In today’s fast-paced business world, Knowledge Management (KM) has become a crucial ingredient for success, but a challenging one to implement. Indeed, it’s all about a well-defined approach to gathering, organizing, and sharing valuable knowledge. Thanks to breakthroughs in AI, Data Science, and graph tech, KM systems have experienced an unprecedented surge in scope and effectiveness. So, let’s dive into the unrealized advantages of knowledge management and discover the diverse knowledge types organizations need to harness. Plus, I’ll introduce you to 12 ways innovative technologies like AI and data science are transforming the way organizations handle their knowledge more effectively.
Knowledge Management: What Is It?
First, let’s start with a definition. Even if your company does not have a formal knowledge management (KM) system in place, I would think that most of us are familiar with the KM activities associated with this definition below.
“Knowledge management (KM) is the collection of methods relating to creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organizational objectives by making the best use of knowledge.”
Wikipedia
From my experience, knowledge management is both boring and frustrating. For example, I can think of the many times I have either set up a content management system (CMS) or a Wiki page, and then it was never very effective. Specifically, either people did not use it or it was always out-of-date or challenging to find any useful information.
On the other hand, an organization’s knowledge is critical. Indeed, organizational knowledge is the basis for a company’s culture. It is what drives productivity and efficiency. Further, a company’s intellectual property provides the basis for a company’s innovation and continued success. So, most companies do have some type of knowledge management strategy in place, even if it is not formally spelled out. For instance, in all businesses, people share knowledge. Also, management creates repeatable processes such as new employee training. Another example of KM is where the customer service department maintains frequently asked questions (FAQs) documentation.
The Unrealized Advantages of Knowledge Management.
Often organizations are not able to realize the full advantages of knowledge management. Indeed, the reasons for this are many. For instance, there may be some individuals in an organization who are resistant to sharing knowledge or the information is confidential. Another reason is that knowledge is challenging to maintain and gets out of date quickly. Thus, it becomes costly to maintain the data and people do not trust that the knowledge base is accurate. Lastly, especially in large organizations, searching in a company’s knowledge bases is time consuming.
So, there are many reasons that the benefits of knowledge management are not realized by organizations. Further, despite these challenges, organizations cannot afford to give up on managing their knowledge. To detail, below are the many advantages of knowledge management.
The Advantages Of Knowledge Management
1. Efficient Information Retrieval.
A cloud-based document management system can allow employees to quickly locate and access relevant documents.
2. Enhances Decision-Making, Forecasting, and Insights.
With a comprehensive view of internal data, a company can identify patterns and trends. Hence, this enables more informed strategic decisions, accurate forecasts, and valuable insights.
3. Boosts Employee Engagement and Retention.
A culture of knowledge sharing makes employees feel valued and engaged.
4. Strengthens Customer Relationships and Satisfaction.
KM enhances customer service by enabling service representatives to quickly access information needed to resolve customer issues. Thus, this leads to increased customer satisfaction.
5. Minimizes Skill Gaps and Duplication.
By centralizing and sharing knowledge, employees can learn from each other, minimizing skill gaps, and preventing the duplication of work.
6. Streamlines Workflows, Communication, and Collaboration.
Implementing KM tools such as collaborative platforms can streamline workflows, improve communication, and foster collaboration among teams.
7. Empowers Employees Through Self-Directed Learning.
Knowledge management systems can provide resources for employees to learn and develop skills at their own pace.
8. Boosts Organizational Agility and Responsiveness.
With knowledge readily available, organizations can quickly respond to changes and seize new opportunities.
9. Reduces Costs By Minimizing Operational Redundancies and Inefficiencies.
Through sharing best practices and standardizing processes, knowledge management can eliminate redundancies and improve operational efficiency. Hence, this leads to cost savings.
10. Basis For Continuous Innovation and Adaptability.
Knowledge management encourages the generation and sharing of new ideas. As a result, this fosters an environment of innovation and allowing the organization to adapt to changes more effectively.
11. Expands Market Competitiveness through Industry Expertise.
By harnessing and leveraging collective knowledge, a company can position itself as an expert in its field. Thus, this gains a competitive edge for businesses.
12. Leverages Intellectual Capital for Business Success.
Knowledge management allows organizations to capitalize on their intellectual assets. As a result, this converts tacit knowledge into explicit knowledge that can contribute to business growth and success.
Types of Knowledge For Organizations To Capture And Exploit.
Managing knowledge effectively requires understanding the different types of knowledge that exist within an organization. Indeed, knowledge at its very instance is a fact or condition of being aware of something. Before the written word, knowledge was something that humans retained. And, if they did not pass it on to another human before they died, the knowledge was lost.
