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Turning Information Into Action and Business Results using Business Intelligence Solutions and Predictive Analytics
Companies must develop the capability to manage increasing amounts of data more effectively in order to access more information, and so improve decision making. Using the business intelligence life cycle can help companies take control of the process to develop capabilities in predictive modeling that enhance decision making and ultimately help drive high performance.
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During the past few years, the volumes of data generated by enterprises have become staggering. Managing this “big data” has become a challenge—but getting data management right is hugely beneficial. Available data makes it possible for organizations to perform predictive modeling even more accurately.
This paper argues that the business intelligence life cycle provides a solid foundation for predictive analytics by providing a framework to help companies create higher and more sustainable business value.
Companies looking to adopt business intelligence solutions typically face a number of challenges, both organizational and functional. Organizational challenges are:
CIO perspective. CIOs need to improve their ability to manage information effectively.
Business perspective. Managers report they frequently miss useful information and often act on the wrong information.
Data growth perspective. Data and semi-structured data is growing at a rate of 30 to 60 percent annually.
Common functional challenges include.
In light of these challenges, corporate boards are asking key questions about how to manage and disseminate business intelligence within their businesses. They include:
Do we have explicit strategies for data and information management? How do we know they are truly consistent with our business goals?
How do we make BI widely available to decision makers throughout the organization?
Have there been times when crucial decisions couldn’t be made because of a lack of good information?
Do our decision makers spend too much time analyzing the data and too little time acting on insights gained from the data?
How do we manage the increase in volume and variety of data sources, including unstructured information?
What should we be doing next? What are we not thinking about?
How do we prepare for cloud applications?
How can we continue to drive down IT and process costs?
Working with Microsoft, Accenture and Avanade apply deep industry-specific insights to help clients answer these questions to create sophisticated capabilities in data analytics. Contact us to learn more.
April 5, 2012
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