(Il)logical Knowledge Management: A Guide to Knowledge Management in the 21st Century 1838678069, 9781838678067

In today s world, strategic knowledge management is a critical practice for all businesses seeking to protect its assets

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Table of contents :
1. Sources and Segmentation
Knowledge Strategy
Data, Information, Knowledge, (Il)Logical Knowledge
Implementing a Knowledge Plan
Case Study – Part 1
Logical Knowledge as an Asset
Logical Knowledge
Knowledge Trail
Knowledge Sources
Knowledge Content Segmentation
Logical Knowledge Environment Benefits
2. (Il)Logical Knowledge Process
Context for Content
Culture and Collaboration
Knowledge Transfer Rules
Knowledge Distribution Rules
Logical Knowledge Management Process
Case Study – Part 1 (Addendum)
3. Tools for Knowledge and Organizational Learning
Knowledge Management and Organizational Learning
Measuring Success
Case Study – Part 2
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United Kingdom – North America – Japan – India Malaysia – China

Emerald Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2020 Copyright © 2020 Emerald Publishing Limited Reprints and permissions service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters’ suitability and application and disclaims any warranties, express or implied, to their use. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-83867-806-7 (Print) ISBN: 978-1-83867-803-6 (Online) ISBN: 978-1-83867-805-0 (Epub)

CONTENTS List of Figures


List of Tables


About the Author








1. Sources and Segmentation Knowledge Strategy Data, Information, Knowledge, (Il)Logical Knowledge Implementing a Knowledge Plan Case Study – Part 1 Logical Knowledge as an Asset Logical Knowledge Knowledge Trail Knowledge Sources Knowledge Content Segmentation Logical Knowledge Environment Benefits

1 5 10 19 23 27 31 36 38 45 50

2. (Il)Logical Knowledge Process Context for Content Culture and Collaboration Knowledge Transfer Rules Knowledge Distribution Rules Logical Knowledge Management Process Case Study – Part 1 (Addendum)

53 61 64 71 72 75 80




3. Tools for Knowledge and Organizational Learning Knowledge Management and Organizational Learning Measuring Success Case Study – Part 2 Conclusion

83 102 107 109 114






Figure 1.1.

Logical Knowledge Formation.


Figure 1.2.

Validation Conditions.


Figure 1.3.

Knowledge Assets.


Figure 1.4.

Logical Process.


Figure 1.5.

Content Reasoning.


Figure 1.6.

Segmentation Key Process Activities.


Figure 2.1.

Using the Right Data.


Figure 2.2.

Content with Context.


Figure 2.3.

Main Channels of Knowledge Environment.


Figure 3.1.

High-level Knowledge Landscape.


Figure 3.2.

Logical Process Phases.



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Table 1.1.

Examples of Knowledge Use.


Table 1.2.

Logical Knowledge Phases.


Table 1.3.

Knowledge vs Information Management.


Table 1.4.

Content Reasoning Counterparts.


Table 3.1.

Knowledge Environment Team Roles.



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Beverly is the author of Delivering ITSM For Business Maturity: A Practical Framework and a high-performing business technology leader. She is an IT Business Strategist that specializes in information technology service management (ITSM), knowledge management, and business strategies for technology environments. She currently works as an independent consultant, where she provides strategic business and technology management education and consultancy. Beverly has led multiple implementations of knowledge management and ITSM in a variety of industries, such as finance, healthcare, professional services, insurance, and manufacturing. Beverly’s experience includes information and knowledge management, service management, IT governance, organizational transformation, and quality assurance practices. She has a knack for integrating information and people with technology. Beverly’s career in IT started with beta software testing and support. Service Operations is her home in IT. She has a passion for technology and focuses on the valuable ways to balance life in the modern world. Beverly is the Founder of edifyIT, LLC, a company she began in 2009, which provides Business and Technology Management education and training.



About the Author

Beverly also has a passion for yoga and is an Experienced Yoga Teacher (E-RYT). Yoga is a big part of her self-care system and she has blended a regular yoga practice into her busy corporate life. It’s given her a perfect blend of a life–work balance that’s helped her manage modern-day stress.


Knowledge management encompasses a broad scope of topics concentrated on a core set of information. Businesses are accustomed to handling and managing the information it generates through systems, interactions with customers, through product development, planning, etc. Knowledge is made up of the human elements to information. The human element gives form and context to data and as a practice business collects knowledge with a resolve to distribute and with anticipation people will share between departments. Information as a tenant of knowledge is relative to a specific topic and its advanced with details about the topic from a person’s experience, learning, and understanding. This is one example of how knowledge comes to be. The idea is to advance information to a state where it represents a comprehensive narrative about the subject. Knowledge combined with human insight, known as tacit knowledge, is often referred to as wisdom. We interchange the use of knowledge and wisdom very closely as if they are the same, but they are not. Wisdom is a presence and knowledge are an entity, an asset. For the purposes of this book, our focus is entirely on understanding knowledge based on two perspectives: logical xiii



and illogical knowledge and achieving good knowledge management practices using modern technology. It isn’t as simple as it may seem, and designing a good infrastructure for knowledge systems is one small part. There are many complex areas to consider while creating a knowledge strategy. One area is the knowledge sandpit. There is a hidden sandpit within knowledge management? The sandpit is how I describe excessive amounts of information being passed off as knowledge. Information comes from data we collect; however, it’s not all eligible to be considered knowledge. Knowledge should align to certain conditions associated to a topic. Let’s say you have information that meets the criteria at hand, and it’s formally approved as useable knowledge. Approach filtering carefully because the context of the content may be illogical (not ideal). Just because content becomes part of a community knowledge repository doesn’t mean it’s logical (ideal). There is a major problem with unfounded knowledge being passed off as factual and logical knowledge. Illogical knowledge doesn’t have a place in business and it can invoke ominous situations when people use or follow illogical knowledge. To avoid a sand trap, rational thinking in businesses managing knowledge is needed today more than ever before. Knowledge is found everywhere in our advancing world of technology. Technology should be making things easier and in some capacity it is; however, we are a long way away from learning how to balance the use of technology where is deemed helpful. We are in a pivotal time to provide better education on integrating technology and people for usefulness, value, and effectiveness. Notice, I’m not including efficiency. Efficiency doesn’t belong here, and being efficient is only meaningful when the task or situation needs it. The considerable amount of illogical knowledge being used and the refrainment of integrating people and technology in a



balanced way is a major motivating factor to why I’m writing this book. In today’s world, the twenty-first century, it’s really important to help bring awareness and understanding on effecting knowledge management successfully. Better understanding and awareness will help increase the value knowledge will bring to your business community. There is a significant difference between illogical and logical knowledge, and I believe investing in a plan to produce logical knowledge is a vital factor for the plan to succeed. It’s important to zone content by logical (ideal) and illogical (not ideal). Illogical knowledge carries extra costs and wasted time because of its unfounded sources or because of unreasonable conditions on how the content is considered to be knowledge. Another reason I’m writing this book on Knowledge is because of its area of interest personally. I wrote a paper in college on self-knowledge and the older (wiser me) wishes to have this paper today. Knowledge is so prevalent in today’s world and has massive amounts of tenants to it. Knowledge and service management are major areas of experience in my Information Technology (IT) career. I write this book from this experience and insight. Knowledge management is a blend of various commodities, and effecting knowledge management is a valuable business asset. It supports communities of interest and can be a time saver when done properly. To do knowledge properly involves comprehensive understanding of knowledge management and use of a distinct strategy to put it in place. Sharing knowledge in responsible and logical ways is the motivation behind this book. It’s something I exercise in business and personal life. When it comes to knowledge, just be open to other possibilities outside of its scientific models and processes to manage it. This book is instrumental to enduring the complexities of managing knowledge in the twenty-first century!

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This project wouldn’t have been possible without the opportunities I am grateful to have had during my career in Information Technology and Business. Thank you to each person I worked with along the way, and to the companies I’ve had the honor to represent with my work. Knowledge is an area that I’m particularly interested in since school age years. In college I wrote a paper (wish I still had it) on self-knowledge. Although this project focuses on the concepts of illogical and logical knowledge in advanced modern times for business, self-knowledge is a big part of what has guided me through a successful career. Nobody is more important to me than my family. Their unconditional love and support has helped me grow and succeed in my work. Thank you to all at Emerald Publishing for their experience to bring my books to the public.


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Knowledge is a complex and confusing area because it’s harder to define than basic information. The path that knowledge flows within an organization is equally important to the content being distributed and shared. Knowledge mostly flows bilaterally in various directions. Typically, an organization focuses on knowledge that flows and is shared vertically and horizontally. This isn’t enough because there are sources of knowledge in many channels that extend beyond up or down and across. These channels are those linked to the major vertical and horizontal pathways. Knowledge sources are like pockets, pockets connected to the organization layers both internal and external. A good way to describe it is to think about a sponge and its unique permeable surface. The circular pocket pattern on a sponge surface represents pockets of knowledge in an organization. The absorbency of the sponge represents how well knowledge is absorbed and shared. This makes identifying the pockets of knowledge content and how it flows within an organization critical to understand. By comparison to information, knowledge relies heavily on the human aspect and good understanding of existing pockets of knowledge. Information is more exact and flows in single lanes between systems. Information management focuses on data and activities on a factual basis. Knowledge management focuses on xix



individual’s experiences, and methods of how knowledge is shared within an organization or community. Information combined with experience creates knowledge. Knowledge helps people in a variety of ways. For instance, learn and understand about business- or work-related topics. Knowledge also helps to solve problems, figure out causes to problems, and serves as a method of education. One angle to view knowledge is that knowledge management evolved from information management. Knowledge is a much broader area and it is more people centric than dealing with information. Being people centric makes knowledge management more difficult to decipher and express. The challenges to interpret and articulate knowledge is the very cause to producing mass amounts of illogical or useless knowledge. This perspective creates an uncompromising situation and a common belief that collecting knowledge and a drive to store as much knowledge as possible is an effective strategy. It isn’t, it’s a perspective that will inflict disorder. This perspective doesn’t care much about the quality or logical aspect to the inner parts of knowledge. The basis of this book is focused on knowledge management from an illogical and logical standpoint. The ideal perspective to change is approach knowledge management consistently and realistically. In the information age, the boundaries between information and knowledge are blurred substantially making the task to choose content difficult. This creates issues with data waste, information overload, and the burdens of cost to house useless knowledge. In this book, I talk about methods to avoid these types of issues and how to segment data selectively, filter information to feed into knowledge management, and create context and guidelines for effective knowledge management practices. A good strategy for



managing knowledge and is one that creates a wellstructured environment to support it. Poor knowledge can come from an inadequate architecture; difficulties applying content to be useful, too much content, poor quality of content, or inconsistent and poor collection methods. Having good knowledge is attainable but if people can’t retrieve or find knowledge they need, then the environment is not useful. Knowledge is useless without proper context and application. Users need a fundamental understanding on what knowledge is and why the organization needs knowledge management procedures. In my experience, high-level plans for knowledge often do not work and will steer a good plan off course. Succeeding with knowledge management comes from a balanced plan with attention to detail to interconnect the pockets of knowledge, build quality logical knowledge assets, and methods to share them. This helps its users understand knowledge, how to use it, and where to find it. A balanced plan includes business logic behind the plan and ways the company will manage it. In this book there is a useable approach to support the creation of logical knowledge from a balanced knowledge management plan. This will aid its readers to understand this complex area. Quality knowledge is a highly effective nontechnical system in a pool of highly technical resources. It helps you to diligently make choices based on need and purpose. This book represents logical knowledge acquired and modernized to fit with current technical systems and tools.

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Knowledge management is a sensible practice that encompasses a series of phases to produce a finished knowledge product. The finished product is a knowledge asset associated with an organization or community of interest. Content that is used to construct knowledge assets is ever changing and elusive. This makes housekeeping and the task to keep knowledge current extremely challenging. To a level, it may seem like an unworthwhile effort. It seems much more effective to collect knowledge in abundance and let people sort through it and figure it out themselves. Up front, this seems like the path of least resistance, but in the long run, it is not a good idea. It is not a good idea because it produces the most ineffective benefits to the user base. The user base includes customers which puts a business at risk to impacting good customer relationships, and revenue. The greatest amount of effort is invested in the preplanning and planning stages of knowledge management. Preplanning and planning stages of knowledge management and involved extensive resource and time investments will produce the most effective benefits to the user base. Mainly, the value will be experienced through



(Il)logical Knowledge Management

gained efficiency and increased productivity for the organization’s staff users. For customers, it will improve their experience from interactions they have with the business. Portions of knowledge are meant to be used in many different ways and by different communities of people. Think of the sponge and interconnecting the pockets of knowledge sources to make them available throughout the organization. This requires a robust plan to stay ahead of requirements for knowledge and creativity that continually explores and improves the life cycle methods used to distribute and share knowledge assets. This is what we know as knowledge management (Table 1.1). Managing knowledge is a difficult process to develop and sustain without central direction. Central direction is required for any knowledge program to achieve its goals. A common and major goal for managing knowledge well is to adopt a uniform approach and flexible set of activities. The major aspect that drives knowledge management is the fundamental understanding on why the organization needs knowledge management. Another major aspect is to have a good view of and understanding of the layout of the organization to be able to recognize viable sources for content. Knowledge management is more than just mapping information from the business intelligence areas within an organization. Mapping information is only one exercise and part of a knowledge management plan. Knowledge quality depends more on the human aspect and how well the content is formed to be logical knowledge. The human aspect comes from an individual’s insight, their experience, and skills they hold. Insight into an internal knowledge of an individual is just as ever changing as the content being used as a knowledge asset. Keeping knowledge current is an issue that most likely cannot be mastered, but it can be an area that is significantly improved through the use of a realistic strategy and process. The mistake most

Sources and Segmentation


organizations make is approaching knowledge the same manner and with similar processes that we use for information management. Remember knowledge is elusive and is ever changing. For example, a knowledge contributor provided insight to a specific situation that helped define conditions on how a decision was made. This insight will change over a period of time. The reasons why insight changes can be from new information or experiences. New information and/or experiences has improved their insight. The elusive part is related to how well knowledge contributors maintain their knowledge assets. This makes managing knowledge a multifaceted discipline entailing a set of processes and driven through intellect and awareness. Knowledge management is a complex and dynamic area that provides a considerable amount of business value and a lot of struggles at the same time. Once an organization has a good understanding on why they need knowledge management and able to define requirements for a knowledge program is when planning begins. Strategic planning begins by defining the traits of the program and what knowledge is used for. This book is written from a strategic perspective rather than a tactical one. This viewpoint will follow a strategic path from a clear starting point to guide the reader through an approach to focus on the logical aspects to knowledge management. Knowledge management considers how people learn, share, and apply content. Information management considers business intelligence and data generated within systems. Knowledge and information are very similar in nature but have a distinct difference. Distinction between the two is important to understand before creating a knowledge plan. Understanding the difference between information and knowledge will be helpful in identifying what parts of information is used for knowledge content. Content is handled


(Il)logical Knowledge Management

through content management practices. Content management practice is a part of knowledge management. Technology systems used to manage content and knowledge are very similar in functionality if not the same. For example, you can create a new web page and it could be part of an organization’s intranet. There can be content on this web page that could have a link or multiple links to an external website. The new page that was created can be accessed from a laptop or a mobile phone. The content of the web page is made available to the people within the organization, enabling them to search for information on the new web page. For both content and knowledge management practices, the web page content remains on a central storage repository. In this example you would see that knowledge management sits within the content management realm because they share the same systems. The distinct difference is that content does not specialize in knowledge. Content management is like the factory warehouse doing the work for knowledge, and knowledge management is the packaging of the product being made in the factory. Content and knowledge management are commonly known through websites accessed via the Internet and found on company’s internal intranet. Content is made available through open platforms because it is the easiest type of platform to collect large amounts of knowledge in a short amount of time. Content is what is managed in a knowledge management environment and processed to ensure the substance of the content is logical, useable, and reliable. Open platforms for knowledge environments are tricky. There are guidelines to differentiate between good and poor knowledge; however, they are sparse. Once a knowledge platform is open publicly to the organization, it exposes the content to damaging effects that can devalue its use. Knowledge user agreements are a good way to align knowledge

Sources and Segmentation


content with need. Knowledge user agreements should be developed in part of the planning phase for a knowledge program. Knowledge user agreement gets the entire user base within an organization that will benefit, contribute, transfer, share, and train on knowledge on the same page and coordinates them to align to the same set of procedures. A knowledge user agreement covers • How to contribute to the knowledge platform and expectations for how frequent content is maintained. • Instructions to edit knowledge content. • Details on the distinction between what is factual and subjective. This part sheds light on the logical and illogical knowledge variances. • How to transfer knowledge and what systems and methods are approved to use. Details on who is authorized to receive knowledge. For knowledge that is protected under regulation and compliance, consult with the organization’s legal department and use contractual agreements where needed to protect the company’s knowledge assets. • Descriptions and attributes about the knowledge management culture.