Now, besides humans being a source of knowledge, we also have knowledge in documents and stored digitally. So, organizations manage all these different bits and pieces of knowledge that are either in humans or stored in an artifact. Further, organizations need to take a different approach to knowledge management depending on the type of knowledge. Below is a description of different types of knowledge that organizations need to manage.
1. Explicit Knowledge Management.
Explicit knowledge is documented and easily transferable. Additionally, it refers to knowledge that can be codified and shared digitally or via documents. An example of explicit knowledge is a company’s annually published financial reports. Specifically, these reports are accessible to everyone within the organization and serve as a reliable source of information about the company’s financial status.
2. Tacit Knowledge Management.
Tacit knowledge is subjective and hard to document as it is rooted in personal experience, ideals, and values. Specifically, this is the knowledge that individuals acquire over time, and it is often challenging to communicate or transfer to others. For example, a seasoned employee’s understanding of the company culture or a chef’s ability to make a dish perfectly without a recipe both represent tacit knowledge. Indeed, one objective of knowledge management is that where possible, transform tacit knowledge into explicit or higher form of documented knowledge. Otherwise, it is critical that organizations provide employees access to these experts and advisors.
3. Declarative Knowledge Management.
Declarative knowledge refers to “knowing what” – it is factual information that is explicitly stated from the organization’s perspective. For instance, a company’s policy manual or a database of customer information both represent declarative knowledge. Further, this organizational information is factual, easily articulated, and can be shared with others. In many cases, this type of information is also explicit knowledge. The difference is that this type of data is not just collected, but also curated to clearly document the company’s perspective.
4. Procedural Knowledge Management.
Procedural knowledge is “knowing how” – it’s the practical understanding of how to complete a task or achieve a goal. Further, this type of knowledge is often developed through practice and experience. For example, a customer service representative’s understanding of how to handle a disgruntled customer or a machine operator’s knowledge of operating a complex piece of equipment are both procedural knowledge. These skills are learned over time and through practice, rather than being easily written down or explained. Thus, the organization has procedural knowledge to codify the way they do business, creates efficiencies, adds unique value to their customers, drives continuous innovation, and is key to success.
Here’s How Organizations Are Using AI and Data Science in Knowledge Management.
AI and Data Science are transforming the way organizations handle KM. For instance, AI technologies such as Machine Learning (ML) and Natural Language Processing (NLP) can automate the process of extracting and classifying knowledge from vast amounts of data. Similarly, Data Science tools can analyze complex datasets to uncover patterns and insights, aiding in knowledge discovery and decision making. Below are 12 more examples of how emerging technologies like AI and data science technologies are transforming the way organizations approach knowledge management.
Examples Of How Emerging Technologies Are Transforming Knowledge Management
- Conversational Chatbots / Virtual Assistants.
- Streamline Data Analysis.
- Automated Content Indexing.
- AI-Driven Predictive Analytics.
- Personalized Recommendations.
- AI-Augmented Collaboration and Innovation.
- Document Management Assisted By AI Agents.
- AI-Driven Agent For Knowledge-Based Tasks.
- Knowledge Discovery and Insights.
- Automate Content Curation and Maintenance.
- Streamline Expert Identification and Collaboration.
- Generative AI To Assist With Creation Of Procedural Documents.
For a more detail discussion of how KM automation is transforming how organizations are managing knowledge, see SC Tech Insights’ Knowledge Management Breakthrough – The Best Way With AI, Data, And Graph Tech.
Knowledge Management Breakthrough – The Best Way With AI, Data, And Graph Tech.
This article will delve into knowledge management (KM) automation strategies to harness the powerful synergy that is emerging from combining artificial intelligence, data science, and knowledge graph technology. Positively, these groundbreaking advances in automating knowledge management aren’t just pushing the envelope. Indeed, they’re completely redefining how companies understand and use their collective intelligence to drive innovation and secure a competitive advantage.
Click here to explore the explosive synergism of AI, data, and graph tech and the criticality of having a data-centric mindset to leverage these transformative KM technologies. Also, I’ll provide 12 examples of how data-intensive industries such as supply chain and ecommerce can leverage knowledge management automation.
For more information on knowledge management and how emerging tech is changing KM, see the following references: GetGuru’s What Is Knowledge Management?, Forester’s How Generative AI Is Affecting Knowledge Management, LeewayHertz’s AI IN KNOWLEDGE MANAGEMENT, and Tettra’s What Is Knowledge Management?. For information on data science, see SC Tech Insights, Data Science Definition – The Truth About This Discipline And Its Massive Growth. Also, for more on AI, see 10 Examples Of Artificial Intelligence Technology That Will Empower Your Business.
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Writer and expert in supply chain technology and operational analytics. Passionate about giving actionable insights on information technology, business, innovation, creativity, and life in general.