The ultimate guide to enterprise knowledge management in 2024

McKinsey reports that employees searching for internal data waste an average of 9.3 hours, or about 20% of their weekly working hours.

This is equivalent to employing one dedicated employee whose only job is assisting different teams in providing the information required to generate productive output.

And that’s not feasible for many enterprises. Most operate across different locations, and hiring one dedicated resource for information search at every location is too much of an overhead cost. This kind of setup only encourages the siloed structure that most enterprises are trying to lift off.

But then, how do you ensure that the least time is devoted to finding information and solutions to problems that happen frequently or have happened in the past?

Addressing inefficiencies like this requires a more structured approach to information handling, and this is where Enterprise Knowledge Management (EKM) comes in.

EKM systems enable faster decision-making and increased productivity by creating a single source of truth for all scattered information.

This guide will discuss enterprise knowledge management and its best practices in detail. Let’s get started.

What is enterprise knowledge management?

Enterprise Knowledge Management, or enterprise information management (EIM), is the systematic process of capturing, organizing, and leveraging an organization's data using advanced technology to enhance its strategic capabilities.

It goes beyond simple information cataloging, focusing on the intelligent curation and deployment of knowledge assets to drive innovation, streamline decision-making, and facilitate cross-functional collaboration.

A knowledge management system helps you find information and answers to your questions/ issues. It eliminates the need for a dedicated team to help find answers to already existing solutions.

For example, you can quickly find answers to questions about company policies, like the leave policy or accessing the company VPN.

With tools like Atomicwork, this becomes easier as the AI Assistant, Atom, understands your message and its context to provide the best answer and the source.

For example, you can ask Atom questions like:

• How do I set up my email on my phone?
• What should I do if I receive a phishing email?
• When is the next payroll date?
• How do I apply for parental leave?
• How do I access my work files from my home?

How has enterprise information management evolved?

EIM has evolved significantly over the years, becoming more agile and user-friendly.

Initially, organizations heavily relied on human agents or self-service portals that allowed employees access to information. The result was human agents overflowing with support requests they could barely handle.

Alternatively, self-help portals were difficult to use and remained underutilized in most enterprises. They also lacked proper integration with daily operations and workflows and provided generic responses, limiting the effectiveness of early EIM systems.

No wonder all these led to employees resorting to manual processes for information.

As technology advanced, we witnessed the rise of collaboration platforms like Slack and MS Teams, which integrated EIM seamlessly into our daily operations.

These platforms deliver enterprise information directly within the platform, empowering employees not to switch between multiple tools at the same time.

In the last few years, this efficiency has been further enhanced by integrating AI-powered assistants with such collaboration platforms, leveraging LLMs, and offering more natural and contextual responses, saving valuable hours locating critical data or information.

Why is managing enterprise knowledge important?

Managing enterprise knowledge helps organizations and employees to:

1. Faster responses for end-users: With a robust knowledge management system, end-users can self-serve information and don't have to wait for their queries to be answered. This leads to quicker problem resolution and improved user satisfaction.

2. Reduced team workload: Service agents are not bogged down with repetitive queries as requests are deflected from the service desk with a rich knowledge management system. This allows support teams to focus on more complex issues and strategic initiatives.

For example, Ammex Corp, a leading safety gloves distributor, experienced significant improvements after implementing an AI-driven knowledge management system. They were able to achieve a query deflection rate of 65% with our AI assistant, Atom.

This improvement allowed Ammex to maintain its IT service team without adding any headcount for six months despite the company's growth.

The ROI on deploying Atom across our teams has been incredible. Unlike Jira Service Management, Atom allowed us to maintain our IT service team without adding a single headcount in six months. It handles simple queries that used to interrupt our Finance team, and it provides our CEO with real-time updates on shipments and orders - questions that would normally require a phone call or an email or a meeting, disrupting someone’s day - Chad Ghosn, Ammex’s CIO and CTO

Read the complete case study here.

