, providing access, and promoting an environment and opportunities for knowledge creation and sharing.


References

Awaza, Y. & Desouza, K. (2004). The knowledge chiefs: CKOs, CLOs, and CPOs. European Management Journal, 22(3), 339-344.

Baldwin, T. & Danielson, C. (2000). Building a learning strategy at the top: Interviews with ten of America's CLOs. Business Horizons, 43(6), 5-14.

Bonner, D. (2000). Enter the chief knowledge officer. Training & Development, 54(2), 36-40.

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Elsevier Buttwrworth-Heinemann.

Jones, T. (2007). Raising the stakes: The strategic role of the CLO. Chief Learning Officer, 6(11), 52.

Phillips, J. (2004). The CLO's critical role: Nine areas for action. Chief Learning Officer, 3(12), 50-53.


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

March 21, 2008

Knowledge and Change Management

Knowledge and learning management initiatives have the potential for making a significant impact on organizational culture and how work is conducted. For example, imagine the shift from a knowledge-hoarding culture to one where knowledge is freely shared and employees work cross-functionally to generate new knowledge and innovations. Dalkir (2005) argues that “corporate culture is a key component of ensuring that critical knowledge and information flow within an organization” (p. 185). To operationalize such organizational culture changes, change management is a critical component for the success of any knowledge and/or learning management initiative. And if the knowledge management initiative is one of an organization’s first, the culture changing implications can be very far-reaching. Thus, having a strategy for managing the change becomes critical for successful implementation.

In looking at change management for knowledge initiatives, Schein (as cited in Dalkir, 2005) “uses the classic three-step approach to discuss change: unfreezing, cognitive restructuring, and refreezing” (p. 184). Schein also emphasizes the importance of the role of leadership in facilitating the change. Cameron & Green (2004) further recommend that “leaders of change need to balance their efforts across all three dimensions of an organizational change: [1] outcomes: developing and delivering clear outcomes; [2] interests: mobilizing influence, authority and power; [3] emotions: enabling people and culture to adapt” (p. 5). These dimensions can be very important in a knowledge and learning management initiative since sharing knowledge—and other aspects that go along with many of these initiatives—can be very scary or intimidating to people. As Cavaleri & Seivert (2005) share, “continually improving the quality of your knowledge for action…is not always easy or comfortable. It means a willingness to be a learning-novice when you enter unknown territory, and also a willingness to change beliefs and behavior when you discover they are no longer effective” (p. 78).

Cavaleri & Seivert (2005) also offer the following advice: “During change efforts, including knowledge initiatives, leaders must be careful to safeguard and sustain [the] essential parts of the organization [such as function, identity, values, and essence] while simultaneously letting go of what is not essential to it” (p. 314). By staying true to their essence and those things that make the organization sustainable, organizations can act efficiently and effectively. Without this central focus, it is all too easy to focus on the wrong things—like simply making money, which is not a goal but a desired end-product for many businesses.

Ultimately, by linking to the company’s essence, knowledge and learning management initiatives can become strategic levers for mobilizing cultural changes that can lead to the growth and sustainability of the organization.


References:

Cameron, E. & Green, M. (2004). Making sense of change management. London: Kogan page.

Cavaleri, S. & Seivert, S. (2005). Knowledge leadership: The art and science of the knowledge-based organization. Burlington, MA: Butterworth-Heinemann.

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Butterworth-Heinemann.


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

March 24, 2008

References: Knowledge Creation through Informal Learning and Communities of Practice

Argote, L. (1999/2005). Organizational learning: Creating, retaining, and transferring knowledge. New York: Springer.

Choi, M. (2006). Communities of practice: An alternative learning model for knowledge creation. British Journal of Educational Technology, 37(1), 143-146.

Clarke, N. (2005). Workplace learning environment and its relationship with learning outcomes in healthcare organizations. Humand Resource Development International, 8(2), 185-205.

Cross, J. (2007). Informal learning: Rediscovering the natural pathways that inspire innovation and performance. San Francisco: Pfeiffer.

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Elsevier Butterworth-Heinemann.

De Laat, M. (2006). Networked learning. Unpublished manuscript. University of Utrecht, Utrecht.

Eraut, M. (2000). Non-formal learning, implicit learning and tacit knowledge in professional work. In F. Coffield (Ed.), The learning society: The necessity of informal learning (Vol. 4, pp. 12-30). Bristol, UK: The Policy Press.

Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26(2), 247-273.

Eraut, M., Alderton, J., Cole, G., & Senker, P. (2002). Learning from other people at work. In R. Harrison, F. Reeve, A. Hanson, & J. Clarke (Eds.), Supporting lifelong learning (Vol. 1, pp. 128-145). New York: Routledge.

Kannan, G., Aulbur, W., & Haas, R. (2005). Knowledge management in practice: Making technology work at DaimlerChrysler. In M. Rao (Ed.), Knowledge management tools and techniques, Burlington, MA: Elsevier Butterworth-Heinemann.

Kaplan, R. S. (2001). Strategic performance measurement and management in nonprofit organizations. Nonprofit Management & Leadership, 11(3), 353-370.

Kocakulah, M. C. & Austill, A. D. (2007). Balanced scorecard application in the health care industry: A case study. Journal of Health Care Finance, 34(1), 72-99.

Loermans, J. (2002). Synergizing the learning organization and knowledge management. Journal of Knowledge Management, 6(3), 285-294.

