Implementing Business Intelligence Systems (BI) requires a lot of resources and time. The statistics show that billions of dollars are spent on these business intelligence systems (BIS), which show how important they are. Also, the cost of these systems is a large part
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Implementing Business Intelligence Systems (BI) requires a lot of resources and time. The statistics show that billions of dollars are spent on these business intelligence systems (BIS), which show how important they are. Also, the cost of these systems is a large part of the expense of the organization. Unfortunately, with all these huge costs in these systems, more than half of the BI projects do not go to the real benefits of business intelligence systems. Here's one reason why organizations are not able to grasp the real benefits of business intelligence systems: Many of them are not ready for these systems. This is due to some of the challenges in implementing BI systems in organizations. BI implementation experiences show that the successful implementation of BI is beyond the implementation of technical infrastructure (hardware aspects) and requires the control of soft aspects and change management, which are recognized as the most difficult aspects of the successful implementation of BI applications. Business intelligence is a complex concept and has multi-layered architecture, which is why the BI readiness model is needed. Assessing BI readiness identifies specific implementation risk sections to manage and reduce these risks and thus increase the likelihood of BI success. So far, several models have been developed to prepare BI systems. In this paper, introduced models for BI readiness are presented, and then these models are compared based on the factors influencing BI readiness.
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