3. Manage support costs: Businesses can control support costs with a lean support team and an effective self-serve system. Organizations can allocate resources more efficiently and reduce overall operational costs by reducing the need for large support teams to handle routine queries.

4. Improved productivity and efficiency: A well-managed system streamlines processes and reduces redundancy, helping improve decision-making across departments. Companies like Siemens implemented knowledge-sharing platforms to streamline the deployment of new technologies and optimize processes, improving operational efficiency.

5. Improves cross-department collaboration: Enterprise information management streamlines open communications and collaboration. It helps employees be more productive by quickly finding the answer to their queries.

Google uses open communication and data-driven decision-making to encourage collaboration and ongoing learning, leading to groundbreaking innovations.  

6. Standardize knowledge discovery and handling: When you use a knowledge management system, you set standardized methods and processes for capturing data, storing it, and disseminating it. This helps create a structured format and consistency in knowledge assets, making it easier for employees to consume the information.

7. Helps mitigate loss of information: Without centralized knowledge management, information retrieval depends on individuals. Therefore, there is a risk of losing critical information after an employee leaves. Knowledge management mitigates this risk by creating an automated system that pulls information from various sources, updates it, keeps it safe, and makes it usable.

The stages of enterprise knowledge management

Managing enterprise knowledge is a multi-stage process that requires careful planning and implementation.

Let us break down the critical stages:

Stage 1: Knowledge capture

The first stage covers identifying and collecting useful data and information from other sources in the enterprise. These sources involve communication channels like Slack and Teams, asset management platforms like SharePoint and Google Drive, HR and payroll software, etc.

Stage 2: Knowledge storage

After capturing, the knowledge data is organized and stored for easy retrieval. This involves systematically arranging and indexing the data, using knowledge management systems, databases, and repositories for intuitive searches.

Stage 3: Knowledge sharing

If knowledge is not available or remains hidden, it loses its value. To help employees discover the right information at the right time, use systems designed to provide easy access to knowledge. These systems tailor the information to the user’s specific needs and quickly retrieve it, maximizing the adoption and ROI of EKM.

How to manage enterprise information effectively?

A solid information management strategy allows employees to easily find the needed resources, streamlines workflows, and minimizes inefficiencies. Organizations must have a well-structured system that facilitates smooth information flow and boosts overall productivity.

To accomplish this, organizations must utilize advanced tools specifically designed for enterprise knowledge management.

Atomicwork simplifies information handling by providing a centralized hub, automating routine tasks, and ensuring secure data management.

It pulls information from trusted public sources for common IT questions, like troubleshooting steps or how-tos for tools in your enterprise stack.

For example, if you want to know why Outlook isn’t syncing between your phone and desktop, need help installing Zoom on your laptop, or have encountered error codes in Salesforce, just ask the Atomicwork assistant. It will give you a concise summary of the tool’s support site.

But how can you efficiently manage your enterprise’s data?

Here’s a step-by-step guide:

1. Set up your communication channels

Define how your teams, such as Slack or MS Teams, will interact with the information in the system. Ensure that your key communication platforms are connected. This makes finding information easier for employees as they can directly access information from their familiar channels. For teams relying on email communication, enable email forwarding.

With Atomicwork integration, you get a conversational AI assistant, Atom, that helps you find answers to your questions and resolve issues yourself.

You can interact by @mentioning Atom in a channel or through DMs.  

2. Organize different workspaces for every department

Different departments in your organization have unique information management needs. For instance:

• Your HR department may need to maintain and make information on leave policies and nominee processes easily accessible
• The IT team might want to own a repository of troubleshooting guides for common device issues
• The Finance department could require a centralized location for expense policies and reimbursement procedures

To address these needs, it's crucial to organize your teams and knowledge sources to ensure employees have access to the right information from the right team.