KNOWLEDGE STRATEGY A high-performing knowledge program begins with a well thought out and practical strategy. A knowledge strategy is to build the environment that creates, stores, supports, maintains, distributes, combines, and improves knowledge assets. Begin strategizing with brainstorming sessions. From brainstorming, the charter for the knowledge environment is decided and


(Il)logical Knowledge Management

documented. Develop a clear strategy that supports the vision and mission for the organization to achieve its intentions (goals). Brainstorming and strategy creation is done first because the majority of the work involved to set up a knowledge environment is done first, before the processes are designed and documented and the technology setup and configured. How the knowledge will be used is a big part of the strategy and the brainstorming sessions. For instance, most organizations use knowledge management and relation to organizational learning. Much of the knowledge assets are used for organizational trainings for new employees and continuing education for existing employees. Knowledge specifies what actions to take in relation to a specific set of circumstances. This relates to organizational learning as much as it does in supporting daily business operations. Individuals are capable of knowing how to handle and manage knowledge; however, knowledge management is an organizational activity that focuses on knowledge management goals and how to achieve them. The following key steps are involved in creating a knowledge strategy: 1. The first step is to create the knowledge environment design model. Make a list of what the organization needs for managing knowledge and define what exists in the organization for business intelligence. Use this list to determine what information from the company’s business intelligence will be utilized in the knowledge environment and link content to users. Explain who the audience is for each packet of content. Group content by audience interest. In a design for the knowledge environment group them by • Organizational level, organizational learning, customerrelated, support-related, service or product delivery, and

Sources and Segmentation


vendor management: Grouping audiences into major groups will help drill down and define subgroups within each higher group. This makes designing the landscape for the knowledge environment well defined for process, technology, public content, proprietary content, roles and responsibilities, and content ownership. Public content is shared at the organizational group level and support-related content would be considered proprietary contact. The reason we separate public content from proprietary content is to determine the specific type of technology that will be used to store and distribute the content to the group community. This includes information that is created within the occupational silos that could be utilized by other groups in the organization to save time from having to recreate content. For example, a wiki-type technical platform is best suited for public content that is shared to the organizational group and its subgroups. • The theme of the knowledge environment is to transport business intelligence (information) to a centralized area of the organization and feed it into acknowledge technical landscape (in Chapter 4, technology is explained for the knowledge environment). 2. The next step after brainstorming is to prepare for content collection. We have established business intelligence (information) is a feed into the Knowledge Management process and it runs in a knowledge environment. Content collection is a set of procedures utilized to leverage business information and utilize it as a knowledge asset. Collection methods will be a combination of automation and manual effort and is done by a role that has investigative capabilities. Content collectors are like detectives; they are familiar with the business layout and where to find current and


(Il)logical Knowledge Management

authorized information. Content collectors trace the content to the originator or the person or team who developed the content. 3. After content collection is accomplished, the next step is storing. Content storing is a set of activities that moves the content that was collected and brings it into repositories within the knowledge environment. The repository is set up to support either public or proprietary content. In preparation, activities for this step focus on storing public content into a public repository and proprietary content into a proprietary repository. Once the content is stored in the knowledge environment public or proprietary repository, from there the content is tagged based on specific specifications for the use of the knowledge content. 4. The next key step while strategizing to build a knowledge environment is categorizing and classifying the collected content stored in public and proprietary repositories. Classification followed by categorization is done by community grouping, content topic, process, or department or categorized based on technical and nontechnical information or by customer, etc. If there are unclear arrangements for this step, you may need to go back to the brainstorming phase to deliberate more on what is the best way to classify and categorize the content that has been collected. This will help decide which structure for the classification tree will best suit the knowledge environment and how the content will be used. • Reasoning skills can also be applied when you regroup to brainstorm on the best way to structure and distribute the knowledge content already collected. Looking at the content that has been collected is helpful to determine the labels and the tree structure. It also helps to

Sources and Segmentation


determine which tools in the technical landscape are needed and the systems the content will be made available from. It is important not to lose sight between what is public content and proprietary, so work on each repository separately, meaning work through the logical knowledge process for the content in the public repository from start to finish. • Complete all steps of the logical process for the public content from start to finish. The logical process steps include filtering/context, content sourcing, set criteria targets, validation, verification, segmentation, and testing. Content processed through these steps will produce a knowledge asset containing logical knowledge. • Filter content and use reasoning competencies. Reasoning helps to isolate content based on type,. i.e., projects that involve improvement work versus project work requiring from new structure and implementations. 5. Knowledge distribution happens when content is processed through all major and minor knowledge process activities. Knowledge is distributed to the people in the organization who will benefit from using its content. Distribution achievement is solely reliant on the organizations capabilities to distribute to meet the needs of its staff. Visibility to knowledge and the methods used by the organization are important. Knowledge distribution is different than knowledge sharing. Knowledge sharing is done by informal methods and between people within the organization. People share what they know with coworkers, a customer, or anyone else in or associated with the organization. Knowledge sharing is not a controlled practice nor is it triggered by any direct request for it. It is in formal


(Il)logical Knowledge Management

fashion and is usually done in the moment during a meeting or in passing through a conversation or by conversation in an email. Knowledge distribution is a controlled practice directed by the organization through various channels that will move knowledge assets from the centralized location in the technical landscape to appropriate recipients. • Use of formal knowledge management process best practices combined with distribution models offer good guidance on how to carry out knowledge distribution well. • Ensure the quality of what is being distributed meets all quality assurance and logical knowledge management criteria. There are both strategic and tactical practices for managing knowledge. The tactical tasks deal with data and information and are carried out with specific instructions. Strategic planning deals with content, knowledge, and knowledge as an asset within an institution. The association between data, information, and knowledge is a common core structure, and logical knowledge is an addition representing the process to validate its content.

DATA, INFORMATION, KNOWLEDGE, (IL)LOGICAL KNOWLEDGE In the common core knowledge structure, there are two dependent mates called data and information. Let us look at the interconnectedness and formation of data, information, knowledge, and logical knowledge. Data are the tangible

Sources and Segmentation


attribute to knowledge. Data are a type of information that are objective and systemic. Data are abstract in context and provided in a structured format. Information is formed from data that have been given interpretation and facts. Information is data that have been formatted, given meaning, and have been filtered. Information provides a factual attribute to knowledge. At the information level, basic data are given facts which mature data to be content suitable. For example, communication and messaging. Information is shared with a label (subject) through communications with a sender of the message and an audience who receives the information. Once information has been cleared for use, it is known to be business intelligence. Information as business intelligence is the output of data filtering and formatting. People’s wisdom has an important purpose within an organization and is valued for what it contributes to functioning and success of the business. Business intelligence or information is the input to all processes related to managing knowledge. Managing knowledge overall is the function of a knowledge environment. Knowledge uses data and information as a foundation that has gone through a validation process. Knowledge can be broad in nature and has an intangible aspect to it. The intangible pieces come from insight or from the experiences that is added to the information. An individual’s experiences can be subjective and difficult to manage. In the topic for this book, one’s experiences and insight represent a level of wisdom. In a business setting, wisdom is demonstrated by a person’s actions and interpretations. Therefore, wisdom can be more difficult to manage due to its intangible nature. Knowledge that has grown into wisdom comes from people’s experiences combined with their expertise and skills. Businesses invest in people, which means they are investing in their wisdom as well as their skill set.

(Il)logical Knowledge Management


Knowledge provokes understanding, understanding awakens wisdom, and both are instrumental facets to teaching. The basis of understanding to awaken wisdom is leveraged through learning, insight, experience, or through making a mistake or wrong decision. Understanding and wisdom are used to enhance business value. To utilize wisdom will depend on how well it is imparted into content populated in a knowledge environment and how accessible it is to the user community. To achieve business value depends on the quality of the content used. The aspiration of the knowledge environment is to produce content to a reach a logical state and distribute it properly. The pyramid of knowledge (Fig. 1.1) includes logical knowledge and it sits at the tip of the triangle. Logical knowledge is the ideal quality state to strive for and develop. Knowledge encompasses a blend of intangible information from individuals within the organization, linked to pieces of data and considered tangible information. It’ is not necessary that all three are used together, but it is important to know the

Logical Knowledge



Knowledge •Business Intelligence/ Informa on


Informa on

Fig. 1.1. Logical Knowledge Formation.

Sources and Segmentation


difference of the three parts to know which pieces are tangible and intangible to understand its context. The context of content supplies the knowledge processes. Knowledge is divided into two areas, and businesses commonly refer to them as tacit and explicit. Explicit knowledge is easier to express through words and stems from the data level (tangible). It is scientific and specific from an instructional standpoint. Employee manuals, technical documentation, and work procedures are good examples of outputs of explicit knowledge and can be transferred effortlessly across the organization. Tacit knowledge is not as easily articulated (intangible). Tacit knowledge is more personal and tied to an individual’s internal makeup of experience, skills, and intuition. These internal attributes make tacit knowledge more difficult to capture, distribute, validate, verify, replicate, and reinforce. As a result, distributing and communicating this type of knowledge with others will fail most times. Odds to succeed with utilizing tacit knowledge effectively increase with a detail-oriented structure which facilitates people to contribute their tacit knowledge to the program. Tacit knowledge is significantly tied to an individual’s accomplishments (practical use of their knowledge) from their experiences and their ability to relay this information to others (cognitive application). Establishing a culture to share tacit knowledge is more likely to foster participation in the knowledge environment. The knowledge culture is considered into the construct of a knowledge environment as well as involving setting up processes, tools, systems, policies, roles, and governing principles. These activities help user communities easily retrieve and discover content for knowledge use and reuse. The knowledge environment’s function is viewed as a forum that fosters knowledge sharing and collaborating with other groups of people. It also provides training and education on how to use the knowledge environment affectively. The knowledge environment also includes design specifications for the technical


(Il)logical Knowledge Management

landscape. The technology in the landscape is used for many tasks including segmenting and formatting content. Content segmentation makes finding content easier. Verifying, validating, and testing content makes the content useable and more easily understood. The knowledge environment is instrumental to helping transform data and information into useable and valuable knowledge. It also is instrumental to combining effective use of both tacit and explicit knowledge. Using the logical process helps this transformation take place. However, having the ability to enact on both tacit and explicit knowledge is a pivotal funnel to producing logical knowledge as well. Executing a combination of tacit and explicit knowledge is a bit complex, but a rule of thumb to help use this combination well is to recognize and identify the content that is coming from a tacit source. Remember tacit knowledge is more difficult to manage and distribute than explicit. This means content should be clearly labeled with an identifier letting the user know which parts of the content are based on theory or opinion (tacit knowledge). There is no piece of content that is better than the next. There is an extraordinary amount of knowledge and information that could be utilized. Collecting content from an open-sourced platform creates a massive amount of information from unmanaged sources. This setup for knowledge management produces many problems and users spend an excessive amount of time to get to the information that is needed. In a business organization, the setup of knowledge management on an opensourced platform is a quicker, easier, and more cost-effective solution to implement. However, this knowledge design is not effectively managing knowledge. It is consuming valuable resources and time that a staff is spending on searching and retrieving knowledge that could be spent on more productive tasks. For example, the organization has 5,000 employees and on average employees are spending an hour a day allocated to

Sources and Segmentation


searching and retrieving knowledge content. The math will show the cost in dollars is significantly high as well as resulting in a decline in productivity. Time and cost investments should be made up front. Estimate the investment allocation right at the beginning. The return on investment is greater when the time and cost investment in the knowledge environment are made up front. Doing so also reduces the risk of productivity being affected. The time and cost investment are on brainstorming, knowledge flow mapping, a technical blueprint, and other design work for the logical process. Making higher investments in planning and implementation stages for a knowledge environment will increase the odds of creating knowledge that is useable and efficiently distributed to its intended group of people. Knowledge management practices should be producing content that is understood and distributed to the appropriate groups of people that could utilize it best. In the logical knowledge structure, there are two important components to consider during building a strategic plan for managing knowledge. They are sources and segmentation. • Sources supply content and are authorized for use. • Segmentation includes processes and procedures to methodically portion the content to suit a specific requirement base. In this chapter, sources and segmentation are explained as to why these two components are vital to a knowledge management program. From a logical standpoint, expectations from a knowledge program is to produce coherent and useful content. To create a program that produces useful knowledge depends on a doable and realistic approach. There are many ways to consider approaching knowledge management. This adds a bit of confusion in selecting methods to use and makes handling knowledge even more challenging. If there are too


(Il)logical Knowledge Management

many different knowledge strategies, the odds are the level of complexity to create the right plan becomes fuzzy. To be clear, remain focused on the organization’s knowledge requirements and development of a high-performing and effective knowledge management environment. Developing and managing contents for a knowledge environment is mostly handled from a tactical level than strategic. This could expose knowledge to encompass contents, that is, illogical knowledge. Illogical knowledge has negative impacts within a business because it is unreliable, time consuming, and costly. Illogical knowledge is considered ineffective and could impact growth and quality sustainability within the business. The concept of logical knowledge in a knowledge environment is to minimize the use of illogical knowledge and increase the production of logical knowledge. In an environment with an open-sourced platform where knowledge is collected through many unauthorized and different types of sources, is the most likely area where illogical knowledge will outnumber logical knowledge. In this example, searching and retrieving content, filtering, sorting through content, interpreting content, and trying to make some sensibility through a messy pile of content are burdensome to the users. This is what affects productivity and wastes work time that is taken from time that could be utilized on a more productive task. It is important to reduce or eliminate all remnants of illogical knowledge in a knowledge environment. To do this, you need to be able to identify illogical knowledge. The best way is to know the signs of illogical knowledge. Signs that knowledge content could have illogical factors to it are: • Content without proper context for its intended use. • Tacit knowledge. • Unauthorized content sources.

Sources and Segmentation


• Unofficial or unauthorized knowledge. • Users are misinformed or content invokes confusion and misunderstandings. • The source where the content originated cannot be traced or proven. • Content was not vetted through a formal validation and testing process. • Content is fragmented. • Unable to decipher the content’s meaning or how to apply the information in a real situation. • Content is missing facts, or there is no way to validate the content for authenticity. • Content is poorly documented, unable to “take action” from it. • Unable to explain the value of the content and how effective the content is. • Users are spending too much time on search activities and still unable to find knowledge that is needed. • Users are using content on the wrong work tasks or communicating incorrectly to customers or other people in the organization. Knowledge management is a knotty process with activities that get entangled with each other. This is what makes knowledge management puzzling and captivating at the same time. There are also different interpretations of what knowledge management actually is. It becomes so frustratingly complex mostly from plans that are too technical or robotic. Another reason is because of inadequate delineation between


(Il)logical Knowledge Management

information management and knowledge management. In the early days of implementing knowledge management processes, common issues then had to do with collecting and documenting knowledge. This is because most knowledge is stored in an individual’s brain and not documented for use by other people. We are a long away from those days, and in the 21st century, knowledge management struggles are about having effective strategies to be able to sort through giant piles of information to package it appropriately for knowledge and make it available, useable, and reliable. There is still a degree of people’s knowledge that is undocumented but not to the levels of earlier times. The bigger problems today are from the volumes of data and information that are being passed to be knowledge without filtering it or packaging it with parameters. Knowledge plans address volume issues as well as the design models that will be used for affecting good management practices. In today’s business environment, itis more important to have design models and concise strategies for managing knowledge. Without a specific model for knowledge, it will be extremely difficult to manage, share, and apply content well. There is neither one clear way to help prepare properly for a knowledge program nor one simple way for knowledge management to work seamlessly. For the knowledge program to work well requires a significant amount of design work, preimplementation work, and governance planning up front. There can be well-documented procedures with high user adherence levels, and still users will experience complex issues while executing activities that are involved with knowledge. Managing knowledge is more than a structured program. Managing knowledge is a well-rounded environment complete with all parts to work together. These parts together provide a function that delivers knowledge to the right

Sources and Segmentation


individual or group of people, at the right time, and in a sensible useable format. Knowledge management is basic in nature and complex in execution.

IMPLEMENTING A KNOWLEDGE PLAN A knowledge management implementation plan needs to have a well-rounded strategy that plans how content is sourced, segmented, and validated. These three main steps are required to transform content to a state known as logical knowledge. Logical knowledge is a good model to use to develop a knowledge environment function. A knowledge environment not only produces logical knowledge and distributes it well but also addresses the complexities that could be experienced when executing on a plan for knowledge. For example, complexities could include: • No formal work procedures in place for creating knowledge to align to specific scope or list of criteria. • Knowledge is not shared between staff. • Repeating the same mistakes. • Information systems – missing data; information stored for knowledge is not tested. • Knowledge that is not documented and should be deciphering what knowledge needs to be documented. • Numerous repositories being created without the content being validated, tested, and maintained to a set of standards.


(Il)logical Knowledge Management

• Unable to link knowledge to the appropriate audience or user group. • Users unable to locate knowledge content easily and or use it in alignment to their job. • Maintaining content to be current with the organizations needs and strategic goals. • Linking content to build knowledge relationships between content. • Unable to find experts within an organization. • Unable to trace content to its original source or validate its life expectancy. The best method to overcoming obstacles is to know what they are. The above are examples of what to look for in the organization. When an obstacle is spotted, document it with all issues found, which would be considered a roadblock to the construction of a knowledge environment. The obstacles within your organization are documented in the knowledge planning phase. This is assuming knowledge is a central focus of the organization and the organization supports a plan to create a centralized knowledge environment. Business intelligence sits across the organization and can be found in every department, group, functional team, and project team. However, information management is not a centralized function. It is left up to staff to find what they need and build relationships with other groups of people and departments to share crossdepartmental information. In a business intelligence model, there is no requirement to share knowledge someone has from experience that is not a requirement for a job, a process, or a function. People are most likely reluctant to share knowledge on their own. This is addressed through motivating a knowledge sharing culture.

Sources and Segmentation


Knowledge management is a centralized function to support a sharing environment without threat to loss of job or other dire consequences. Collaboration and culture of the knowledge environment are covered in Chapter 2 and is a significant part to its success. It is important to realize for a business to grow and succeed in their market that a knowledge environment needs to be a central function. A centralized function using proper validation procedures. Validation is contextually difficult to define. It involves people to agree on what the validation criteria is. Getting the appropriate people to define and agree on validation criteria is done in the brainstorming phase of the logical process. In the logical process, validation is an internal process and needs to be defined as such. The conditions to define validation in the knowledge management environment are equated to value, consumption, and trustworthiness (Fig. 1.2).



Fig. 1.2. Validation Conditions.


(Il)logical Knowledge Management

Many professionals still believe a good set of best practices are all that is needed to succeed with knowledge management. This is false. You need more than best practices to invoke a valuable and useable knowledge program. Best practices are helpful in developing processes and setting up a framework. There is so, so, much more to building a knowledge environment that produces meaningful and valuable content. Developing a robust knowledge environment puts a functional foundation in place for knowledge. A knowledge strategy, business information assessments, foundation design, knowledge processes for filtering and validation, segmenting sources into proper categories, and maintenance are assembled to produce logical knowledge. In addition to producing logical knowledge, it creates an environment where content is easily found and retrieved. It will take some groundwork to learn about the groups of people in the organization and what type of knowledge would help add value to their roles and job functions. To construct a functional environment producing logical knowledge requires a comprehensive program to produce a good design as well as clear policies and controls. The knowledge environment will set a tone from the business culture. The cultural aspect is important to ensure that it is a culture supporting the environments acceptable structure. For example, one reason why people are reluctant to share their knowledge that is not a direct responsibility of the job requirement is because of fear of job loss due to downsizing. Downsizing is a prominent trigger to an organizational quest to collect knowledge. This is important to be clear on; the knowledge environment (logical knowledge process) is not created to only collect knowledge. It is a forum of sharing, distributiong, and producing logical knowledge for growth. Growth applies to people and all groups across the organization. It defines how well knowledge programs will perform. Success with managing knowledge is relative to the quality of

Sources and Segmentation


content it holds and the level of value it provides to its users. From this perspective, we start at the beginning by building a foundation because the foundation is the substance that holds the entire knowledge environment together. Knowledge sources and segmentation can be found at the beginning of a knowledge trail. A knowledge trail is an essential lifeline to the environment where knowledge is manufactured. Where does knowledge come from? It comes from variable and reliable sources. In the age of collaboration, there is a risk to forming an environment that is unmanageable and in this context much of the content can be discredited. The following case study outlines a technology company’s struggle with unmanageable and illogical content. CASE STUDY – PART 1 BABM is a technology company, headquartered in NYC. The company provides technology management consulting services, managed solutions for networking, and help desk services. BABM’s major goal is to provide world class services for network and help desk services. Their goals to accomplish over the next 12 months are: • To increase turnaround time for service design work by utilizing existing knowledge. • To improve consistency on network designs by having a standard design model to begin with. • To improve the customer experience with BABM help desk services. • To help clients lower their costs per call and incident volumes by implementing core IT service management (ITSM) business models.


