Each second brings to the world new piece of information, accelerating progress. At the same time knowledge is no more reserved only to high-technology (and highbrow) spheres like chemistry, cosmonautics, medicine – it’s universal and cross-boundary. Any company at any industry can create and accumulate an individual body of knowledge and put it to use. Moreover, when applied and managed correctly, knowledge may turn into a great competitive advantage and even become a key success factor. Application of knowledge is rather individual matter and should be left to it owners; while knowledge management is a sensitive topic in the context of a current fast-paced information flow, and the most acute aspect of it in professional circles is knowledge relevance.
Unfortunately, no matter how integral or vital the knowledge is, it’s doomed to become outdated, as the context, objects and subjects change. Here’s the picture illustrating the typical knowledge lifecycle proving our point.
The issue lies is not generating new knowledge itself – this process should be substantial and underlying and can be automated in many ways. Replacement of obsolete information with the relevant one is a real hard case. From our personal, quite extensive experience of ITSM consulting only a few knowledge management systems allow to automate this process.
This conundrum was occupying the minds of our development team for quite a while. At the end we decided “divide and rule” and came up with a PART of the solution – Data Relevance Alert for Confluence.
First things first – why Confluence? Confluence is a knowledge management system by Atlassian and one of the most popular in the world, making it to top-3 at the popular portal for finding soft Capterra https://www.capterra.com/knowledge-management-software/?utf8=%E2%9C%93&users=&sort_options=Most+Reviews. It has both cloud and on-premises versions and similarly suitable for IT teams, startups and large tech companies. Integrating with corporate user management system, it creates a flexible content access system. What is more, Confluence stands out with its powerful basic functions for lifecycle and knowledge support and, if you wish to upgrade your experience, there’s a wide range of custom plugins for any problem.
So the baseline was the following: Confluence offers a full range of instruments for knowledge management, but offers no solution for knowledge relevance tracking. Since we really needed the solution, we invested some brain and time and got ourselves a custom developed plugin.
By default Confluence contains a “Scheduled Jobs” module that is used to arrange regular execution of any algorithm. On the other hand, on Confluence this module doesn’t allow users to configure planned tasks from graphics interface, so we actually needed to develop the plugin first so that it could be seen by “Scheduled Jobs”.
After development we created our own addon configuration screen and set the following parameters for the task: spaces (where the information should be checked for relevance), groups (they contain content owners that need to be informed), time period (within which knowledge is still relevant) and head and body of an alert letter.
As a result we got a plugin that will: