2003 Rubenstein_Installing and Managing Workable Knowledge Management Systems

Briefing Document: Installing and Managing Workable Knowledge Management Systems

I. Introduction to Knowledge Management (KM) Systems

A. Core Purpose and Focus: The book emphasizes that the primary focus of KM systems, beyond technical aspects, lies in non-technical factors such as "individual perceptions, abilities, needs, and behavior, as well as group and organizational processes and constraints." (p. 2). The overarching goal of a workable KM system is to "cost-effectively identify, store, transform as needed, and help the user(s) retrieve and use accrued knowledge, including intellectual nuggets, to help achieve organizational objectives." (p. 3).

B. Defining Key Terms:

• Knowledge Management (KM): "the management of intellectual capital (IC) in the interests of the enterprise." (p. 2)
• Intellectual Capital (IC): "includes knowledge, lessons learned, and other information held for use over time and in other places in the organization." (p. 2)
• Intellectual Nuggets (Nuggets): "some of the units that carry the knowledge, lessons learned, etc." (p. 2). The most valuable structure is an "If X...then Y" format, often implying causal statements or strong correlations between actions and outcomes. (p. 2)
• Supernuggets: "items tied specifically to expressed or implied needs of the organization." (p. 2), representing high-impact knowledge.

C. Expectations and Current Limitations: Organizations have diverse expectations from KM systems, ranging from modest document storage and retrieval to providing "wide-ranging 'Intelligent Assistance'." (p. 3). Many KM systems still operate on a "push" basis, delivering voluminous information that users don't want. Users desire "direct answers to their questions" rather than lengthy reports or citations. (p. 3). The current capability to "pull" useful information is still limited.

D. Book's Comparative Advantages: The authors highlight their book's unique contributions:

1. Elaborated concept of "knowledge or intellectual 'nugget'" in operational detail.
2. Strong emphasis on metrics for designing, monitoring, and assessing KM systems.
3. Focus on organizational and behavioral factors influencing success, particularly user needs and behavior, and organizational barriers/facilitators.
4. Emphasis on user-KM system interfaces as critical to success, tailored to user needs and information-seeking styles.
5. Leveraging four decades of basic and applied research and consulting on user needs and behavior in implementing information and KM systems.
6. Providing guidelines and methodologies for starting and implementing KM systems from an organizational and individual objective viewpoint.
7. Breadth and depth of treatment for critical topics like needs, critical success factors, metrics, design variables, key players, and special cases.
8. Focus on "how to do it" via tested "organizational design" methodology and process flow models. (p. 4-5)

II. The KM Process Flow Model

The book introduces a "Process Flow Model" (Figure 1.1) to conceptualize the KM process, emphasizing the "nugget" as a primary carrier of knowledge.

A. Entities in the Model:

1. Events/Situations: Present sources of intellectual capital (nuggets) or give rise to the need for them (e.g., end-of-project reviews, problem identification).
2. Sub-processes: Critical operations on potential nuggets.
3. Databases: Contain nuggets at different stages of development and use.

B. Key Sub-processes (Figure 1.1):

• Debriefing/Downloading: The initial step where potentially useful knowledge is made available, culminating in a flow of potential nuggets to the "raw nugget pool." (p. 7) This involves collecting experiences from individuals or projects.
• Nugget Extraction: Refining, combining, verifying, tagging, and associating raw nuggets with likely applications. Efficiency and effectiveness are crucial to prevent "garbage" from entering the "Ready Pool." (p. 7-8)
• Probe Process: Driven by potential users' needs, triggering near-term or longer-term searches for applicable nuggets. (p. 8)
• Screening Process: The user (or surrogates) examines candidate nuggets to determine if they fulfill a need and meet surrounding conditions. (p. 8)

C. Downstream Impacts and Outcomes (Figure 1.2): The process extends beyond identifying and retrieving nuggets:

• Application: Found nuggets are applied to resolve problems or seize opportunities through decisions, actions, or policies. (p. 8)
• Direct/Immediate Impact: Application affects an organizational process or situation, measured by intermediate indicators. (p. 9)
• Indirect/Longer-Term Impact: Direct impacts, influenced by environmental parameters, affect overall organizational performance measures (e.g., profits, growth, market share). (p. 9)

III. Why KM Works (or Fails)

The success or failure of KM systems depends on a complex interplay of organizational, human, and inherent system factors.

