1. Decisions are the unit of work to which BI initiatives should be applied.
2. Providing access to data and tools isn't enough if you want to ensure that decisions are actually improved.
3. If you're going to supply data to a decision-maker, it should be only what is needed to make the decision.
4. The relationship between information and decisions is a choice organizations can make--from "loosely coupled," which is what happens in traditional BI, to "automated," in which the decision is made through automation.
5. "Loosely coupled" decision and information relationships are efficient to provision with information (hence many decisions can be supported), but don't often lead to better decisions.
6. The most interesting relationship involves "structured human" decisions, in which human beings still make the final decision, but the specific information used to make the decision is made available to the decision-maker in some enhanced fashion.
7. You can't really determine the value of BI or data warehousing unless they're linked to a particular initiative to improve decision-making. Otherwise, you'll have no idea how the information and tools are being used.
8. The more closely you want to link information and decisions, the more specific you have to get in focusing on a particular decision.
9. Efforts to create "one version of the truth" are useful in creating better decisions, but you can spend a lot of time and money on that goal for uncertain return unless you are very focused on the decisions to be made as a result.
10. Business intelligence results will increasingly be achieved by IT solutions that are specific to particular industries and decisions within them.
BI historically has been about dashboards and scorecards developed for specific uses, says AMR Research analyst John Hagerty. But that's changing. "All of a sudden it's about integrated analytics within applications," he says. "The conversation is starting to shift to looking at information in the context of specific decisions and roles."