The Role of Collaboration in Business Intelligence
“Two heads are better than one.” It may be an old saying but it is still true today. In today’s fast-paced,
economically challenged environment, making better decisions is not just a “nice-to-have,” it is vital
to the very survival of businesses. The ability to bring together the appropriate personnel, expose all
the pertinent information, make a sound decision, and then act on it immediately gives enterprises a
definitive edge over their competitors, and results in happier customers, partners, and employees.
Collaborative Business Intelligence (BI) is a relatively new concept in which the two technologies of
business intelligence and collaboration are beginning to merge in support of an improved decision-
making environment. We define it as:
“The combination of business intelligence and collaborative computing processes and technologies with
the objective of enhancing business decision-making. This is achieved by improving user communication
and information sharing, adding business knowledge to BI results, and making collaborative decisions.”
From this definition, we see that collaborative BI fulfills three main business requirements.
• Collaborative interaction: Business people want to interact with each other to improve overall
communication. They must be able to easily discover the BI analytics available to them and then
share them with their team. Finally they must be able to discuss the meaning of the analytics and
the decision options to improve, reduce or maintain the analytic indicators. The ease of discovery
and the documentation of the ensuing discussions are major features of truly collaborative BI
• Information enhancement: There is a need to enhance the information resulting from BI
processing. To do this, business people must be able to add their own knowledge to the BI results.
They can provide information about why events are unfolding the way they are, discover related
content to the work at hand, and provide the necessary and important business context surrounding
the BI results. For example, a trend may be heading down. Is this good news or bad? Adding team
expertise and knowledge about the trend makes it clear that the trend is good – customer churn
is lower than the same time last year. Published BI results can be enhanced through feedback
mechanisms such as ratings, comments and tagging, and in some cases, blogs and microblogs.
• Collaborative decision-making: The last step is of course to decide on the appropriate action(s)
to be taken based on the two previous activities. The collaborative BI environment must be able
to track these decisions and later be able to analyze the accuracy or impact of them. This analysis
produces feedback to the teams in terms of how they can improve upon the entire process. It enables
best practices to be recorded and allows information workers to track the types of information
that provide useful content for decision making. Collaborative decision-making should also include
the analysis of social networks and other informal teams to determine influencers of communities,
who has needed expertise, and who makes the decisions in these informal networks.
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