If we approach this question from the perspective that the end product of Business Intelligence is Opportunity Analysis and that Opportunity Analysis, once classified, becomes an organisation’s Intellectual Capital, then the concept of defining Business Intelligence as Knowledge would appear to be a logical inference. This deduction is reinforced by the interpretation of Intellectual Capital. Thomas Stewart defines Intellectual Capital as:
“Intellectual capital is the sum of everything everybody in a company knows that gives it a competitive edge.”
If we apply Stewart’s rationale of Intellectual Capital to Knowledge Management and Business Intelligence we cannot fail to recognise the common goal – competitive advantage. Therefore it is difficult to argue against the notion that Knowledge Management and Business Intelligence are one and the same activities. Yet there are those who would argue that there is a fundamental difference between the two. One argument finds its roots in the principle of knowledge sharing. As a former intelligence officer, the concept of Knowledge Management and the principle of sharing knowledge is in direct contradiction with the rule of applying the ‘need to know basis’ that intelligence managers have traditionally applied to the sharing of intelligence. This is a factor that some competitor intelligence specialists may refer to when defending the need to uphold Competitor Intelligence as a profession apart from that of Knowledge Management. But this argument is surely not sufficient grounds for making the case. What then are the factors that differentiate KM from BI while recognising that both activities strive for identical goals?
Business intelligence (BI) has always had a “pipeline” orientation—in other words, a primary focus on the one-way flow of data, information, and insights from “sources” (e.g, your customer relationship management systems, enterprise data warehouses, and subject-area data marts) to “consumers” (e.g., you). But we all know that this pipeline orientation—also known as “simplex” information transfer—doesn’t describe the predominant flow of mission-critical intelligence in our lives. Quite often, the most important insights are those that issue from other people’s heads, not from our companies’ data marts. Many real-world intelligence flows are full-duplex, many-to-many, and person-to-person in orientation. This fundamental truth will continue to drive the spread of “social” architectures in core BI and advanced analytics.