Knowledge management (KM)

Knowledge management (KM) is the process of creating, sharing, using, and managing the knowledge and information of an organization. KM often refers to a multidisciplinary approach to achieve organizational objectives using knowledge as an asset. Many large companies, public institutions, and non-profit organizations have resources dedicated to internal knowledge management efforts, often as a part of their business strategy, information technology, or human resource management departments. As well, there are several consulting companies providing advice regarding KM to these organizations, and there are software vendors offering KM software.

Knowledge management typically focuses on organizational objectives. These objectives can include improved performance, competitive advantage, innovation, the sharing of lessons learned, integration, and continuous improvement. These efforts often overlap with organizational knowledge; KM is often distinguished from organizational knowledge because of its greater focus on the use of knowledge as a strategic asset. KM is often used for organizational learning. The complexity of knowledge management systems has increased over time, with digital transformation and the increased challenges from the volume and speed of information flows and knowledge generation.

The concept and terminology of knowledge management began within the management consulting community. With the rise of the internet, those organizations realized an intranet (an in-house subset of the internet) could be used as a tool to make information accessible and shareable among geographically dispersed units of an organization. In building tools and techniques such as dashboards, expertise locators, and best practice databases, these communities and organizations acquired an expertise, which was a new product that could be marketed to other organizations—especially organizations that were large, complex, and dispersed.

This new emerging product was knowledge management and has been attributed to first being used in its current context at McKinsey in 1987, for an internal study on their information handling and utilization. The type of information captured as part of this new product included organizational documents, team data, organizational data, and organizational news.

Knowledge management systems work to disseminate information throughout an organization, and the type of system used offers different benefits and can make it easier to disseminate the information throughout an organization. A reliable knowledge management platform can serve a range of needs, both at departmental and holistic company level. As well, a system can make it easier to retrieve and share information.

Part of knowledge management is the definition of the types of knowledge that can be collected as part of a knowledge management system: tacit, implicit, and explicit knowledge. These types of knowledge are largely distinguished by the codification of the information.

Tacit knowledge is typically knowledge acquired through experience and is intuitively understood. This is knowledge that can be challenging to articulate and codify, making it difficult to transfer to others. Examples of tacit knowledge can include language, facial recognition, or leadership skills.

While some equivocate implicit knowledge to tacit knowledge, others break this type of knowledge out separately, with the belief that the definition of tacit knowledge is more nuanced. While tacit knowledge is difficult to codify, implicit knowledge does not necessarily have this problem. Instead, implicit knowledge has yet to be documented and tends to exist within processes. Implicit knowledge can also be referred to as "know-how" knowledge.

Explicit knowledge is captured within various document types, such as manuals, reports, and guides, allowing organizations to easily share knowledge across teams. This type of knowledge is perhaps the most recognized, with examples of these knowledge assets that include databases, white papers, and case studies. Explicit knowledge is important to retain intellectual capital within an organization and to facilitate successful knowledge transfer to new employees.

The knowledge management process is often summarized in seven steps, starting from knowledge acquisition, creation, refinement, storage, transfer, sharing, and utilization. However, some further synthesize the process of knowledge management into three main steps which capture the above seven steps. These steps include knowledge creation, knowledge storage, and knowledge sharing.

This first step includes the identification and documentation of any existing or new knowledge that organizations want to have circulated.

This second step often includes an information technology system typically used to host organizational knowledge for distribution. Information may need to be formatted in a particular way to meet the requirements of that repository.

In this final step, processes to share knowledge are communicated broadly across an organization. The rate of which information spreads varies depending on organizational cultures, with companies encouraging and rewarding this behavior often having a competitive advantage over other ones in the industry.

Knowledge management can boost the efficiency of an organization's decision-making ability by making sure all employees have access to the overall expertise held within the organization, creating a workforce that is capable of making informed decisions, often faster. This can make innovation in an organization easier to foster, and customers can, in turn, benefit from increased access to best practices. Often, employee turnover is reduced.

Companies begin the knowledge management process in a variety of situations; examples include:

• a merger or acquisition that could spur the need for codifying knowledge and sharing expertise within teams;
• the imminent retirement of key employees, necessitating that the company captures their knowledge; and
• an upcoming recruitment drive and assisting in the training of new employees.

Further benefits of knowledge management systems can include the following:

• A more efficient workplace
• Better and faster decision making
• Increased collaboration
• Building organizational knowledge
• Employee onboarding and training process optimization
• Increased employee retention with an increase in valuing of knowledge, training, and innovation

While businesses can benefit from knowledge management systems, programs can also benefit from a clear, documented, and business-relevant strategy. If the business use case is capable of demonstrating an understanding of an organization's critical knowledge needs, the knowledge management program can outline:

• the value proposition for knowledge management, or how knowledge management can solve business challenges;
• the tools, approaches, and roles an organization needs to solve those business challenges;
• a budget; and
• the expected impact of knowledge management or the return on investment.