(Il)logical Knowledge Management

BABM leadership is turning to knowledge management as a main part of their strategy to achieve these goals. There is not a formal knowledge management program in place; however, some staff within information technology and sales implemented some knowledge management as best practices. BABM leadership decided to leverage existing strategies and processes already in place as a means to improve the customer experience and to minimize the high amount of time redoing network designs from scratch. The CTO is teaming up with the department heads from the business to strategize and determine next steps. They agree to start with a formal ITSM evaluation to take place with a Management Consulting firm specializing in ITSM programs. The evaluation was completed over an 8-week time frame. The evaluation uncovered several core issues that are impacting service quality to BABM customers. A detailed report was provided to the CTO and shared with department heads. The issues reported to the CTO and department heads are mostly related to: • Their methods for managing knowledge content. • Ineffective use and inadequate compliance using systems and tools to support knowledge. • Their ways to disseminate and distribute knowledge are ineffective. • Their approach to knowledge management is decentralized and unsupported by key personnel. They have multiple bodies of knowledge and each is managed by their department. Findings show some redundancy on effort and content. • There is a gap between qualifying information and content validation. • There is no formal process in place to distribute and share knowledge.

Sources and Segmentation


The causes to these issues need to be carefully analyzed, as these are major influences to creating high costs for service design work, and cost decisions are impacting the quality of service designs being created. There are other issues identified; however, the above core issues are of highest impact priority for BABM in order to achieve their goals on time. The CTO and department heads are joining efforts on a project they call Evolve–Solid. Evolve–Solid is a program to develop an integrated knowledge management structure for the entire company. Evolve–Solid will also address the issues identified from the ITSM evaluation, update outdated technology that includes implementing a knowledge management system and tools to support the new knowledge management structure. The staff to support Evolve–Solid include a Program Manager and two Project Managers, one for process delivery and the other overseeing technology delivery. A Knowledge Manager was hired, who is responsible for assembling a knowledge management team that includes a Knowledge Management Consultant to head design and development, a compliance analyst, ITSM Consultant, and several Knowledge Content Managers. A formal Knowledge Management Office (KMO) is established to bring the vision for Evolve–Solid to life. Their plan was fully executed. A knowledge structure is developed and implemented in seven months. Knowledge management best practice process framework and systems are implemented. Several months after go live, user complaints became increasingly high, even though there is some improvement on the core issues. The Evolve–Solid program team did some research on the plan implemented and investigated user complaints. The investigation revealed there were new and more complex issues occurring from the new knowledge management environment. The issues are so


(Il)logical Knowledge Management

convoluted; it is the produced problems that seem too overwhelming to solve. For example, knowledge content is worsening service quality and creating significant delays to a point the business wants to do away with the new knowledge management structure. The quality of the content from the knowledge management systems is not as stellar they believed it would be. For instance, there are user instructions for a business application, which was supplied by an employee using this application. The user instructions were not clear, and reports showed people following it were making mistakes. The project team’s investigation identified an issue with verifying and validating content, and sources for content are not put through an approval process. An analysis showed these new perplexing issues are mostly related to the illogical state of the information used to build knowledge content and how the sources for knowledge are selected. The KMO puts a structure in place similar to a wiki-like platform. This platform was chosen due to the simplicity and short time lines to implement. The knowledge platform is an open door for anyone to record what they perceive as knowledge and is able to contribute said knowledge as long as it relates to topic. The design was simple and the search criteria unfriendly except if you are a savvy user capable of advanced Internet searches. Other issues users complain about have to do with informal methods and distribution of knowledge. The design is not set up to distribute knowledge as much as it is set up to collect knowledge in any form, on any topic, from any person within BABM. Stakeholders and users all agree there is a critical need for a knowledge management environment. They can see the end vision and can visualize many benefits to the program once these new issues are resolved. They decided to bring in

Sources and Segmentation


consultants who are experienced in dealing with complex knowledge management issues.

LOGICAL KNOWLEDGE AS AN ASSET One of the key functions in modern day business is managing knowledge. Knowledge management is a well-organized way of handling information and resources. This involves sharing knowledge, reusing knowledge, and providing intellectual capital (an asset in business). The business has sources of intellectual capital that sits at the corporate level and shared with every person in the organization. Intellectual capital comprises business information. There is intellectual capital that is sorted by various topics, for example, by job type, department, and customer. All these aspects of intellectual capital are considered part of business intelligence (information). Knowledge that is derived by an individual’s intellectual capital is an example of tacit knowledge. The individuals own their intellectual capital, and they may share some of it with the business, but the business does not own it as it was not created specifically for the organization. Intellectual capital from an individual or an external source can be utilized; however, a legal contract and disclosure agreements would be required. There are some tricky parts and blurred lines between intellectual capital that an individual owns versus what the business will own. This is commonly worked out between the individual and the legal department within the organization. If an employee creates intellectual capital to fulfill a job requirement, the organization owns it and considered business intelligence. Business intelligence form knowledge assets and knowledge assets live in the knowledge environment.

(Il)logical Knowledge Management


Knowledge is an asset for the purpose to create value. Value is described as the content used for knowledge can be applied effectively, it is easily understood, and the user communities are able to meet their goals. Strategically, knowledge is formed for a purpose and focuses on resources to fulfill the purpose. Some examples of knowledge uses are given in Table 1.1.

Table 1.1. Examples of Knowledge Use. Knowledge







Business plans, design plans

Insight or advice

Strategic or

Interpreting information,


forecasting, building solutions, theorizing, predicting outcomes of a problem situation



Time lines, assessments, road maps



Focus group notes, meeting notes, brown bag events, emails, messaging, specific business information, i.e., customer data

Work instructions


How to use a business application; how to set up an email signature




Troubleshooting a system issue; resolving a customer problem

research Processes

Tactical or strategic

Proactive processes are considered strategic, for example, proactive problem handling and forecasting budgets, reactive or routine processes are tactical such as operating manuals

Sources and Segmentation


Knowledge can be formed around a user base, and in organizations with a hierarchy, knowledge can be structured with content leveling. Content leveling is for information that is geared toward a specific audience in the hierarchy, i.e., company staff, consultants, Group or Team Lead, Managers, Executives, and Corporate Business. Business knowledge also factors compliance standards from a corporate and departmental level. Plans for new business setups or expanding an existing business should include defining knowledge as assets. There should be guidance on establishing governance and policies for the knowledge assets the business creates, not only for regulation standards but also on policies for authorizing content and the sources that supply content. Knowledge planning activities involve collaborative efforts. Collaboration (Chapter 2) has different meanings between individuals or between different groups of people. Most likely these meanings will conflict with each other, so it is important to define what collaboration means and include it in the plan. Collaboration in a knowledge environment if not carefully controlled will be a contributing factor to invoking risk and impacting content quality. Knowledge content to be formed as an asset should only come from authorized sources. Collaboration occurs in a crossfunctional way, and to avoid replicating knowledge, and to ensure it “fits” properly, content is sourced only from allocated and authorized sources. Authorized sources for knowledge mean the container of knowledge has gone through a cycle of review and qualification steps to indicate the source is credible and reliable. The goal is to validate sources and certify them as contributing knowledge providers. Avoid using all knowledge that is not traceable to a source and/or originator of the content. There are different types of knowledge to consider within an organization, and where it comes from will determine its


(Il)logical Knowledge Management

strength to serve its purpose properly. The word knowledge will have several different meanings to different people. There are various ideas and methodologies for managing knowledge and various technologies available to support a knowledge environment. However, there are missing pieces that need to be connected in order to create a valuable environment with reliable sources for content and build knowledge assets successfully (Fig. 1.3: Knowledge Assets). There is a significant amount of information available for designing knowledge processes that can be confusing. Best practices for managing knowledge endure and offer good insight to design processes well. However, best practices are not ideal on implementation strategies and approaches for a knowledge program. A knowledge program that constructs knowledge assets well. The program should be able to implement from best practices into a coherent living entity (the knowledge environment). Through the logical knowledge process, a sound model is provided to design the knowledge environment foundation. The logical knowledge process will evolve a knowledge environment to deliver a significant return on investment and user benefits. An environment for knowledge and its sources for content are linked. Some may say, there is not enough information to fully understand what knowledge management really is. There are so many similarities between content management, information management, and knowledge management that make a difficult area to understand. To sort out what is needed, consider each of these practices separately and remember knowledge management is producing quality packages of knowledge and packets are compiled for specific uses. Stay focused there and avoid taking on too much of it at once. Transitional phases to transform an existing environment to a logical knowledge environment will take some time to accomplish. There are many variables

Sources and Segmentation


to consider and the time to sort it out well can be significant. This can be time well spent when it is done with perspective to ration information and appropriately align with an organization need. Defining knowledge management for your business is more about: • Complete understanding of knowledge management. • Constructing a healthy, high-performing knowledge environment. • Collecting and segmenting knowledge content properly. • Filtering information for appropriate and useable content. • Validating sources providing knowledge and that it aligns with specific criteria.

LOGICAL KNOWLEDGE Logical knowledge is formed at a strategic level and executed on a tactical level. Logical knowledge ensures authenticity of the content it uses. Collecting knowledge is not the same as creating an environment that produces “useable” knowledge. Useable and logical knowledge come from information that is validated, verified, and tested. This is a process to ensure content is transformed to logical knowledge (Fig. 1.4: Logical Process). Logical knowledge provides the most value and serves a purpose such as to carry out a task or shed light on a situation to understand it better or to solve a problem. Validation in the logical knowledge process cycle assures the purpose of content is suited to the appropriate receivers of the knowledge being shared with them.

(Il)logical Knowledge Management


Informa on

Business Intelligence

Knowledge Assets

Logical Knowledge


Fig. 1.3. Knowledge Assets.

Data/Information Filtering (Filtering gives context to the knowledge content)

Data /Information

Content Source



Criteria Knowledge Environment


Segmentation & Testing


Fig. 1.4. Logical Process.

What is logical knowledge? • Logical knowledge is data or information that has proper context for its intended use and credible. There is a clear understanding on where content comes from and proven through a consistent authorization and validation process. • Logical knowledge is formed from unique and different sources. When combined from different sources, it becomes

Sources and Segmentation


integrated. Integrated knowledge is developed to a useable state where people can clearly understand the knowledge and apply it effectively with minimal support. Users of knowledge can establish and explain this knowledge and be able to decipher its meaning, use, and what parts of the knowledge apply accordingly to the user’s needs. • Data that are processed and given actual facts. • Information that is processed to be actionable. • Other characteristics of logical knowledge is knowing and being able to explain the value of knowledge, the life span of knowledge that demonstrates its validity and criteria, and how the knowledge evolves during its life span. So, how does information become useful and viewed to be credible knowledge? It begins at the source of data/information. The logical process includes instruction on: • Brainstorming – How a strategy forum or project will deliver content to meet specified criteria. Where the data/information will come from and the selection process to determine what is authorized as a business information source for content, who owns the content, who is authorized to contribute knowledge, and who is assigned to maintain the content. • Collecting – Covers the systems and tools for the automated processes to gather the information, for manual methods, procedure detailing the steps, roles, and responsibilities involved to gather the information.

(Il)logical Knowledge Management


• Storing – When information is collected, it needs to be stored somewhere. Select a common single area with repositories with enough capacity to store the content. Ideally, this is the knowledge platform that will be used for the knowledge environment. If not, then select a transitional holding store. • Categorizing and classifying – This is filtering that takes place along the path to reach the knowledge environment. Categorizing and classifying the information helps carry out the segmentation tasks more efficiently. The main phases of logical knowledge management are shown in Table 1.2. There are business intelligence processes already in place within an organization which produces official business information. These processes are used as inputs to the logical knowledge process. There is not a new suite of processes to consider with using the logical blueprint. Rather it is a model to interconnect the knowledge environment to business intelligence and invoke filtering to a higher standard to differentiate logical content from illogical content. This process heightens the ability to make decisions during tasks when shaping content into its contextual meaning. The logical knowledge management process is designed to coordinate existing activities handling content, information, and knowledge into one cohesive high-performance process.

Sources and Segmentation


Table 1.2. Logical Knowledge Phases. Logical Knowledge


Process Phase Finding knowledge

Knowledge is found within information systems, manuals, and from subject-matter experts. Content detectives work within this phase to discover information in the business and across the organization that could be leveraged as valuable content and formed into a knowledge asset.

Sharing knowledge

Occurs from the willingness of people to share their knowledge. The cultural aspect influences people’s willingness to share and the knowledge environment provides the appropriate tools and systems to share efficiently and effectively. There are guidance principles to help with knowledge sharing. For example, guidance on how to select the right content to share, how content is related to topic, and how to distinguish from sharing too much or too little information. People are less reluctant to share knowledge when they have the right amount of guidance and resources to do so.

Recycling knowledge This phase is a time-saver. Recycling knowledge eliminates the time it takes to start from scratch. Caution to avoid plagiarizing and using copyrighted or trademarked content. Compliance training on handling documentation and labeling will help guide people to know when and what content is good to be recycled. Explicit knowledge within a business is a good prospect for recycling knowledge. Replicating people’s ideas and their tacit knowledge is not a good prospect for recycling knowledge.

(Il)logical Knowledge Management


Table 1.2. (Continued ) Logical Knowledge


Process Phase Producing

This phase covers where content is produced.


Producing knowledge is about linking to authors, subject-matter experts, creators, writers, etc. It is the trail that you follow and it leads you back to the content location or where the content originated from.

Knowledge asset

A knowledge asset is formed from the content that was collected or shared, and it is known where the content originated from. It is an authorized packet of information to be used in the knowledge environment and distributed within the organization.

KNOWLEDGE TRAIL A good way to discover knowledge sources is by following the knowledge trail. It is a trail within the organization or to external sources linked to the organization. To track where knowledge was sourced from and who the originators or creators are requires knowing some basic details to begin tracing it to its roots. Knowing where knowledge essentially starts is not something that is automatic or easily spotted. Knowledge management is intangible, vast, and elusive. Information management is systemic and scientific. There is a significant difference between knowledge and information (Table1.3). If you want one word to describe what knowledge management is, that word is PEOPLE. This is where knowledge begins.

Sources and Segmentation


Table 1.3. Knowledge vs Information Management. Knowledge Management

Information Management

• Is a blend of learning,

• Is based on data and facts.

experience, and application. • Is not easily identifiable because • Is easily identified and it is elusive and vast. • Knowledge management handles content to create

organized. • Information management handles data and information sources.

knowledge assets. • Creates an environment for learning and transformation.

• Information management manages business intelligence from systems, documentation, etc.

• Human factor is key. People are • No human factor needed and an important role in knowledge

managing information can be

management. They are creators,

done outside of a people

validators, illuminators, users, and presenters.


People illuminate, design, create, contemplate, validate, demonstrate, present, and use knowledge. There is a droplet of something that sparks an idea for knowledge content. Content for knowledge grows through people’s experiences, perceptions, and intentions. This droplet is like a seed that produces a plant. The condition of the plant depends on the condition of the seeds. The same rule applies to knowledge. The quality and condition of knowledge content depends on the condition of the knowledge environment. The condition and usefulness of knowledge depends on the validity and reliability of the source it came from. A knowledge trail begins with knowledge collection from validated and reliable sources. You would not randomly collect seeds


(Il)logical Knowledge Management

and put them just anywhere. The location, soil condition, plant food, and gardening tools are selected before planting seeds. There are different types of seeds with unique planting and care requirements that are considered as well. While designing a knowledge environment, think of it as a Garden of Wisdom. A Garden of Wisdom will evolve informational content from a specific set of handling and care requirements. This is the very critical beginning to producing credible and useful knowledge that is referred to in this book as logical knowledge. Useable knowledge fits a purpose and comes from creditable and properly segmented sources. When content is collected from these sources, it is put into the garden. The garden represents the knowledge environment. To ensure the garden does not get overgrown with weeds, the source is validated, organized, and filtered to specific criteria. Any data outside of the criteria definition are considered a weed. In order to organize and filter data effectively, you need to clearly define content and segmentation procedures. These procedures filter data at the source (Fig. 1.4: Logical process), and it lays the groundwork for the content to grow and evolve to a useful and useable level. • Useful content fills a purpose and produces useable knowledge. • Useable knowledge pertains to the quality of the content.

KNOWLEDGE SOURCES There are different types of knowledge sources to consider. The sheer volume of information to acquire is not as important as the quality and significance the content possesses. Remember, the meaning and context of the content carries

Sources and Segmentation


more weight to the value it provides than volume. Do not collect information and knowledge just to collect it. Use specific criteria and stay on track with it. Use the logical process to filter the information to logical knowledge. Use specific criteria for: • Content collecting methods that are acceptable and authorized. • Categorizing, classifying, and organizing procedures that produce standardized ways to systemizing content. • Editing and storing guidelines. • Documentation management – version control and management. • Collaboration and linking people together on relatable topics. • Cultural support and fostering willingness so people will share their knowledge. • Providing methods to capture tacit knowledge. • Installation of appropriate systems and tools to support the knowledge environment. • Content detectives to seek out new content. • Communities of practice and their involvement in the knowledge environment, i.e., learning, technical diagnostics, onboarding, etc. Points to consider when selecting sources and putting it into appropriate context are: • How the information was created. Identify the person or group where the information originated. Ideally identify the


(Il)logical Knowledge Management

person or entity who owns the information. Name the authors and their expertise or experience they have on the topic. • Identify where the information was created and when. Specify the life span of the information and how long it is valid. Include update requirements to keep content current and ensure it maintains relevancy to the topic at hand. • Detail how the content is been used and whether or not it proved to be successful. • Detail how the content was verified and validated. • Research if there are other sources for this type of knowledge, if it can be used, and if it is similar to the content under review. • Use a standard test plan like the logical process to ensure the content is examined thoroughly. Knowledge sources can also be known as a knowledge base. When considering information from a knowledge base, consider the aspects for logical knowledge and determine if the content was examined and verified. Most likely, content from a knowledge base will contain information from many contributors and it has not been examined properly. Content in knowledge bases are most likely filled with unedited, illogical, and messy information. Tagging is done by content reviewers of the knowledge base to select specific information to be allocated to the knowledge base. Knowledge bases are databases holding content and span across a business. They act as a repository for content. Knowledge bases can serve parts of or the entire organization. The knowledge bases are filled with content relative to a

Sources and Segmentation


fundamental purpose. For example, troubleshooting a specific desktop software issue can be supported by a knowledge base containing desktop software problems and solutions. Knowledge bases that are populated in an openly public domain can become overgrown and filled up with illogical knowledge that does not fit a fundamental purpose. Content in the form of knowledge and when applied accordingly to situations should enhance understanding. Content is cultivated from individuals. Each business area should bring knowledge together to form content and contribute to the knowledge environment and such content should be reviewed, validated, and verified. A knowledge environment is created with all existing knowledge in a company and it is packaged with a core set of good management practices. Good management practices form consistent methods to how knowledge content is collected, stored, shared, distributed, and applied. These management practices are different than information management processes. Knowledge bases could also contain data imports from management systems where it is unknown what level of quality assurance was applied to the data. Raw data is not an ideal prospect for building logical knowledge, but given proper context combined with logical filtering and validation, there can be some value in it. There are many different outlets for data sources. This particular area is critical because it is easy to entangle data sources into one outlet. It is important to recognize the outlets of the sources first. Then link the data source to the associating outlet. Public outlets are considered to be open sources and not an ideal source for logical knowledge. If your knowledge environment uses content from a public outlet, then stricter review and validation procedures are needed. Stricter procedures will reduce the amount of illogical knowledge and improve the quality for a logical knowledge state.

