Business Intelligence 2.0

By Mark Brousseau

A new buzz in business intelligence (BI) is business intelligence 2.0. That’s according to Accenture. While traditional business intelligence and data warehousing are concerned with analyzing the past, BI 2.0 concentrates on the future. Put simply, it refers to drawing inferences from historical data, applying the resulting insights to events as they happen and then managing future events through predictive analysis, Accenture says.

Just a few years ago, it took weeks or even months to detect an unusual process, analyze the event, formulate and take the required actions. BI 2.0 provides these capabilities in real-time. BI 2.0 brings a burst of radical thinking and a fair number of promises that, when realized, will make a real difference to bottom lines and help companies move towards high performance levels. But what is really needed to embrace BI 2.0? Smart CIOs are examining their data management.

Accenture’s research has shown that 92 percent of CIOs widely include structured data in their information strategies and almost 60 percent see BI as a core component for competitive differentiation. These findings come as no surprise but disturbingly, traditional business intelligence is too often used in an undifferentiated way. Aggregated data from the past is often viewed outside of its context and compared with static key performance indicators. Knowledge workers receive standardized reports and then take time to interpret the data and make decisions.

Business intelligence 2.0 focuses on business events and how business processes and business users respond to them, Accenture says. For example, unusually high returns of a best-selling product would lead to the examination of many factors. Is that particular batch of product faulty, is there a pattern to the consumers who are returning this product, is there a problem with the packaging, or the sales staff, or even evidence of fraud? In this simplistic example, an "event" called "product return" triggers a series of responses that require access to information and should trigger intelligent decision-making, based on a variety of conditions.

The vast majority of applications and processes have limited ability to absorb changing business needs, are not explicitly defined and do not have comprehensive metadata management processes, Accenture notes. If we are to make BI 2.0 a reality, we first need to look at the assumptions and promises of BI 2.0 from a data management perspective.

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