Knowledge Management (KM) is a concept that has evolved significantly since its inception. While Tom Davenport’s early definition – “the process of capturing, distributing, and effectively using knowledge” – remains a concise summary, understanding KM requires exploring its origins, goals, and operational components. This guide offers a detailed explanation of what knowledge management encompasses in the modern business environment.
The Genesis of Knowledge Management
Knowledge Management emerged from the management consulting world. As the internet gained traction, consulting firms realized the potential of intranets to facilitate information sharing across geographically dispersed teams. They developed tools and techniques, such as dashboards and expertise locators, and recognized that they had developed a new service they could offer to other organizations. This service was named Knowledge Management. The term is believed to have first been used at McKinsey in 1987, and it gained wider recognition at a conference organized by Ernst and Young in 1993.
The consulting organizations then spread these concepts and methods to different sectors, professional groups, and academic fields. This came at a great time because the intellectual capital excitement of the 1980s had already prepared the way for people to understand that information and knowledge are very important resources for any organization.
Objectives of Knowledge Management
What does KM aim to achieve within an organization? Several key objectives define its purpose:
Fostering Enhanced Communication
KM seeks to cultivate an environment mirroring successful Research and Development (R&D) settings – one characterized by robust, in-depth, and transparent communication and information accessibility. In today’s information age, knowledge workers are the cornerstone of innovation. Research domains, particularly the pharmaceutical industry, have demonstrated that open communication, both internally and externally, is a key element for research success. KM aims to replicate these conditions for all knowledge workers.
Cultivating Situational Awareness
Situational awareness, recently emphasized in KM, enables an organization to make informed decisions. While the term gained prominence in military contexts, its importance translates to business. KM tools and processes aim to provide organizations with the awareness they need to make strategic decisions effectively.
Formal Definitions of Knowledge Management
The Gartner Group offered this definition, which has since become the most quoted:
“Knowledge management is a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise’s information assets. These assets may include databases, documents, policies, procedures, and previously un-captured expertise and experience in individual workers.”
However, KM has broadened beyond just internal assets to include relevant information from external sources.
Mapping Knowledge Management
IBM developed a visual representation for its KM consultants, distinguishing between “collecting stuff” (content) and “connecting people.” This framework categorizes activities into directed information search, serendipitous browsing, and their corresponding methods for connecting people.
| Graphic Map of KM | COLLECTING (STUFF) & CODIFICATION | CONNECTING (PEOPLE) & PERSONALIZATION |
|---|---|---|
| DIRECTEDINFORMATION & KNOWLEDGE SEARCH EXPLOIT | – Databases, external & internal – Content Architecture – Information Service Support (training required) – data mining best practices / lessons learned/after action analysis (HARVEST) | – community & learning – directories, “yellow pages” (expertise locators) – findings & facilitating tools, groupware – response teams (HARNESS) |
| SERENDIPITY &BROWSING EXPLORE | – Cultural support – current awareness profiles and databases – selection of items for alerting purposes / push – data mining best practices (HUNTING) | – Cultural support – spaces – libraries & lounges (literal & virtual), cultural support, groupware – travel & meeting attendance (HYPOTHESIZE) |
| From: Tom Short, Senior consultant, Knowledge Management, IBM Global Services (Note however the comments below under “Tacit.”) |
Key Components of a Knowledge Management System
What elements constitute a functional KM system? Examining the operational components provides clarity:
(1) Content Management
Content Management is a crucial aspect of KM, involving the organization of data and information and making it accessible through dashboards, portals, and content management systems. Enterprise Content Management encompasses making organizational data available online, coupled with the ability to search internal and external sources. This overlaps with the concept of Enterprise Search. For a visual snapshot of the content management domain, Real Story Group’s Content Technology Vendor Map provides a valuable resource.
(2) Expertise Location
Expertise location systems identify individuals within an organization with specific knowledge. These systems, also known as “expertise locators,” help connect people with the right knowledge. Data for these systems comes from employee resumes, self-identification of expertise, and algorithmic analysis of electronic communications. These systems often rank expertise levels and balance requests to avoid overloading specific experts, allowing requestors to prioritize their requests based on their importance.