Knowledge management software assists with identification, creation, distribution, and organization of an organization's knowledge. This software at its best gives an organization a unified pool of information, meant to make companies more profitable. This software also contains a range of methods and systems for the collection of information, as well as how the information is stored and accessed. This software stores data such as stakeholder feedback, comments, database records, videos, images, and documents. It works to streamline the centralization, reporting, and sharing of the information.

As well as helping organizations collect and share information with employees and customers, KM software can be used for creating white papers, user manuals, articles, and business processes. It can also provide a range of benefits, including personalized customer service interactions, faster support solutions, and reduced service volume.

In order for organizations to reap the expected benefits, KM software often requires several key features to increase the capabilities of the software and improve its usefulness and accessibility. These features include: search functions, a question-and-answer engine, reporting and analytics, access on any device, workflow integration, tailored solutions, ability to scale, collaboration features, content authoring and editing, and useful integrations.

One of the primary goals of many organizations searching for a KM software solution is to improve the productivity of employees. Incorporating a search function can reduce the time those employees spend on searching for information and is necessary for KM software. This function can allow employees to find what they want using different search parameters. This is achieved by solutions that deep-index all content across all file types to make everything, including videos, searchable—not just document titles and descriptions.

A software platform that allows employees a chance to post questions can offer users a chance to crowdsource answers from subject matter experts across an organization. The platform can also deep-index questions and answers so they become searchable, allowing other employees who have the same question to find it through a keyword search. A feedback function can allow organizers to know if users like an article or if there are any suggestions to help make a knowledge base more relevant to readers.

Software that includes analytics tools can help an organization understand what questions customers ask most, which pieces of content help employees increase productivity and quality of work, which employees are collaborating and sharing knowledge with others, and which employees can help answer questions and optimize knowledge management systems. This can help departments also see which members have viewed and engaged with different pieces of content, helping to hold those employees accountable for keeping up-to-date with the knowledge they need to do their jobs.

The ability for users to access information they need on any device and in remote situations can help employees be more efficient; a knowledge management software solution optimized for multiple device types and offering easy navigation and information digestion regardless of screen size can increase this efficiency.

A knowledge management tool that can integrate with other sets of tools used on a daily basis can decrease the friction of users, allowing users to access the information they need in other programs and in the flow of work.

A platform that feels familiar for users and offers an intuitive user interface is more likely to be adopted by the employees expected to use the software and often has higher continued use rates amongst those employees when compared to a completely unknown entity. Therefore, knowledge management solutions that offer custom branding options can allow organizations to tailor the interface to their company culture and brand to reduce those employee use frictions.

Platforms that allow users to scale with a business is an important feature, including the ability to set different roles for users, which allows administrators to set control permission levels within a platform. The ability to create groups or communities to create distinct destinations within the larger platform is also useful for scaling organizations.

Knowledge management platforms are best when they represent collaborative efforts in an organization, where members come together to create, manage, and maintain a knowledge platform. These collaboration features can allow team members to have defined roles and responsibilities, and these roles can, in turn, define their roles and responsibilities to the knowledge management tool.

Another important feature for knowledge management platforms is the editor. Since content forms the core of a knowledge base, the tool should offer features to help teams write, edit, and publish content effortlessly. As well, an editor that can offer a Microsoft Word-like feature set is often seen as desirable, as it often offers styling and formatting options other editors do not provide. Such an editor can provide advanced features, like inserting images, tables, and videos to a knowledge base; changing paragraph formats, indentation, add page breaks; and adding bullets, anchor links, and more related content.

Similar to the editors and other integrations, the ability for a knowledge management platform to integrate with Google platform tools, such as Google Fonts, Google Translate, and Google Analytics, can increase the options and usefulness of a knowledge management system. These services can offer users an increase in access to more font options, a user knowledge base that is available in over ninety languages with the ability to improve translations manually, and a tool that can allow users to know which efforts in building a knowledge base are bringing the best results.

For organizations wanting to develop their own knowledge management software, they can build an open-source knowledge base that is built on open-source software. The reasons users may want to use an open-source knowledge base in the construction of knowledge management software are based on some common benefits and use cases:

• A user can customize a system to their liking
• Organizations can save money, as the original code is free
• Organizations can rely on internal experts and developers for support when using and growing a knowledge base, rather than paying for access to a SaaS knowledge base's support team
• A user's knowledge base can be integrated with other software already in use
• A knowledge base can be self-hosted on their servers, versus another product's servers
• An organization does not limit the possibilities for scalability or growth, which can occur with a pre-built SaaS knowledge base

Knowledge management, as a term, was first utilized in the 1980s by Peter Drucker and has been recognized as a discipline since the early 1990s. Although, the impulse for knowledge management has been around for as long as humans have been driven by the need to capture, store, and distribute more efficient knowledge. Over time, technologies offering to make this process more efficient have been developed.

