Much of the focus of business intelligence capability is providing the “right information” to the “right people” at the “right time.” Yet the opposite is also true.

Often, the greatest value of BI is keeping information away from business users, instead allowing process-embedded analytical tools to extract real time information and initiate rules based actions to appropriate transactions. That’s actionable BI.

Automated decision making relies on the lack of human intervention.

At present, humans are using intelligent dashboards and BI portals to make informed decisions. But it is suggested by many BI enthusiasts that as much as 95% of decisions can be automated. In most businesses today, the most common and time consuming action is ‘waiting for a decision’. By allowing ‘systems’ to make the bulk of decisions, managers can more profitably apply their time to review and action the 5 percent ‘difficult’ or ‘tricky’ decisions.

The impact on transaction speeds of injecting business intelligence into the business process management framework would be staggering. And the technology available today is capable of achieving much of this – SOA, BPM and business rules management.

Using the SOA/BPM environment, applications can be constructed from components or services with different properties. Leveraging business intelligence in a business process for automated decision making depends on the ability to support real-time analytics. Data mining and operational analytics effectively ‘see’ what a smart person would see if they could visualize the data transform it into usable formula, calculations and rules.

So we face the dilemna, that sharing the same information as used by BI systems to automate decision making is not only wasteful, but counter-productive. Information is interpreted by humans depending upon the emotions and experiences they attach to the information. Different people will make different decisions – and so interrupt the clear logic applied in a system driven decision. This can create conflict and distrust in the decision system, thereby preventing adoption.

Letting go of decisions is a difficult task for many managers to achieve. The key is engaging them in forming the logic that is used to drive the intelligence engine against which data is applied. This builds trust in the system, and in the outcomes.

Freeing decision makers from the day to day, general decision making, allows them to concentrate on the 5 percent that will make a critical difference to the performance of the enterprise. Once the results start showing, the decision support system gains further user support.

Its an evolving process that takes time. So be patient.