A. Organizational Factors:

• Ownership: Where the KM system resides in the organizational structure can lead to resentment or lack of influence. (p. 29-30)
• Processes: Lack of clear, cohesive processes to integrate KM with existing workflows can make it a "stand-alone entity." (p. 30)
• Economics/Funding: "A poorly designed, poorly funded, and inadequately introduced and maintained KM system is doomed from the start." (p. 30)
• Cultural Integration: Overcoming cultural barriers is crucial for successful integration. (p. 30)

B. Human Factors:

• Reluctance to Cooperate: Workers may disregard, fear, or be unwilling to deposit knowledge, seeing it as "giving away their power, skills, and the ability to survive in the turbulent corporate climate." (p. 30-31)
• Resistance to Change: KM systems can be perceived as intrusive, generating strong resistance. (p. 31)
• Lack of Participation/Understanding: Implementing KM without user participation or understanding of its purpose and benefits can lead to failure. (p. 31) Efforts like CNA's CEO email explaining the system demonstrate proactive human factor management. (p. 31)

C. Factors Inherent in KM Systems:

• Insufficient Interactivity/Sophistication: Systems may not be engaging enough to attract knowledge. (p. 31)
• Taxonomy/Relevance: Different taxonomies can lead to irrelevant, unattractive, or difficult-to-digest extractions. (p. 31) For instance, Sun Microsystems had to train its sales force to interpret data from "SUNTAN." (p. 31)
• Scope: Technological sophistication may be less critical for focused systems, but corporate-wide systems may struggle with insular knowledge treatment. (p. 31-32)

D. Strategies That Do Not Work (as identified by Milkana Stefanova):

• "Shooting blind" (no specific goals).
• "One size fits all" (generic systems).
• "Notify once and forget it" (lack of continuous education).
• "Let the solution speak for itself" (lack of promotion).
• "Take it and like it" (lack of workforce involvement). (p. 32)

E. Why KM Has Worked (Success Factors):

• Focus: Successful KM systems are "focused on selected processes" (p. 32), like CNA's real-time reports or Integra's documented knowledge integration.
• Explicit Knowledge: Concentration on "documentation, files, databases, and similar explicit manifestations of organizational knowledge" rather than tacit knowledge initially. (p. 32-33)
• Link to Existing Problems: Addressing a "recognized problem or set of problems in the organization" (p. 33), as seen with Procter & Gamble facilitating R&D and marketing communication.
• Ease of Use: Systems that are "applied and used with relative ease" (p. 33) foster cooperation.
• Integration with Organizational Framework: Fostering cooperation among people and units. (p. 33)
• Continuous "Selling": The need for ongoing promotion and adaptation, understanding that "it's a change in the way we operate and behave in an enterprise." (p. 106)

IV. How to Start and Implement a KM System

A. Initial Steps and Principles:

• Good Start is Crucial: Reduces negative fallout and costs of re-starting. (p. 37)
• Fast Track: Important projects should be on a fast track to maintain interest. (p. 37)
• Simplicity and Modularity: Start simple, building in a modular fashion. (p. 37-38)
• Experimental Approach: Record and disseminate "design lessons learned." (p. 38)
• Top-Level Kick-Off: Initial sponsorship or championship from top management is a "critical success factor." (p. 38)

B. The Design and Rollout Team:

• Overlap in Skills: Conceptual design and implementation teams should have significant overlap. (p. 38)
• Internal Talent: The team should consist of internal members "familiar with its culture and history of information transfer and communication." (p. 38) Avoid relying on new outside groups or solely on IT departments, who "tend to think technology first or exclusively." (p. 39)
• Grass-Roots Effort: Manned by respected individuals, provided with incentives. (p. 39)
• Build on Existing Systems: Avoid a "greenfields" or "blank page" approach; adapt and integrate existing components. (p. 39-40)
• Team Size: Small enough for quick decisions (3-6 people), but diverse enough to avoid parochial views. Must be a full-time task force. (p. 40)

C. Keeping it Simple (Fast Prototyping):

• Technology Last: Focus on "what they want, why they want it, and how to proceed in terms of content and user needs" before acquiring sophisticated technology. (p. 40)
• Tailoring: The system's size and shape should depend on organizational factors (size, decentralization, geographic spread, diversity, culture, time constraints). (p. 41)
• Limited Scope for Initial Design: Start with a "quick prototype exercise without all the bells and whistles" (p. 41) in a small, select group to test basic concepts, such as organizational culture's acceptance of sharing, availability of nuggets, key player participation, and ability to evaluate value.
• Personal/Face-to-Face Component: Maintain this for verifiability, trust-building, clarification, elaboration, and assurance of nugget quality. (p. 42)
• Use Primitive Tools: Don't hesitate to use simple tools for initial trials (e.g., 3x5 cards) to demonstrate key elements. (p. 42-43)

