Knowledge Bases Are The Next Big Thing: Here’s Why
Almost every organization out there has databases brimming with data dedicated to some project or application. And for some reason, some companies still shy away from it, sticking with the good old spreadsheets. While there’s nothing wrong with it fundamentally, oftentimes, some of this siloed information is restricted or simply not accessible to other parts of the organization, for whatever reason. And there’s information that’s hidden away from your customers — information that they will need access to either for troubleshooting or for simply starting up.
A test conducted by BBC in the UK back in 2009 showed that customers had to wait up to 24 minutes to access customer service of some kind. These situations drastically differ from the original use cases of databases, and hence, the need arises for knowledge bases.
A knowledge base is a form of digital storage or encyclopedia of information that serves as a self-service help desk. It may include training resources for your employees, guides for customers, etc., and is a perfect solution for scaling up your customer support program.
Major Business Benefits of Knowledge Base
A seemingly 5% growth in retention can increase your profits by up to 95%. On the same note, developing and maintaining a knowledge base can prove to be highly beneficial for both customer retention and improving employee efficiency. Here’s how:
- Every entry in a knowledge base includes meaningful descriptions that may even include entire web pages.
- It acts as a reference database, consisting of products, people, locations, and so on.
- It can integrate a digital asset management system or even serve as one.
- As connections get richer, it gets more valuable with time.
- It’s easier to maintain provenance trails with knowledge bases. These make room for accessing information at the attribute level. Information can be easily duplicated if you wish to develop other knowledge graphs.
- The data format is generally universal, and so data for newer knowledge bases can be sourced or spawned from existing ones.
As for applications, knowledge bases can be quite versatile. For instance, production studios use knowledge bases for managing their inventory, online retailers use it to maintain product catalogs, and search engines use it in the backend to issue content related to the search. You’ll find governments using KBs as holding places for laws and legal codes, and logistics and supply chain management companies using it to track their resources over the network. Here’s an example from McAfee in the Antivirus and web security sector:
A Look At The Big Picture
Taking a look at the bigger picture, organizations are now focusing on what they know best and are persistently acquiring the intellectual resources they need to deliver and perform. Driven by the global economy, the future is competitive, and more than 50% of customers prefer technical support via a knowledge base.
Organizations that have implemented a knowledge base have reported a substantial increase in productivity and employee engagement. And while the benefits are far-reaching, even at a slightly higher point of view, everyone from employees to customers feels empowered and benefit.
Dynamic Interfaces With Knowledge Graphs
Data systems in any organization generally have two major demands that can be roughly segmented into centralization and distribution. While centralization controls data structures that govern entities like people, products, and events, the descriptive content goes beyond numeric data — relationships between categories, provenance information, etc.
When you’re designing relational data systems, there are, again, two key approaches. The first is to perform baseline data modeling or hardcoding the existing relationships directly into the database. While this is a common and faster approach, it prevents you from changing the model later.
Creating customized UI often requires input from multiple programmers. And if anything prompts the data model to change, the UI, too, has to comply. In the case of a knowledge base, the model is a description of the interface. This implies that interfaces automatically and dynamically change with the model — a major factor since there may be hundreds of thousands of classes being used in an enterprise.
That said, changing a model may not be such a big issue, but the aftereffects of playing with the viewers and the editors add up quickly. The same goes for drop-down lists — faceting is a cakewalk with knowledge bases, i.e. you can easily add specific and relevant options to your category listings and search result pages.
Semantic systems are inclined to be more accurate while weighing text searches like abstract descriptions. And since values of the properties can also be indexed, a semantic knowledge base will come in handy for delivering what is being searched for.
Integrating AI, Chatbot, and Knowledge Base Creates a Masterpiece
Knowledge is the single biggest deciding factor when it comes to providing support. By extension, a knowledge base serves as the foundation which can support a high-functioning chatbot and other NLP systems like it. All you have to do is provide a few keyword tags for ML and AI to look for and segment.
In other words, tying artificial intelligence and machine learning with your knowledge base can help create chatbots that serve to your advantage.
Challenges In Developing a Knowledge Base
Legacy models of knowledge bases aren’t doing anyone any favors. The data is only getting more complex, and introducing new repositories is not a solution. Systems being fragmented only make it harder to access information, and before long, the data will become outdated.
But the problems go far beyond. Many organizations understand the importance of maintaining a knowledge base, but they make wrong assumptions on what it must constitute. When the knowledge base is brimming with assumptions, you aren’t helping anyone. Sadly enough, most organizations start cramming it with FAQs without ever seeing the real questions floating around.
Another issue at hand while developing and managing a knowledge base is that many take the one-size-fits-all approach. We need to understand that an article that might help some 10 people in a year isn’t worth the resources that your top item gets. The takeaway is to utilize your resources wisely so as to provide value in an efficient, sustainable manner.
Opportunities To Improve Knowledge Management Going Forward
The future manifestation of knowledge bases practically revolves around how it serves as a medium that connects people with processes and technologies. In ensuring that the right technologies are matched with the concerned people using the correct resources, lie the opportunities to improve knowledge bases.
For instance, AI plays a major role in connecting customers with agent feedback loops. Bringing these two entities together will allow you to learn from one to influence the other. Taking a more analytical approach with AI can help you save resources and maximize the output too.
Other than that, ever since it became a web-based resource, the knowledge base has been about continuously creating and sharing knowledge for holistic organizational success.
Knowledge bases are often considered optimal solutions for providing customer support, training employees, and managing enterprise-grade data. They offer better quality content and set a much higher expectation of curation than any other data-based applications.
That said, a knowledge base isn’t a silver bullet, but it can go a long way towards reducing the complexity in applications.
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