Maki-Komsi, S., Poyry, P. & Ropo, E. (2005). Learning and knowledge building in distributed work environment. The Electronic Journal for Virtual Organizations and Networks, 7, 34-55.

Marsick, V. J. (2006). Informal strategic learning in the workplace. In J. Streumer (Ed.), Work-related learning (pp. 51-69). Dordecht, The Netherlands: Springer.

Marsick, V. J., & Watkins, K. E. (1990). Informal and incidental learning in the workplace. New York: Routledge.

Marsick, V. J., & Watkins, K. E. (1999). Facilitating learning organizations: Making learning count. Brookfield, Vermont: Gower Publishing.

Marsick, V. J., & Watkins, K. E. (2001). Informal and incidental learning. New directions for adult and continuing education, 2001(89), 25-34.

Marsick, V., Watkins, K., Callahan, M. W., Volpe, M. (2006, February). Reviewing theory and research on informal and incidental learning. Paper presented at Academy of Human Resource Development International Conference, Columbus, OH. Retrieved February 23, 2008, from http://eric.ed.gov/ERICDocs

Mason, J. (2005). From e-learning to e-knowledge. In M. Rao (Ed.), Knowledge management tools and techniques (pp. 320-328). Burlington, MA: Butterworth-Heinemann.

McElroy, M. (2003). The new knowledge management. Burlington, MA: Butterworht-Heinemann.

Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. New York: Oxford University Press.

Rao, M. (Ed.). (2005). Knowledge management tools and techniques. Burlington, MA: Elsevier Butterworth-Heinemann.

Senge, P. M. (1990/2006). The fifth discipline: The art and practice of the learning organization. New York: Doubleday.

Skule, S. (2004). Learning conditions at work: A framework to understand and assess informal learning in the workplace. International Journal of Training and Development, 8(1), 8-20.

Snyder, W. (1997). Communities of practice: Combining organizational learning and strategy insights to create a bridge to the 21st century. Retrieved December 15, 2007 from http://www.co-i-l.com/coil/knowledge-garden/cop/cols.shtml

Speckbacher, G. (2003). The economic of performance management in nonprofit organizations. Nonprofit Management & Leadership, 13(3), 267-281.

Spence, P. (2005). Knowledge networking on a national scale: A New Zealand case study. In M. Rao (Ed.), Knowledge management tools and techniques (pp. 206-213). Burlington, MA: Elsevier Butterworth-Heinemann.

Wallace, D. D., & Colbert, E. M. (2001). Adult learning and collaboration in a school culture. Unpublished doctoral dissertation, Teachers College, Columbia University.

Wenger, E. (1990). Toward a theory of cultural transparency: Elements of a social discourse of the visible and the invisible. Unpublished doctoral dissertation, University of California.

Wenger, E. (1991, Fall). Communities of practice: Where learning happens. Benchmark, pp. 82-84.

Wenger, E. (2002). Cultivating communities of practice: A quick start-up guide. Retrieved January 9, 2008 from http://www.entreculturas.pt/Media/start-up_guide_PDF.pdf

Wenger, E. (2004). Knowledge management as a doughnut: Shaping your knowledge strategy through communities of practice. Ivey Business Journal, 68(3), 1-8.

Wenger, E., McDermott, R., & Snyder, W. (2002). Seven principles for cultivating communities of practice. In Cultivating communities of practice: A guide to managing knowledge (chap. 3). Retrieved January 9, 2008 from http://www.askmecorp.com/pdf/7Principles_CoP.pdf

Zboralski, K., Salomo, S., & Gemuendon, H.G. (2006). Organizational benefits of communities of practice: A two-stage information processing model. Cybernetics & Systems, 37(6), 533-552.

Knowledge Creation through Informal Learning and Communities of Practice, part 1

Introduction

Differing views abound on the relationship of learning and knowledge management. Some believe they are unique and separate disciplines, and others see significant synergy between them. This paper will link learning and knowledge management through an exploration of how learning—and informal learning in particular—offers a viable gateway to accessing tacit knowledge. It will also explore how communities of practice (CoPs) can be an effective knowledge management application for realizing the knowledge creation and sharing potential presented by informal learning. The approach taken will be a review and analysis of the literature for informal learning and CoPs, followed by applied research that shows the role of knowledge management in both informal learning and CoPs. A critical analysis of the literature and research follows, leading to a discussion of the implications for practitioners. The paper concludes with a proposed application of these concepts to a large nonprofit organization; included are key survey results from their recent learning organization assessment plus resulting recommendations for implementation (including potential metrics).

To begin, it is important to understand two of the key concepts that will be covered in this paper: informal learning and CoPs.

Informal Learning

Informal learning is often defined as the individually driven lifelong learning that occurs outside training or a classroom. Depending on the study, informal learning comprises 70, 80, or even 90 percent of workplace learning (Cross, 2007, pp. 243-244). Ironically, most organizations focus their investments on only the 10, 20, or 30 percent of formalized training that occurs inside a classroom, in pre-scheduled meetings, or on a computer via e-learning. Marsick and colleagues have studied and published a great deal on the subject over the last 20 years. In addition, Eraut has performed multiple studies on informal learning in the last decade.