D. Suggested Development Program (New or Redeveloped KM System):

1. Identify Information/Knowledge Needs and Styles of Key Individuals and Groups: Use methodologies for user-centric design. (p. 43)
2. Examine Current KM Version (if any): Review processes, tools, and identify subtle flaws. (p. 43)
3. Develop Metrics: For assessing "sharing" culture and the KM system's impact (direct, intermediate, ultimate). (p. 43-44)
4. Design and Test Nugget Extraction/Refinement: Crucial for accessible, credible, and useful nuggets. (p. 44)
5. Design and Test Monitoring/Assessment Procedures: Ongoing and periodic evaluations of usage and effectiveness. (p. 44)

E. Methodologies for User-Centric Design:

• Personal Communication Charting and Communication Flow Matrix
• Individual Information-Seeking Propensity Profile
• Critical Incident Method
• Black Hole Analysis
• Gatekeeper Analysis
• Knowledge Transfer and Application Mapping
• Individual and Group Risk-Taking Propensities
• Blame-Placing Behavior
• Bureaucratic Analysis and the Role of Organizational Politics
• Indicators for Statistically Out-of-Control Behaviors (p. 44-46)

F. Field Experiments (Quasi-Experiments): Mini-field experiments can provide quick, credible information on KM system impact, testing "If...then" design propositions. (p. 46-47)

V. Measuring Costs and Benefits of a KM System

Measurement is crucial for informed managerial decisions and to establish effectiveness.

A. Why Measure: To understand what is happening, how the system contributes to objectives, and to compare costs against benefits for better management. (p. 51)

B. What to Measure:

• Total Costs: Include direct costs, infrastructure, training, and internal promotion. (p. 52)
• Benefits and Impacts: Often dispersed and difficult to isolate. (p. 52)

C. Levels of Metrics:

• Individual User Level: Assess the "cost/benefit ratio" from the user's perspective, influenced by their perceived need and effort. (p. 52-53)
• Organizational Unit/Group Level: Aggregate metrics of costs (time, resources) and benefits accruing to the unit. (p. 53)
• Overall Organizational Level (Three Categories):Immediate (Proximal) Outputs/Benefits: "number of nuggets put into KM system," "number of queries answered," "retrieval time," "perceived accuracy/quality/completeness/usefulness of answers." (p. 54) These assess ongoing KM system performance.
• Intermediate Outputs/Benefits: "savings in time and effort," "mistakes avoided," "new ideas engendered," "added organizational credibility," "project or program success," "improved decision-making/policies." (p. 54)
• Ultimate Outputs/Benefits: "new sales," "cost reductions and cost savings," "increase in profits," "increased growth and market share," "improved regulatory compliance." (p. 54)

D. Setting Up a Metrics System:

• Develop a flow model specific to each unit/organization, including cost and benefit indicators and who pays/benefits. (p. 55)
• Collect data periodically, with immediate outputs measured more frequently than ultimate outputs. (p. 55)
• Incorporate periodic surveys of users (depositors and extractors) as an integral component. (p. 56)

E. Role of Culture and Procedures:

• The willingness to invest in capturing past experience is cultural. (p. 56)
• Ignoring past lessons leads to repeating mistakes and missing opportunities. (p. 56)
• A formal KM system can enhance internal intelligence, especially in preventing "fatal or expensive flaws in strategy" (p. 57) by providing early warnings.
• "Proper procedures are very important in assuring the effective use of metrics." (p. 58)

F. Linking Metrics to Managerial Practice:

• Metrics provide feedback for individual users and managers, shaping future behavior and influencing organizational culture regarding KM. (p. 58-59)
• The stage approach allows managers to interpret benefits (immediate to ultimate) and compare them with costs, informing actions and policy. (p. 59)
• Metrics don't have to be strictly quantitative; "more," "better," "highly or moderately satisfactory" can be sufficient for design, monitoring, and evaluation. (p. 60)

VI. Intellectual or Knowledge Nuggets

Nuggets are the fundamental building blocks of a KM system, encapsulating experience for reuse.

A. Introduction and Examples:

• Nuggets can range from "trivial" rules of thumb to "profound encapsulations of experience" (p. 61).
• They are typically "compound statement[s], which has an 'if X, then Y' kind of structure." (p. 61) This structure helps clarify consequences of actions.
• Examples include: lessons from mergers and acquisitions (e.g., verifying assets), auction strategies, purchasing tricks of the trade, and R&D insights. (p. 62-65)
• Nuggets are the "convergence of the tacit and explicit knowledge of individual experts and their organizations." (p. 63)
• Supernuggets are those with "clear potential for re-use and even important re-use," addressing specific, urgent organizational needs. (p. 63)

B. Nuggets vs. Planning and Forecasting:

• Nuggets are "basic building blocks" and "units of flow" but are raw material until refined. (p. 66)
• KM systems are tools, not direct instruments of policy or decision-making; they aid forecasting and planning by providing knowledge about capabilities and avoiding "wishful leaps into the future." (p. 66-67)
• "Knowledge is not necessarily power, if you do not follow the rules generated by or reflecting that knowledge base." (p. 68)

C. Trust in Sources and Experts:

• Credibility: A significant issue in using nuggets is how much a user trusts the source (specialist A trusting specialist B). (p. 68)
• Expert vs. Knowledge: Experts may "own" a body of knowledge containing nuggets, but their advice must be relevant and timely. (p. 69)
• Verification: Users must critically evaluate nuggets, especially if historical trust is lacking. This may involve seeking additional sources, direct verification with originators, or even quasi-experimental testing. (p. 71-72)
• "Nonsense-in/nonsense-out" applies; KM systems should not generate an illusion of truth from fast, neat, plentiful output. (p. 71)

D. Parsing and Peeling Nuggets:

• The critical part of the KM process is to "strip a nugget of its irrelevancies and expose the embedded key idea(s) or lesson(s) learned." (p. 72)
• Nuggets are non-material "abstractions derived from the experience and work of others." (p. 76)
• Layered Formation: The bare nugget is the first layer, followed by further layers providing context and conditions for original formulation and safe use. (p. 113)
• Interaction: Direct person-to-person interaction with the nugget's originator is crucial for clarification and elaboration. (p. 77, 113) A KM system should facilitate this.

E. Keywords and Other Tags:

• Standard keyword systems often fail due to too many hits or no hits, because originators and future users may not share the same interest sets or terminology. (p. 77)
• More "clever methods of parsing information sets with the use of both semantic and pragmatic probes" are needed. (p. 77)

F. Supernuggets:

• Supernuggets fill "a hole that could have significant impact" (p. 78), addressing urgent needs.
• Push vs. Pull: Overwhelming users with "pushed" information leads to "receiver fatigue." Supernuggets have a better chance of being noticed if they align with a user's current need (pull). (p. 79)

G. Transferability of Nuggets:

• Nuggets are generally transferable across times, places, users, and contexts, but this requires safeguards in the debriefing, extraction, probe, and screening processes. (p. 79)
• Context is Key: Applying nuggets requires careful consideration of the specific situation's parameters and constraints. (p. 79-80)
• Examples of transfer issues: military officers to civilian government (different compliance modes), hotel management to mental health (crucial differences in patient care), R&D knowledge to different business units (knowledge silos). (p. 80-82)
• Transferability is often more difficult in "soft" areas (management, healthcare) than "hard" sciences. (p. 82)

H. Nuggets as Personal Property: The concept of intellectual capital or nuggets as "personal property" versus "organizational property" is introduced, implying potential for individual negotiation or value. (p. 82)

VII. Key Players in a KM System

Successful KM requires willing and enthusiastic participation from various stakeholders.

A. Categories of Key Players:

• Management Champions: Initiate, support, and tolerate KM activities. They provide funding and run interference against critics. (p. 85-86)
• Information Technology (IT) Facilitators or Blockers: Can significantly help or hinder KM, depending on their enthusiasm, workload, and biases. (p. 86-87)
• Operating or Functional Management: Can be facilitators or blockers. They control their people's time and may resist "wasting time" on past lessons or acknowledging predecessors' contributions. (p. 87)
• Other Potential Skeptics or Critics: People at any level who don't see the need for another system. Continuous "selling" is crucial to gain their support. (p. 87)
• Information Specialists: Librarians, marketing/business intelligence people who protect their "territories." They can be powerful allies or formidable enemies. (p. 87-88)

B. Experts: Internal and External:

• Internal Experts: Possess specialized knowledge in various fields (e.g., law, finance, R&D). Their nuggets form a significant part of the KM system. Credibility varies. (p. 88-90)
• External Experts: Consultants or specialists who write manuals or provide advice. Their nuggets also need evaluation, especially if the risk of uncritical application is high. (p. 90-91)
• "Nugget Review Task Forces": Advocated to bring additional judgment and experience to bear on extraction, probing, and screening. (p. 91)
• Valuable raw nuggets can come from "line production workers, salesmen, or clerks" (p. 91), not just formal experts.

C. Roles Related to the Process Model Tasks: The book proposes a matrix (Figure 7.1) distributing direct tasks (Debriefing, Extraction, Probing, Screening) and supporting tasks (Initial Design, Provision of Support, Monitoring/Assessment/Improvement) among key players (Champions, IT/KM People, Management, Users, Information Specialists). (p. 92)

D. Changes in User Population and Needs: KM systems must be "open-ended" and adaptable to evolving user rosters and needs influenced by:

• Organizational changes (mergers, acquisitions, job changes, retirements).
• Changed user expectations and experiences with the system.
• Evolving functions and duties of user groups.
• Requests for individualized features and broader scope/functionality.
• Emergence of new user categories (e.g., vendors, customers, regulators). (p. 92-94)

VIII. Selling KM Systems

KM systems require continuous "selling" to overcome resistance and ensure adoption and effectiveness.

A. The Challenge of Selling KM:

• Resistance to change is common; people cling to old systems. (p. 97)
• Generational differences exist in openness to new technology. (p. 97)
• KM is not "just information"; it's a "more complex effort" with "many additional and unique benefits." (p. 98)

B. What is Being Sold:

1. Attributes of the KM System Itself: Ease of use, cost of use, time to locate/extract nuggets, usefulness of nuggets. (p. 98-99)
2. Potential Value to Users and Managers: Intermediate outcomes like better utilization of new technologies, problem-solving, improved performance, and efficiency. (p. 99) Gartner Group survey reasons include improved knowledge sharing, competitive response, accelerated innovation, cost reduction, intellectual asset retention, and facilitating global operations. (p. 99)
3. Core Competency of the Enterprise: KM contributes to an organization's valuable added competence in producing knowledge on demand, enhancing timely and effective relationships with stakeholders. (p. 99-100)

C. How to Sell to Internal Customers:

• Personal Approach: Encouraging widespread participation through:
• Championing by a respected person.
• Initial marketing campaigns (websites, announcements).
• Incentives for participation (depositing and using).
• "Buy-in" by integrating KM use into performance appraisals. (p. 100)
• Publicizing immediate, personal benefits.
• Senior management's vocal and active support. (p. 100)
• Organizational Approach: Complementary focus on:
• Articulating the connection between KM and business objectives/strategy.
• Developing and publicizing a roadmap for implementation.
• Establishing transparent metrics for progress and long-term success.
• Publicly underscoring benefits to participating units. (p. 101-102)
• Enterprise-Wide Approach: For broader rollout:
• Articulating overall benefits (knowledge transfer, value creation, enhanced revenues).
• Establishing a framework for managing KM-engendered changes.
• Publicizing successful trial phases. (p. 102)

D. Selling in Stages:

1. Idea Stage: Focus on individual approach milestones.
2. Introduction/Trial Stage: Sell the importance of careful introduction and experimentation. Enlist early adopters as salespeople by highlighting benefits. (p. 103)
3. Scaling-Up Stage: This is often difficult as resistance emerges. Focus on both individual and organizational benefits. Failures occur when personal incentives are overlooked (e.g., Pillsbury Co.'s "field of dreams" system). (p. 104) Address fears of sharing knowledge (e.g., managers fearing loss of power). (p. 104)
4. Steady-State Operation: Re-emphasize benefits and ensure the KM system aligns with how people actually work and interact. (p. 105)

E. How to Sell to External Customers:

• KM influences external customers by:

1. Interfacing with External Networks: Abiding by standards of quality, output, format, and response time. (p. 105)
2. Intelligent Interactions: Enabling organization members to interact "more intelligently, faster, more effectively, and more efficiently" with external entities. (p. 105)
3. Aura of Prestige: Providing the enterprise with an image of sophistication and competence. (p. 105)

• Selling to external entities must be linked to internal selling; a lack of internal enthusiasm will impact external acceptance. (p. 106)
• "It's not just another information system—it's a change in the way we operate and behave in an enterprise." (p. 106)

IX. Users: Needs and Characteristics

Understanding user needs, preferences, and behaviors is paramount for effective KM system design.

A. Need for Improved User Interfaces:

• User perceptions and behavior significantly affect KM success. (p. 108-109)
• Customization vs. Standardization: Individualization, though costly, greatly aids adoption. Interfaces should accommodate visual, auditory, or text preferences. (p. 107-108)
• Individual/Group Differences: Needs vary based on training, profession (doctors, lawyers, engineers), and function. (p. 108)
• Information-Seeking/Using Styles: Persistent behavioral patterns, cost of changing them, age, and reliance on intermediaries influence adoption. (p. 108)
• Front-End Preparation: More attention needed for user needs/abilities during design, not just technology. (p. 108)
• Credible Metrics: To justify investment, derived from business objectives, not just technical efficiency. (p. 108)
• Barriers to Adoption: Identify and act on low accessibility, ease of use, perceived usefulness, credibility, or output quality. (p. 108)
• Buy-in: Recruit key players early, offering incentives for participation. (p. 108)
• User Cost/Benefit Perceptions: Identify and incorporate into design. (p. 108)
• Ease of Use & Accessibility: Crucial, as users desire "bang-bang" or instant response features. (p. 109-110)
• Critical Stakes: For high-stakes situations (e.g., surgeons, lawyers, competitive strategy), high sophistication and fail-safes are justified. (p. 110-111) Often, information exists but is not "flagged, integrated, and presented to the people who needed to act on it." (p. 111)

B. Interactive Interfaces:

• Beyond traditional database interaction, KM systems need to support deeper interaction, particularly between the source and user of a nugget. (p. 112)
• Context: While bare nuggets are a first layer, further layers are needed to provide full context and conditions for original formulation. (p. 112-113)
• Person-to-Person Interaction: Crucial for clarifying nuances and addressing user questions, despite potential time/cost burdens. (p. 113)
• Nuggets should be tagged with sources and contact information. (p. 113)
• Direct interaction can also foster knowledge exchange, where the user contributes to the original source's thinking. (p. 113)

C. Information Seeking and Using Style:

• People vary in their "information style"—how they search for, store, and use information (e.g., reliance on hard sources vs. human contacts). (p. 114)
• Style influences whether retrieved nuggets are effectively converted to useful ideas. (p. 115)
• Interfaces should be flexible and adaptive to accommodate major style variations, offering options (e.g., human intermediaries for busy executives). (p. 115)
• User Templates: Can anticipate future needs; the more precise the template, the less "dross" is returned. (p. 117) These templates need to adjust as user interests and organizational needs change. (p. 118)

D. Individual KM Systems:

• All organization members have personal KM systems (mental, physical files, electronic). (p. 116)
• The challenge is integrating these individual caches into an organization-based system. (p. 116, 184)
• For knowledge workers, time/incentive to process vast amounts of data into usable nuggets is a major problem. (p. 118)

E. Role of Intelligent Assistants:

• Some users prefer human or non-human "intelligent" intermediaries who "know" the individual user's work, interests, goals, and preferred interface style. (p. 118-119)
• Software and "understanding" developments show promise for meeting these requirements. (p. 119)

X. Special Cases and Application Areas

KM systems can address specific organizational situations and crises.

A. Key Issues in Special Cases:

• Customization: How much tailoring is required for different circumstances and user groups? (p. 121)
• Costs/Benefits: Of tailoring the KM system for specific applications. (p. 121)
• Adaptability: Capability to serve unforeseen application areas. (p. 121)
• Temporary Modules: How to set up super-specific modules for transitory or urgent circumstances without clogging the general system. (p. 121-122)
• Security: Measures for restricted access to sensitive nuggets (e.g., mergers, legal proceedings). (p. 122)
• Purging: Periodic review to preserve relevant nuggets and remove obsolete ones, balancing historical value with current usefulness. (p. 122)

