What is knowledge management?

Knowledge management is the process of creating, capturing, structuring, storing, analyzing, and sharing knowledge within an organization for operational efficiency. Because all organizations rely on data, knowledge management tools help ensure effective decision-making. How organizations manage data (or knowledge) directly impacts productivity, growth, and resilience. Effective knowledge management systems allow employees to access information quickly when needed. The result is improved collaboration, faster response times, better customer service, and overall business outcomes.

Knowledge management captures, records, and disseminates essential information from team and organizational data to internal and external news. Market trends, performance reports, strategy documents, procurement flows, and more make up the web of information that, when effectively managed, can improve operational efficiency.

Knowledge management is reliant on a knowledge management system, made up of databases and protocols. Effective knowledge management also requires understanding the processes, critical or ancillary, serving an organization's operations. As data volumes increase and companies grow into distributed models, efficient knowledge management offers organizations more agility, speed, and better insights. This is where search comes in. By harnessing the power of search and search AI technology to boost knowledge management systems and capabilities, organizations empower their decision-making and drive innovation.

Organizations rely on three main types of knowledge: explicit knowledge, tacit knowledge, and implicit knowledge. Explicit, implicit, and tacit knowledge play different roles within an organization. They are often described as know-what, know-how, and know-why knowledge, respectively. Understanding which type of information falls under which type of knowledge is key to effective knowledge management, guiding knowledge identification, capture, and storage.

Explicit knowledge

Explicit knowledge is defined as knowledge that can be easily defined, recorded, and disseminated. It is the most easily shared type of knowledge. Explicit knowledge can include operational procedures, company policies, research reports, financial and historical data, approved FAQs, and more. If you can say it or write it down, it's explicit knowledge.

Businesses need explicit knowledge to train new employees, maintain quality control, and ensure compliance with regulations. Knowledge repositories, like a company's standard operating procedures, contain explicit knowledge and guide employees in a variety of tasks. By effectively managing explicit knowledge, organizations improve their efficiency and resilience: teams can reduce errors and ensure that best practices are followed consistently. 

Tacit knowledge

Tacit knowledge is the knowledge gained from individual experience and is harder to define. It includes the set of instincts, intuition, and skills acquired over time. Gaining tacit knowledge is less straightforward than accessing explicit knowledge. It can be transferred through mentorship, coworking, shared space and experiences, and apprenticeship. 

An example of tacit knowledge might be the way a project manager reads a client's needs: they might understand through their intuition and years of experience that the client needs more frequent updates and a more collaborative approach to deliverables to maintain a successful relationship. The project manager may not be able to clearly explain their instinct, but they will have the tacit knowledge required to succeed. 

Implicit knowledge

Implicit knowledge, while sometimes used interchangeably with tacit knowledge, can be defined as the application of explicit knowledge — that is, know-how. It has yet to be codified but serves as the bridge between explicit and tacit knowledge. For example, a coder might consult a peer to understand which course of action to take for a specific problem. Their peer will share their implicit knowledge to help problem-solve.  

To record implicit knowledge, organizations can encourage reflective practices, such as debriefs or post-project reviews, during which employees can discuss their experiences and insights. This increases implicit knowledge visibility, making it accessible to others, and serves the process of knowledge management within an organization.  

Ultimately, organizations can rely on the 5 Ps of knowledge management: purpose, people, process, platform, and performance.

1. Purpose: The question to ask here is what are the organization's overall objectives, and how can knowledge contribute and help to achieve those strategic goals.
2. People: People with the right skills can contribute to an organization's knowledge. Knowledge management also depends on understanding the needs of end users and stakeholders.
3. Process: Knowledge management is tied to the organization's systems, governance, and policies, and ensuring those are followed efficiently.
4. Platform: Capturing and sharing knowledge is dependent on finding the right tools, technical approaches, and solutions.
5. Performance: Like with any management project, continuously measuring performance against organizational goals and setting up a feedback loop is essential.

By defining these components, organizations can form tailored strategies and establish their own best practices for initiating efficient workflows, choosing the right tools, identifying stakeholders, and measuring the success of knowledge management initiatives.

The knowledge management process varies from organization to field in the same way that processes and standard practices do. However, effective knowledge management is at its core a systematic process, sometimes defined by four Cs: creation, capture, curation, and collaboration. While there may be variance in the names given to different stages of the process, capturing, storing, sharing, and utilizing knowledge within an organization typically involves the following steps:

1. Knowledge creation

The first step in the knowledge management process is identifying what knowledge exists in the organization and what information is critical to operations. This is knowledge creation. Understanding the difference between explicit, tacit, and implicit knowledge in this step is crucial to setting up the following steps in the management process.