(3) Lessons Learned
Lessons learned databases capture operationally obtained knowledge, often “how to do it” knowledge, that would not otherwise be documented. This practice aims to make explicit the knowledge embedded in personal expertise. The military has embraced this concept through “After Action Reports.” To ensure the knowledge is captured and disseminated, an individual (typically in KM) is assigned to conduct the debriefing and create the report.
The most common cause of KM failure is the project team being disbanded before any after-action report assembled. An example of a “lesson learned” is the new pediatric medicine, and the discovery of the efficacy of adding orange juice to the recipe. This raises the issue that KM is much more than content management. It extends to how one structures the organizational culture to facilitate and encourage knowledge sharing, and that extends to how one structures the organization’s compensation scheme.
Implementing a lessons learned system requires careful planning, including determining who vets submissions, how long items remain in the system, and how outdated items are handled.
(4) Communities of Practice (CoPs)
Communities of Practice connect individuals with shared interests to share stories, discuss problems, and exchange best practices. These groups emphasize the social nature of learning, particularly in geographically distributed organizations. The World Bank’s CoPs, encouraged by James Wolfensohn, serve as a notable example. One CoP focused on road construction and maintenance in arid conditions, involving experts from diverse organizations.
Effective CoP management requires filling key roles like manager, moderator, and thought leader. Crucial considerations include:
- Defining roles and responsibilities.
- Determining the process for managing the CoP.
- Establishing a mechanism for member recruitment and evaluation of the CoP’s continued relevance.
- Reviewing CoP activity and maintaining its vitality.
- Establishing rules for posting, editing, and archiving content.
- Coordinating CoP files with the enterprise search/taxonomy function.
Stages of Knowledge Management Development
KM has evolved through distinct stages:
First Stage: Information Technology
The initial stage focused on leveraging IT to use information and knowledge more effectively. The Internet provided the tool. The hallmark phrase of Stage 1 was first “best practices,” later replaced by the more politic “lessons learned.”
Second Stage: HR and Corporate Culture
This stage recognized that technology alone was insufficient. It required incorporating human and cultural elements. KM implementation necessitates changes in corporate culture, particularly in how it rewards knowledge sharing. Easy-to-use systems and user-friendly interfaces are critical.
This second stage incorporated Senge’s work on the learning organization and Nonaka’s research on tacit knowledge. The hallmark phrase of Stage 2 was “communities of practice,” CoPs.
Third Stage: Taxonomy and Content Management
The third stage emphasizes the importance of content retrievability through effective organization, description, and syndetic structure. “It’s no good if they try to use it but can’t find it” – this is an excellent explanation of this stage. The hallmark phrases are content management (or enterprise content management) and taxonomies.
The third stage continues today and is expanding. A major theme now is “data analytics” and “machine learning” for “enterprise search.”
One More Definition/Description
The late 20th and early 21st centuries witnessed a series of related topics and enthusiasms:
- Minimization of Unallocated Cost
- I.T. and Productivity
- Data Driven System Design
- Decision Analysis
- Information Systems Stage Hypotheses
- Managing the Archipelago (of Information Services)
- I.T. as Competitive Advantage
- Management Information Systems (MIS) to Decision Support Systems (DSS)
- Enterprise-Wide Information Analysis
- Information Resource Management
- I.T. and Organizational Structure
- Total Quality Management (TQM) and Benchmarking
- Competitive Intelligence (CI)
- I.T. and the Shift from Hierarchies to Markets
- Business Process Re-Engineering
- Core Competencies
- Data Warehousing and Data Mining (more recently known as Big Data)
- E-Business
- Intellectual Capital
- Knowledge Management
- Enterprise Resource Planning (ERP)
- Customer Relationship Management (CRM)
- Supply Chain Management (SCM)
- Enterprise Content Management (ECM)
One can look at KM as the recognition of that forest of trees and a much better and more recognized name than “information driven management.”
