Several years ago I heard a rather enlightening semi-facetious exchange at the start of a business intelligence lecture that went somewhat like this:

Analyst: “What is the secret of your success?”

Executive: “Right decisions.”

Analyst: “And what is the secret to making right decisions?”

Executive: “Experience.”

Analyst: “And what is the secret to getting experience?”

Executive: “Wrong decisions.”

So let’s talk about the topic of decision-making and business intelligence. There is a great deal of confusion throughout both the private and public sectors as to the difference between decision-support and business intelligence. I think the simplest way to look at it is that the better the quality and timeliness of your business intelligence, the better prepared you are to make the right decision. Business intelligence, we have previously said, is another name for analytics. Analysis in turn is “the act or process of breaking something down into its constituent parts.” Ultimately, analysis is about extracting meaning from data.

There used to be a time when it was suggested that the goal in decision-making was to make “informed decisions.” The implication being that if a decision is made in the absence of sufficient information, the probability will be very small of it being the “right” decision. But what exactly is a decision? Webster’s dictionary defines a decision as the “act or process of selecting a course of action.” Hence decisions are invariably tied in some way to action.

Adm. A. W. Radford, who was a pioneer in naval aviation and the third chairman of the Joints Chiefs of Staff (1953 to 1959), had a classic definition. Radford said that, “A decision is the action an executive must take when he has information so incomplete that the answer does not suggest itself.”

If you take this definition a step further, you can see that the objective of decision-support, hence, must be to make the decision-making domain as small as possible. One does this by bringing to bear as much timely and relevant business intelligence as possible into the process of “selecting a course of action” in order to make that choice completely obvious.

How do we do this in a way that makes the most sense in the public sector? Well, in the private sector decision-making is primarily focused on helping an enterprise do well in the marketplace. That basically means to make it as profitable as possible over a specific time horizon. If we factor in the evident, mainly that the objective of government is not to make a profit, what role then does decision-making play in this space?

We must remember that anytime that we seek to improve a specific situation we must “select a course of action,” that is, make a decision. What new course of action do we select when we are faced with having to improve the state of affairs on environmental issues, law enforcement, healthcare, defense, homeland security or taxes? We need to bring the most relevant business intelligence to bear on the problem area in order to conduct analysis and select a course of action.

An example is probably in order. Let’s take the case of the privatization of social security, which is currently such a major topic of debate in the public policy arena. What is the problem? That because of the demographic changes resulting from what is often referred to as “the aging of America” there will soon be too many retirees being supported by too few workers for the current social security model to work well in the future. This means that we have a state of affairs that needs to be improved. What then do we do?

Now is when the fun begins, and everything necessitates business intelligence. Here are some of the questions that must be asked in order to do analysis and select some new course of action. Obtaining many of these answers can be extremely difficult in some cases and the results themselves will probably be challenged by other policy mavens.

• How large is the social security trust fund now?
• How fast is it growing with the current FICA contributions?
• How is it invested for future growth? (Where and at what rates and with what guarantees?)
• What are the specific demographic trends behind “the aging of America?”
• How many people is the fund supposed to support over what period of time?
• How does the fund’s balance—dollars coming in vs. dollars flowing out—play out over the period 2005 through 2070?
• What are the life expectancies of Americans during that period and how will they change?
• What kinds of returns can be expected over what timeframes with individual private investment accounts?
• What has been the experience in countries where these schemes have been adopted?
• Are these experiences relevant to the U.S. situation?
• What is to happen if an individual’s private investment accounts don’t perform during the critical retirement period?
• Will the government and society accept indigence based on such an outcome or will there be the need for another minimal safety net?
• What percent of an individual’s fund should be available for private investment accounts?
• Etc., etc., etc.

I understand that there is massive oversimplification in my articulation of this example in order to make the point. Yet, we know that there will have to be millions of decisions made for hundreds of thousands of situations involving the establishment of thousands of specific programs, policies and/or practices dealing with the topic. Somewhere along the line the executive branch will have to develop a “new course of action” embodied in some proposed legislation. Congress will review, discuss and modify it as it enacts a new law that captures the gist of that new course of action. And, capping my argument, each individual senator or representative will have to make a decision on whether to vote yes or no on that bill. As constituents, the least we can and should demand is that they make “informed decisions” based on the most timely and relevant business intelligence available. And it will be up to us in the business intelligence community to assist government in that process.

Recent articles by Dr. Ramon Barquin

• The Rule of 151: How to Move Knowledge Management and Business Intelligence from Margin to Mainstream
• What the Healthcare Reform Effort Needs is Better Business Intelligence
• Dashboards, Dashboards Everywhere
• Knowledge Management in the Federal Government: What’s Happening?