What is Knowledge Management? A Practical Guide to Building a Fail-Safe System and Utilizing AI

First, can you clearly explain what knowledge management actually is, including the differences from related terms? Here, let's organize the basic concepts that form the premise of this initiative.

1-1. The Basic Meaning of Knowledge Management

What is knowledge management? It is not simply about storing internal company information on a server. It refers to efforts to make the knowledge, experience, and know-how that each employee has cultivated through daily work reusable across the entire organization. It is important to go beyond merely gathering files and to establish an environment where the right people can access the necessary information at the right time and apply it effectively in their actual work.

1-2. Difference from Knowledge Sharing

There is a term similar to knowledge management called "knowledge sharing." Knowledge sharing refers to the behavioral process in which individuals disclose and communicate the knowledge they possess to other members. On the other hand, knowledge management means the overall management approach that systematically handles the shared information and leads to improved organizational productivity. In other words, knowledge sharing can be said to be the first step toward the success of knowledge management.

1-3. The Relationship Between Tacit Knowledge and Explicit Knowledge

An essential concept for understanding what knowledge management is involves the ideas of "tacit knowledge" and "explicit knowledge." Tacit knowledge refers to the knowledge that exists in an individual's mind, such as experiential rules and intuition, which have not yet been verbalized. In contrast, explicit knowledge is knowledge organized in a way that anyone can understand, such as through documents or diagrams. In knowledge management, the process of extracting an individual's "tacit knowledge" and converting it into "explicit knowledge" that everyone can use is indispensable.

So far, we have explained what knowledge management is and its basic concepts. Now, why are many companies focusing on this initiative today? Next, we will explain the background behind this.

In recent years, the importance of knowledge management has been increasingly recognized by many companies. Various reasons lie behind this, including changes in work styles and advancements in technology.

2-1. The risk of work becoming person-dependent is increasing

As work becomes more complex, the risk of "person-dependence," where only specific individuals understand how to proceed, is increasing. If those individuals are absent, there is a risk that work will be delayed. It is becoming increasingly necessary to manage knowledge as an organizational asset and maintain a state where anyone can respond with a consistent level of quality.

2-2. Increasing Burden of Training and Handover

In today's environment of high workforce mobility, training new members and handing over tasks place a significant burden on the workplace. When the content varies depending on the instructor, proficiency levels can become inconsistent. With systematized knowledge, stable handovers can be conducted without relying on the skills of individual instructors.

2-3. Internal information is dispersed, making it difficult to find necessary knowledge

The diversification of tools for exchanging information, such as chat tools and file servers, has caused the problem of information becoming scattered. To resolve the situation where it is unclear where past know-how is stored and time is wasted just searching for it, it is necessary to organize the access paths to information.

2-4. The Importance of Organizing Internal Data for AI Utilization is Increasing

The number of companies attempting to improve operational efficiency by using generative AI is increasing. However, high-quality internal data is essential for AI to provide appropriate responses tailored to the company's operations. Whether the internal knowledge is organized in a format that AI can easily read greatly influences the effectiveness of AI technology utilization.

It has become clear that social changes and the wave of AI utilization are driving the need for knowledge management. As a result, more companies are starting initiatives, but often things do not progress as expected once they begin. So, why do they fail? In the next chapter, let’s structurally organize the causes.

Many companies consider introducing tools for knowledge management, but there are also quite a few voices saying, "We introduced it once, but it stopped being used." The cause is rarely a lack of functionality in the tools themselves; it is mostly due to the absence of operational rules.

3-1. The Purpose of Accumulating Knowledge Is Ambiguous

Even if the promotion department takes the lead in introducing tools, if the field does not understand "why the information is being recorded," the input work will be seen as merely a burden. Without a clear understanding of the purpose, spontaneous sharing is difficult to expect.

3-2. Tacit knowledge is not documented

Even if tools are provided, it is meaningless if the know-how in the minds of veteran employees is not verbalized and remains tacit knowledge. Without sufficient support on how to document it, the hurdle to converting tacit knowledge into explicit knowledge becomes higher.

3-3. Storage locations and classification rules for information are not standardized

If the file storage locations differ by department or the way titles are assigned is inconsistent, it becomes difficult to find the desired information. When employees repeatedly experience "searching but not finding the information they want," they tend to think "it's faster to just ask a senior colleague," and stop using the tool.

3-4. Manuals and FAQs Become Outdated Without Updates

Knowledge is not something that is finished once written. If business workflows change but the information is left unupdated, trust in the knowledge will be lost. When the perception spreads that "that manual is old, so it's useless to look at," it becomes a major factor in rendering the knowledge meaningless.