Communities of Practice

Beginning with its roots in anthropology, CoPs have been studied by many since Wenger and Lave first introduced the concept in 1991. CoPs can be defined as “a group of people having common identity [and] professional interests and that undertake to share, participate and establish a fellowship” (Pickett as cited in Dalkir, 2005, p. 112). Dalkir (2005) describes CoPs as typically informally-created groups centered around a common focus or goal, whether a profession, work function, problem, topic, or industry; furthermore, members’ commitment is driven by trust and professional behaviors/practices (p. 124) and they typically possess a virtual workspace in which “to store stories, artifacts, tools, discussions, glossaries, [and] historical events” (p. 125).

Next:

We'll explore the literature that underlies informal learning, communities of practice, and knowledge creation.


References:
http://www.blog.klpnow.com/2008/03/references_knowledge_creation.html

- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

March 25, 2008

Part 2: Knowledge Creation through Informal Learning and Communities of Practice

Literature Review

Informal Learning

To further understand informal learning, Marsick & Watkins (1990, p. 12) contrasted informal learning versus formal learning as follows:

Formal learning is typically institutionally sponsored, classroom-based, and highly structured. Informal learning…may occur in institutions, but it is not typically classroom-based or highly structured, and control of learning rests primarily in the hands of the learner…[Furthermore, it] can be deliberately encouraged by an organization or it can take place despite an environment not highly conducive to learning.

Characteristics of informal learning include a learning process that (a) is integrated with daily routines, (b) is prompted by an unexpected internal or external event, (c) is mostly unconscious, random, and influenced by chance, (d) includes opportunities for reflection and action, and (e) links to the learning of others (Marsick & Volpe as cited in Marsick & Watkins, 2001, p. 28).

Marsick & Watkins’ informal learning model.
Marsick & Watkins (1990) developed a model for enhancing informal learning, which they further modified in later work (Cseh, Watkins, & Marsick, as cited in Marsick & Watkins, 2001). View image
In their model, the center circle of Work and outer circle of Context represent Marsick & Watkins’ “belief that learning grows out of everyday encounters while working and living in a given context” (2001, p. 29). Informal learning begins with Triggers, the perception of which are influenced or framed by our previous experiences. The learner then progresses through the remaining phases not necessarily in sequential order, but rather as Marsick & Watkins characterize as “an ebb and flow as people begin to make sense of a situation” (2001, p. 29). The new situation is experienced and the learner applies different strategies to examine the situation and devise potential solutions. Once this portion of the cycle is complete, the learner implements the selected solution. Ideally, the learner continues the cycle by reflecting on the selected course of action to evaluate its consequences and identify lessons learned. The first phases of the informal learning model are where the learner is applying his/her meta-learning skills to the new situation. Reflection and evaluation are key components of the middle portion. Then, in the final portion of Marsick & Watkins’ informal learning model, the process concludes with the identification of lessons learned—and therein lies the greatest potential for capturing newly created knowledge so that it can then be shared with and applied by others.

Additional theorists’ contributions.
Building upon Marsick & Watkins’ work, additional theorists have made noteworthy contributions to the study of informal learning. Eraut (2004) has developed and revised a typology of informal learning modes further breaking down informal learning into implicit learning, reactive learning, and deliberative learning—all of which can occur in the past, present, or future. With Marsick acting as their dissertation sponsor, Wallace & Colbert (2001) focused on implementing the theory of informal learning by identifying the factors most important to learning in daily work situations versus in problem solving situations; these factors included talking, perspective sharing, reflection, and trust. They also developed a set of recommendations for how “to structure an organization to support a community of work-learners and…ways to build collaborative work and learning skills” (2001, p. Abstract). Eraut, Alderton, Cole, & Senker (2002) defined and provided examples of informal learning methods, or what the authors termed ‘organized learning support’ that include mentoring and coaching; rotations, visits, and shadowing; and designated experts. They also provided examples of how work group collaboration and learning from outside one’s workgroup can support informal and lifelong learning. Skule (2004) identified seven learning conditions that affect informal learning at work, creating measurable factors that can be used to quantitatively assess workplace informal learning; these factors included exposure to change and high demands, the extent of one’s professional network, feedback, management support for learning, and rewarding proficiency. Clarke (2005) provided empirical evidence of the effect that different aspects of the learning environment have on informal learning in the workplace such as opportunities for independent on-the-job learning, empowerment, and support for reflection and job challenges.

Communities of Practice

The study of CoPs began with predominantly ethnographic studies, progressed through to qualitative studies, and then more recently has expanded into quantitative studies that are attempting to display a link between CoPs and improvements in organizational performance. Wenger is considered by many to be the seminal theorist on CoPs and has published much on the subject. Through an impressive ethnographic study in his dissertation, Wenger (1990) began his investigation into the characteristics of communities and the people and practices that make up those communities. In 1991, Wenger first published on the subject of CoPs. His article introduced the idea of “learning as a social phenomenon… [where] information only takes meaning in the context of the social practices of the communities that give it cultural life… [Furthermore,] through our membership in their communities…we come to know—and be empowered by what we know” (Wenger, 1991, p. 83). This concept was further reinforced in Wenger’s work that year with Lave where they first identified the CoP concept in their “research toward a ‘social theory of learning’” (Zboralski, Salomo, & Gemuendon, 2006, p. 535).

