Three Aspects of Collaborative Business Intelligence
Collaborative business intelligence is an environment within which users can easily collaborate and communicate with each other, sharing ideas, information, and decision making within their community.
Every day, no one captures the millions of items of intellectual property (conversations, e-mails, and telephone calls) in organizations all over the world. Using collaborative software to institutionalize quantitative (structured) and qualitative (unstructured) information — which would otherwise be lost — can enable the sharing of information, thoughts, insights, and best practices.
How we have progressed this far without leveraging collaboration within business intelligence solutions is beyond me. The use of collaboration software can enable your users to capture intelligence from outside the data warehouse and operational systems and use this captured intelligence as part of the business intelligence solution.
Through such collaboration, users can begin reusing existing ideas and/or capabilities, removing the need to reinvent the wheel — which happens quite often when information technology departments isolate a user’s experience to reports. Using collaboration software side by side with business intelligence software can enhance information presented to users, enabling everyone to share insights they gain with other users in their community.
Collaboration allows participants to share knowledge, observations, and analytics in a community of interest with the goal of producing an action response to a situation. This sharing can become infectious. Remember your first experience with eBay or YouTube?
You probably arrived at these very popular sites after one of your friends or colleagues directed you there. This guidance is viral in nature. If users find software sites and solutions easy to use, discuss, and gain support for, they pass the word on to others.
Such activities resulting from user-to-user collaboration will drive the sharing of knowledge across organizational boundaries — including observations, insights, and data from customers; economic and industry information; and psychographic information (interests, attitudes, and opinions). In other words, your data warehouse will grow and become more virtual in nature because the conversations that occur will require much information from both inside and outside the boundaries of a single organization’s data warehouse.