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Executive Summary

Collaborative Business Intelligence: Optimizing the Process of Making Decisions
Collaboration and business intelligence (BI) are beginning to intersect. Most BI professionals recognize that collaboration can improve analysis and decision effectiveness, and plan to consider collaboration features when selecting their next BI tools. Adoption rates for collaboration software whether standalone collaboration platforms or collaboration features built into BI and other applications should begin to climb in the near future.

This report evaluates the role of collaboration in a BI environment and surveys BI professionals about their interest in and adoption of collaborative capabilities. Here are some key findings:

  • Attitudes. Eighty-seven percent of BI professionals believe collaboration tools can have a positive impact on analysis and decision-making activities.

  • Product selection criteria. Fifty-eight percent of BI professionals plan to evaluate collaboration features when they purchase their next BI tools, up from 16% who evaluated collaborative capabilities when selecting their current BI tools.

  • Implementation. Less than half (44%) of companies have implemented collaborative BI capabilities, while 67% have implemented a standalone collaboration platform. More than three-quarters of the latter group count Microsoft SharePoint as their collaboration platform.

  • Usage. Twenty-five percent of users who have access to collaborative BI features don't use them.

  • Traditional approaches. The most popular forms of collaboration are phone calls, meetings and email.

  • Favorite features. The top collaboration features that BI professionals want in a BI tool are annotations (67%), threaded discussions (62%) and shared workspaces (60%).

  • Users. Power user are more than twice as likely as casual users to use collaborative BI features and about 30% more likely to use collaboration platforms.

BI lifecycle. The report also extends the traditional BI lifecycle (collect, analyze, decide, act) to include collaboration subcycles at each step and an additional review step at the end. During the review process, the people who participated in a decision reflect on the process by which the decision was made, including every step of the BI lifecycle, to see how it can be improved.

Collaboration styles and characteristics: There are two drivers of collaboration that are relevant for this report: data-driven collaboration and decision-drive collaboration. In data-driven collaboration, anomalies or trends in the data cause users to alert others and possibly discuss the situation and decide on a course of action. In decision-drive collaboration, a team comes together to undertake a project or make a decision. BI tools with collaboration features are best suited to data-driven collaboration, while standalone collaboration platforms are ideal for decision-driven collaboration.

Finally, the report dissects the different ways that business users interact and maps collaboration features to each. For instance, collaboration can be unidirectional or bidirectional, synchronous or asynchronous, manual or automated, formal or informal, and internal or external. Understanding how users collaborate helps organizations select the correct collaboration features and tools to implement.

Read the entire study.