(Il)logical Knowledge Management


Examples of public outlets are: • The Internet; • Blogs, books, seminars; and • Social media, wiki-type platforms, etc. Data linked to these outlets are sourced from the public. For example, libraries, businesses, individuals, charities, entertainment, gaming, education, content marketing, Facebook, LinkedIn, Instagram, Pinterest, etc. You can see using information from data supplied by public outlets is almost impossible to validate properly for it to meet logical knowledge criteria. Knowledge stemming from a pubic source most likely in nature would be considered to be illogical knowledge. Proprietary outlets are linked to sources that are more controlled, monitored, and can effectively be traced to the creator and confirm its validity. Proprietary outlets are typically internal and can be found within occupational silos. Data and information linked to proprietary outlets are ideal to fit the logical knowledge criteria. Examples of proprietary outlets are: • Internal databases within an institution or business • Employees and customers • Suppliers, vendors, consultants • Content through licensing agreements, etc. Data sources linked to proprietary outlets mostly come from within an organization. For example, employees, projects, departments, suppliers, customers, volunteers, authors, programmers, emails, cookies, applications, surveys, etc.

Sources and Segmentation


Knowledge sources could supply content in what is considered raw form. Logical knowledge is screened by reasoning and from it draws conclusions, makes decisions, and establishes borders around the content to fit the criteria for context. When content is provided, the criteria for context it will produce value and the value increase comes from how well the content is refined. Reasoning practices is what establishes the difference between logical and illogical knowledge. Illogical knowledge usually is sourced and formatted to fit a centralized and public platform in which users can access and search, i.e., wiki. There is not any form of filtering or reasoning to ensure the contextual yardstick is used to appraise its value. Reasoning collects the facts and generalizes the information to fit into proper context giving it proper meaning. A common filter for reasoning is shown in Fig. 1.5. Using the basis of the following four counterparts will help shape the context of knowledge content. When applying these principles, take into account the source of the information and its reliability. Once the source of content is distinguished and

Theory and

Planning and

Cause and

Idea to the

Fig. 1.5. Content Reasoning.





(Il)logical Knowledge Management


Table 1.4. Content Reasoning Counterparts. Reasoning Counter Description Parts Theory and fact

Separate the factual bits of information found in the content from theory or abstract information. Decide how much of the theory applies to the topic, can be relayed easily, and adds value to information.

Planning and evidence

After building content from fact and adding the valuable theory components, find the evidence to support the facts. Reasoning in this category isolates content that is factual and requires data to layout the content in certain way.

Cause and effect

Find the cause and effect patterns and relationships in the content relative to topic. Match up each relationship across different segments of content.

Concept to logical

This is the end-to-end view from conceptual


knowledge to logical knowledge. The path content takes to produce logical knowledge from the initial idea or request. In this reasoning stage, separate the idea from the output. Review the content and link the segments that associate with the original concept in how the knowledge will be used. Determine which segments are needed to produce logical knowledge.

deemed to be reliable, analyze the content in segments on each reasoning category (Table 1.4). Knowledge is an asset that is a central focus point of awareness and balance within service delivery, customer experiences, and business operations. Reasoning also highlights the importance on discarding the illogical pieces of content. Filter out what is not relevant, useful, or has any bearing of value.

Sources and Segmentation


KNOWLEDGE CONTENT SEGMENTATION The second important component to knowledge management is content segmentation. Segmentation helps to put pieces of content into spaces to avoid a sea of useless knowledge. This is not a common practice, due to the nature of it being laborious and a time-intensive practice. Automated segmentation practices are commonly used today for market or customer data sectioning. Typically, in a standard knowledge management program, processing content includes categorization by type, which happens at a higher level than segmentation practices. Content segmentation is merely identifying and establishing the separator element. Segmenting content is a bit tricky and you may feel for nonmarketing data that are not worth the effort. Although, there is an intricate and finite level of detail involved, it is equally important to segment information for nonmarketing data. Remember, once a sale is made, the rest of the business’ performance determines the life span of customer relationships. This should not be a discouraging factor and using the logical knowledge process for segmentation will help. In the logical process (Fig. 1.3), segmentation steps are executed after criteria are definitively defined. Segmenting content establishes a beginning and an end. It creates the borders for which the content will fit in. Carefully select content that fits within the borders (criteria settings). Setting specific criteria will scale down on haphazard content selections which are not aligning with criteria or a purpose. However, there can be a percentage of content that is selected to be subjective. The goal is to narrow this percentage to a lesser amount. The lesser portions of subjective content increase the value of logical content. Logical content is the goal and scope for segmentation. Keep segmentation activities to within scope and remember to discard pieces of

(Il)logical Knowledge Management








Fig. 1.6. Segmentation Key Process Activities.

information that can be skewed or unable to validate (Fig. 1.6). • Prepare the content for segmentation and ensure it meets the specified criteria for how it will be used as knowledge. • Locate individual segments and identify a starting and ending point for each individual segment. Select segments by: – Workflows, programs, projects, user base, groups, roles, topic, date, category, author, function, etc. – Take segments as you would read a short story. – Be sure there is a logical summary of information and group them accordingly. – There can be a subsegment with the main sections. • Edit each section and link the pieces of information to one or more criteria points specifically defined for the content. Finish editing for each section. Any section which cannot be linked back to a criteria point is discarded. • Pair and link up all the segments together that are related into the appropriate form of documentation. • Bundle by grouping linked segments into packages in preparation to distribute content to a storehouse in the knowledge environment.

Sources and Segmentation


• Interpret and understand the meaning of the grouped segments, read through the content, and ensure content is rational and meets the knowledge purpose. Breaking down content into smaller amounts of information is highly recommended to minimize risk of illogical content slipping through. The best approach is a balanced method of automation with human oversight and intervention. Human oversight and intervention bring a higher level of quality reinforcement to the logical and segmentation process. In today’s technological world, automating segmentation is probably the preferred method; however, quality controls for segmentation are the same for manual and automated methods. When it comes to automation, it is important to identify if users trust content that is validated by technology more than they trust knowledge from people. In reality, there are two types of knowledge management environments, and there is not one better than the other. The first one is a technology- oriented solution, and the other is a people-centric system. Part of the knowledge plan is to define which type is appropriate for your organization or perhaps a blend of both. It’s very important to know if a user community is best served by a technology-oriented solution or by a people centric system. Quality control during segmentation is where risks to content integrity are spotted. Use quality controls like a fish net to catch the bits of information that do not meet the criteria, are illogical, can be skewed, or cannot be traced to an authorized source. Automating segmentation is done by algorithms. Algorithms are used for segmentation on data which can link to cue words in text or by images. Between the starting and


(Il)logical Knowledge Management

ending point of a section to segment, the algorithm is designed to pick up on these cue words and pull the information into a program which will then utilize the data for content. This is one area where controls are extremely important and information pulled from its source is run through a rigorous validation process. Segmentation seeks to group together related data. Data that are not related or similar in content will span across different content segments. In the Case Study – Part 1 (Chapter 1), the issues BABM were having stemmed from not segmenting content into compartments related to the same topics. To address this particular issue, BABM executed on content segmentation to improve the accuracy of content to topic. Remember in the case of BABM, the knowledge environment set up was more conducive to collect knowledge than it was to properly examine and authenticate. The initial knowledge management program also did not consider or properly plan for knowledge sharing and distribution. Segmentation helped BABM improve some of the problematic areas experienced with the new knowledge platform. BABM invoked segmentation by: • Reestablishing the criteria by department. With the new criteria in place, they sorted through all the content and logically set variables for sectioning. • They developed custom algorithms to automate some of the segmentation process on cue words supplied by each department. • They assembled a review team to manually sparse the content that did not meet the specifications for automation and to validate the outputs of content that was organized through automation. This is a project team that helped mitigate the program issues. A quality role is established,

Sources and Segmentation


called Content Reviewer and this task is assigned to this role. The model had one Content Reviewer role for every two Content Managers. • A separate team was put together for the governance controls. BABM staffed this team internally with existing employees: one from compliance, one from corporate business, and one from information technology. • QA team was trained and assigned content testing responsibilities. • Each segment of content went through the logical process. All content that was processed and signed off by quality reviewers was moved to a new storehouse in the knowledge environment. Tips for sourcing content and segmentation: 1. Create templates and manage them through effective change control. Automate templates where applicable. • Use portal technology as a front door to collecting information for content use. 2. Stay consistent with small details across similar topics. 3. Update content regularly to maintain relevancy. 4. Add context where possible to frame the information to useable and logical content. 5. Create a framework within the knowledge environment for content creation. 6. Decipher what is important and what is not. Avoid the information overload syndrome when creating content.


(Il)logical Knowledge Management

Too much information really is a detriment to effective use of knowledge. LOGICAL KNOWLEDGE ENVIRONMENT BENEFITS Everyone will most likely agree there are more benefits associated with building a knowledge environment than there is with implementing a knowledge management process. There are more formalities and strategic components derived from a knowledge environment that increases the number of benefits, especially within the culture for collaboration benefits. Knowledge management although with restraints on some informal practices will still produce many benefits. Invoking a formal plan to create a knowledge environment that utilizes and manages knowledge as an asset will produce logical knowledge and promote collective work ethics producing even more benefits. This is because most benefits in relation to knowledge management are derived from the strategy and governance aspect. The knowledge strategy and governance framework increase beneficial value to the knowledge it creates. The knowledge environment strategy will aid in achieving the most benefits. Common benefits to expect from a knowledge environment are: • Reduces time spent on routine tasks. • Helps to streamline decision-making. • Reduces redundant documentation. • Saves time in routine work tasks. • Expedites processes and improves process performance. • Reduce redundancies in processes, tools, documentation, and work tasks.

Sources and Segmentation


• Reusing internal knowledge that is proven to produce results. • Increased productivity and overall growth of capabilities across the organization. • Transparency in process, diagnostics, and problem solving. • Decrease in the number of mistakes made across the organization. • Better knowledge on customers and customer retention. • Improved customer satisfaction scores. • Improved communication with customers, among staff, and across the organization. • Improved response rates to customers. • Better teamwork and collective collaboration. • Improved competence development within the organization and with new hires. • Improved staff involvement and their willingness to share knowledge. The knowledge environment is a good way to make the most effective use of knowledge resources. There is an opposing side to benefits and that is the obstacles that can get in the way to producing a knowledge environment with a unified culture. There are many variables that differ between organizations that will influence what barriers get in the way to developing a unified culture and a high-performing knowledge environment. Some common barriers you may encounter are: • A culture that prevents people from developing a perspective on important decisions.


(Il)logical Knowledge Management

• A culture that enables people to deny access to information that is required to carry out a specific task or to address a specific issue/situation. • Lack of credible content sources and/or content with too many illogical aspects to it, which impacts one to fully understand it or apply it appropriately. • The viewpoints of being too internally focused within occupational silos that shadow the ability to see the overall picture. • Strategies that vague and provide little to no guidance. A strategy that invokes confusion is not a strategy at all. • Messy metrics and the inability to measure the effectiveness of the knowledge environment.


Knowledge is a valuable asset and instrumental to a business’s success. The value of knowledge is interpretative based on the content involved and should be protected as an asset. A turning point occurred years ago where in business it was challenging to know who you could or could not share knowledge with. Today, it is completely opposite and all about collecting massive quantities of knowledge, and it seems acceptable to share it with anyone who could benefit by it. This makes it risky for business because there is knowledge derived from business information that is restricted to specific user access. Access controls apply in knowledge management to protect knowledge assets from being shared to unauthorized parties. Business compliance provides clear guidelines on how to handle access and sharing rights within the organization for information. These same guidelines need to be considered when putting together a knowledge management strategy. These are compliant and regulatory requirements from information and content management that are carried into a knowledge management


(Il)logical Knowledge Management


plan. This is because information from business intelligence is the input to knowledge management so the content that we are packaging through knowledge processes needs to have the appropriate level of security and complying controls around it as well (Fig. 2.1). Knowledge is sourced from various repositories and through a formal process data is transformed into knowledge. To complete the picture regarding knowledge, it is important to add people to the data transformation model in creating

Gain understanding

Describe how to handle the situa on Describe the situa on. What is happening?

Role/s of subject ma er expert/s

Fig. 2.1. Using the Right Data.




Knowledge of Something



Environm ent



Fig. 2.2. Content with Context.

(Il)Logical Knowledge Process


knowledge. People come before data, regardless if the data are collected manually or automatically. The maturity of knowledge is essential to the level of wisdom an organization owns. Wisdom is obtaining full understanding of an organization in correlation to the various departments in it. Information supplies the content to package as knowledge and people supply the wisdom to the knowledge from their insights and experience. Information plus content equals knowledge. Wisdom plus knowledge equals knowledge assets. Information focuses on the measurements of three key areas: 1. Quality; 2. Speed; and 3. Cost. Information is used for various reasons and comes in many different forms. Despite the differences in data, the types of data available to the business remain constant with some variations. Variations contribute to the maturity of data to become a knowledge asset and are used across the organization supporting different areas and services. Decisions are only as good as the knowledge available at the time a decision is needed. A decision is made based upon the knowledge available at the time and its interpretation of it. Wisdom does not come in a bottle and the handling of knowledge will determine the quality of its use and its role in decision-making. The issue of collecting obscene amounts of data that are put in storage is a waste of the business’s investment, especially when the business is not sure how to make good use of it. The label for storing data in a warehouse could imply untidy and disorganized content.


(Il)logical Knowledge Management

Data stores are put to good use, and with good grooming, it can elevate to a knowledgeable level. Logical knowledge management is taking past experiences to solve the current issues. The past is doing things right and wisdom is in the future where you are doing the right things. Data are at the seat of information and knowledge. Knowledge offers fundamental understanding about a topic or relevant area of the business. Knowledge management begins where data are first recorded. It is the actual information being generated from within the organization about the business. Knowledge transformation activities involve all aspects of technology including the interfaces and tunnels that connect systems and tools and documentation and databases. In addition, there are activities which are responsible for collecting data. The collection of data must be carried out in conformity and best done with the use of technology. Knowledge management is a choice and vast commitment. Aside from the obvious costs involved to manage knowledge sufficiently, the overturn of people’s experience also has a high risk of impacting an organizations capability. The knowledge possessed by people come from various sources, and it matures overtime. When there is an overturn of people within the organization, there is a risk of loss of this valuable wisdom that is hard to replicate in any form. People’s wisdom can come from their longevity in the industry or from how well they understand the organization’s business. A knowledge environment can hold the wisdom within the organization. Wisdom is not something to capture automatically. It is a distinctive internal part of a person, and good knowledge management relies on the cooperation and commitment of people to contribute their wisdom to the knowledge environment. Knowledge is something than can be collected

(Il)Logical Knowledge Process


because it comes from business information that has been contextualized for knowledge use. “The seat of knowledge lives in the heart” The knowledge part of the organization represents the brain and the heart. Knowledge processes represents the energy movement to keep the organization’s heart healthy and thriving. The value and quality derived from the logical knowledge management process depends on the health of the knowledge environment. Together the knowledge strategies and processes hold up the entire knowledge environment, activities, tasks, decisions, reports, analysis, assessments, diagnostics, etc., and include all events happening in the knowledge environment with an emphasis on validating content. Validate content so that it is a stellar level of quality. Knowledge management brings life to theory into the reality of the business by: • Feeding the knowledge environment with useful information to produce useful content and knowledge assets. • Testing the knowledge technical services individually and together. • Validating knowledge content to reach-specific results and test its applied use. Change the fundamental nature of success, and the movement of agility is part of this nature. Through agility, professionals can move too quickly causing businesses to lose valuable wisdom during overturn of people. Wisdom can also be lost as a result of poor knowledge management practices. Knowledge assets are only as valuable as the company’s capability to hold on to the content that makes up the asset and keep it relative and current. Holding on to knowledge


(Il)logical Knowledge Management

does not mean the volume of knowledge acquired. Holding on to knowledge is relative to the substance of the content in relevancy, meaning, usability, and quality. Holding on to information is about volume and has less emphasis on content quality and usability. Common practices of knowledge management can be confused or overlapped with practices of information management. For example, knowledge management repositories are overgrown with excessive amounts of information. The volume aspect from information management is carried over into the knowledge management environment, and it creates significant bottlenecks when users search for content. The sheer volume of information that is set up as a knowledge management environment is a structure that is not organized and leaves users unable to find anything of significance related to their need. They just search for it, and the return of results is overwhelming and massive to sort through to find what they are looking for. It becomes a daunting and time-consuming task. Most times users do not find what they are looking for and will ask coworkers for help. This invokes another timewasting activity that could have been prevented with proper vetting of content that was sourced in a knowledge management environment. Knowledge management does not deal with volume, and it does not need volume in excess for it to be successful. Knowledge management that is successful is one that has less volume and better context within content that is easily distributed and retrieved. The volume in knowledge management could be a result of the knowledge repository’s open access. The knowledge environment is open to anyone in the organization who can contribute content, update content, and replicate content into different versions. There is no filtering, no organization by category or type, no validation, and there is no sensical set of criteria that will link content to purpose. This type of setup is

(Il)Logical Knowledge Process


missing the quality aspects that is needed to organize the content affectively so users can easily search and retrieve it. The quality aspects associated with organizing the content is doneduring the knowledge preplanning and planning stages. Setting up a knowledge environment that mirrors what the Internet can do or mirrors a wiki setup will severely impact productivity among staff. Without governance or control mechanisms in place, there is not a well laid out process that guides a user through a knowledge search leading to content they are looking for. In some organizations, when their knowledge environment is not working properly, they will often swap out one technology for another. Swapping technology is not a viable solution for these types of problems. A better solution would be to evaluate and address the issues with governance, people, and process because these types of issues are not technology related. The problems exist from a lack of governance, insufficient resources, undefined roles and responsibilities, and from unorganized processes to validate and verify content. Problems also exist due to excessive amounts of knowledge content that have no logical structure or filtering to make it readily accessible to users. The volumes of content are instrumentally important to monitor. The philosophy of more is better does not apply to effective knowledge management strategies for business in the 21st century. More attention needs to be paid to the governance pieces and methods utilized to scale down the amount of information and only take what has substance, meaning, and provides a value to the users it applies to. Another area of attention is on how current the content is in a knowledge environment. Knowledge content needs to stay current while information environments deal with volumes. The volume of information is important to business intelligence as it needs to be held for compliance reasons. Information management will provide historical evidence, i.e., time line of events and customer information. Information acts as a seed that forms


(Il)logical Knowledge Management

content for a knowledge environment. From the logical perspective, the emphasis is on in the context of the content more than the volume of content. People’s wisdom from experience and their know-how also plays an important role in knowledge management. They possess wisdom on multiple topics, which contribute to shaping the context of content. People have insight to situate a well-structured, meaningful, knowledge environment. Utilize people from the organization that has a fundamental understanding of what it in takes to construct a knowledge environment and understand the distinct difference between knowledge management and information management. Keeping knowledge current is a significant challenge in knowledge programs, and staffing people with valuable wisdom is a good way to overcome it. Utilize the appropriate people with the insight to decipher what context is needed and identify which content should be tagged for knowledge inclusion. Logical knowledge provides capabilities to keep a company’s knowledge updated and consistent. How the knowledge environment is managed will affect how it provides the necessary capabilities to produce logical knowledge and effective processes to impart it throughout an organization. A poll from a webinar I presented showed 44% of the audience claimed their biggest challenge in knowledge management is keeping the knowledge current within their organization. 33% claimed they are keeping their heads above water and 22% reported there is not much knowledge to update. The most important reason for maintaining current knowledge is that it increases productivity and promotes manageable agility. A company gains a competitive edge within their market when the know-how to collect, coordinate, collaborate, store, and distribute knowledge to the appropriate communities and the people in the communities know how to use it.

