The Hexaware published in its BI blog this week, a post entitled Business Intelligence Value Curve, by Karthikeyan Sankaran.
Sankaran talks that every business software system has an economic life. During its useful life, the "Value Curve” establishes the fact that the real intention of creating the system is to provide business value. As a BI practitioner, his focus is on the “Business Intelligence Value Curve” and it typically goes through the following stages as shown in the diagram.
Stage 1 – Deployment and Proliferation
The BI infrastructure is created at this stage catering to one or two subject areas.
Stage 2 – Leveraging for Enterprise Decision Making
This stage takes off by addressing the problems seen in Stage-1 and overall enterprise data warehouse architecture starts taking shape.
Stage 3 – Integrating and Sustaining
The scalability issues seen at the end of Stage-2 are alleviated and the BI landscape sees much higher levels of integration. Knowledge is built into the set up by leveraging the metadata and the user adoption of the BI system is almost complete.
Stage 4 – Reinvent
The organization, after appropriate feasibility tests and ROI calculations, reinvents its business intelligence landscape and starts constructing one that is relevant for its future.
Sankaran also talks that a good understanding of the value curve would help BI practitioners provide the right solutions to the problems encountered at different stages.
This is an interesting point of view, but I also think BI is not just another IT project, BI is a continuous process. As a continuous process, BI sometimes can be reinvent, but BI also can to evolve, keeping the BI infrastructure or part of it, depending on the kind of evolution adopted. For example, you can adopt new tools but keep the same data warehouse or only make some changes in it.
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