The Red Binder dilemma
Organisations collect a lot of valuable data in all kinds of formats and not always digitally. In fact, you would be amazed at the amount of information that is stored in red binders, manilla folders, paper notebooks and so on, often only known or accessible to a select few. In addition, digital information that does exist, is usually fragmented, decentralised, inconsistently formatted and hard to find. And if you’re lucky and you can find and decipher it, the information may not be up-to-date.
This of course, is detrimental for your company and might lead to a whole slew of problems:
- Limited access to, albeit, sensitive data can lead to a productivity slow-down (or even stop!)
- Degraded service and support to your customers, suppliers or internal data consumers due to outdated or simply non-existing documentation
- Missed opportunities in almost every department due to the lack of sharing and transfer of knowledge.
- Inefficiency due to time spend in searching relevant information
- Preventable costs because of redundant searching and repeated creation of the same content
- and so on…
Defining the Knowledge Base
At its core, a Knowledge Base is about sharing knowledge: by offering internal and external users a centralised storage point, they should be able to find what they need and what they are allowed to see. It is clear that security in all its aspects, plays a paramount role in the deployment of a Knowledge Base.
Another crucial component in the usage of a Knowledge Base is enrichment: every bit of knowledge that is introduced should be categorised, tagged and if possible supplemented with relevant information.
What kind of content are we talking about?
- SOPs (Standard Operating Procedures)
- (Training) Manuals
- Documentation of all kinds, including links to online knowledge pools like Wikipedia.
- Reports and Evaluations
Now let’s bring AI into the picture
Not only is a Knowledge Base a solid source of information for any AI implementation later on, AI can help you import your knowledge into the database, analyse the content, suggest tags and security levels, extract media, and most importantly, connect the dots by revealing the underlying relationships and associations.
So when a Knowledge Base has sufficient content, AI can help by
- Simplifying knowledge discovery using semantic search, natural language processing and machine learning.
- Provide important knowledge management metrics to get better insights into - and ultimately assist in the improvement of - its usage
- Maintain your knowledge base by scanning for outdated content or at least alerting operators to update the content if necessary
Rollo and your Knowledge Base
As one of the main pillars of implementing AI, data collection is the most important: without it, there is no in-depth analysis possible. That’s why we at Rollo understand that offering a Knowledge Base-solution is an important part of the bigger equation.
If you want to know how Rollo can help you out in setting up your Knowledge Base, contact us.