2. Knowledge capture

Once knowledge has been acquired, it must be captured, recorded, and/or codified. Organizations can document explicit knowledge in structured databases like spreadsheets or manuals. Implicit and tacit knowledge can be captured through interviews, mentorship programs, or case studies before it is stored.

3. Knowledge storage

Knowledge storage is a key step in the knowledge management process. How and where information is stored determines the ease of access by concerned parties. This step requires an information technology system, or IT system, to be in place: this is where knowledge becomes information, which becomes data. Most types of knowledge are categorized as unstructured data in an IT system and are stored in knowledge repositories or databases. Different types of data may require different formatting to fit in given repositories.

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4. Knowledge sharing

Once knowledge has been acquired, captured, and stored, it can be shared for personal and collective use in an organization through training, briefing, and exchange. Successful knowledge sharing or dissemination is tied to organizational culture: if a company encourages knowledge sharing from the ground up, it helps the spread of information. This, in turn, can help an organization maintain a competitive advantage through increased productivity, better morale, and ultimately, more resilience.

5. Knowledge review and update

Reviewing and updating knowledge is a vital part of what is, all in all, a continuous and ongoing process. As knowledge evolves, so too must its capture. Outdated information can be a kink in any organizational machine. That's why conducting frequent knowledge reviews through audits and updating knowledge as needed is important.

When done right, the benefits of knowledge management extend from internal performance to business growth. Organizations consume and produce information to function. Understanding, harnessing, and applying this information to business practices keeps companies competitive. Effective knowledge management systems influence productivity, efficiency, and the bottom line by optimizing operational efficiency and driving innovation.

Better performance

Accessing information when they need it, with little to no friction, empowers employees to make decisions faster, to collaborate better, and to work more efficiently. As a result, overall organizational performance improves.

Improved competitive analysis

Knowledge management that is tailored to an organization will, in the knowledge identification stage of the process, factor in what data is relevant to the enterprise. By gathering, processing, and storing information related to market trends, competitors, and customer preferences, organizations get a leg up on their competitive analysis processes.

Continuous improvement

Knowledge sharing contributes to continuous improvement within the organization. When employees learn from one another and have access to updated information, the organization benefits, especially if it has implemented a knowledge-sharing culture. Capturing knowledge is also a part of a continuous feedback loop that supports the refinement of processes, products, and services.

Fostering innovation

When knowledge is freely shared and easily accessible, innovation can thrive. Successful knowledge management facilitates the exchange of ideas, encourages collaboration, and helps break through silos by connecting disparate pieces of information. This leads to breakthrough innovations. By making knowledge more accessible and fostering a knowledge-sharing culture, organizations can tap into the collective intelligence of their workforce to generate new ideas and solutions.

Identifying successful knowledge management strategies can start with understanding how knowledge management fails. Hoarding knowledge — the anti-knowledge sharing — can result in significant knowledge gaps and actively decrease productivity. Sharing outdated information can equally negatively impact the bottom line. Most commonly, searching for information can be time- and resource-consuming — the antithesis of productivity and efficiency. Effective knowledge management relies on these strategies:

• Organizational culture and leadership: Culture is the antidote to knowledge hoarding or gatekeeping, and the heart of a successful knowledge management system. An environment that actively encourages and rewards knowledge sharing — explicit, implicit, and tacit — helps collaboration and productivity and drives innovation.

• Incentives and rewards: To cement a culture of knowledge-sharing, organizations can implement incentives and rewards for their employees. Encouraging employees to participate in knowledge management ultimately helps the continuous process overall: replacing outdated information is critical to successful knowledge management. Implementing a protocol for frequent knowledge updates can help deal with the constant flux of information flowing through an organization.

• Knowledge management systems: Knowledge management systems (KMS) are crucial to the capture, storage, and dissemination of knowledge. For these systems to serve their users, they must be user-friendly, accessible, and integrated with necessary tools.

  Searching for information can be the biggest obstacle to efficiency. Implementing search tools in knowledge management systems is crucial to effective knowledge dissemination and application. Harnessing AI through conversational search applications can also be considered the next step up in search and knowledge management integrations.

• Training and development: While implementing a knowledge-sharing culture, incentives, and rewards is a key strategy for efficient knowledge management, it needs to be bolstered by employee training and development. This ensures knowledge management standardization within the organization and results in an empowered workforce.

Search is key to effective knowledge management. Elasticsearch is a highly scalable tool for building internal knowledge base search experiences — no matter the size of the organization or the volume of data.

Powered by AI, Elastic's advanced search capabilities help minimize search time by centralizing sources, improving relevance through machine learning, and unifying data on one platform.

With Elastic Observability, organizations can enhance their knowledge management processes with real-time analytics, cross-vertical systems visibility, and actionable insights.

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