In 1997, Snyder built on Wenger’s and others’ early work by identifying CoPs as a tool for enhancing organizational learning, building organizational competencies, and improving organizational performance. To support this claim, Snyder (1997) argued that “competencies in the current environment are rarely static, so high-performance [CoPs] engage in continuous learning activities to ensure that competencies are built, shared, and applied effectively” (p. 8-9). Furthermore, CoPs:

“…are aligned with competencies…they both enact competencies…and develop and renew competencies through a variety of learning activities. [They] “also constitute influential organization conditions…that influence communication and coordination… [and] are aligned, therefore, with several of the factors associated with a performance-based model of organizational learning.” (Snyder, 1997, p. 9)

Snyder’s most important contribution in his 1997 article was the introduction of a “set of [33] testable hypotheses about how CoPs influence performance, how they learn competence, and what conditions facilitate competence development” (p. 14). These 33 hypotheses can be used to test the interrelation between CoPs and organizational learning, organizational competence, and organizational performance. In fact, this set of hypotheses for testing the interrelation between CoPs and organizational learning, organizational competence, and organizational performance went on to encourage many research efforts including those by Lesser & Prusak; Dove; Lorenz; Smith & McKeen; Webb, Wunram, Lettice & Klein; Lucas; and more.

In 2002, Snyder and Wenger collaborated (along with McDermott) on the writing of the seminal book Cultivating Communities of Practice: A Guide to Managing Knowledge. In it, they introduced seven design principles for CoPs:
1. Design for evolution
2. Open a dialogue between inside and outside perspectives
3. Invite different levels of participation
4. Develop both public and private community spaces
5. Focus on value
6. Combine familiarity and excitement
7. Create a rhythm for the community
(Wenger, McDermott, & Snyder, 2002, p. 51)

This work also led to the creation of Wenger’s quick start-up guide that succinctly presented the major concepts related to CoPs (Wenger, 2002). View image In 2004, Wenger reinforced his earlier proposition of the social nature of knowledge by arguing that “communities of practice [are] the social fabric of knowledge” (p. 1). He further described the three elements of a community of practice (domain, community, and practice) and defined the role of management sponsorship to “enable communities to thrive and have an impact on the performance of the organization” (Wenger, 2004, p. 7).

Knowledge Creation Model

Providing an application for both informal learning and knowledge management, CoPs can be a very effective mechanism for knowledge creation and conversion. As defined by Nonaka & Takeuchi (1995), knowledge is created through processes by which an individual’s tacit or explicit knowledge is converted through socialization, externalization, combination, or internalization. View image Socialization is the conversion of tacit to tacit knowledge, often involving face-to-face interactions; this is a common method of knowledge conversion seen in informal learning and CoPs. Externalization is the conversion of tacit to explicit knowledge, often involving interviews or other methods to capture another’s expertise; this is a common method of knowledge conversion most often seen in formal learning (particularly in the process of instructional designers working with subject matter experts in the creation of learning programs). Combination is the conversion of explicit to explicit knowledge, often involving the synthesis of existing data, information, or knowledge in a new way; this is another common method of knowledge conversion seen in formal learning programs. Internalization is the conversion of explicit to tacit knowledge, often involving ‘learning by doing’ so that the knowledge or skill becomes deeply internalized and rote; this is a common method of knowledge conversion seen in both informal and formal learning through mentoring and apprenticeships. In CoPs, socialization is the primary knowledge conversion mechanism employed, while the others can play supporting roles. For example, if CoPs are taking steps to capture their knowledge, externalization will be an additional source of knowledge conversion.

Next:

We'll explore the applied research that has been conducted on informal learning and knowledge management, as well as communities of practice and knowledge management.


References:
http://www.blog.klpnow.com/2008/03/references_knowledge_creation.html


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

March 26, 2008

Part 3: Knowledge Creation through Informal Learning and Communities of Practice

Applied Research

Where theoretical works help to define concepts and models, applied research aids in identifying what problems the theory can solve.

Informal Learning and Knowledge Management

Marsick & Watkins.
Beginning with their earliest work, Marsick & Watkins (1990) saw informal learning as a way to access tacit knowledge of which Nonaka & Takeuchi discuss in their knowledge creation model. Marsick & Watkins continued to make this connection in subsequent research, showing how informal learning can help a learning organization tap into its knowledge potential through the use of CoPs, knowledge repositories, goal-based scenarios, and groupware (Marsick & Watkins, 1999; Marsick, 2006).

Eraut.
Eraut strengthened the link between informal learning and tacit knowledge, and identified “several different types of situation[s] in which tacit knowledge may be either acquired or used or simultaneously both acquired and used” (2000, p. 28). Like Marsick (2006), Eraut cited Nonaka & Takeuchi’s (1995) knowledge creation spiral model. In particular, Eraut argued that socialization—the first phase of Nonaka & Takeuchi’s model—is an integral part of the knowledge creation that occurs via informal learning (Eraut, 2000; Eraut et al., 2002). Eraut also defined four practical reasons why an organization would want to make tacit knowledge explicit:
- to improve the quality of a person’s or a team’s performance
- to help to communicate knowledge to another person
- to keep your actions under critical control by linking aspects of performance with more and less desirable outcomes
- to construct artifacts that can assist decision making or reasoning (2000, p. 28)

Eraut (2004) defined work activities that lead to learning via informal learning environments, and emphasized the importance of relationships, social context, and management support and facilitation for successful informal learning in the workplace. In his 2004 research article, Eraut also addressed the role and limitations of tacit knowledge in informal learning. He argues that “tacit knowledge does not arise only from the implicit acquisition of knowledge but also from the implicit processing of knowledge” (Eraut, 2004, p. 253). He also cautions that “tacit knowledge is personal knowledge that may be used uncritically because people either believe it works well for them or lack the time and/or disposition to search for anything better” (Eraut, 2004, p. 253).