(Il)Logical Knowledge Process


CONTEXT FOR CONTENT Content is derived from information that is packaged through the knowledge management process. The nature of the content is closely matched to data and information the business has, however, to bring it to a more meaningful level will require it to form features which give context to it. To give content contextual meaning requires a human factor to it because context is mostly derived from people’s wisdom. Context is a set of conditions that shapes content into coherent material. Content without context is simply that content or information. Defining context and applying it to content is a significant role in a knowledge environment. It generates knowledge from information at the individual level, underpins the process to create logical knowledge, and aids in the creation of new knowledge. Contact is typically handled by people, but with new technology, contacts can be stored and utilized as needed. In equality assurance process if automation is applying context to content, there still is a validation step in the process that cannot be skipped. Validation step is to ensure that the technology produced a sensible and graspable piece of content. Content is the product of bundled information, and knowledge management handles the packaging. In addition to packaging content to be a knowledge asset, the knowledge management process handles the tasks involved to give context meaning to content. Context is the differentiator between creating content for knowledge in generic form and creating content with meaning. To make it simpler, context enables people in an organization to understand how the business operates, about customer experiences, and have important information about business services and products. Context helps content to be personalized and shaped


(Il)logical Knowledge Management

according to fundamental features that gives content meaning. Context is what makes knowledge understood and how it is applied in situational events or tasks. Context shapes content in appearance, functionality, and behavior in the technical landscape. Context is a set of relevant conditions surrounding a situation and making it unique. Context is an influencer to make knowledge comprehensible. You can make use of context models; however, it is not necessary as much is the need for relevancy for reoccurring context to keep up with use and purpose. To understand context in a knowledge capacity means you understand the tasks taking place in the organization at the individual level, group level, and corporate level. Context models can be used for topic relevancy and to avoid generating generic knowledge. Content with context is utilized to support specific situations (Fig. 2.2) from knowledge of something. Context is the framework that takes knowledge components and puts them into a sensible format. Putting content into context also involves activities like tagging. Tagging is the procedure where existing information is flagged for knowledge content. The information needs to go through a series of activities laid out in the logical knowledge process. For example, filtering information to sort and eliminate unusable content, segmentation and testing of content, and validating that it meets the criteria for valid knowledge. When content is being fitted for context, these activities are coming from content management practices. For the purpose of this book, we are staying focused on the knowledge management aspect of a strategy plan to create a knowledge environment that functions to produce logical knowledge. Content management and knowledge management have a lot of overlap between them. Content and knowledge management have a lot of similar activities between them,

(Il)Logical Knowledge Process


but knowledge is focused on the processing of data through a cycle of activities to become knowledge where content management focuses on forming packets of information into content with contextual meaning. Think of content management as the activities that form this content into understandable bits of information and not a separate framework. The knowledge management framework is where content processes perform in conjunction with knowledge management processes and both live in the knowledge environment. A knowledge management framework is the layer for contextual content and where all the knowledge components are in place and interconnected. Performance of a knowledge framework and the condition of the outputs rely heavily on a solid knowledge environment strategy. Planning is the most essential task to achieve a high-performing knowledge environment. A plan that includes content evaluation to produce logical knowledge is a compelling practice. Contextual content forms the knowledge environment. This is an important attribute for the knowledge management to serve the communities across the organization. To do this effectively, collaboration among staff is more than working together. It is working together to achieve the same goals and intentions. Some guidelines to consider when adding context to content are: • Use templates to collect content along with conditions, insight, and experiences on topic based on scenario or problem. • Remain consistent on details, either small or large. • Crowdsource knowledge across different teams. This sourcing method returns a higher level of context.


(Il)logical Knowledge Management

• Encourage community action to share their wisdom that will help define context conditions and keep up with changing requirements.

CULTURE AND COLLABORATION The word knowledge today is commonly used, and its approach is mostly reliant on a robust knowledge technical landscape. It is important to realize even in the 21st century of robust and innovative technology. PEOPLE are the holders of valuable knowledge. A company decision to engage in constant cycles of overturning people as a way to reduce costs and overhead, will cause the company to loose valuable knowledge and there is a cost associated to this loss. Valuable knowledge is wisdom people possess, and most likely it is not replaceable. Success with managing the logical and illogical aspects of knowledge management or the capability to keep knowledge updated comes from the people in the organization. As soon as a person leaves the company or a project, there is a specific quality of wisdom that cannot be replaced. This wisdom could be collected prior to the person separating from the company; however, if this is common practice, it will have a negative influence on the knowledge culture. Staff turnover should be considered and assessed to know the risk and value the loss of wisdom will have to the knowledge environment and the impact to the business. Overturn of people that happens on a regular basis will create an undertone within the culture that will stop people from sharing knowledge. It is important to know this because the culture is the direct influence of how well people will share knowledge that they possess not only with knowledge they have about the business and their job but how well they know their area of expertise from an industry

(Il)Logical Knowledge Process


perspective. The idea is to ensure that there is a culture that promotes and makes knowledge sharing easy and comfortable without any threat to one’s livelihood. Creating a culture that values people and their wisdom is the best way to increase the company’s worth and maintain a knowledge environment effectively. Keep in mind, knowledge collection is not the same as managing knowledge and each person will have a different interpretation of knowledge. One good way to keep knowledge current is by: • Creating a culture that values wisdom gained from experience and that leverages experiences effectively. • People who are valued for their experience and wisdom are willing to share what they know. • In a sharing culture, the biggest challenge to keeping knowledge active and current is overcome. A sharing culture sets a stage where present knowledge helps plan for tomorrow’s strategy. Dedicating resources to an ongoing process for managing content helps to progress and increase the company’s knowledge value. Remember we are building a knowledge environment encompassing all the workings that are technical and nontechnical to produce logical knowledge. This is covering every aspect of the business. The easy part is implementing a knowledge management process. The harder parts are with the interconnectedness of all the processes involved, the technical landscape, validation and verification activities, and dispersing knowledge throughout the organization. The most difficult parts are with putting content into appropriate context, instill a culture that shares and collectively collaborates within its communities in unity with the knowledge environment and across the different communities.


(Il)logical Knowledge Management

It is difficult to change a business culture because of different personalities and types of management styles leading the organization. This is not about changing culture as much as it is to promote understanding about knowledge management and what the knowledge environment function is and what it provides to all its user communities. It is also to help inform people about what their role is within the knowledge environment and how to use it. We can only do that when we know how the knowledge environment functions and is organized. The easier part to managing knowledge is in the beginning of a new initiative. The budget is healthy with scores of resources available to support it. What happens next is the knowledge environment is moved into a steady state of operation. At this point, budgets may get scaled back. This is not the time to abandon resourcing to manage the environment. This is when knowledge assets are formally put into the scope of asset management when they are made available from the knowledge environment. It is at this point the resources will change and change management processes are required to manage changes from this point on. It is crucial for the knowledge environment’s structure to be sound and able to manage new knowledge assets for their life cycle. Put knowledge assets into the scope of existing asset management and change management processes. This will provide the control mechanisms to maintain and properly track knowledge assets. After the knowledge environment is implemented and live, the logical process remains in effect staffed with the appropriate roles and governed with the appropriate controls. Keeping the logical process in effect will continually maintain and improve the quality of content the knowledge environment provides. It is the most crucial time to maintain a sharing culture, keep resources intact, and maintain processes and tools to continually manage, update, and improve knowledge.

(Il)Logical Knowledge Process


The condition of the business culture could have a direct influence and be a critical factor that is contributing to problems experienced in a knowledge environment. Cultural issues could stem from poor communication and crossdepartmental conflicts. These types of issues have an impact to knowledge retrieval and transfer of knowledge between different departments. Other example of cultural issues impacting knowledge management is a culture where staff have interpersonal conflict and lack of trust. A knowledge environment without a high level of trust will most likely prevent people from sharing knowledge with each other. In addition to creating a culture of sharing, we also want to build a learning culture as well. A sharing and learning culture forms the foundation for organizational learning, and it helps people and the business evolve. Learning within the organization must be continuous and occur at all levels. Learning is carried out through formal an informal method. Informal methods rely heavily on a knowledge sharing culture where job shadowing and mentoring take place. When people are faced with problems, they will seek to learn about new ways of solving them. If the culture is not conducive for open sharing and continual learning, this will be an obstacle that prevents staff from solving business issues internally. Seeking knowledge outside the company usually will incur additional cost. The business culture is the foundation of the organization for communication, understanding, and interpersonal relationships. This foundation seeps into the knowledge environment. Essentially the business culture and knowledge environment has a social aspect and relies on good relationships that will instill open and sharing interactions between different departments or groups of people. The culture of sharing fosters collective collaboration affecting good quality content for valuable use.


(Il)logical Knowledge Management

Organized collaboration is restrictive and will most likely sabotage unified collaboration. Collaboration is more successful with a culture that promotes it. It is human nature to want to collaborate with other people from a social and professional aspect. However, people could be collaborating exchanging information, and when the interaction is over, the outcome did not produce advancement or a solution. The parties involved continued working in different directions. A collaborative effort should bring back new ideas and solutions to the occupational silos that influence improvement or advancement of a problem in the same direction. Take this into account when evaluating the business culture. Put more emphasis on getting people working on and toward the same goals. This will require a knowledge transfer and sharing strategy that draws people out of occupational silos into a centralized one. A centralized silo is a knowledge environment. Collaboration is a blend of the following:


Shapes content into meaningful knowledge that is easily transferred and understood by its users.


Is engagement within the business culture and how the culture facilitates knowledge sharing and transfer


Are groups of people formed into communities of

between communities. practice that share and transfer knowledge between them. Coordination

Is directing the knowledge activities and tasks within the knowledge environment and aligning them to knowledge requirements. Effective coordination influences good cooperation between the business communities.

(Il)Logical Knowledge Process


Any combination between content context, communities, cooperation, and communication that is done well will have a positive influence on collaborative efforts. It also helps assess how people share knowledge and provide insight into knowledge needs of communities. This helps group people together by topics of interest and job types that can make use of the same type of knowledge. Facilitating groups of people with similar knowledge needs help to associate content to group and determine tools needed to support it. Knowledge sharing at some degree is happening in the culture already. How people currently view knowledge sharing and are willing to share information is an influencing factor to how well people will effectively collaborate on their own within their community and across communities. There is a level of dependency that knowledge management has on collaboration; however, in order to instill a working interpolationship, the organization needs to recognize how much collaboration is actually needed. The extent of collaboration that is going to be needed in the organization will depend on what the topic is or what area and knowledge management could be better through the practice of collaborating between communities, for instance, problem solving; there may be a problem one occupational silo is responsible for but, another occupational silo has insight into the problem that could be helpful to the other team, in this scenario, determining time needed from the group with insight and what level of communication could take place to help transfer that insight. In knowledge, strategy will be hard to pinpoint every possible scenario to provide guidelines on collaboration, and this is the part that is independent to each person in the organization to assess the extent in time commitments of collaborative activity. Technology has a way of bringing information that is shared through a unified solution. Unified solution has the capability of collecting data and information


(Il)logical Knowledge Management

across different devices and computers and platforms into a single repository. Consider these three things in relation to collaboration: 1. The extent of dependency knowledge management has on collaboration. 2. The extent to which communications and collaboration are supported, managed, and what parts are supported by technology. 3. The availability of information from unified technology and if it is enough to influence collaboration between staff. For instance, Facebook for business is a social and professional platform where staff can share and converse. Unified collaboration will increase the degree of knowledge sharing and transferring knowledge between and across different communities. People are typically open to collaborating; however, if they are not putting collaborative efforts in action, then this will have a direct impact to achieving the same knowledge goals. Collaboration is about unifying the efforts, so people are achieving the same knowledge goals. Knowledge sharing in part of unified collaboration will produce much more effective results and supply the knowledge environment with what it needs. The knowledge environment needs adequate collaborative support to supply the means to collect, store, transfer, and distribute knowledge (Fig. 2.3). Coordination and knowledge management means that we are looking for level of coordination with existing practices and plays combined with aspects of the logical knowledge process to be comprehensive producing quality management in executing content validation and testing. Unified flow is not in the number of people, it is the seamless effort that produces the knowledge outcome. Unified

(Il)Logical Knowledge Process

Content Data/Informa on



Collec on methods

• Transfer • Distribute

Fig. 2.3. Main Channels of Knowledge Environment.

collaborative efforts help when there are some guidelines in place when it comes to transferring and distributing knowledge. It could help steer collaboration between people and between communities. Below are examples of rules for knowledge transfer and knowledge distribution.

KNOWLEDGE TRANSFER RULES • Identify different methods or approaches to transferring knowledge in the organization, i.e. mentoring, coaching, peer shadowing, documentation, user needs, podcasts, wiki, storytelling, context, and type of knowledge, etc. • Define which knowledge collected is being used for transferring knowledge and stipulate why it is being transferred. • Specify the receiving party the knowledge is being transferred to. • Specify if knowledge transfer is for compliance obligation. • Internal knowledge transfer is within the same organization. External knowledge transfer will require authorization and context review to ensure no sensitive information is being transferred outside the organization.


(Il)logical Knowledge Management

KNOWLEDGE DISTRIBUTION RULES • Enable the flow of knowledge to enable learning processes and promote knowledge sharing. • Identify ways knowledge is distributed. • Drive the creation of new knowledge. • Foster understanding by using content that is validated and processed to produce logical knowledge. Illogical knowledge is not ruled out completely, rather it is carefully identified and categorized appropriately. Knowledge sharing is almost completely reliant on people’s willingness to share and what it is means to be collaborative. Staff seldom shares knowledge, and storing it within a system does imply information is being shared between staff. This could mean at times staff is not getting enough information from their mentors or coworkers. Sometimes there is a wide gap between senior staff levels to junior staff levels. Employees in different business units will have different work practices, and there could be a lack of interdepartmental communication. Knowledge analytics are a good way to know the effectiveness of knowledge sharing between staff. Procedures for work that is not standardized will help bridge the gap between staff levels and provide guidance on unique situations. Define collaboration for the organization or for the knowledge environment to instill a mutual understanding of what is expected when we use the term collaborate. Does collaboration in your organization mean exchange of information? Just because someone asks for information does not mean it should be shared. There should be some guidelines around what the collaborative goals are. This is a

(Il)Logical Knowledge Process


major part to the organization’s culture that leads to knowledge sharing behavior. If the culture is ignored, most likely people within the organization will be unwilling to collaborate or participate in knowledge sharing practices. Science and formal management practices can only provide a certain level of guidance to help build an acceptable business culture, instill collaboration effectively, and produce sufficient level of engagement within the communities of people. The social factors play an important role to a knowledge environment. Building good relationships and fostering a sharing and open business culture will help maintain good staff engagement. The state of the culture may not always be functional at best, but there is a difference between dysfunction and harmfulness. There is a degree of dysfunction in any business, but how the culture deals with disruption should not be harmful in any means. Problem resolution is another factor to consider when assessing the culture. Remove harmful influences and address those that are disruptive when dealing with dysfunction. The skill of being able to assess the organization’s existing culture far outweighs exact science in this area. Fill the roles within the knowledge environment with people who have excellent people skills. People skills are needed to effectively coordinate strategies to address cultural issues that are impacting the organization’s productivity. The knowledge environment’s capabilities to share useful information instill unity within the culture. It is not the other way around. Focus on developing a high-performing knowledge environment, and as a result, the outcome will be a unified culture. The outcome of unity will depend on managing people extremely well because managing people influences the atmosphere of the organization’s culture. It is best to


(Il)logical Knowledge Management

influence a unified culture that will enable good engagement to the knowledge environment. Spending time on gaining people’s buy-in to influence the culture can be time intensive. Focus on the culture itself and find ways to unify the people in it toward a common ground, that is, the knowledge environment. Doing so will lead to productive results. There are complexities in layers and groups of people, and this is where the entire knowledge environment can break down. Tasks are somewhat controlled within smaller size teams and have integrated associations to departments and other groups. The hidden areas of useable content are most likely sitting in these smaller teams. It is important that small teams do not become an occupational silo. An occupational silo is a team which separates what their function is from the rest of the organization. There is not an integrated view of the work they do and how it impacts the core business function. These are the areas to assess and work with to prevent small teams from becoming occupational silos. Occupational silos obstruct effective coordination of groups that make up the organization and create information gaps. These gaps will carry into the knowledge environment and impact unity within the organization’s culture. Information gaps expose the organization to wasted investment, delays to requests, and inefficiencies within workflows and cause quality issues with knowledge content. Occupational silos will most likely result in poor performance and cause problems with collaboration and coordination within the business culture. Governing knowledge encompasses processes to collect, store, distribute, and use content. The concept of a knowledge environment is essentially creating a governing body setting quality controls across the organization for managing knowledge.

