Using automatic knowledge sharing in Slack
Very flexible, too remote
Work doesn’t always happen at offices and many employees work on the go. Either they are travelling between business meetings or checking their email on the way from home to work, it is essential today being online and being in touch with your colleagues.
The number of employees, who work primarily from home, has been increased to 140% since 2005, according to the research by Global Workplace Analytics, and probably it is going to continue growing. For instance, there are discussions in Germany to provide legal rights to work from home.
One of the major centres of communication for many teams is Slack nowadays. It integrates with many popular online services, additionally to the integrations with your own enterprise services. According to the Slack team, they have 10 million active users (DAU) worldwide.
Slack claims that we are looking at the evolution of how people work together nowadays. We’re building the world, where you might easily achieve any flexibility you want and the size of your company is becoming irrelevant. As a result of the better communication, consistency and adaptability, teams will spend less our effort and energy and they may use their intelligence and creativity to the full to achieve a common goal.
It seems that we all are going to be part of this evolution and work in a chat window. The question is how we could gain more from this process?
Lots of knowledge, knowledge everywhere
According to the recent research from Slack, there are a few things which we can do for this: more transparency, more communication and more connectivity. One of the ways is to improve our knowledge management system.
Knowledge management — is how we collect, saving and structuring information in companies. This is how we receive knowledge from one person or the whole team and how we make this knowledge available for everyone else. Knowledge might be in your files, documents, emails and text messages. This is basically maybe in any form of communications where you send important information.
The goal of knowledge management is to connect people who have valuable and relevant information with the others who are looking for it.
Deploying a knowledge management system is a vital key if we want to increase the productivity and efficiency of our company.
Saving everything, using a part of it.
Slack provides in their apps directory a set of applications which might help teams to achieve this target.
- The applications to integrate Wiki systems, like Atlassian Confluence, or the Q&A platforms, like Stack Overflow for Teams. Using those solutions we might save instructions, FAQ, etc., and also keep them up to date.
- Using сloud storage providers, like Google Drive or Dropbox, to save all of the important documents is the most popular approach to manage knowledge. Unfortunately, in practice, it is still hard to find and to structure company knowledge in those systems.
- A different approach is using smart bots that might respond to your questions in your channels or saving your Q&A pairs for similar questions further. Also, there are applications which might save the links your teams share every day to use and cataloguing them after.
Each of these solutions has its pros and cons, but all of them depend hugely on people actions: manually saving, editing and managing knowledge. Even in the case of a smart chatbot, which might react to links or questions, someone should make additional effort to save and manage this knowledge and most of the time usually in a separate Web user interface.
Paul Ronto, a marketing director from RunRepeat, which is a site with sport shoe reviews with a remote team of 55 members, says that processes, systems and structures we use to manage our knowledge in our company really depend on our ourselves. If you want to improve productivity, you have to simplify everything you can, and your teams will be grateful for it.
In other words, according to Paul, many teams don’t ready to make too much effort to save and structure their knowledge, not to mention keeping them also up to date.
Another problem is mostly related to human nature. “In competitive work environments, employees try to outdo one another and are less likely to share what they know with others”, says Dana Case, an operational director from MyCorporation.com. “It’s important for organizations to adapt a knowledge culture where information is shared instead of safeguarded for professional gain or benefit.”
The good news is that in real life conversations in Slack channels, we probably could achieve the desired effect. Martin from Autodesk mentioned that their #help channel had suddenly become some kind of catalyst for building a community. The channel had frequently asked questions, and many employees with different roles referred to them in their dialogues. Apparently, it isn’t any important what implementation of your knowledge management system you have if you didn’t create an environment which prone to knowledge sharing.
Based on this, we might try now to generalise the team’s experience to the following. We need an environment to share our knowledge. It might be implemented as a simple solution like creating Slack channels to help newbies to support your onboarding process, channels with your own FAQ or channels to your internal support. Mini communities, which might be developed inside those channels, will play a vital role not just to improve collaboration and confidence to work in the teams with remote employees, but also might give more opportunities for new ideas and innovation.
On the other hand, we need a solution to discover, save and deliver knowledge, and that solution should work automatically to spend less effort of your team members.
And here we go again, AI to the rescue
Using AI and automation, there are many attempts to improve the speed and usability of your work in digital channels. AI might also be the right tool to manage your knowledge.
Let’s consider short text messages, which might have valuable knowledge. They might be represented as questions and answers, which happens in everyday conversations in many of your Slack channels. Applying machine-learning models we might implement automatic knowledge discovery. In Slack, it would be automatic knowledge extraction of Q&A pairs in your channels.
To do that, some application with a trained model should analyse short text messages and find questions, filter them out to detect useful questions. Next, the application should find and do the same to the answers and save those pairs to use further. In this implementation, there is zero additional effort from your team members, they just share their knowledge in text messages as they do every day.
The second important part is finding that knowledge and deliver answers for similar questions. Questions might have the same meaning but different lexical structure. For example:
Hey, where to find an instruction manual for our office printer?
Where to find a manual for our printer?
The application should recognise those kinds of questions and find the right answers in indexed Q&A knowledge.
As a result, we have a smart tool to automatic Q&A knowledge extraction from text messages in your channels and automatically deliver answers to all those questions. The application shouldn’t interfere with team conversations and should deliver only useful answers.
We’ve been implementing exactly this idea and developing Slack application — Memonia, to provide you automatic search, indexing and delivery knowledge of your team. Comparing with the other solutions available in the Slack directory to our application, it doesn’t distract your teams making them responsible for managing and creating knowledge manually.
Try Memonia for free in your own workspace right now. The application works without any configuration and settings. The supported language is English at the moment. You are in full control of your data and decide where it may work. Your data is handled in accordance with the EU General Data Protection Regulation (GDPR).
Liebe Grüße from Germany.