Communities of Practice and Knowledge Management

Snyder (1997) referred to the role of early CoP case studies completed by Brown & Gray, Cook & Yanow, Orr, Snyder, and Wenger in demonstrating “that learning occurs most effectively within communities that have developed trust, shared understanding of problems, and a language to communicate new and old solutions” (p. 9). Ever since, CoPs have been identified as an effective knowledge management application in numerous case studies, providing useful examples and best practices for how to design and foster CoPs in organizations. For example, DaimlerChrysler found CoPs “to be an efficient means to achieve business process improvement and manage complexity” by improving the flow and sharing of knowledge throughout the organization (Kannan, Aulbur, & Haas, 2005, p. 138). And New Zealand has used predominantly virtual CoPs as an effective means of encouraging “inter-organizational knowledge networking on a national scale” (Rao, 2005, p. 206; Spence, 2005).

In additional applied research, Choi (2006) examined the potential of CoPs as an alternative learning model for knowledge creation and performance training in corporations; Choi also acknowledged CoPs as a key engine for creating and sharing both tacit and explicit knowledge. Choi (2006) also identified factors that facilitate or encourage CoP activity including “learning motivation and desire for learning, creation of work-related knowledge and sharing of expertise in CoP participation, …trust among members, and the leadership trait of the team leader” (p. 144-145). Later in 2006, Zboralski et al. developed a measurement model to evaluate the CoP constructs of information exchange, networking, network position, knowledge effect, business performance effect, and socialization. Importantly, Zboralski et al. (2006) demonstrated “that CoPs have a close connection and positive direct impact on business performance” (p. 547) by quantitatively proving CoP members with a strong network position due to their involvement in a CoP have a positive effect on the knowledge base, the business performance, and the socialization between staff.

Next:

We'll complete a critical analysis of the literature on informal learning and communities of practice.


References:
http://www.blog.klpnow.com/2008/03/references_knowledge_creation.html


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

March 27, 2008

Part 4: Knowledge Creation through Informal Learning and Communities of Practice

Critical Analysis

Turning to a critical analysis of the theoretical works and applied research, there have been varied contributions to the body of knowledge.

Informal Learning Literature

Marsick and her colleagues have been prolific contributors on the subjects of informal learning, workplace learning, and learning organizations. Their contributions have been well-informed and grounded in the research that came before them, and they have encouraged further research by other scholars (e.g., Wallace & Colbert). Their communication style is clear and complete, displaying scholarly rigor as well as helpful implication considerations for practitioners. For Marsick and colleagues’ research to be even more compelling, it would be helpful to incorporate quantitative research methods in addition to the qualitative research studies they have been performed. Many organizations look to quantitative studies to prove results; this is a challenge that confronts not only Marsick and colleagues, but all those who study learning and knowledge. Marsick, Watkins, Callahan, & Volpe (2006) themselves acknowledge this limitation in the current research and recommend cross-company and industry studies, “research aimed at learning what works to enhance this type of learning,” as well as research to examine “the impact of new distributed working arrangements (including telecommuting, outsourcing, and use of contingency workers) on informal and incidental learning in workplaces” (p. 799).

Communities of Practice Literature

Turning to a critical analysis of the theoretical works and applied research on CoPs, let us focus on Wenger’s contributions from the theoretical perspective and Zboralski et al.’s contributions from an applied research perspective.

Wenger.
Some strong points of Wenger’s work include his solid work to conceptualize CoPs and emphasize the need for them to be very flexible, organic, and evolving in nature. In addition, his writing is approachable and appealing to readers, with many statements possessing good face validity, e.g., “intuitively, everybody knows what knowledge is. When you have it, you are likely to understand situations and do the right thing; when you don’t, you are in trouble” (Wenger, 2004, p. 1). However, his published work (including the materials cited in this paper) focuses more on the practitioner than the scholar; thus Wenger’s materials are sometimes lacking in scholarly rigor. For example, much of his published work is targeted to practitioners and most of his articles and materials were not published in peer-reviewed journals. Despite this, Wenger’s material has become the seminal work on CoPs.

Wenger’s 2004 article was particularly disappointing. While the “doughnut” analogy for his model may make it feel more accessible to practitioners, he may be doing a disservice to the discipline of knowledge management—made all the worse by the fact that he begins the article stating that the field has had to deal with numerous skeptics and detractors. But then he goes on to state, “I will argue that when it comes to knowledge, management is a doughnut…and noting that the center of the doughnut is empty, I will argue that knowledge management is primarily the business of those who actually make the dough—the practitioners” (Wenger, 2004, p. 1). Again, perhaps this is an approachable analogy, but the light-heartedness of its description may make the reader question if knowledge management is a respectable discipline. Then in looking more closely at the writing of this article, the model is not directly linked to the structure of the paper. Ensuring the article’s structure directly followed the model (e.g., with consistent terminology and labeling of sub-sections) and illustrating all the concepts on the model would have greatly improved the quality and coherence of Wenger’s article and model.