B. Specific Application Areas:

• Committees and Task Forces: Major sources of nuggets, especially insights derived from interpersonal interactions. Need systematic procedures to parse meeting outcomes and capture nuggets, including "reasoning underlying the actions and decisions." (p. 123-125)
• Purchasing: Functions like purchasing, logistics, and supply-chain management hold "tricks of the trade" and "rules of operation" (nuggets) that are not obvious or formally codified, offering significant cost savings. (p. 125-127)
• Management of Medical Technology: Healthcare involves complex knowledge flow. Medical records and telemedicine are KM systems. The "Physician's Desk Reference (PDR) is a unique knowledge system." (p. 127-128) Knowledge from medical errors is minimally codified, largely due to malpractice concerns, though mortality and morbidity sessions attempt to share lessons. (p. 150-151)
• New CEO or Other Senior Manager: Turnover creates a need for rapid learning. A KM system can provide invaluable guidance on organizational operations, culture, and specifics (e.g., "dos and don'ts"), especially for external hires lacking institutional memory. (p. 128-130) Mentoring can be supported by KM. (p. 130)
• Fatal or Expensive Flaws in Strategy: KM can help "abort or modify potentially fatal or expensive moves, based on lessons learned within the organization or outside it." (p. 131) This involves analyzing past strategic mistakes and "gaming" situations based on available nuggets. (p. 131-134)
• Downsizing and Restructuring: These events often lead to significant knowledge loss. Planning should include capturing valuable elements of the knowledge base through debriefings. Ideally, organization members continuously contribute nuggets. (p. 134-136)
• Retirements, Individual Reassignments, Promotions, Turnover: Significant knowledge loss occurs when key people leave. Debriefing through structured introspection can yield valuable nuggets, requiring incentives and careful handling of resentment. (p. 136-138)
• Refocusing R&D/Technology Programs: Changes in R&D direction can lead to loss of skills and knowledge. KM systems can bridge gaps by providing access to knowledge about existing products, processes, and past technical decisions. (p. 138-140)
• Capturing and Preserving Intellectual Property (IP) in Acquisitions and Strategic Alliances: Financial due diligence is common, but "seldom...is there a corresponding effort devoted to creating, assessing, and preserving the intellectual capital represented by 'lessons learned' and 'how to do it' nuggets." (p. 141) KM can ensure awareness and access to combined knowledge assets. (p. 140-142)
• Knowledge Silos: Natural tendency to hoard information within groups due to personal value, organizational structure, and evaluation systems. KM systems need to bridge these silos and encourage sharing, often facing resistance from "keep away" attitudes. (p. 142-144)
• Fast Track Projects: Often neglect documentation, leading to loss of "paper trail" and conceptual reasoning. KM systems should integrate quick, accurate access to relevant nuggets to avoid reinventing wheels, despite time constraints. Incentives and automated tools for capturing nuggets are vital. (p. 144-146)
• Strategic Partners: Increased dependency and intimacy between organizations necessitate extensive knowledge sharing. KM systems should extend across these "semipermeable boundaries" to leverage combined experience, skills, and knowledge. (p. 146-148)
• The Arts: Organizations in the arts (e.g., theater groups) can benefit from KM to capture "knowledge nuggets" about their own histories and common pitfalls, aiding in preventing failures. (p. 149-150)
• Military and Other Government Organizations: Despite extensive intelligence systems, failures often occur due to inability to integrate and present information effectively. KM can help process vast raw data into actionable nuggets for decision-making. (p. 151-153)
• Technology Transfer Processes Downstream of R&D: R&D results are often limited in dissemination. KM can reformulate these results into nuggets for broader and future use, tying into general KM systems. (p. 153-155)
• Mentoring: A key use of KM is passing on knowledge to new (or re-assigned) members, smoothing transitions. KM can provide condensed tutorials and guidance, complementing human mentors. (p. 155-159)
• Unit Managers' Needs: Unit managers often focus on KM that directly benefits their own units, potentially contributing to knowledge silos. (p. 159-160)
• National Knowledge Systems: Examples like the National Transportation Safety Commission and the CDC demonstrate comprehensive, obligatory data deposition from all principals, leading to pattern extraction and guideline formation. Corporate KM can draw lessons from these. (p. 160-161)

XI. Visualizing the KM Process

This section details the practical execution of tasks within the KM process flow model.

A. Task Allocation: The matrix in Figure 7.1 shows how tasks are distributed among key players (Champions, IT/KM People, Management, Users, Information Specialists).

