Why Providing Knowledge Doesn’t Mean You’re Resolving Issues

by | Jul 28, 2020 | Knowledge Automation

It took us 20 minutes to find this post on Reddit and yet companies take years to realize that providing content does not mean providing answers.

Tips for reducing average handling time suggest: The more knowledge agents have of their whole business, the easier it is to answer customer questions and reduce time to get the correct answer.
But is more always better? Would 57 articles on the topic reduce AHT or even resolve an actual question?Searching, reading and analyzing large pieces of information and coming up with an effective process to resolve an issue doesn’t fit into the timeframe of 6 minutes and 10 seconds – the industry standard.

Why our tools don’t work

#1 We create content to inform not to resolve
On one hand, creating content for customers is a big deal. Departments conduct hours-long meetings simply debating visuals, fonts, colors, etc. But on the other, have your internal documents ever gotten this much attention? In reality, we tend to cobble together a wiki or dig out a PDF sent to us by a coworker 2 months ago that “should do”.
Issues occur as soon as a customer inquiry doesn’t fit with our approach to documenting knowledge. Even when the answer is simple, it might be buried in numerous PDFs, GDocs or wikis and, even worse, an agent is expected to guide clients to that specific answer instantly. 
Content should be created with the end-consumer in mind. It’s format has a direct effect on how easily your agent and customer will get a grip of the answers. That’s why employees whose performance depends on content quality and its accessibility often struggle to perform. 

Treating every question with a single content format is exactly why traditional knowledge management fails.

#2 Using ineffective knowledge management solution

Most companies choose the format for their content based on the knowledge management system they have in place, often corporate wikis or simple GDocs. And since it does not provide an ability to search within a variety of content types, a whole list of other issues arise. 

The typical Knowledge Management techstack is some combo of these tools:

Wiki + GoogleDocs + SharePoint + Dropbox

In reality, we should also include communication channels like Email or Slack as well as a couple of supervisors who possess institutional knowledge that has never been documented.
Even though this approach allows creating assets of various formats, it has a major flaw that might just undermine its benefits. 

Decentralization of your content leads to managing multiple tabs and repositories, and constantly running multiple searches over and over again. As a result, valuable time is wasted and searching for content turns into an additional skill for the agents. 

Distributed teams depend on how you distribute knowledge
Knowledge management has always been a struggle for support teams, often overlooked by the managers that could compensate for its absence with their own expertise.
However, with Gartner recently revealing that 74% of companies plan to permanently shift to more remote work post COVID-19, distributing knowledge to remote teams has become an issue teams are looking to resolve immediately. 
There’s good news—new AI technology is removing the roadblocks of knowledge distribution, helping remote agents be more efficient while working on their own.

Look deeper into smart knowledge management and learn how to overcome these problems in our latest guide: A Practical KM Best Practices Guide.