Zboralski et al.
In contrast, Zboralski et al.’s (2006) article was particularly impressive for not only its contribution to quantitatively proving a relationship between CoPs and organizational performance, but also in its thorough scholarly approach. The article begins with a thorough literature review, establishing a strong relation between Zboralski et al.’s research and the existing body of knowledge. However, like most research projects in the social sciences, there were some weaker areas. For example, Zboralski et al.’s sampling is somewhat problematic. Within the selected multinational company, there were 220 CoPs that met the researchers’ criteria; yet over a four month timeframe they were only able to get questionnaire responses representing 36 of those CoPs. The researchers claimed that their coverage of “about 31% of all active community members…can be considered a valid representation of the overall population” (Zboralski et al., 2006, p. 542). However, it is not entirely clear by what objective criteria this claim can be made. The questionnaire for their measurement model was pre-tested, resulting in revisions prior to releasing the questionnaire to the sample population. However, the authors did acknowledge that a common method bias could not be ruled out. In addition, the study is somewhat limited in that it was based on one German multinational company with an extensive number of CoPs, and the measures were based on the CoP members’ perception of the CoPs’ effects on organizational performance. Overall, Zboralski et al.’s conclusions were justified by the results; however, they could be strengthened further by replicating the research with other companies plus comparing the results to the perceptions of non-members of CoPs or to objective performance measures that could not be influenced by the participants’ perception.

Next:

We'll discuss the implications of the research on informal learning, communitiies of practice, organizational learning, and knowledge management and how it can be applied.


References:
http://www.blog.klpnow.com/2008/03/references_knowledge_creation.html


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

March 28, 2008

Part 5: Knowledge Creation through Informal Learning and Communities of Practice

Discussion

Informal Learning and Communities of Practice

Despite many organizations’ tendency to focus on formalized training, informal learning should not be overlooked for it represents a significant opportunity to create new knowledge. With the knowledge creation and sharing activities that can occur through informal learning channels, this results in significant untapped potential for taking knowledge from an individual level to a work group and even organizational level. By applying the discipline of knowledge management to informal learning, new learnings can be captured, shared, and applied. Thus through Nonaka and Takeuchi’s concept of socialization, informal learning can become a viable gateway to accessing tacit knowledge—and converting it into something that can benefit entire work groups and organizations.

At the same time, CoPs have long been considered an effective application method for sharing and creating individual and organizational knowledge. Recently, researchers are seeing the synergies between informal learning and CoPs. Marsick (2006) argues that “the emerging field of knowledge creation and management provides a framework for understanding how informal learning might be enhanced without divorcing the phenomenon of learning from the work itself” (p. 57)—and CoPs can be an effective tool for making that happen. Marsick et al. (2006) further argue that “three areas that seem particularly important for understanding informal and incidental learning in today’s workplace are tacit/implicit knowing, whole person learning, and communities of practice” (p. 796). De Laat (2006) also links informal learning, knowledge conversion, and CoPs as follows:

Communities not only provide an open learning space where they develop their knowledge domain and practice. It is also a place where community knowledge is kept alive and learning is situated in the activities, context, and culture of the community. (p. 8)

Maki-Komsi, Poyry, & Ropo (2005) argue that participation in CoPs provides the “fabric of learning” for dispersed communities of workers (p. 38). Further, they caution that in order to create knowledge it is critical for communities to “collaboratively pose questions, and intentionally seek for alternative solutions in order to create new knowledge and expand the community’s capabilities” (Maki-Komsi et al., 2005, p. 38).

Organizational Learning and Knowledge Management

In the past decade, more and more researchers and practitioners have begun to acknowledge the potential synergies and interrelationships between knowledge and learning. This is particularly evident in the convergence of the concepts of the learning organization (LO) and knowledge management (KM). Senge (1990/2006) first introduced the concept of the learning organization as a set of core learning capabilities that enable an organization to innovate (i.e., to create new knowledge) and create sustainable advantage. In 1999, Senge shared that he saw KM addressing “the same critical issues [that the Society of Organizational Learning] members have been struggling with—the sustainable creation, transfer, and dissipation of organizational knowledge” (Karlenzig as cited in McElroy, 2003). In studying the areas of organizational forgetting, organizational memory, and how knowledge transfer is a key to creating organizational learning, Argote (1999/2005) posits that “patterns of knowledge creation, retention, and transfer contribute to differences in the rates at which organizations learn” (p. 203). Loermans (2002) defines the relationship between KM and LO by stating that the LO focuses on the learning process and generating new knowledge while KM “takes the output from the LO, manages it and ensures that an appropriate environment to perpetuate the generation and management of knowledge capital is being properly maintained” (p. 292). Loermans (2002) also cites the research of Brown and Woodland, Wikstrom and Norman, and Allee, observing that organizational learning claims “that learning is the process of acquiring knowledge” while KM claims “that each aspect of knowledge has a corresponding learning activity that supports it” (p. 290). McElroy (2003) argues that “second-generation KM [is] a management discipline that focuses on enhancing organizational learning…[and that] KM is an implementation strategy for organizational learning” (p. 19). Mason (2005) also argues that “learning and knowledge have a symbiotic relationship; they depend upon each other” (p. 321).

