I define BI readiness in 4 steps : Data Intelligence, Reporting Intelligence, Integration Intelligence, Business Intelligence. You can read more about this in my article titled "Select a BI software with full knowledge of what it does".
Now say that you understand the importance and concept of gaining organizational data maturity to harvest Business Intelligence. But the next question is that if an organization wants to get BI ready, do they need to open up a new data center or a few servers running on memory steroids? Cloud is a growing trend for infrastructure elasticity, and Microsoft is also gearing up fast on Azure platform. But again the question is, are you ready for Cloud BI?
Migrating or developing BI solutions on the cloud needs an assessment of your existing line of business systems. I have authored another article titled "5 cloud BI considerations for a successful rollout", which can be read to gain a little deeper insight into this topic.
Finally when your understanding of BI and your infra requirements to host the same are resolved, one another and most important question would hit you - How to recognize / build a true BI software / solution ? Every business has Sales, WorkForce, Products, Business Operations and other Business As Usual constituents. If you have ever studied statistics and statistical methods which are used for analysis by senior business management to analyze different aspects of the business, you would have heard of analytical methods like Time Series Analysis, Deviation Analysis, Regression Analysis, Correlation Analysis, Distribution Analysis and more. These are high level categories of analytical methods and needs a mathematical and scientific approach to analyze and visualize data.