(Il)Logical Knowledge Process


Governance includes: • Compliance – business practices people have to adhere to; • Quality validation of content used to produce knowledge – logical knowledge process; • Ownership of content; • Knowledge transfer rules; • Knowledge sharing principles; • Editing knowledge; • Handling situational knowledge to solve problems. Establish and execute on streamlined knowledge management policies and governance processes to align with the knowledge solutions. Prioritize and focus on knowledge that will enhance customer the customer experience. Through holistic policy and governance, create a knowledge management mission to bring the business strategy to life. Ensure investments deliver value to the organization. Improving the management of knowledge activities and enabling business leaders to exercise proper oversight of business programs and acquisitions.

LOGICAL KNOWLEDGE MANAGEMENT PROCESS The illogical/logical knowledge management process outlined in Chapter 1 is an end-to-end cycle of activities concentrating on quality, validation, and content context to ensure the content product is understandable. The purpose of the logical knowledge management process is to prepare and bundle knowledge from content and ensure


(Il)logical Knowledge Management

it has proper context and comes from a validated or authorized source, to ensure content is filtered and segmented for quality review and there is clear understanding between logical and illogical knowledge. The process strives to reduce illogical aspects from knowledge content and makes use of systems and tools for knowledge, documentation management, analytics, and filtering. To make knowledge available in quality, improve efficiencies in search and retrieval of knowledge. This process focuses on the strategy elements more than it does on the tactical although there are tactical activities involved. Processes in knowledge management refer to all activity phases, subprocesses, and controls. There is an interconnectedness component to design within the processes and between activities, and these will differ from one organization to another. There are many different approaches available and research on knowledge management in general. The key input to the process is business intelligence (information), and the primary output is logical content. Logical content is made available from the knowledge environment and shared across the organization to the appropriate communities that will benefit from it. This process operates within the knowledge environment and has a dependency on business support investment. This process is not independent, and it is designed to work with the other components in part of what we call know as knowledge management. This includes processes, technical landscape, tools, governance framework, definitions of terms, a sharing culture, and logical content. Knowledge assets are in scope of change management processes.

(Il)Logical Knowledge Process


Key strategies: • Provide technology infrastructure and support for knowledge research, learning, and creative activities. • Provide responsive knowledge support and innovative technical solutions to meet the needs of staff and across the organization. • Expand expertise in high-performance specialty areas like engineering, product specialist, computing, conferencing, mobile devices, etc. • Environments. • Leverage reliable, secure, and efficient technology infrastructure. • Maximize staff potential to foster innovation and excellence. • Provide a robust, resilient, and reliable knowledge support system where users are guided through a process when searching for knowledge. • Provide a robust and reliable communications infrastructure, i.e., voice, messaging, social frameworks, etc. • Identify and implement improvements that reduce knowledge management–related problems within the organization. The major activities of the logical knowledge process are: • Identify the need for knowledge. – Plan: determine knowledge domains, define knowledge procedures and methods, and determine the technical

(Il)logical Knowledge Management


landscape – the tools, systems, devices, and type of technology required. – Identify and assign ownership to knowledge assets. – Define knowledge management and define collaboration and culture goals. – Define the feedback mechanisms to collect from people using the knowledge assets. – Analyze and diagnose the need for knowledge. – Content ownership. – Identify content source. – Define criteria targets for context. Context provides experiences and wisdom. Allow for the process to accept new experiences and wisdom as situations change. • Collect content and determine where it will stored. – Develop and prepare content to be used for knowledge publication. This is known as knowledge acquisition. – Acquire knowledge or content using business intelligence/ information (input). Information collected is transformed into useful knowledge. After collecting content categorize and classify so it’s clear how to use it. Categorizing content relative to the how it will be experienced. – Organize your knowledge assets. Establishing a knowledge hierarchy will help the user communities browse and discover new content and topic-specific content and could help their productivity. For this activity, take as much time that is needed a really strategize brainstorm about a knowledge structure that makes sense for your organization.

(Il)Logical Knowledge Process


– Utilize feedback from people within the organization that are involved directly with specialized content and they should work with the knowledge environment team – Filtering content for context by defining and setting conditions for content collected. Note: setting conditions for context can be done in the planning stages for repeatable content pieces relative to the same/similar topics. – Validation and verification. – Segmentation and testing. – Create logical knowledge (output) and organize to create collections of knowledge. The filing structure is designed based on how the organization is set up and using knowledge. Consider knowledge outlets in the structure, for example, which content is public and proprietary. • Share and distribute knowledge – distribute and publish – Output, illogical, or logical content. – Publish content. – Pilot published knowledge to establish how it is being applied and the outcome of using the knowledge. – Utilize feedback channels to improve the logical knowledge management processes and procedures. • Maintain logical knowledge – finding knowledge, sharing knowledge, recycling knowledge, producing knowledge, knowledge assets – Utility, retrieving, and distribution of knowledge use of knowledge – Applying knowledge learning an explanation


(Il)logical Knowledge Management

CASE STUDY – PART 1 (ADDENDUM) BABM leadership left out the important aspects of their strategy for knowledge management. They did not factor the impact or influence the business culture has on the knowledge environment. Nor did they examine how knowledge was or if shared across the organization or considered the ramifications to downsizing to soon after the launch of the knowledge management program. From Case Study – Part 1 (Chapter 1), BABM leadership decided to leverage existing strategies and processes already in place as a means to improve the customer experience and to minimize the high amount of time redoing network designs from scratch. This is one area where leadership failed in their strategy. They focused more on avoiding having to redo processes and used existing strategies that were from occupational silos. The sourcing of information from the occupational silos created too many information gaps than they could handle. There were gaps in the initial plan for assessment of the existing strategies to ensure they were sufficiently equipped to support the new knowledge management program and accomplish its goals to improve the customer experience and reduce duplicated efforts on network designs. Had they done this, the complex issues could have been prevented. If leadership made a better investment in time and cost to examine these strategies, it would not have burdened the business with extra financial and time pressures as well as incurring a loss in steady revenue. The new program issues did not improve the customer experience and resulted in a loss of three major clients. From Case Study – Part 1 (Chapter 1),

(Il)Logical Knowledge Process

The investigation revealed there were new and more complex issues occurring from the new knowledge management environment. The issues are so convoluted; it is the produced problems that seem too overwhelming to solve. For example, knowledge content is worsening service quality and creating significant delays to a point the business wants to do away with the new knowledge management structure. The quality of the content from the knowledge management systems is not as stellar they believed it would be. For instance, there are user instructions for a business application, which was supplied by an employee using this application. The user instructions were not clear, and reports showed people following it were making mistakes. The project team’s investigation identified an issue with verifying and validating content, and sources for content are not put through an approval process. An analysis showed these new perplexing issues are mostly related to the illogical state of the information used to build knowledge content and how the sources for knowledge are selected. The Knowledge Management Office puts a structure in place similar to a wiki-like platform. This platform was chosen due to the simplicity and short time lines to implement. The knowledge platform is an open door for anyone to record what they perceive as knowledge and is able to contribute said knowledge as long as it relates to topic. The design was simple and the search criteria unfriendly except if you are a savvy user capable of advanced Internet searches. Other issues users complain about have to do with informal methods and distribution of knowledge.



(Il)logical Knowledge Management

The design is not set up to distribute knowledge as much as it is set up to collect knowledge in any form, on any topic, from any person within BABM. In addition to not examining the existing strategies within the occupational silos, leadership did not factor in the process to filtering content and incising it with proper context as it related to the needs of the business. Other than compliance and legal standards there were no governing practices put in place. In addition, collaboration and knowledge sharing was not addressed at all in the initial strategy and was left up to the departments to manage this part. Doing this resulted in a disjointed collaboration and fragmentary processes for sharing knowledge. The technical landscape design did not factor in much of user navigation and search capabilities. The engineer who designed this part did not do it from the people within the user communities and did so more from a technician’s perspective. The design resulted in the unfriendly setup for searching with ease and took more time for users to do searches and retrieve information.


Technology plays an important role in the use and evolution of knowledge management. The important role it plays is by providing useful tools. Knowledge management activities and processes are mostly automated. The business infrastructure should be evaluated to ensure that it can keep up with the automation demands for a knowledge environment. Design specifications for content management, documentation management, and knowledge management are all similar, but they could overlap in the use of tools, meaning one system for documentation management may not have suitable features or functionality to support all the processes and activities for knowledge management. The design and capacity of the existing infrastructure should be assessed against the technical requirements for the knowledge environment. The gap analysis should provide enough insight on what technology will need to be added to support the end-to-end knowledge processes (Figs 3.1 and 3.2). Data handling practices for knowledge management become more efficient through the use of modern tools. The disciplined


(Il)logical Knowledge Management


Content Business Intelligence Quality Valida on and Verifica on Logical

Processes Decision making Communica on Compliance, best prac ces Learning

Technology Collabora on (unified tools), collec on, storing, distribu ng, workflows, messaging

Analysis, pa ern recogini on, deep learning, language processing

Fig. 3.1. High-level Knowledge Landscape.

Finding Knowledge

Sharing Knowledge

Recycling Knowledge

Producing Knowledge

Knowledge Asset

Fig. 3.2. Logical Process Phases.

practices for mining data, sorting through information, categorizing, and classifying information, search capabilities, storage allocation, etc. need to be refined through the strategic plan for your knowledge environment. Consider every aspect of automation since most of the knowledge environment relies on technology. Modern tools are used in knowledge management for activities like discovering, searching, and analysis of content. Modern tools also perform tasks like transforming content into the right format and sharing and distributing content. Distribution shouldn’t be driven solely by the ability of the technology. Technology is simply the vehicle to distribute and the emphasis MUST be on the quality, integrity and useability of the content that is being distributed. Modern tools reference the types of technology that are used for unified cloud solutions, cognitive computing, artificial intelligence (AI), analytic tools, enterprise management systems, social platforms for the workplace, messaging, and video conferencing. These are the common modern tools in place today.

Tools for Knowledge and Organizational Learning


Modern technology has not reached its peak yet and will continue to evolve and transform businesses for decades to come. The use of new modern technology will continue to rapidly saturate throughout the business world. Many businesses in healthcare and finance and travel are already using some versioning of the modern technology. There are many benefits and efficiencies to gain through this newer type technology, but we still have a lot to learn on how to use it affectively and set it up with good designs to retrofit need and without causing insurmountable issues and overwhelming stress. Benefits from modern technology are outweighing the issues; however, with big data issues continuing to rise, there will be an increase of issues at the same time modern tech is evolving and taking over business functions. No matter how advanced technology becomes, it will always come back down to people and process. People are using technology as a means to drive business decisions and that is a costly and can be a high-risk mistake. For some businesses or specific areas of a business, highly intelligent tools are not necessary. When evaluating the business to determine its technology needs be realistic on the automation requirements. For technical specifications, be careful not to over or under engineer the design. Right size the necessity and growth forecasts and plan the technology accordingly. If businesses changed technology as fast as it is advancing then the cost’s would outweigh any benefit and impact profit margins. Include forecasting in your strategy to see what type of problems could be associated with the technology to be implemented. Big data in large amounts of contents to manage is one example of a major issue businesses are experiencing, and it needs much more attention than it is getting. Another major issue is with knowledge content quality and validation. Who is paying attention to quality and validation methods for content being shared in a knowledge management environment? To ensure sourced content that is stored in the knowledge environment


(Il)logical Knowledge Management

contains only the highest quality knowledge will require stringent validation processes. To help streamline the validation process, users within the organization can contribute their time and expertise to help validate content. It’s important to align people from the organization that have subject-matter expertise or experience on the topic of the content they are reviewing. Validation includes various types of review processes, and these are transparent to the people in the organization. The transparency is to help encourage people be involved in the knowledge environment and support the level of activities involved for quality assurance. Validation practices are systemic in nature, but trying to enforce them to be restrictive in their review process could alter the results. Validation may influence acquiring knowledge, and the validation process should make it possible to acquire the right knowledge. The knowledge environment should be looked at from an integration standpoint. Knowledge acquisition and validation are the two main points of integration. The knowledge strategy will outline the guidelines in which the knowledge will be validated by. Validation guidelines are not generic; they are developed through specific conditions that are based on the topics and relevancy of the material. In the world of software development, validation could be interpreted as building the right product or coding the right feature or fix. Verification in the software development world means building the product right. The software development philosophy can apply to validation of knowledge content, and as long as the content meets the structural guidelines for usage, then your approach for validating content is sufficient. Modern tech does not replace jobs or the need for human intervention and interaction, it just changes the types of jobs for humans to do. Advanced technologies such as AI and cognitive computing are progressing how knowledge is altered, utilized, and applied. AI is predominately used for problem

Tools for Knowledge and Organizational Learning


solving and assistant-type tasks. AI technology is applied from algorithms to carry out a task or solve a known problem. Cognitive computing is a bit different where it simulates human thinking patterns to assist people in decision-making. This is the intended use of design for these technologies and used in most major industries. The use of AI and cognitive computing will continue to grow creating a critical need for businesses to take significant steps toward implementing them with enhanced strategies to prevent common issues that can easily be solved with better processes and governance. AI is used in many businesses to support process activities in a customer contact center to handle administrative phone tasks. AI fulfills receptionist duties and other processes as well. Cognitive computing problem solves by reasoning, i.e., cognitive computing is used in finance to analyze the stock market and make suggestions to clients based on analysis findings. Another example is in wellness and fitness industry. Cognitive computing is used in devices like a Fitbit where fitness professionals can utilize information captured in the device to make suggestions on healthcare options. Cognitive computing is involved with deep learning, and it is used in knowledge management for areas such as language processing, pattern recognition, and data and text mining. When we look at integrating knowledge together from different occupational silos, cognitive computing technology is best for automating data integration automation. Knowledge management as a multidisciplinary area that has many aspects of cognitive purpose, for instance, organizational learning. Knowledge management helps organizations create, share, use, collaborate, use, and reuse knowledge as much as possible. The same portion of knowledge can be used in unique ways at different times and at different levels of detail. It is important to know what portions are used in multiple pockets and when that knowledge is needed. Lay this out when designing a logical


(Il)logical Knowledge Management

structure for storing and retrieving knowledge. This is to organize and adapt the same knowledge that can be coordinated to suit different needs. Some examples where the same knowledge portions are used at different times are: • For learning purposes – training material is adjusted to fit the participant’s needs. • For analysis purposes – same information with different levels of detail to complete an analysis from different angles. • For referencing – being able to construct sentences or paragraphs to suit different needs and/or scenarios. AI revolves around knowledge and is considered a central component in knowledge management. AI provides mechanisms that are needed to accumulate knowledge and utilizes it for organizational learning. AI also helps to collect knowledge from various sources and process information based on the rule setup configured in the technology. The content collected is then stored in the repositories for knowledge and utilized later to support decision-making. AI is not a good technology that does decision-making well; however, cognitive computing can fill that gap. AI and knowledge management both reside on the same side of the landscape and perform robust process–related activities; however, the challenges in AI and knowledge management resulted in cognitive computing. In the future, knowledge environments will grow enormously to even larger sizes than what we are faced with today. These drastic increases in knowledge content requires more relevancy to text analytics as a way of keeping up. A few significant challenges are happening with cognitive computing and AI, and they are associated with keeping up with key activities like quality assurance, content validation, and organization of massive knowledge volumes. In today’s business world, these challenges are very real, and it is affecting staff

Tools for Knowledge and Organizational Learning


productivity, customer relationships, and customer service, and budgets are overrun by these types of issue incurring enormous unforeseen costs to solve. The emphasis on the technology aspect in knowledge management has become so complex that these types of issues are almost accepted as the norm. It is not normal to have such impacting issues that waste valuable time (priceless asset), waste hard earned money, and invoke unnecessary stress. Let us get some perspective on this, observing people in the industry get stressed to a point that it is affecting health over machinery isn’t a healthy normal. Modern technology assists business and life with its advances in automation to help simplify tasks and free up time from doing these tasks manually. Over burdened systems that it takes more time to figure it out than to it manually or semi-automated isn’t a sustainable norm. Over stressed people using modern technology isn’t how it should be nor is it acceptable and should not be accepted as the norm. People just assume these are normal consequences for using modern technology believing we have no control over it. This is not true, we do have much control over design and development and the process strategies used to implement, maintain, and use the technology. A good amount of these problems can be and should be addressed now. Do not blame it on a learning curve and accept the problems making overwhelming impacts to people. This is an important piece to consider when constructing a knowledge environment from the logical knowledge process perspective. This is a step toward tending to these complex issues within your organization that needs attention. These kinds of issues need attention for key reasons. They are: 1. The lack of quality assurance in unstructured content that is being published through knowledge management outlets. 2. How the content is being passed through the knowledge outlets unstructured, unedited, and unverified for accuracy, relevancy, and how the content originated.


