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Business users and organizations need the ability to quickly analyze their data to identify issues, causes and opportunities for improvement. Once these analyses are identified, they need to be monitored and distributed often to others. With traditional business intelligence (BI), creating and maintaining effective and understandable analyses can take months to define and develop and require expensive resources to maintain. And by the time they are created, the business situation will have likely evolved, potentially doing harm to the business and its customers. In today’s marketplace, the half-life of BI is typically shorter than the life of the project needed for its implementation. This means that companies are getting a continual negative return on their BI investment. It is time to approach the problem from a new direction and empower the business owners and knowledge workers to quickly and easily find the answers to their questions.
In response, a new BI term has emerged: Operational Business Intelligence. It promises to empower everyone within an organization to make day-to-day decisions by using better analysis of sales and marketing trends, customer interactions, manufacturing plans, inventories and other areas of the business. Some say this is a new trend in BI — except that it’s not new. Many people in an organization might call it “making do with Excel” or “the secret report that my IT buddy runs for me,” but these are forms of guerrilla operational BI. In fact, many organizations have already found ways to enable employees with the access and tools needed for operational BI – some sustainable and some not. The main question is, what are the business requirements of an operational BI system? What does it take to provide the environment and capabilities needed for operational BI? Can an organization afford to wait for a top-down operational BI initiative? Are there better, more rapid options than disconnected spreadsheets and disparate reports?
The paper discusses the seven major requirements businesses need to consider when evaluating this generation of BI.
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