How Knowledge Bases Fuel AI’s Rise

In the age of information overload, knowledge is scattered like dust bunnies under the couch. We have it stashed in emails, buried in documents, and trapped in the minds of experts. This fragmented reality impedes progress, especially for our burgeoning AI companions. But what if we could gather this knowledge dust, weave it into a tapestry of understanding, and use it to power AI’s evolution? Enter the knowledge base, a silent hero ready to bridge the gap between human know-how and machine intelligence.

Think of a knowledge base as a well-organized library for AI. It stores facts, relationships, and insights in a structured format, like a chef compiling a recipe book. This curated information then becomes the training ground for AI models. Here’s how it works:

1. Supercharging Supervised Learning: Traditional AI training relies on mountains of labeled data. A knowledge base provides a readily available, pre-organized treasure trove of facts, ready to be tagged and fed into supervised learning algorithms. Imagine training a customer service AI with a meticulously labeled FAQ base—it’ll learn to answer your questions like a seasoned agent in no time!
2. Enabling Unsupervised Exploration: But what about information that’s unlabeled, the hidden gems buried in unstructured documents? A knowledge base can act as a map, helping AI models navigate and make sense of this data. By identifying relationships and patterns within the structured facts, AI can start to infer meaning from the unstructured, paving the way for unsupervised learning breakthroughs.
3. Bootstrapping the Bootstrap: Once an AI model learns basic concepts from the knowledge base, it can use its newfound abilities to further enrich the base itself. It can identify missing information, suggest connections between seemingly disparate facts, and even flag inconsistencies. This virtuous cycle of learning and refinement makes the knowledge base a living, breathing entity, constantly evolving alongside the AI it powers.
4. Fostering Trust and Transparency: With explainable AI gaining traction, knowledge bases become crucial for building trust. By tracing an AI’s reasoning back to its roots in the knowledge base, we can see the logic behind its actions. This transparency fosters a sense of understanding and trust, essential for human-AI collaboration.

Beyond the hype, capturing knowledge in a knowledge base is not just a cool trick; it’s a strategic investment in the future of AI. It unlocks the potential of our data, fuels intelligent machines, and paves the way for a future where AI and humans work in harmony, guided by the collective wisdom housed in these digital libraries of knowledge.

So, the next time you stumble upon a nugget of information, don’t let it vanish into the digital void. Feed it to your knowledge base, and watch it become the fuel that propels AI towards a brighter future. Remember, knowledge is power, and in the age of AI, sharing it is the key to unlocking the true potential of intelligent machines.

Let’s start building smarter AI, one well-stocked knowledge base at a time!

UFFA: The Bedrock of Knowledge-Centered Support

At the heart of Knowledge-Centered Support (KCS) lies a simple yet powerful principle: UFFA. This acronym stands for four key actions support personnel can take when seeking information in your knowledge base: Use it, Fix it, Flag it, Add it.

Use it. When an article perfectly answers the question at hand, your knowledge management tool should provide a way to track its effectiveness. This typically involves linking closed support cases to the article’s ID, effectively “voting” for its quality and completeness. This data can then be used to influence search algorithms, reward content creators, and prioritize content review.

Fix it. If an article contains inaccurate information or lacks detail, support agents should be empowered to fix it readily. The knowledge management system should facilitate easy editing, including peer review and oversight processes to ensure quick and reliable publication of corrections. Remember to acknowledge the value of edits alongside new content creation, as they often contribute significantly to the knowledge base’s accuracy and effectiveness.

Flag it. Sometimes, the answer may be imperfect, but the agent accessing it may not be equipped to fix it. In such cases, a flagging mechanism is crucial. This allows the issue to be escalated to a dedicated team or added to a group discussion for collaborative resolution. Consider allowing public users to flag content if it fails to resolve their specific queries.

Add it. When no existing article addresses the question, adding a new one should be seamless. Incentives, recognition, and rewards encourage content creation, but be cautious of imposing quotas. The easier it is to create new articles, the better. Integrating with the case tracking system to auto-populate certain fields can further streamline the process. Additionally, consider implementing mechanisms to ensure compliance with style and quality guidelines. Efficiently reviewing and publishing new content ensures it reaches those who need it most, just in time.

While modern knowledge management platforms offer various features and enhancements, UFFA remains the cornerstone of a successful KCS implementation. By ensuring your platform effectively supports these four core actions, you empower your support team to leverage knowledge effectively, resolve issues efficiently, and ultimately deliver exceptional customer service.

