By all accounts, the business intelligence (BI) industry is thriving. Numerous reliable surveys confirm that CIOs consistently rate BI a top priority in their plans. Attendance at industry events and vendor conferences is up 10 to 20 percent, and analytics has been featured in top business publications such as The Harvard Business Review thanks to thought leaders like Tom Davenport. The surge in interest is being fueled by the rapidly changing, technology-driven business landscape. Organizations are striving to get "smarter" by forming a deeper understanding of their extended enterprise. That requires intelligence - BI. After decades of being on the periphery of computing, BI is now right in the thick of it.

However, to capitalize on this opportunity, the BI industry must adapt too. Most BI users today are still consumers of information that has been gathered, manipulated and packaged by others. BI deployment practices, and even the BI tools themselves, stratify usage into arbitrary roles based entirely on unchallenged assumptions, not a foundational theory. While the often-stated goal of BI is to present the right information to the right people at the right time so they can make better decisions, the current practice cannot possibly meet those requirements. Decision-making is a more complicated process than just reviewing information. Though the subject of decision-making in organizations has been studied for decades, BI operates without any formal model of its nature or use, leading to arbitrary and ineffective practices and product design.

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