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January 1, 2003

Two Heads Are Better Than One

BI is usually a solitary pursuit — so when and why should users collaborate over reports and analyses?

by Philip Russom

Collaborative analytics are an emerging practice for business intelligence (BI) whereby end users collaborate when producing or consuming reports and analyses. The point is to share expertise to reach consensus-based decisions. On the one hand, collaborative analytics are a team-building exercise pursuing the noblest of goals in knowledge management. On the other hand, because knowledge workers tend to study and consume information in isolation, they run against the grain of established BI practices.

Against the Grain

The established analytic practice, especially with online analytic processing (OLAP), typically involves a solitary user exploring data in what's usually a one-off experience. However, the emerging practice of collaborative analytics involves a communal user consuming information in a predictable and repeatable manner. The older practice lets an analyst go wherever data and imagination lead, enabled by an analytic tool's open-ended user interface. Yet a feature now supported by many OLAP and reporting platforms is the "analytic procedure," a linear user interface that guides a user through a series of reports, branching according to a kind of workflow based on the reports' contents.

These are just a few of the ways in which collaborative analytics run against the grain of established BI best practices. Despite the divergence, collaborative analytics are evolutionary, not revolutionary. They complement older, more established practices without replacing them.

Collaborative analytics aren't a mainstream practice, but they have gained footholds in a few areas where collaborating via BI technologies makes sense, namely "BI for the masses," business performance management (BPM), and BI portals. (See Figure 1.) As these areas grow in prominence, they bring collaborative analytics into more and more corporations. But note that collaborative analytics can take different forms and are driven by different needs in each area.

Assimilating the Uninitiated

The ongoing BI-for-the-masses movement is bringing many new users online who have no experience interpreting reports, much less creating them. Most new users depend on colleagues in the information chain (whether power users or IT personnel) to package and automate BI functions for them. For these users, the analytic procedure is a powerful collaborative medium that captures the expertise of experienced knowledge workers so it can be reused across the enterprise. Analytic procedures can help assimilate uninitiated users, while bringing them up to speed with the collective knowledge of the organization.

Collaboration aside, the analytic procedure offers other benefits. By automating recurring analytic and data monitoring tasks, it gives users a productivity boost. A body of analytic procedures can add needed structure to analytic applications. Analytic procedures encapsulate the analytic best practices of a business function and therefore constitute an effective alternative to expensive and time-consuming training.

Safety In Numbers

BPM is a way of running a business by the numbers. Metrics represent business entities that are measured and monitored to improve their performance. Metrics exist in a hierarchy where they roll up to other metrics or key performance indicators (KPIs). Because all metrics have dependencies and influences in the hierarchy, BPM practice demands that managers collaborate regularly to find the root cause of metrics or KPIs that are off plan, so the appropriate business entity can be corrected tactically.