(Il)logical Knowledge Management

3. Time management: It is an issue because the searches and retrieving specific knowledge based on keywords are responding with content that doesn’t apply or is outdated or not on topic. It takes too long to find a valid piece of content to address the situation or to obtain the information someone is looking for. These three major issues impact business productivity, customer service, and reputation. Other modern technologies used for knowledge management are social media platforms and mobile devices. Handsfree business is beneficial, and the effort we put into implementing modern tech on the fast track needs to shift. Reassess knowledge strategies and shift the driving forces to collect knowledge to managing and controlling knowledge. There is a time investment to make this switch and the benefits to doing so are not immediate. They are accumulated over time, and once the organization has reached a level of sustainability on the knowledge environment, the benefits undoubtedly outweigh the investment. It is critical for organizations to invest in a strategy and a governing set of controls. It is also critical to put down a level foundation in order to manage content to be a valuable commodity and maintain relevancy. The acceptance in society of technology today has resulted in some high price tags along with it, not just in cost but in invoking overwhelming stress. Technology is causing stress because there isn’t sufficient education or resources on how to right size technology’s place in business and personal life. It is important to understand the reasons why there is discord in the organization from the activities involved in information technology. These issues when ignored worsen over time and will be a detriment to building a knowledge environment successfully within the technical atmosphere. Knowledge

Tools for Knowledge and Organizational Learning


management planning includes understanding the knowledge requirements and the state of the technical atmosphere. It is important to understand this because the state of the technical atmosphere will either hinder or help usefulness of the knowledge produced from it. The technical landscape is part of the overall knowledge atmosphere of the entire organization. Therefore, the existing culture in the technical environment will impact the knowledge environment. Avoidance of addressing the existing problematic areas in the technical atmosphere carries over into the knowledge plan as risks. These risks hinder the intended use of knowledge, and implementing the plan with high risk is like purposely derailing a train so it does not reach its destination. Resolving the significant issues ahead of implementing the knowledge environment will help its usefulness and will keep the train on track so it does reach its destination. Having a good strategy to manage knowledge is necessary to keep the train from derailing and causing harmful outcomes. We will not get away from technology and why should we; automation is extraordinary when its right sized to serve the purpose. Technology is a service, and, somehow, we have it backwards. We are serving the technology and wearing down the business with thinner people resources. It takes people to right size technology, a vital necessity in order for technical assets to be utilized to deliver what it is been designed to do. Giving weighted value to the technology tenants in a knowledge environment will right size the scope of the knowledge landscape. Over-engineered infrastructure can be overwhelming and problematic. An under-engineered infrastructure is overwhelmingly problematic. It is imperative to design a technical landscape that fits the current need and factor in sufficient capacity and bandwidth for the next 12 months. This is where right sizing sits. Consider the business need and timeline when engineering technical landscapes.


(Il)logical Knowledge Management

Knowledge in the 21st century is mostly about technology although one may argue knowledge is all technology. Technology has a major role in knowledge management. It would be nearly impossible to handle the amounts of information being collected and distributed effectively. Knowledge workflows are focused on more than on the content that moves through the workflow. Institute content quality measures in all technical plans and include knowledge asset processes to support the plan. Often when implementing technology systems, there is not much fore thought in the planning stages. They are driven technically and from a systemic aspect. Technology education derives from the science of computerization. It is definite, exact, and instructional. How technology is used turns out to be a completely different area that is much more reliant on people’s knowledge, expertise, experiences, and lessons learned. Textbook education cannot teach this level of wisdom. Technology use is managed through process, and processes are matured from an investment in wisdom more than they are matured through an investment in textbook resources. Technical maturity is essentially important to construct a useful technical landscape that fits the organization in how it will be used by its users. Maturity is directly related to the measures of process adoption and the ability to progress. From an education and learning perspective, the practice is that outlined in the book or a blend of technical and business management concepts. Technology areas are lacking sufficient information on business management practices, and business areas are lacking sufficient information on technology management practices. To keep up with the demand of ever-changing technology in a business world, there is a need for better operating models to support an integrative solution for knowledge. In modern day, the line that separates technology management from business management needs to be removed.

Tools for Knowledge and Organizational Learning


During the 1980s, 1990s, and early 2000s, business and technology areas worked separately in occupational silos. Technology areas contain an additional layer with more occupational silos. Since the earlier days of those decades not much has changed in technology areas working in occupational silos. Technology has gotten better to align with business functions; however, there is still much more room to mature on full integration of one business model for all practices that are business and technology. For modern-day business, the core business functions and technology are managed as one. Let us refer to this as know-how trade management. Know-how trade management is the combination of practices from technology management and business management. It is imperative to understand and apply this rationale because when the technical management and business management practices are separated their principles will clash. There is conflict between the two because managing technology handles design, setup, and implementation of the technology components. Technology management does not focus on process from a maturity perspective. This is where it clashes with business management practices. Business management is entirely focused on process, improving process, and maturing process. Business management looks at the return on investment and evaluates the benefits gained from technology systems. Blending management practices for business and technology produces a know-how set of management practices that cover the entire spectrum of an organization. It covers the finite science of technical engineering and setup as well as the governance, process, and improvement controls. This know-how management structure is the establishment of the logical knowledge environment. Using a know-how management structure in a knowledge environment expects technology requirements to be driven


(Il)logical Knowledge Management

from a path of which knowledge flows throughout the organization. The knowledge flow is derived from anyone in the organization, but mainly from subject-matter experts meaning technical designers will erect the environment to specification, but the roles form the knowledge environment team will determine design and usage capabilities. The volumes of information to manage in business today would be almost impossible to do effectively without automation. The biggest challenge is not the knowledge management process or tool, it is the ability to keep up with the overwhelming amount of content, while maintaining its quality. Another common struggle people are feeling is there does not seem to be enough resources to undertake all that is required. Content can outdate itself quicker than it takes to create and validate it. Tackling this issue more strategically with a right sizing attitude will help tackle the technological landscape that supports the organizations knowledge and learning environment. The makeup of the environment and right sizing content to need helps professionals keep up with knowledge demand. There are many pockets within a business that have specific knowledge that is tied to their domain and managed at the domain level. This is normally where knowledge management practices are implemented. Knowledge Management practices whether formal or informal, it is standard business operation decorum to have each department govern their own knowledge accordingly. In the logical sense for knowledge management, there is a top corporate business level of knowledge that is also kept and maintained by business operations. What should be considered part of standard practices for managing knowledge is constructing a knowledge environment where all these different pockets of knowledge management link together in a single landscape. Overwhelming to think about, yes it is; however, to raise the bar a bit and evolve knowledge

Tools for Knowledge and Organizational Learning


content into a capital asset is why it is necessary to accomplish this. The tools and resources are available to make it happen. What is missing is helpful guidance to integrate a knowledge environment using only content that has been processed through a logical string of activities. The (Il)Logical Knowledge Process (Chapter 2) is what makes the distinction between valuable knowledge versus unusable knowledge. This process is designed for a knowledge environment to produce logical knowledge and matching up knowledge to need. Discard ideals about collecting and hoarding knowledge and right size the knowledge repositories with substantial and useful content. Use the knowledge trail to trace where content comes from. When tracing content ask these key questions: • Is it from data or information? • Was it captured through a system or from an individual’s self-knowledge? Data and information are sectioned into meaningful structures through segmentation (Chapter 1). In segmentation, knowledge content is built into relationships and the illogical aspects of the information are discarded. Data mining is done in part with segmentation combined with quality assurance and experiences. Data mining brings related material together, segmentation puts them into constructs that are manageable, and experiences make them meaningful. Quality assurance ensures material is logical, correct, and useable. In the technology landscape for knowledge management, tools used and how they function are essentially the largest aspect of the strategic framework. The best automation for a robust knowledge environment comes from defining the assortment of technology it will take to support it. Any system


(Il)logical Knowledge Management

or tool that aids in the transfer, storage, or tracking of information is a candidate for the knowledge technical landscape. For example: • Communications software – groupware, messaging, web conferencing, etc. • Intranet/extranet • Content management systems • Learning management systems (LMS) • Data stores and data mining tools • AI tools/assistants • Service call or customer tracking systems (known as capturing systems) • Wiki applications • Document management systems • Information management systems • Tools used for decision-making • Search tools • Knowledge bases • Asset Tools – used to track and manage logical knowledge content. Information technology supplies tools to support the process seats in the knowledge environment. The technical landscape is supported by a technology department, and there are rules within the knowledge team that are technical. The knowledge technical roles in conjunction with the ITM will

Tools for Knowledge and Organizational Learning


support knowledge assets, content and information, communications knowledge creation, knowledge validation, and ways to present knowledge. Functionality and performance of knowledge management tools in modern organizations will determine its ability to manage knowledge in both informal and formal matters. Business intelligence and knowledge management are interrelated. Business intelligence stores information across the organization. Information feeds the knowledge environment and its processes. Business intelligence uses technologies and applications for collecting, integrating, analysis, and presentation of information. It also supports business decision-making. Knowledge management performs integrated activities from business intelligence while pursuing and creating new knowledge. The following are issues that may occur between business intelligence and knowledge management: • Having a single repository for all the organizations knowledge. • Making it easy and intuitive to find what you are looking for. • Managing organizational engagement participation with the knowledge environment and the quality of interactions. • Identifying topic experts and capturing their knowledge. Encouraging members of the community to share their knowledge. Reducing duplicate content. • Making relevant content easy to find. • Facilitating collaboration on long-range geographically dispersed community. • Customization to reinforce standards internally and externally.


(Il)logical Knowledge Management

• Analysis to know the effectiveness of your knowledge management effort. From a technical perspective, the landscape of automation will have weaknesses when it comes to quality assurance and validation. Validation is the critical part of the logical knowledge process. Leaning on technology to handle quality assurance and validation end-to-end is not advisable. Technology is good for validating data, but at the knowledge level, the human element is needed to add meaning and value. The roles in knowledge management cover the phases of the logical process (Fig. 1.4), and this should have technical roles included. A technology knowledge team is blended with the process team to ensure the focus is to produce a knowledge environment that produces logical knowledge content. A team encompassing responsibilities for governance, process, and technology is called a knowledge environment team. Roles included in the knowledge environment team are shown in Table 3.1. Technology and knowledge systems will underpin and support the main phases of the Logical Knowledge process (shown in Chapter 1 Fig. 1.4). Technology for knowledge will interconnect the complex layers and groups of people across the organization. It supports the knowledge workflow and stores, segments, shares, distributes, and tracks all pieces of content which make up a knowledge asset. Building a knowledge environment does not come without its issues. Failure is often equated with technology. Technology will fail, and it will be in need of maintenance and repair. Software will at some point behave erratically, software bugs appear, security threats to contend to, and software is continually enhanced with new features. The knowledge environment factors in the probability of what will fail from a

Tools for Knowledge and Organizational Learning


Table 3.1. Knowledge Environment Team Roles. Role


Functional Area


Develop and manage the

Knowledge environment


knowledge environment

governance, processes

or Manager

plan, implement and manages the knowledge

and tools.

environment. Knowledge strategy and change management on knowledge assets. Chooses and in conjunction with technology experts, designs the technology knowledge landscape. Content

Develop, maintain, and


improve knowledge content. materials that makes up

Data, information, and

Ensuring content meets the

content useable for

criteria and from authorized


sources. Content

Responsible for the format,

Content editing to ensure


language attributes,

users can understand


proofing, of knowledge

and utilize knowledge

content. Contributes and in


support of Content Manager ensures content is from authorized sources. Keeps content up to date. Content

Responsible for interpreting

Much like a business


user’s needs and business

analyst responsibilities to

requirements for knowledge. translate users’ needs to Can be combined with

content, only the scope

Content Detective role. Able is strictly for the content to validate content.

authorized for use in the knowledge environment.

(Il)logical Knowledge Management


Table 3.1. (Continued ) Role


Functional Area


Knows where content is

Seeker of material for


located and where to search knowledge content. for it. Able to validate

Content Detectives know

content. Can be combined

where to locate

with Content Analyst role.

knowledge on request.

Knowledge Asset

Develop and maintain the knowledge asset

Handle and manage the life cycle of all


management plan. In

knowledge assets.

conjunction with the Knowledge Manager, identify and define knowledge that is authorized for sourcing, sharing, and distributing. Develop knowledge asset assessment criteria; sourcing, sharing, and distributing. Reporting – prepare a plan for the life cycle of knowledge assets, including cost and usage. Technology

Understand, configure, and

Data mining,

Experts –

maintain the specific

segmentation of digital


function of each system/tool content (all media

of systems

used in the knowledge

types), management

and tools

environment including the


selected to

asset management system.

be in scope

Understand the limitation of

of the knowledge

each system/tool.


Tools for Knowledge and Organizational Learning


technical and process perspective. Examples of issues that can come up in a knowledge environment: • Lack of fully understanding knowledge systems and their limitations. • Difficulty on where to draw the line when making decisions on systems for knowledge. • Lack of content management. • Inadequate quality assurance measures. • Believing knowledge management is only a technical system. • Keeping content up to date. • Inability to validate content that is of value, consumable, and trustworthy. • Maintaining reliable content. Reliable content in this context means keeping content current and updated with relevancy. • Challenges with transferring knowledge and leveraging effectively for organizational learning. Sharing knowledge in today’s business environment relies on automation. Poor knowledge sharing techniques are costly, inefficient, and could reduce productivity levels among staff. The most common reason why is from excessive amounts of time staff uses looking for sources of knowledge for problem solutions or time replicating the same information. Using automation is considered good knowledge sharing practices and will increase productivity among staff. Sharing knowledge is a bit different than distributing knowledge. Knowledge sharing is done between individuals or groups of


(Il)logical Knowledge Management

people. Knowledge is shared from business subject matter experts with knowledge content managers. Distributing knowledge is tied to organizational learning. In a learning environment, knowledge is distributed through a course and relayed from teacher/trainer to participant (learner).

KNOWLEDGE MANAGEMENT AND ORGANIZATIONAL LEARNING Knowledge management in the concept of logical knowledge is the strategic planning of knowledge assets in the form of documentation, manuals, brochures, emails, imaging, processes, procedures, best practices, systems, data stores, communication, printing, copyrights, and employee’s knowledge of how to do their jobs, etc. Knowledge assets are made available to the organization as a resource to enable innovation among staff. Organizational learning is the concept of applying knowledge in an education setting. Approaches that separates organizational learning into two paths is not the goal of a logical knowledge environment. One path being that knowledge management represents the entire businesses intelligence and the other path being that knowledge management is structured by individual practice communities. The knowledge environment is implemented with a blended approach. The foundation and center of the knowledge environment holds the business intelligence and it is linked to individual practice communities. Communities of practice are set up by topics and made up of people with expertise on that topic. The knowledge environment is blended into the communities of practice. The blended approach will aid in keeping content current and promote efficiency to the teams trying to maintain it to be current. Organizational learning’s success rate relies heavily on understandable content and effective delivery. This perspective

Tools for Knowledge and Organizational Learning


continues to follow the strategic path in this book explaining interconnectedness between managing knowledge, structuring the knowledge environment, and its influence to organizational learning. Organizational learning is aimed not only at improving problem solving but also at knowledge advancement. Advance knowledge in the organization for people to be well versed about the business. From the case study, there are two principles BABM followed under advisement that it was in good practice. The first principle is that knowledge management feeds organizational learning and both are continuous. The second one is that organizational knowledge is collectively developed. Although this is good practice and true, when practiced without governance to validation and segmentation process it will be the driver of issues. This practice resulted in BABM’s knowledge management framework to be solely focused on collecting knowledge with no attention to content quality or on validation. Knowledge management and organizational learning have a direct relationship and correlation to authenticating effective communication. Communication is vital to effecting good relationships between knowledge and learning. Knowledge management does not replace open communication. In some organizations knowledge practices are replacing it and it’s creating confusion and impacting learning initiatives. To prevent learning from being impacted and producing poor quality of communication, it’s imperative to have a knowledge plan that includes communication as a critical dependency. • Communication methods are tied to delivering and receiving messages of information. Communication is information sharing. • Knowledge management methods are tied to sharing material that is knowledgeable material. Knowledge management is content sharing.


(Il)logical Knowledge Management

The knowledge environment enables knowledge assets to evolve. Each type of business communication is critical for organizational learning. When choosing the types of messages to communicate with, ensure to factor in the amount of information and keep it relative to topic. Distinct information is what is essential to produce smooth transfer of information from one party to another. The communication needs to be sharp for a teacher/trainer to relay knowledge in a learning environment successfully. Success is the measure of the percentage of material retained and ability to share what is learned with others. Business information stemming from facts, events, and experiences are more clear-cut to formulate and share. Information stemming from theory is a bit more complicated and has an unreliable factor to consider. The unreliable factor means theory is more challenging to put into words and has a wider opening for misreading what is trying to be conveyed across from the teacher to learner. Theory is interpretative, and when sharing theory-based information, be sure to clarify what the basis of the theory is for. Issues stem when theoretical information is being formed and passed on like factual information. This is misleading, leaves it open for interpretation, and will have a negative impact to organizational learning. Learning participants should be informed of the differences between facts, theory, and opinion. When participants are not informed, this could alter understanding of the material and risk of misusing it in their job. When the material is misused, it could result in making wrong decisions, wasting time on efforts not supporting, or growing the business. The level of intervention to mitigate misuse risks and actions to resolve issues from it will depend on the degree of misunderstanding. It is the teacher/ trainer’s responsibility to set it up and clearly state theory from fact. The Content Managers and editors are responsible for ensuring the content is clearly noted as theory, fact, or

Tools for Knowledge and Organizational Learning


opinion. It is not advisable to use opinion-related information in the logical knowledge process. Organizational learning’s major goal is to leverage the knowledge environment across the organization to retain a greater proportion of material delivered through leader trainings. This is a vital component to increasing the overall business capability. Managing the knowledge as an asset provides information to substantiate the return on investment. It also adds authority to the quality of content. The knowledge environment team utilizes resources across the entire organization. They scout the organization not only for content but also to ensure the technical landscape is sufficient and performing well. The technical landscape is periodically reviewed and for future planning purposes where new technology maybe required. The knowledge team is a proactive strategic team that advises the business on knowledge environment needs for process, policy, and technology. Organizational learning is a major driver to these assessments to aid business growth among the groups responsible for growth. The knowledge technical landscape includes the LMS. This links LMS platforms to learning material from trustworthy sources. Training content managers are able to trust the content available to them due to the quality-controlled validation process. Better efficiencies, enhanced capacity, and higher improved capabilities are a few major benefits to organizational learning. Goals for organizational learning from knowledge management are: • Build learning processes for educating the communities within the organization. Processes address content and delivery. Content is supplied from the knowledge environment and processed through the logical criteria.


(Il)logical Knowledge Management

• Continually improve training content to enable organizational learning providers to meet course objectives. • Examine the teaching process within the organization. • Learning participants sustain what they have learned on process, techniques, and systems. • To establish and measure return on investment against the learning curriculum. • Learning participants able to share what they learned with other teammates. • Produce lessons learned from learning sessions. Organizational learning is the major output to a knowledge management process. Knowledge management that supports organizational processes will show improvement over time, instil collaborative decision-making, and produce efficiencies in retrieving information. In the setup of a knowledge environment that produces logical knowledge, there are other outputs to consider, and the manner in which to form content will be shaped from the output in how it will be used. For Organizational learning, shaping content will involve a bit more in editing, presentation, and segmentation in order to produce consumable material. Knowledge management for organizational learning is executed at the individual level and collectively at a group level. Interpretation is the most influential part to learning. Logical knowledge processing can be adjusted based on learning requirements so that the individual or group of individuals are able to interpret and apply what is learned in their jobs. Knowledge as an asset is reducing illogical parts to what is used for learning. Reducing illogical information will increase retention.