What are the advantages of knowledge management?

1. The quality of the information you provide is better. You can give consistent information across different personnel or locations. Once a piece of knowledge is perfect, you will never miss a step or give wrong advice. You give the right answer the first time every time.
2. You can provide these answers faster. You eliminate the need to research the same problem over and over again. You can walk the customer through the solution in real time with relative ease and confidence that it will work.
3. Or even better, they can look it up for themselves. If you open up your knowledge base either partially or entirely, you enable self-help. That eliminates the need for one-to-one (expensive) support by enabling online self-help.
4. You can break down silos in the organization, which is beneficial for everyone. You don’t end up with “The SQL Guy.” That’s the employee who is the only one that can answer questions about SQL, and therefore they always do. When they’re on vacation, you grind to a halt and wait for The SQL Guy to return. It’s not good for the team and it is also not very fun being The SQL Guy either. It’s better if you can share the load.
5. You don’t lose knowledge when you lose people. As bad as it is when The SQL Guy is on vacation, it’s even worse when they retire. Suddenly you realize nobody is able to take over that subject matter. If they document everything they know before leaving, you can continue to leverage that expertise after they’re gone.
6. You also retain the ability to service very old or outdated products. You’re not necessarily going to have a new hire ramp up on obsolete products. That’s not fair to them or very useful for you. However, if you’ve documented obsolete products completely, you can rely on that for lingering service needs.
7. You can upskill new hires much faster. They can often be immediately viable. All they need to do is search for known answers and regurgitate them to the customer. That makes them an immediate asset instead of spending many months shadowing or training before they can help.
8. If you do this really well, in a Knowledge Centered Support methodology, paired with a CRM, you can use the linkage reports to discover the most pressing problems and actually use it to drive product development. Documenting a problem makes support quick and painless. Fixing the problem eliminates the need entirely.
9. All of this leads to higher customer satisfaction if they know they can always call and get a complete and consistent answer regardless of who they are connected to. Or better yet, they can just search and solve themselves. Depending on your industry that can be a real differentiator.
10. And last, and probably my favorite having come from that world, it increases employee satisfaction. Nobody likes being caught on the phone without an answer or back up. It’s isolating and stressful. However, if you know that 80% of the time, you can rely on and contribute to a shared resource, you have a greater sense of purpose and a less stressful job. The result is you can actually get some longevity out of your teams.

What is Knowledge Centered Support?

Knowledge Centered Support (KCS) is a customer service methodology that focuses on knowledge as a key asset of the organization. It is a way of interacting with knowledge which enables teams to answer questions quickly, deliver answers where people are looking for them, and train new employees faster.

KCS derives from the idea that knowledge is created when people solve problems. When a customer support team member solves a problem, they capture that knowledge in a knowledge base so that it can be reused by others. This knowledge base constantly evolves as new problems are solved and new solutions are discovered.

KCS has a number of benefits, including:

• Reduced costs: KCS can help organizations reduce costs by reducing the time it takes to resolve customer issues. This is because support team members can quickly and easily find the information they need to solve problems in the knowledge base.
• Improved customer satisfaction: KCS can help organizations improve customer satisfaction by providing customers with access to self-service knowledge resources. This allows customers to solve their own problems without having to wait for a support team member to help them.
• Improved support team satisfaction: KCS can help improve support team satisfaction by giving support team members a sense of ownership over their knowledge. Support team members are encouraged to contribute to the knowledge base and share their knowledge with others.
• Faster training for new employees: KCS can help organizations train new employees faster by providing them with access to a comprehensive knowledge base. This allows new employees to learn from the experience of others and get up to speed quickly.
• KCS is a powerful methodology that can help organizations improve the efficiency and effectiveness of their customer support operations. It is a good fit for organizations of all sizes, in all industries.

Here are some examples of how KCS can be used in different industries:

• IT support: IT support teams can use KCS to capture and share knowledge about how to solve common technical problems. This can help them resolve customer issues more quickly and efficiently.
• Healthcare: Healthcare organizations can use KCS to capture and share knowledge about medical conditions, treatments, and wellness advice. This can help them provide their patients with better care.
• Education: Educational institutions can use KCS to capture and share knowledge about teaching methods, curriculum, and student assessment. This can help them improve the quality of their educational programs.

If you are interested in learning more about KCS, there are a number of resources available online and through the Consortium for Service Innovation.