This is where the concept of workspaces comes in. With Atomicwork, you can segment and set up dedicated 'workspaces' for each team or department. These workspaces allow you to:

• Create separate knowledge hubs for HR, IT, finance, and other departments
• Customize each workspace with its own set of knowledge sources and information
• Ensure that employees can easily find department-specific information without wading through irrelevant data

For example, you can set up an HR workspace with all HR-related policies and procedures, an IT workspace with technical guides and troubleshooting information, and a finance workspace with budgeting tools and expense guidelines. This segmentation helps streamline information access and maintains content relevance for each department.

3. Connect your knowledge sources

Finding accurate answers requires the AI to be connected with the right knowledge sources and learn from them continuously. It learns from:

• Conversations in the Slack/Microsoft channels you’ve added
• The documents you upload, like PDFs, CSV files, etc., and the URLs you provide.
• Notion pages and SharePoint documents are available if you connect your Notion/SharePoint account to Atomicwork.
• FAQs which can be saved as verified answers (we’ll check this next)

To do so, you must connect your workspace to various knowledge sources like SharePoint, Confluence, and Notion. This helps your AI assistant to pull knowledge directly from these platforms and keep them up-to-date.

For example, you can link Confluence to the IT workspace if your IT department uses that for documentation.

Upload all the documents relevant to each department, such as the employee handbook, PPT, or other documents. Add all the relevant URLs, such as the company’s VPN access guide, so that the database is updated frequently.

Atomicwork lets you link various external platforms, upload documents, and add URLs directly. You can upload important documents with the following extensions: DOC/DOCX, PPT/PPTX, XLS/XLSX, PDF, ASPX, CSV, or TXT.

4. Organize by topics

The best way to expedite the search is to categorize the knowledge in the workspaces you set up by adding relevant topics. This helps the AI assistant provide you with more accurate answers quickly by understanding the context of the queries.

For example, topics for IT workspace could include software installation, password resets, and network issues. For HR, these can include leave policies, onboarding, and employee benefits.

Pro-tip: Define the audience for each topic that you add. This will help the AI find answers to the document topic only for employees added to the segment.

5. Setting up verified answers

As enterprise information management has evolved, we've seen a shift toward using AI assistants and Large Language Models (LLMs) for knowledge retrieval. While these AI systems can generate answers on their own, there's a more efficient approach for handling frequently asked questions: verified answers.

Verified answers are pre-approved responses to common queries reviewed and validated by subject matter experts within your organization. They offer several key advantages:

• Providing a single, correct answer to specific questions ensures that all employees receive the same accurate information every time
• When an AI assistant encounters a question with a verified answer, it doesn't need to generate a response using the LLM. Instead, it can directly fetch and deliver the pre-approved answer. This bypasses the need for pre-processing and post-processing, significantly reducing computational demands
• Because verified answers don't require real-time generation, they can be delivered almost instantaneously, improving user experience
• Quality Control: Subject matter experts can review and approve these answers, ensuring the information provided is always correct and up-to-date

To implement verified answers effectively:

• Identify common questions across your organization
• Draft clear, concise answers to these questions
• Have subject matter experts review and approve these answers
• Input these verified answers into your knowledge management system

For example, if someone asks, "How do I connect to the company VPN?" Instead of generating an answer each time or risking providing inconsistent information, your AI assistant can immediately provide the verified answer containing step-by-step instructions specific to your organization's process.  

Challenges in enterprise information management

In the absence of a dedicated enterprise information management tool, enterprises often encounter any one or more of the following challenges:

• Lack of unified best practices leading to inefficiencies, poor data quality and security risks
• Automating data extraction from various structured and unstructured data sources is complex and requires advanced tools
• Information overload with the overwhelming volume of data which makes filtering valuable insights difficult, affecting decision-making
• Information silos where data is stored in isolated systems, blocking collaboration and leading to duplicated efforts
• Integration with  incompatible legacy systems, making integration challenging and costly
• Maintaining compliance with evolving data privacy regulations, requiring strict management and documentation practices
• Ensuring employees have seamless access to relevant information across devices and systems