3-5. Not Integrated into On-site Workflows

If the creation and updating of knowledge are treated as "extra tasks to be done during spare time," they inevitably get postponed in busy workplaces. Without embedding the steps to refer to and update information as needed within the daily work processes, it is difficult for knowledge to take root.

So far, we have explained the main reasons why knowledge management fails. To avoid such failures, thorough planning before implementation is essential. Next, we will explain specific points to lead to success.

To avoid the failures introduced in the previous chapter and to establish knowledge management within the organization, a well-planned system is essential. What becomes important is designing rules divided into two phases: "Preparation for the Execution Phase" and "Preparation for the Operation Phase." Let’s take a closer look at what should be specifically defined at each stage.

[Preparation for the Execution Phase] Define who, what, and how knowledge will be shaped

4-1. Clarify the purpose, users, and usage scenarios

First, specifically envision "for what purpose," "who," and "under what circumstances" the knowledge will be used. For example, the form of the required information changes depending on whether the goal is "early development of new employees" or "reducing inter-departmental inquiry responses." It is important to design the information according to the purpose and users, considering the reader’s perspective, such as whether to include explanations of technical terms or the level of diagrams.

4-2. Define the Scope of Knowledge to be Shared

If you try to gather all information within the company, important information will be buried in noise. Once the purpose and users are clear, set an appropriate scope accordingly, such as "an overview of tasks for onboarding new employees" or "procedures for handling irregular cases."

4-3. Establish Rules for Notation, Terminology, and Structure

To ensure the readability of documents, unify the rules for notation and structure in advance. For example, set terminology rules to eliminate inconsistencies such as between "customer" and "client," and establish broad structural rules like "operation manuals must always be written in the order of 'Purpose → Preconditions → Procedures.'" This allows for the creation of clear knowledge that is consistent regardless of who writes it.

[Preparation for the Operation Phase] Establish rules and mechanisms for continuous improvement

4-4. Decide on the person responsible for updates and the update process

To maintain the freshness of information, clearly define "who" updates and "when". A vague rule like "whoever notices fixes it" does not work. Specify the responsibility and timing concretely, such as "when there is a change in the business flow, the leader of the relevant department updates it by the end of the month."

4-5. Reflect Feedback from the Field

Knowledge gaps may only become apparent after use. Creating a system that allows users of the information to easily send feedback, such as "a step is missing," and continuously improving the content through this cycle is also key to establishing knowledge management.

So far, we have explained how important operational rules and prior design are. Once the policy is finalized, the next step is to put it into practice. Next, we will explain specific ways to deploy internal knowledge to the field.

There are several approaches to making knowledge management function in daily operations. Adopt the most suitable method according to your organization's challenges.

5-1. Develop Operational Manuals

The most fundamental step is to develop manuals that systematically summarize how to carry out tasks. By including not only specific work procedures but also the purpose of why the task is necessary, precautions, and common points where mistakes occur, the knowledge becomes highly practical.

5-2. Create an Internal FAQ

Standardized questions repeatedly received by departments such as General Affairs and Information Systems are compiled into an FAQ. By providing an environment where employees can resolve issues on their own, the time spent on handling inquiries can be significantly reduced.

5-3. Organize Technical Documents and Educational Materials

Specialized technical documents such as design documents and specifications, as well as educational materials used in past training sessions, are also important knowledge. To prevent these from remaining unused on individual computers, they should be properly tagged and categorized so that those who need them can quickly access them.

5-4. Utilize Knowledge Sharing Tools

To efficiently accumulate and search information, it is also effective to introduce an internal Wiki or dedicated knowledge sharing tools. By using template functions to standardize input and leveraging the system, operations can be smoothed. If the purpose of sharing knowledge is clear and operational rules are well established, it can prevent the situation where "implementing the tool is the end of the process."

5-5. Searching and Utilizing Internal Knowledge with AI and RAG

Recently, methods that leverage generative AI and RAG based on well-organized knowledge have become widespread. When employees ask questions in natural language, AI generates appropriate answers from related manuals, FAQs, and other sources, dramatically improving the efficiency of information retrieval.

In this way, organizing information in the form of manuals and FAQs forms the foundation of knowledge management. Among these, "manual preparation" is especially important as a prerequisite for eliminating dependency on individuals and for utilizing AI. Next, we will delve deeper into why manual preparation is regarded as so crucial.

In knowledge management initiatives, business manuals play a central role. The process of organizing manuals itself provides an opportunity to refine the organization's knowledge.

6-1. Manuals Turn Knowledge into a Usable Form for Work

Manuals are not just a list of knowledge but a conversion into a concrete action process, such as "perform this task in this order." They distill tacit knowledge in one’s mind down to a level where others can directly reproduce it in their work, making them highly valuable explicit knowledge.