The use of knowledge management really increased in the mid- to late-1980s when far reaching economical, social, and technological changes took place globally. Through the process of globalization, many companies began experiencing new opportunities, which led to increased competition and a process of downsizing on the part of some organizations. This led to organizations looking for ways to boost productivity through computer and networking technology.

This process was accelerated as organizations began to try and capture the knowledge lost when experienced employees left an organization. Originally, a common practice was to document everything, but this method often failed because the information was essential and buried in a complex filing structure. This lost information eventually became outdated, and the end-user became frustrated while searching for this documentation; this led to a corporate culture of "re-inventing the wheel" and other inefficient practices. Knowledge was also often locked into departments, smaller groups, or even individuals, and this knowledge could not be easily shared across an organization, leading to duplication efforts. There were often strong resistances, often found at the individual level rather than an organizational level, to give away knowledge, as knowledge was often perceived as power and, in turn, job security.

This led to the initial development of knowledge management systems, which grew from an information management approach. Knowledge was perceived as information to be written or digitized content, and answers to managing that knowledge were sought in IT or internet-based tools, such as databases and libraries, which evolved into what is more commonly referred to as information management. This approach translated into popular tools, such as wikis, blogs, social media, and discussion forums. This approach is also called a "stock" concept, as it aims towards storing information.

These tools allowed organizations to share knowledge across an organization and avoid "re-inventing the wheel" with shared information. In turn, development time and cost were reduced, allowing those organizations to underbid competitors. But this stage of development of knowledge management systems was focused on the effective use of information and knowledge.

After the initial stage of development in knowledge management, tools shifted towards the personal side of knowledge. This was due to the realization that knowledge could not always be contained in information management systems, as it can be personal and objective. This saw the shift of knowledge management towards a human development approach, focusing on the development of personal capacities, as individuals are seen as main carriers of knowledge. This is comprised of methods such as technical, management, and personal trainings, appraisal talks, and formulating personal goals.

However, part of this process involved a need for organizational cultures to change after an examination of how it rewards information and knowledge sharing. Essentially, meaning the organizations needed to reward the sharing of information and knowledge amongst employees, and often this was done through a change in the design of an organization's compensation policy. This process can be very difficult and sensitive. A major component of this second stage was the design of user-friendly systems.

Knowledge management further developed into a focus on people interacting in an environment, such as within a company, a network, or a community. This led to an understanding that more attention needed to be given to the organizational setting in which people work, hence the introduction of concepts such as knowledge-intensive environments and knowledge-workers working in such an environment. The overall objective of knowledge management changes is to help individuals to develop within their surroundings to create an optimal working environment for the knowledge worker. It also focuses on capacity building of stakeholders, thus strengthening organizations and partners in their capacity to apply knowledge and use information.

Part of the development of this stage of knowledge management, and further developments of knowledge management systems, has been the increasing importance of content; the retrievability of that content; and the arrangement, description and syndetic structure of that content. This process has continued to expand, with the introduction of data analytics and machine learning for content searching. However, that content still has to be effectively managed and in order to be effectively retrieved.

Knowledge management approaches have since built into knowledge ecosystems defined by software, in which the approaches described above have built on each other. These ecosystems then allow individuals, organizations, and networks or communities to be equipped to create added and sustainable value.

Other trends have since developed, which have helped organizations move closer to an absolute knowledge management system without need for complete enterprise buy-in or a single solution. This has been done in part through the use of packaged applications that have automated business processes, with an example including ERP systems, groupware applications, and outsourced application providers. These deployments can bring together different sources of data and can provide directories of employee information.

The tools being used have also developed, from groupware applications turning into portal servers, document management systems evolving to include web content management functionality, and business intelligence software offering data mining, reporting, and analytics software. These systems have continued to develop to integrate external communications to enhance scheduling and managing of projects within a knowledge management context. As well, more systems are involving visuals and visual searches to help users more flexibly search and index knowledge. With all of this, the systems have continued to develop to be accessible in remote work situations; to be easier to understand with navigable user interfaces; and to integrate tools such as data analytics, machine learning, and artificial intelligence to strengthen to capabilities of KM software.

With the use of machine learning and artificial intelligence, KM software is able to develop information from user behavior, without using more traditional feedback methods, in order to help users retrieve information and develop behavioral models for information retrieval systems. These include the importance of activities, past actions, specific search behavior, and emotions associated with information. And with the use of weak supervision in artificial intelligence, these systems can be used with data sets existing within a company and without the need to be entered manually and classified. With more use of artificial intelligence, KM software also offers the chance to develop greater automation and reduce the tedious work from knowledge management workers.