Best practices for enhancing enterprise information management

Here are a few best practices to set up your enterprise information management system from scratch:

1. Align EIM with an enterprise’s culture

Create a culture of knowledge sharing and integrate a knowledge management system that streamlines the entire process for the following:

• Find the information you need instantly from your company's knowledge base, trusted public answers
• Keeps answers up-to-date from your public and standard channels
• Helps solve common problems by yourself with one-touch request and resolution skills
• Helps raise requests with your team or report incidents effortlessly
• Connects through multiple channels and gets updates on your requests

2. Simplify knowledge sharing

With templates and easy processes, employees can easily contribute knowledge. Tools like Atomicwork automate routine questions and workflows, easing processes, making knowledge quickly accessible, and allowing teams to spend time on more important work.

3. Assign a dedicated knowledge manager

This enhances the content quality and makes alignment of KM initiatives with organizational goals easy. This dedicated manager will be responsible for:

• Overseeing the knowledge management plan
• Organizing, categorizing, and tagging information
• Conducting audits to evaluate the quality and relevance of existing knowledge and identifying gaps
• Implement access controls for sensitive data
• Strategize, monitor, and analyze usage and consumption patterns and improve the system

4. Measure the metrics for continuous improvement

To ensure the success and continuous improvement of your Enterprise Information Management (EIM) system, it's crucial to track key metrics that reflect employee adoption and satisfaction. By monitoring these metrics, businesses can demonstrate the effectiveness of their EIM system and identify areas for enhancement.

Key metrics to track include:

• Ticket deflection rates: This metric shows how effectively your EIM system reduces agent workload by enabling self-service. A high deflection rate indicates that employees are finding answers without creating support tickets
• Average response times: Faster response times generally correlate with higher employee satisfaction. Monitor how quickly employees receive answers to their queries through the EIM system
• First contact resolution rates: This metric measures how often employees' issues are resolved on their first interaction with the EIM system. Higher rates are directly tied to improved employee satisfaction
• User feedback: Atomicwork allows users to flag whether responses are helpful or unhelpful. This direct feedback is invaluable for improving the system
• Usage frequency: Track how often employees are using the EIM system. Increased usage often indicates growing trust and reliance on the system
• Top searched queries: Identifying frequently asked questions can help you prioritize content creation and updates

5. Implement AI guardrails and ethical guidelines

Establishing clear guardrails and ethical guidelines is crucial when integrating AI assistants into your enterprise information management system. This ensures responsible AI use and protects your organization and employees. Key considerations include:

• Configure your AI to cite information sources and acknowledge AI-generated responses
• Implement robust permissions to prevent unauthorized access to sensitive information. For example, employees shouldn't be able to request colleagues' data
• Define off-limits topics for AI-generated responses, such as religion or politics
• Filter user input to protect AI models from harmful data. Continuously monitor AI-generated outputs for compliance with ethical guidelines and policies
• Maintain comprehensive logs of AI interactions and ensure traceable decision paths
• Implement a user feedback system and review AI performance to improve accuracy and relevance

These guardrails align with responsible AI practices, such as those outlined in the TRUST (Transparent, Responsible, User-centric, Secure, and Traceable) framework. Implementing these measures allows you to leverage AI's power in enterprise information management while maintaining control and ensuring ethical use.

Conclusion

The time wasted searching for information is counterproductive and stifles innovation. Enterprise Knowledge Management changes this by centralizing data, breaking silos, and integrating knowledge into workflows, enabling faster, smarter decisions.

Atomicwork addresses these challenges with a comprehensive solution. It offers a centralized document hub that eliminates silos and makes essential information easily accessible.

By automating data workflows, the platform enables employees to concentrate on more meaningful tasks, enhancing productivity. Its AI-powered contextual search allows quick access to accurate information while integrated collaboration tools foster seamless teamwork across various locations.

Want to see Atomicwork in action? Book a demo!