6-2. Organizing Work Procedures, Decision Criteria, and Points of Caution

During the process of creating manuals, implicit rules such as "how to make decisions in this case" become visible. This allows you to notice inefficiencies and risks in the work process itself and leads to improvements.

6-3. Preventing Variations in Notation and Structure Across Departments

By standardizing the manual format and terminology company-wide, information sharing between departments becomes smoother. Employees who have transferred in can understand manuals written under the same rules more quickly, which promotes active knowledge flow throughout the entire organization.

6-4. Contributes to Document Quality Improvement Before AI Utilization

In the future, when internal information is loaded into AI for use, the quality of the manuals will directly affect the accuracy of AI responses. Creating structured, easy-to-understand manuals without inconsistencies in terminology is an important preparatory task for the successful implementation of AI in the future.

So far, we have explained the importance of organizing knowledge into reusable "manuals." With well-prepared documents, combining them with powerful AI technology enables even more advanced knowledge management. Next, let's look at specific ways to utilize AI.

If the internal document infrastructure is well established, leveraging generative AI can multiply the effectiveness of knowledge management.

7-1. Streamlining Inquiry Responses with Internal FAQs and Chatbots

With conventional keyword-based chatbots, differences in expressions such as "forgot password" and "don't know the password" could lead to varying search results. By leveraging AI, these variations in wording can be absorbed, allowing the system to understand the questioner's intent and present the correct FAQ.

7-2. Provide answers by referencing internal documents using RAG

By using RAG (Retrieval-Augmented Generation) technology, AI can find the necessary information from internal documents such as manuals and generate context-appropriate answers even for individual questions that have not been turned into FAQs. It also enables quick confirmation of complex business procedures through a conversational format.

7-3. Supporting the Creation and Updating of Manuals and FAQs

AI is useful not only for searching information but also in the creation and updating processes. It can generate draft structures for manuals from existing materials and rewrite difficult-to-understand sentences into simpler expressions. This helps reduce the writing burden on on-site personnel and creates an environment that speeds up updates.

7-4. Streamlining Document Summarization, Proofreading, Translation, and Rewriting

Tasks such as summarizing lengthy reports and proofreading to ensure compliance with style rules are also areas where AI excels. Additionally, in companies with multinational members, automating the translation of knowledge enables information sharing beyond language barriers.

In this way, AI becomes an extremely powerful tool to accelerate knowledge management. However, simply implementing it does not solve everything, and there are points to be careful about in its operation. Next, we will explain important considerations when utilizing AI.

To maximize the capabilities of AI, it is necessary to understand certain prerequisites and risks, and to design operations that appropriately control them.

8-1. AI Response Accuracy Is Greatly Influenced by the Quality of Referenced Data

It is directly proportional to the quality of the internal data being referenced. No matter how advanced the AI you introduce is, if the quality of the manuals or FAQs referenced is low, you will not get the expected answers.

The main reasons why AI cannot correctly interpret information can be classified into the following two categories.

・Problems with the document itself
If the manual's text is logically flawed or uses ambiguous expressions based on implicit understandings such as "adjust as appropriate" or "proceed with the usual procedure," the AI cannot correctly interpret the content and will provide irrelevant answers.

・Data Management Issues
If old and new documents are mixed together on the file server, or if there are many inconsistencies in terminology (such as "customer" and "client"), the AI will have difficulty determining which information is correct.

To successfully utilize AI, it is essential to delete unnecessary data in advance, unify notation rules, and organize and tidy up the information.

8-2. Final judgment by humans is necessary

AI generates answers based on past information, but it cannot guarantee the basis or validity of its judgments. It is important to instill within the organization the stance that final business decisions are made responsibly by humans.

8-3. Company-wide implementation without prior verification carries the risk of failure

Suddenly introducing an AI system company-wide may cause confusion such as "not getting the expected answers" or "the field cannot fully utilize it." First, conduct a PoC (Proof of Concept) focused on specific departments or tasks. Gradually expanding the scope while verifying whether it can answer field questions with sufficient accuracy is the shortcut to success.

In the next section, let’s organize specific cases where you should consider consulting external experts instead of handling everything in-house.

Setting up knowledge management requires more time and effort than expected. If you are facing challenges like the following, leveraging the expertise of specialized partners can help move your efforts forward smoothly.

9-1. There is a large volume of internal documents and manuals that have not been fully organized

There are cases where a large volume of documents accumulated over many years exists, and it is not possible to secure time to review and organize them alongside daily operations. By receiving support from experts, you can efficiently carry out inventory and bulk rewriting of necessary documents in a short period.

9-2. The quality and format of knowledge vary across departments

This occurs when each department has been managing manuals according to its own rules, making it difficult to coordinate and unify company-wide. By incorporating the objective perspective of an external partner as a third party, it becomes easier to smoothly establish a company-wide common style guide.