B. Detailed Task Execution:

• Debriefing: Done by anyone with project/job changes. Can be quick and enjoyable for donors. Information specialists can assist. A diffused approach using templates is recommended. (p. 164-167)
• Extraction and Processing of Raw Nuggets: Ideally done by donors and users, as they know the material best. However, time and motivation are limitations. Consultants or outsourced services can assist, with careful attention to privacy. (p. 167-170)
• Probe Process: A major task for users. Can be reactive (specific need) or proactive (browsing in anticipation of future needs). Needs to be structured and guided by user templates. Intermediaries can assist in focusing the probe. (p. 170-174)
• Screening Process: Primarily the user's responsibility. It involves determining the fit between candidate nuggets and current needs. The goal is to produce specific, targeted nuggets, rather than an overwhelming flood of information. User involvement is crucial, as is a good "hit ratio." (p. 174-176)
• Initial Design: A front-end task, but should be done in stages with experimentation ("fast prototyping"). This offers quick results, lower budget, new recruitment, avoidance of "big-bang failure," and accumulation of design lessons. It's best done in-house, focusing on organizational and behavioral aspects, with IT handling technical components. (p. 176-180)
• Provision of Support (Financial & Political): A task for management champions. Crucial for non-urgent KM projects to overcome skepticism. Incentives (Oscars for contributions) or performance evaluation inclusion can encourage participation. KM technology should leverage existing "dual use" technology. (p. 180-181)
• Monitoring, Assessment, and Improvement: Continuous or periodic tasks for all players. Regular assessments (annual/semi-annual) and real-time monitoring of performance are essential. A dedicated "KM person" or IT/librarian can oversee this. (p. 181-183)

C. Organizational Learning: KM systems intersect with organizational learning. Individual nugget caches should be integrated, considering accessibility, willingness to share, technology, terminology, costs/benefits, and metrics. (p. 183-184)

D. Collecting Organizational Nuggets:

• Requires filtering out gossip/speculation and verifying reliability. A "nugget maintenance and verification sub-process" is crucial for clearing invalid/outdated nuggets. (p. 185)
• Nuggets can be found in training manuals, discussions, and personal files. Templates are needed for systematic collection. (p. 186)
• The "nugget brigade" (swat team) can help extract and refine nuggets, considering potential users and applications. (p. 186-187)

E. Response Time: The required response time for KM systems varies, from instant (jet pilot, surgeon) to "academic time." (p. 187)

F. POMRAD Nuggets: Illustrative "propositions" or "working hypotheses" from the authors' research provide lessons learned on KM and related subjects, offering guidance for design and operation. (p. 187-191)

XII. Conclusions and Further Work

This chapter summarizes the "lessons learned" (nuggets) and highlights the analytical needs for successful KM implementation.

A. Lessons Learned (Summary of "If...Then" Nuggets): A comprehensive list of "If...then" statements derived from the book's chapters, providing actionable guidance for designing, implementing, and managing KM systems. These cover:

• Starting the KM system (sponsors, team, simplicity).
• User interfaces and participation (standardization, customization, information style, intelligent assistants).
• Nugget quality (definition, language, specificity, parsing, supernuggets, transferability).
• Trust and credibility.
• The role of KM in planning/forecasting.
• Key players and task assignment.
• Incentives for participation. (p. 193-197)

B. Analysis Needed (Points and Methodologies):

• Points of Analysis: From pre-design (setting up teams, identifying needs, reviewing existing systems, developing metrics) to operation (monitoring debriefing, extraction, probing, screening, trust) and assessing downstream impacts (application, decisions, immediate/longer-term impacts). (p. 198-200)
• Methodologies: A range of formal and informal techniques can be used, including:
• Personal Communication Charting
• Individual Information-Seeking Propensity
• Critical Incident Method
• Black Hole Analysis
• Gatekeeper Analysis
• Knowledge Transfer and Application Methods
• Individual and Group Risk-Taking Propensities
• Blame-Placing Behavior
• Bureaucratic Analysis
• Indicators for "Out of Control" Behaviors
• Field Experiments
• Nugget Brigade/Swat Team
• Proposition Inventories
• The Organizational Design Approach
• Metrics for all phases (p. 201-203)

C. Examples of Applications (Scenarios):

• Retiring Senior Executive: Using "structured introspection/retrospection" to extract lessons learned (e.g., "What were the essential features of your job and the critical success factors (CSFs) by which you judged your own accomplishments in that job?"). (p. 204)
• Committee Decision Reconstruction: Using a "meeting analysis and parsing capability" within the KM system to document arguments, premises, and logical structures for decisions. (p. 204-206)
• Project Goes Awry: Employing continuous nugget collection and extraction during a project's life (via routine briefings, design reviews, and informal sources) to identify "causes" or "influences" on unsatisfactory performance. (p. 206-207)

The document concludes by emphasizing that the book's "mini-manual" of general nuggets serves as a starting point for organizations to develop their own tailored, "living, and open-ended set of nuggets" reflecting their unique experiences and culture. (p. 197-198)