Implications for Practitioners

So what are the implications of this convergence of the theoretical concepts of informal learning, CoPs, organization learning, and knowledge management for practitioners? Loermans (2002) recommends that “a corporate architecture [be created] to facilitate learning at the organization level and to create knowledge sharing and dissemination mechanisms across the organization” (p. 290). Maki-Komsi et al. (2005) recommend the use of CoPs for geographically dispersed workforces:

Communities of practice, even virtual ones, support the individual professionals in their work by providing not only information and knowledge but also support and a feeling of community with remote peers. Informal learning and information exchange occurs within these communities, and they form a structure supporting everyday work. (p. 52)

Mason (2005) recommends considering the use of e-learning as important “knowledge scaffolding” and that “much of the infrastructure development that supports e-learning [is] convergent with systems developed to support knowledge management” (p. 321) —for example, enterprise knowledge portals and Learning Content Management Systems (LCMS). Furthermore, while “content may have been king at the peak of the dot-com boom, [we now know] that context will always shape its usage” (Mason, 2005, p. 322)—and learning is where context and meaning are formed. In addition, any knowledge and learning initiative must be “designed with...[an] understanding of [how to] sustain online culture...[and an] appreciation that “e” [in e-learning] also stands for engagement” (Mason, 2005, p. 322). Thus people, cultural, and infrastructure considerations must always come first for the success of any knowledge and learning initiative. Additionally, practitioners should consider this final piece of advice from Loermans (2002):

If the discipline of KM operates in such a way as to improve an organization’s learning capability, it therefore improves the capacity for the organization to generate new knowledge and thus systematically expand the knowledge base of the organization. For this cycle to operate effectively, organizational learning and knowledge generation need to be fully integrated into every mission critical business process that the organization is involved in. This is more a cultural than a technological challenge. (p. 292) [Therefore], organizations should focus on the total inter-organization learning process (i.e., the creation of new corporate knowledge from the total environment within which the organization operates) and the nurturing of the cultural environment that supports it and ensures its continuing development. (p. 293)


References:
http://www.blog.klpnow.com/2008/03/references_knowledge_creation.html


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

April 18, 2008

MetaKnowledge and MetaData

Dalkir (2005) defines metadata as “information about physical structures, data types, access methods, and actual content” (p. 169). Taylor (2003) defines metadata as “structured data which describes the characteristics of a resource. It shares many similar characteristics to the cataloguing that takes place in libraries, museums, and archives. The term "meta" derives from the Greek word denoting a nature of a higher order or more fundamental kind. A metadata record consists of a number of pre-defined elements representing specific attributes of a resource, and each element can have one or more values.” Following is an interesting link that provides additional information and examples of metadata: http://www.library.uq.edu.au/iad/ctmeta4.html

On the subject of meta-knowledge, Abrams (2000) offers some interesting insights and links meta-knowledge to tacit knowledge in his presentation on knowledge mapping. In describing the meta-knowledge of experienced workers, Abrams (2000) argues that it is the “Old-Hands’ meta-knowledge of knowledge that novices need: document, application, methodology, expert, etc.” (p. 37). This includes such things as description of the content, qualification of the author/expert, authentication, location of knowledge, intended purpose, usefulness, usability, deployment, availability, leverage, interpretation, and potential knowledge gaps (Abrams, 2000, pp. 37-39). In contrast, when describing the tacit knowledge of novices, Abrams (2000) points to the challenges they face and the “meta-knowledge [novices possess] of strengths and weakness of knowledge infrastructure [including]:
- Ways that do or don’t work to get an expert to help.
- Who to talk to find out who knows or where to find the answer.
- Who sits at the intersection of many different communities and personal networks with visibility and access
- Who has organized their metaknowledge and can transmit it without actually having to be reached “face to face” on the phone.
- The limitations of knowledge retrieval systems under urgency.
- Workarounds for knowledge retrieval system limitations.
- When and why training does or doesn’t work. (p. 41)

Some tools and organizations for knowledge mapping include:
- MindManager (http://www.mindjet.com/)
- IHMC (http://cmap.ihmc.us/)
- knetmap (http://www.knetmap.com/)


References:

Abrams, K. (2000, May). Knowledge mapping quick start. Paper presented at 2000 APQC Annual Conference. Retrieved April 15, 2008, from http://www.apqc.org/portal/apqc/ksn?paf_gear_id=contentgearhome&paf_dm=full&pageselect=detail&docid=110657

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Elsevier Butterworth-Heinemann.

Taylor, C. (2003). An introduction to metadata. Retrieved April 15, 2008 from http://www.library.uq.edu.au/iad/ctmeta4.html


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com


April 22, 2008

Games and Simulations in Knowledge Management

Games and simulations have been associated with learning for many years, both in academic as well as workplace settings. In looking at the use of games and simulations in knowledge management, a search revealed the following applications:
- Participating in a simulated organization to practice valuing and managing intangible assets (including knowledge) (Bontis & Girardi, 2000).
- Investigating “how co-ordination in…knowledge networks could be improved with the help of information and communication technologies (ICTs)” (Van Laere, De Vreede, G, & Sol, 2006, p. 558).
- Investigating “the effect of knowledge distribution and group structure on [a group’s] performance” (Rulke & Galaskiewicz, 2000, p. 612).

According to Bontis & Garardi (2000), two of the benefits realized from these simulations and games include being able to “rehearse novel approaches to management in a low risk learning environment” (p. 548) and to create mindset changes that improve receptivity to the importance and value of knowledge/intellectual capital in organizations.

According to Van Laere, De Vreede, G, & Sol (2006), games and simulations can help model and diagnose issues in knowledge sharing, uncovering the “qualitative issues in co-ordination [that] can help to improve our understanding of co-ordination and guide interventions in [improved] co-ordination” (p. 568).

According to Rulke & Galaskiewicz (2000), games and simulations can be used to demonstrate how knowledge distribution affects a group’s performance. In their study, Rulke & Galaskiewicz were able to demonstrate that “in general, groups that had broadly distributed knowledge, i.e., groups made up of members who had general knowledge, outperformed groups that had knowledge concentrated in different members, i.e., groups made up of members who had specialized or both specialized and general knowledge. However, the advantage that the former enjoyed over the latter disappeared when groups of specialists or mixed groups had decentralized network structures” (Abstract).