9-3. Want to improve document quality in preparation for AI utilization and RAG implementation

This is the case when you want to utilize generative AI in the future but are unsure if the current state of your documents is adequate. By building a foundation with expert advice on data structures and writing rules that make it easier for AI to read information, you can prevent setbacks after implementation.

Utilizing Human Science's services is also an effective approach. Human Science offers "Manual Standardization AI Agent Development" as one of the solutions. Based on the knowledge accumulated through years of manual creation, we design optimal quality standards and provide consistent support from bulk rewriting of existing documents using AI to post-implementation operational stabilization.

Companies struggling with manual standardization, please feel free to consult with us.

Manual Standardization AI Agent Development – Special Site for Manual Standardization AI Development Supporting AI Utilization, RAG Implementation, and AI Proofreading Support | Human Science Co., Ltd.

We also offer "MTrans for Office" as a tool to support daily knowledge creation. This is an add-in tool equipped with AI proofreading functions that can be used directly within Microsoft Word. From the document creation workspace, you can perform text proofreading that supports both AI-based and rule-based checks. It is also possible to freely register company-specific rules for proofreading and to share proofreading definitions among team members. This enables smooth unification of notation rules, which tend to vary by department, while reducing the workload on the field and producing high-quality knowledge.

Companies interested in AI proofreading, please feel free to consult with us.

AI Proofreading × Consulting (MTrans for Office) – Human Science Co., Ltd.

Finally, we will introduce a case study of a company that successfully integrated external expertise to simultaneously advance manual improvements and AI utilization.

This is a case study of Mitsubishi UFJ Trust and Banking Corporation, which achieved knowledge standardization and improved the accuracy of the RAG chatbot with the support of an external partner.

10-1. Background: Urgent Need for Manual Reform with a View to AI Utilization

At Mitsubishi UFJ Trust and Banking Corporation, they began improving their operational manuals while aiming to enhance overall company productivity. Until then, manuals were created by each department, lacking company-wide unified rules, resulting in inconsistent quality. Internal surveys also revealed many voices saying the manuals were "hard to understand," making standardization of manuals an urgent task. At the same time, there was a need to organize documents into a "structure easy to understand for both humans and AI," anticipating future AI utilization.

10-2. Solution: Rebuilding the Structure with Consideration for Both Humans and AI

With the support of Human Science, we reorganized the scattered information into a logical and easy-to-understand structure. While retaining diagrams that humans can intuitively understand, we also supplemented the content with text information so that AI can interpret it, and clearly defined the business prerequisites at the beginning, thereby establishing a knowledge base that is easy to understand for both humans and AI.

10-3. Result: Dramatic Improvement in the Response Accuracy of the RAG Chatbot

By organizing the manuals and advancing AI development based on their structure, the response accuracy of the RAG chatbot improved dramatically. It has also received high praise from on-site employees, who say they can now read while grasping the overall workflow. By promoting manual improvement and AI development in an integrated manner without separating them, we succeeded in building a company-wide knowledge management system, leading to enhanced operational efficiency and advanced knowledge utilization across the entire company.

Human Science provides one-stop support from Japanese manual creation to English translation. We have a long history of handling numerous manuals since 1985. If you have needs such as the following, please feel free to contact us.

• I want to improve existing Japanese and English manuals to make them easier to understand.
• I am considering creating an English manual and would like to proceed step by step from the Japanese manual.
• I want to translate and utilize Japanese manuals created in-house into English.

Feature 1: Extensive manual production experience focused on large and global companies

Human Science has accumulated extensive experience in manual production across a wide range of fields, mainly in the manufacturing and IT industries. We have served prestigious companies such as Docomo Technology Inc., Yahoo Corporation, and Yamaha Corporation as our clients.
Manual Production Case Studies | Human Science

Feature 2: From research and analysis by experienced consultants to output

The creation of business manuals is handled by Human Science's experienced consultants. Skilled consultants propose clearer and more effective manuals based on their extensive experience and the provided materials. It is also possible to create manuals from stages where information is not yet organized. The assigned consultant will conduct interviews and create the most suitable manual.
Manual Evaluation, Analysis, and Improvement Proposal Services | Human Science

Feature 3: Emphasis on not only manual creation but also support for establishment

Human Science not only focuses on manual creation but also places great emphasis on the important stage of "establishment." Even after manual creation, we support the establishment of manuals through regular updates and manual creation seminars. Through a variety of measures, we assist in the effective utilization of manuals in the field.
Manual Creation Seminar | Human Science

Thank you for reading until the end. I hope this column provides helpful tips for creating easy-to-understand manuals and utilizing AI.