Tools for Knowledge and Organizational Learning


MEASURING SUCCESS The knowledge environment will be a system where knowledge sharing and learning take place. Measuring its success takes an approach that will cover all indicators of the logical knowledge process, as well its technical landscape. Knowledge assets are the products in the knowledge environment and the roles involved cover the end-to-end spectrum in implementation, maintenance, and support. Monitoring the systems used in knowledge generation, sharing, and distribution is also measured for performance. The baseline for success will be comprised from the logical process and organizational learning as targets to measure improvements overall within the organization. Benchmarking against business plans will provide specific information on content production, content sharing, and how content is being used as knowledge. Methods to use for measuring knowledge success include user interviews and surveys, practice surveys, focus groups, and storytelling. Measure and focus on the tangible change as a result of using the knowledge environment. Collect evidence that shows the value and relevancy of the knowledge initiative. Instil an outlet for taking in feedback on a continuous basis and use feedback to implement improvement actions. The knowledge management should be reviewed every month in the first 90 days and following on once a quarter for one year. Annual reviews are scheduled onward. Measurement is a touchy topic for knowledge management. Measuring the effectiveness of your knowledge management effort is by finding the right evidence within its intangible nature that substantiates how well the environment is working. It is challenging to measure an intangible environment like knowledge management, but it is important to do so to be able to demonstrate the benefits in value of the investment in the knowledge environment. Metrics and


(Il)logical Knowledge Management

measurement frameworks portray progress during the implementation stage, which is where most of the intangible work is done. Data through measurement will help recognize problems and create corrective actions when things are not working as planned. Being able to show evidence of the affectedness from your knowledge environment strategy will be better protected against any organizational changes or cost-cutting efforts. Here are some key methods to use to evaluate knowledge management performance: • Satisfaction metrics from the technical tools and strategy approaches • Return on investment calculations • Feedback from people within the organization using the knowledge management environment • Qualitative evidence on the knowledge environments impact to business outcomes • Knowledge management tools and technology metrics. Deciphering what you read when searching knowledge platforms is a personal interpretation and uses mostly one’s own intuition based on their need at the exact time of need. For example, when stuck on a task, a person will search and dig through as many knowledge bases, articles, emails, and whatever content topic related that is available to them. The time it takes to scour all this information is what makes the difference between setting up knowledge repositories for people to search and setting up a knowledge environment structured for a business. Structuring a knowledge environment with robust automation is where the value comes in and makes content into knowledge assets. There are many

Tools for Knowledge and Organizational Learning


organizations, like BABM (Case Study – Part 2) simply setting up knowledge repositories and leaving the search and interpretation of content to the individual. This in itself is time consuming and costly to do. To take the knowledge repository setup to the next level will require more time and cost to construct the resources and implement. The investment will be worth it in the long run. The value is extraordinarily different because there is a strategic formation laid out in the knowledge environment, and at the bottom line, it saves time and money overall once a knowledge environment is operable and sustainable. Staff is no longer bogged down and delaying important items such as business proposals that could be winning new business. There is a lead advantage to have a knowledge environment versus having knowledge repositories. Knowledge repositories are good for tips and hints and FAQ-type content. These areas do not have time restrictions. Knowledge environments are the best for being proactive and streamlining processes that do have time restriction tasks.

CASE STUDY – PART 2 BABM is a technology company, headquartered in NYC. The company provides technology management consulting services, managed solutions for networking, and help desk services. BABM’s major goal is to provide world class services for network and help desk services. Their goals to accomplish over the next 12 months are: • To increase turnaround time for service design work by utilizing existing knowledge. • To improve consistency on network designs by having a standard design model to begin with.


(Il)logical Knowledge Management

• To improve the customer experience with BABM help desk services. • Help clients lower their costs per call and incident volumes by implementing core it service management (ITSM) business models. BABM leadership is turning to knowledge management as a main part of their strategy to achieve these goals. There is not a formal knowledge management program in place; however, some staff within information technology and sales implemented some knowledge management best practices. BABM leadership decided to leverage existing strategies and processes already in place as a means to improve the customer experience and to minimize the high amount of time redoing network designs from scratch. The CTO is teaming up with the department heads from the business to strategize and determine next steps. They agree to start with a formal ITSM evaluation to take place with a management consulting firm specializing in ITSM programs. The evaluation was completed over an 8-week time frame. The evaluation uncovered several core issues that are impacting service quality to BABM customers. A detailed report was provided to the CTO and shared with department heads. The issues reported to the CTO and department heads are mostly related to: • Their methods for managing knowledge content. • Ineffective use and inadequate compliance using systems and tools to support knowledge. • Their ways to disseminate and distribute knowledge is ineffective.

Tools for Knowledge and Organizational Learning


• Their approach to knowledge management is decentralized and unsupported by key personnel. They have multiple bodies of knowledge and each is managed by their department. Findings show some redundancy on effort and content. • There is a gap between qualifying information and content validation. • There is no formal process in place to distribute and share knowledge. The causes to these issues need to be carefully analyzed, as these are major influences to creating high costs for service design work, and cost decisions are impacting the quality of service designs being created. There are other issues identified; however, the above core issues are of highest impact priority for BABM in order to achieve their goals on time. The CTO and department heads are joining efforts on a project they call, Evolve–Solid. Evolve–Solid is a program to develop an integrated knowledge management structure for the entire company. Evolve–Solid will also address the issues identified from the ITSM evaluation and update outdated technology that includes implementing a knowledge management system and tools to support the new knowledge management structure. The staff to support Evolve–Solid includes a Program Manager and two Project Managers, one for process delivery and the other overseeing technology delivery. A Knowledge Manager was hired and is responsible for assembling a knowledge management team that includes a knowledge management Consultant to head design and development, a compliance analyst, ITSM Consultant, and several Knowledge Content Managers. A formal Knowledge Management Office


(Il)logical Knowledge Management

(KMO) is established to bring the vision for Evolve–Solid to life. Their plan was fully executed. A knowledge structure is developed and implemented in seven months. Knowledge management best practice process framework and systems are implemented. Several months after go-live, user complaints became increasingly high, even though there is some improvement on the core issues. The Evolve–Solid program team did some research on the plan implemented and investigated user complaints. The investigation revealed there were new and more complex issues occurring from the new knowledge management environment. The issues are so convoluted and it is produced problems that seem too overwhelming to solve. For example, knowledge content is worsening service quality and creating significant delays to a point the business wants to do away with the new knowledge management structure. The quality of the content from the knowledge management systems is not as stellar they believed it would be. For instance, there are user instructions for a business application which was supplied by an employee using this application. The user instructions were not clear, and reports showed people following it were making mistakes. The project team’s investigation identified an issue with verifying and validating content, and sources for content are not put through an approval process. An analysis showed that these new perplexing issues are mostly related to the illogical state of the information used to build knowledge content and how the sources for knowledge are selected. The KMO puts a structure in place similar to a wiki-like platform. This platform was chosen due to the simplicity and short time lines to implement. The knowledge platform is an open door for anyone to record what they perceive as knowledge and is able to contribute said knowledge as long as it relates to topic. The design was simple and the search criteria unfriendly except if you are a savvy user

Tools for Knowledge and Organizational Learning


capable of advanced internet searches. Other issues users complain about have to do with informal methods and distribution of knowledge. The design isn’t set up to distribute knowledge as much as it is set up to collect knowledge in any form, on any topic, from any person within BABM. Stakeholders and users all agree there is a critical need for a knowledge management environment. They can see the end vision and can visualize many benefits to the program once these new issues are resolved. They decided to bring in consultants who are experienced in dealing with complex knowledge management issues. The consultants did an assessment on the new KMO setup and researched each issue raised. During the assessment, they uncovered additional issues within the technical landscape and gaps on governance controls, validation process, and the resources to support it. They presented a mitigation plan to redo the KMO and relaunch a Knowledge Environment. The mitigation plan included revamping the roles and to support the knowledge environment. BABM added Content Reviewers/Editors also responsible for seeking out new knowledge (Content Detective), and a Knowledge Asset Manager and Content Analysts to enhance relationships and work with business users. Technical experts were added to the team to implement, maintain, and support the technology used in the knowledge environment. The new roles were sourced, and the new plan implemented. With the new roles in place, there were enhancements made to the knowledge processes to separate, and only source authorized and logical knowledge. The Knowledge Manager in conjunction with the CTO and Business Leaders defined the internal aspects to what validation means and used this as the basis in the logical knowledge process. The entire logical knowledge process was implemented and the new knowledge environment went live within six months. The go-live is


(Il)logical Knowledge Management

transitional by department and large groups of similar user communities. The first 90 days were closely monitored and evaluated to make necessary enhancements that were not predicted in the new plan. There were quick results on the first launch, and the users reported a better experience and found the ease of use in the new environment to be navigation friendly. They specifically were satisfied with having a support team and a wiki to get answers to questions. BABM is on the right track and continued to rollout the knowledge environment to all user bases in a 13-month time frame.

CONCLUSION Knowledge management will be affected by different perspectives. The focus is on creating a knowledge environment and optimizing the processes associated with managing knowledge. Use people and process centric strategies. People and process strategy methods are more important today than ever before. Functional and critical thinking skills are necessary to carry out the elements of a logical knowledge management process. Problem solving skills are essential with high speed and intricate functionality from technology, and from change happening at hyper speed. Just with the change moving too quickly is a problem in knowledge management. The boundaries of change and frequency of it must be set realistically at the organization level. Creativity is needed to design a landscape of interconnected process and technology to make the right knowledge available at the right time to the right audience in an agile manner. It’s also needed to lift the burdens of using knowledge from the user and invoke better structures to deliver more effectively. The capability to carry out these tasks rests on the people in the organization.

Tools for Knowledge and Organizational Learning


Transformations for managing knowledge is from highperforming processes. A frame of reference to knowledge exists, where there is shared experience and common background. The basis and processes of knowledge management is a regimented function; however, the intricate details that alter a smooth process will likely occur. There are too many variables to document and predict in a knowledge strategy. The vital piece to using knowledge in business is ensuring that it is validated, verified, and is logical. Stop the practice of hoarding knowledge. Only collect and store what is needed. There is no need to store knowledge that is not needed because it will outdate itself well before the need will ever arise for it. Knowledge management issues using modern technology can only be addressed and solved through process-centric solutions. Process-centric solutions focus on decisionmaking, quality assurance, and verification on content used for knowledge. Comprehensive process-centric strategies are also needed to enhance our design and development of technology and how it is used in knowledge management. For example, people improve AI decision-making designs and the configuration of pattern recognition software to improve the learning process. Cognitive computing, AI, and knowledge management are predominant in business today and will continue to take over core business functions. It is essential for businesses to adopt process-centric, people-centric, and governance strategies. These strategies will improve: • Content volume management • Handling content through a cycle of activities to meet its purpose and output • Content validity and reliability


(Il)logical Knowledge Management

• Organizing content from logical and illogical states • Filtering and categorizing content appropriately within context requirements • Defining criteria to how content is processed to a knowledge asset • Decision-making done with authority • Realistic technical designs for development. Idea is to right size technical design to the need and add capacity to support a specific timeline • Better design decisions when setting up AI or cognitive computing for narrowing down knowledge to suit specific purposes. Start to discard what is not needed. Stop hoarding knowledge to sit around and clog up the channels to deliver useful knowledge. In the viewpoint of illogical and logical knowledge management, the focus is predominantly on the content made available from a knowledge environment. You talk about quality and integrity of content, but it is much more than that. It is the formation of the material that makes up knowledge. With enormous amounts of information in which we build our knowledge assets, there must be processes to assimilate them in the same manner asinformation. It is just that the wording of knowledge and information overlap and create some blurred boundaries between the two very different processes. Information management in early days of business and computerization is significantly different in how information is managed in the 21st century. During the 1980s, through to the early 2000s, information was processed as it was entered or imported into system store. Data analysis and data mining then were laborious and

Tools for Knowledge and Organizational Learning


involved a combination of automation and manual effort. Today information streaming into knowledge management is formed to produce a state of content that is used to learn or understand a topic or situation. Knowledge is convoluted and is extremely massive and almost infinite because it is continuous. The technology is matured to keep up with the agile pace of managing knowledge. Knowledge management is a continuous effort because there is an error-changing requirement of what type of knowledge is needed. Technology is advancing, but the business world is more entangled with using it than they are with keeping up with it. There are a number of growing problems with executing on knowledge activities well and they mostly have to do with faults in design, development, and use of technology. To reiterate, technology fails mostly because of how it is designed and implemented. There is room to improve this area and it needs to be done better to right size technology to suit its use in a balanced manner. Proper planning and use of knowledge management tools and utilizing knowledge management processes should bring us to where we are working on the right things at the right time. And while doing so, the resources of knowledge should be made available much more easily than they are with the modern technology, but the complexity of using the technology in the way it is designed is not providing those efficiencies well.

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Knowledge management doesn’t come without its problems, and there are various causes and solutions to consider when you encounter them. The common areas of knowledge management problems are related to knowledge creation, retrieving knowledge efficiently and returning exact results, knowledge transfer, and the application of knowledge in situational circumstances. The main cause to these types of problems comes from process, or incorrect knowledge environment structures, or a technical correlation. One solution in these types of problems is work it from the angle of process and nontechnical first. A technical solution will only apply when the existing software or hardware is broken, needs additional capacity, or added infrastructure. The ability to manage knowledge resources is at the core of executing on knowledge disciplines well. Common enterprise knowledge management issues are: • The business suffers from unauthorized knowledge content even with a knowledge team and regular knowledge requirement meetings taking place. • The strategic vision for knowledge management isn’t understood or clearly communicated. • Communications through electronic delivery. • Content with proper context. • Lack of or inconsistent staff involvement. • Weak cost analysis.



Mengwei Tu

• Realizing the benefits from formal knowledge management. • Users impacted or burdened with excessive time constraints to search and retrieve knowledge. • How knowledge is presented within the organization. • The content quality to detail is insufficient. • Knowledge management structures or resulting in poor customer service or poor customer experiences. • High volumes of knowledge content. • The amount of unused knowledge sitting in storage. • Inadequate balance between supply and demand of knowledge and having it available at the right time to the right audience with the right content. This problem is often caused by extremism have either too much technology or not enough. • Using up budgets supporting and storing big data. When a substantial amount of this big data is not in use. • Misuse of policies or not setting sufficient quality policies around knowledge management. • Inadequate knowledge plans. • Unclear descriptions on how knowledge repositories are used. • Designs missing content formatting and repository structure.

INDEX Artificial intelligence (AI), 83–84 technology, 86–88 Asset tools, 96 BABM, 24–27, 48–49, 103, 109–110, 113–114 leadership, 110 Big data, 85–86 Brainstorming, 6 Business compliance, 53–54 culture, 67 infrastructure, 83 intelligence, 12, 97–98 management, 93 Capturing systems. See Customer tracking systems Categorization, 10 Centralized silo, 68 Classification, 10 Cognitive computing, 86, 87–88 Collaboration, 29, 64–71 Communication, 103 software, 96 Communities, 68

Content collection, 8 collectors, 8 with context, 54, 61–64 leveling, 29 management, 4–5 reasoning, 43–44 reviewer, 48–49 storing, 8–9 validation, 57 Context, 68 content with, 54, 61–64 Cooperation, 68 Coordination, 68 Culture, 64–71 Customer tracking systems, 96 Data, 11–20, 56 handling, 83–84 mining, 95 transformation model, 54–55 Deciphering, 108–109 Decisions, 55 Downsizing, 23–24 Evolve–Solid program, 26, 111–112



Explicit knowledge, 15 Facebook for business, 70 Finding knowledge, 35–36 Fitbit, 87–88 Gap analysis, 84 Garden of Wisdom, 37–38 Hands-free business, 90 (Il)logical knowledge process, 11–20 case study, 80–82 content with context, 54, 61–64 culture and collaboration, 64–71 knowledge distribution rules, 72–75 knowledge transfer rules, 71 logical knowledge management process, 75–79 right data, 54 Information, 11–20, 55 management, 4, 37 sharing, 69 stemming from theory, 104 technology, 96–97 Interpretation, 106 IT service management (ITSM), 24–25, 110 Consultant, 26, 32 evaluation, 26, 28, 31


Know-how trade management, 93 Knowledge, 11–20, 53–54, 54–56, 92 analytics assets, 35–36, 57–58, 76, 107 bases, 40–41 distribution, 11 distribution rules, 72–75 repositories, 108–109 sharing, 72, 101–102 sources, 38–44 strategy, 6–11 team, 105 trail, 24, 36–38 transfer rules, 71 user agreements, 5–6 Knowledge content, 59–60 segmentation, 45–49 Knowledge environment, 71, 74, 85–86 team, 98–100 Knowledge management, 1–2, 4, 18–20, 37, 53–54, 56–58, 83, 87–88, 97–98, 102–106, 112 case study, 24–27 framework, 63 implementation plan, 20–24 planning, 90–91 preplanning and planning stages, 1–2 volume in, 58–59



Knowledge Management Office (KMO), 26–27, 111–112

skills, 9–10 Recycling knowledge, 35–36

Learning management systems (LMS), 96, 105 Logical knowledge, 11–20, 28–31, 31–34, 60, 102, 106 environment benefits, 50–52 management, 56, 75–79 phases, 35–36

Segmentation, 16 Sharing knowledge, 35–36 Sources, 16 Strategy creation, 6 Success, 104 measuring, 107–109

Quality assurance, 95

Tacit knowledge, 15 Tagging, 62–63 Technical maturity, 92 Technology, 83, 90–92 education, 92 for knowledge, 98 knowledge team, 98 systems, 4 Textbook education, 92 Time management, 89–90 Tools for knowledge and organizational learning case study, 109–114 high-level knowledge landscape, 84 knowledge management and organizational learning, 102–106 logical process phases, 84 measuring success, 107–109

Reasoning competencies, 10 practices, 42–43

Under-engineered infrastructure, 91 Understanding, 12

Maturity, 92 Measurement, 107–108 Mitigation plan, 113 Modern technology, 85, 88–89 Occupational silo, 74 Organizational learning, 102–106 Over-engineered infrastructure, 91 Planning, 63 Problem resolution, 73 Producing knowledge, 35–36 Proprietary outlets, 42 Public outlets, 41–42



Validation, 22, 85–86, 98 Valuable knowledge, 64 Value, 28

Verification, 85–86 Wisdom, 54–58

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