These three examples show how games and simulations can be used to facilitate experiential learning and produce empirical evidence of the value and impact of effective application of KM concepts.

References:

Bontis, N., & Girardi, J. (2000). Teachihng knowledge management and intellectual capital lessons: An empirical examination of the Tango simulation. International Journal of Technology Management, 20(5-8), 545-555.

Rulke, D. L., & Galaskiewicz, J. (2000). Distribution of knowledge, group network structure, and group performance. Management Science, 46(5), 612-625.

Van Laere, J., De Vreede, G, J., & Sol, H. G. (2006). A social simulation-game to explore future co-ordination in knowledge networks at the Amsterdam Police Force. Production Planning & Control, 17(6), 558-568.


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

May 3, 2008

KM Enablers

The four key enablers of knowledge management include infrastructure, culture, measures, and technology. Culture relates to organizational norms. Infrastructure relates to the “roles, organizational structures, and skills from which individual [KM] projects can benefit” (Davenport & Prusak, 1998, p. 155). Measures relate to being able to provide proof of the benefit of a knowledge management initiative. (This can include qualitative evidence gathered from success stories, as well as quantitative evidence such as an increase in an organizations’ intellectual capital in the form of patents, process, plans, new products, etc.) In addition, technology relates to the enabling platform upon which many KM initiatives are built.

In a comparison of different authors’ critical success factors for knowledge management, technology infrastructure and willingness to share are the top two items listed (Alazmi & Zairi, 2003). This underlines the importance of two of the four KM enablers: culture and technology.

Culture relates to such knowledge enabling (or inhibiting) factors as willingness to share, support for learning from mistakes, encouragement to share knowledge, allowing time for reflection, and recognition for new knowledge created (Davenport & Prusak, 1998; Kline & Saunders, 1993). McDermott (1999) argues that “the difficulty in most knowledge management effort lies in changing organizational culture and people's work habits. It lies in getting people to take the time to articulate and share the really good stuff. If a group of people don't already share knowledge, don't already have plenty of contact, don't already understand what insights and information will be useful to each other, information technology is not likely to create it" (p. 104).

In considering technology’s role in KM, Davenport & Prusak (1998) argue that “technology’s most valuable role in knowledge management is extending the reach and enhancing the speed of knowledge transfer” (p. 125). At the same time, they warn to not place too much emphasis on technology, citing “an excessive focus on technology [as] the most common pitfall in knowledge management” (p. 173). This sentiment is echoed by Fahey & Prusak (1998) who caution, “although IT is a wonderful facilitator of data and information transmission and distribution, it can never substitute for the rich interactivity, communication, and learning that is inherent in dialogue. Knowledge is primarily a function and consequence of the meeting and interaction of minds. Human intervention remains the only source of knowledge generation" (p. 273).


References:

Alazmi, M., & Zairi, M. (2003). Knowledge management critical success factors. Total Quality Management, 14(2), 199-204.

Davenport, T., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston: Harvard Business School Press.

Fahey, L. & Prusak, L. (1998). The eleven deadliest sins of knowledge management. California Management Review, 40(3), 265-276.

Kline, P. & Saunders, B. (1993). Ten steps to a learning organization (2nd ed.). Salt Lake City, UT: Great River Books.

McDermott, R. (1999). Why information technology inspired but cannot deliver knowledge management. California Management Review, 41(4), 103-117.


- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com

May 6, 2008

Personal Information Filtering

Dalkir (2005) defines information filtering as the process by which one can “go through an enormous amount of information to find the small portion that is relevant to us” (p. 238). With the vast amount of information we all have access to today, it becomes imperative to develop our own personal information filtering process. For me personally, I use different approaches information filtering processes—one for work and one for school.

For work, I rely upon consistent electronic file structures to enable easy retrieval of information. This structure is used for files as well as for email (including the use of rules to file emails automatically into the correct folders). I also use color coding of my calendar and any physical file folders to more easily differentiate between clients and projects.

For school, I rely upon EBSCO alerts and an AskSam database that I started in my second quarter at Walden (Seaside software, n.d.). To stay abreast of new articles related to my research focus, I’ve set up a number of EBSCO alerts that are automatically emailed to me; I also have them set up in a Firefox page via RSS feeds so that I can quickly preview the articles as they arrive. For my research database, I’ve applied a number of the concepts from this program. I first spent time defining the taxonomy and structure for my database; this involved defining the key categories and search terms I anticipated using when needing to retrieve information from my research. With key words and categories defined, I then began to enter all my journal articles, class notes, and assignments. The most critical thing I’ve learned is to stay disciplined with this entry process, e.g., using the week between quarters to update my database based on the previous quarter. Now finishing my sixth quarter, I’m already finding my database to be an incredibly useful tool for quickly locating the article or reference I may recall based on just a portion of the title or a quote. It has also been very useful in supporting my further research and writing when I need to search the over 400 entries in my database to see how many related hits I have on a particular topic.


References:

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Butterworth-Heinemann.

Seaside software. (n.d.). askSam. Retrieved May 6, 2008 from http://www.asksam.com/brochure.asp

- Robin

Copyright Robin Donnan 2008. All Rights Reserved.
http://www.perfassocinc.com


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