Additional Considerations in Knowledge Management
Tacit Knowledge
“Tacit knowledge” refers to knowledge that is not explicitly captured. It can be implicit, which could have been made explicit, but has not been. It can also be truly tacit, knowledge that only resides in someone’s head. It is important to identify and make explicit information that should be made explicit.
Knowledge Retention and Retirees
Retaining knowledge from retirees is an ongoing concern. KM techniques, like lessons learned, are helpful. However, it may be more valuable to keep retirees engaged in CoPs and accessible through expertise locator systems. The interaction of retirees with current employees can generate new knowledge.
The Scope of KM
KM’s scope now extends beyond organizational knowledge to include external knowledge from vendors, suppliers, and the scientific community. KM extends into environmental scanning and competitive intelligence.
Is Knowledge Management Here to Stay?
Evidence suggests KM is not a fleeting trend. Unlike other business enthusiasms that peak and decline rapidly, KM has shown sustained growth in the business literature.
| Quality Circles, 1977-1986 – Source: Abrahamson ,1996 |
| — |
| Total Quality Management, 1990-2001 – Source: Ponzi & Koenig, 2002 |
| — |
| Business Process Reengineering, 1990-2001 – Source: Ponzi & Koenig, 2002 |
The charts show an order of magnitude more literature regarding KM:
| A articles in the business literature with the phrase “Knowledge Management” in the title. |
| KM Growth 2001-2011 |
In conclusion, Knowledge Management is an enduring discipline.
References
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Davenport, Thomas H. (1994), Saving IT’s Soul: Human Centered Information Management. Harvard Business Review, March-April, 72 (2)pp. 119-131. Duhon, Bryant (1998), It’s All in our Heads. Inform, September, 12 (8).
Durham, Mary. (2004). Three Critical Roles for Knowledge Management Workspaces. In M.E.D. Koenig & T. K. Srikantaiah (Eds.), Knowledge Management: Lessons Learned: What Works and What Doesn’t. (pp. 23-36). Medford NJ: Information Today, for The American Society for Information Science and Technology.
Koenig, M.E.D. (1990) Information Services and Downstream Productivity. In Martha E. Williams (Ed.), Annual Review of Information Science and Technology: Volume 25, (pp. 55-56). New York, NY: Elsevier Science Publishers for the American Society for Information Science.
Koenig, M.E.D. (1992). The Information Environment and the Productivity of Research. In H. Collier (Ed.), Recent Advances in Chemical Information, (pp. 133-143). London: Royal Society of Chemistry. Mazzie, Mark. (2003). Personal Communication.
Koenig, M, E. D. (2000), The Evolution of Knowledge Management, in T. K. Srikantaiah and M. E. D. Koenig, Knowledge Management for the Information Professional. (pp. 23-26), Medford N.J., Information Today, for the American Society for Information Science.
McInerney, Claire, and Koenig, Michael E. D., (2011), Knowledge Management (KM) Processes in Organizations: Theoretical Foundations and Practice, Morgan and Claypool.
Nonaka, I. & Takeuchi, H. (1995). The knowledge creating company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press.
Ponzi, Leonard., & Koenig, M.E.D. (2002). Knowledge Management: Another Management Fad?” Information Research, 8(1). Retrieved from http://informationr.net/ir/8-1/paper145.html
Ponzi, L., & Koenig, M.E.D. (2002). Knowledge Management: Another Management Fad?”, Information Research, 8(1). Retrieved from http://informationr.net/ir/8-1/paper145.html
Prusak, Larry. (1999). Where did Knowledge Management Come From?. Knowledge Directions, 1(1), 90-96. Prusak, Larry. (2004). Personal Communication.
Senge, Peter M.. (1990). The Fifth Discipline: The Art & Practice of the Learning Organization. New York, NY: Doubleday Currency.
Wenger, Etienne C. (1998). Communities of practice: Learning, meaning and identity. Cambridge: Cambridge University Press.
Wenger, Etienne C. & Snyder, W. M. (1999). Communities of practice: The organizational frontier. Harvard Business Review, 78(1), 139-145.
