It goes without saying that if you know the value of analytics, it can sometimes be frustrating when leaders who may not have an analytic background do not understand or see the difference between basic reporting and advanced analytics. At SAS, we often refer to those two very different things as business intelligence (BI) and business analytics (BA).

Here are two simple ways of explaining why a BI based report that uses only simple statistics like averages can mislead  decision makers.   Let's say instead of store sales or employee performance we talk about the 4 tires on a car.  If we add up the total psi (pounds per square inch) for all four tires and get a value of 120 and take the average, then it appears we are in good shape 120/4 = 30 psi on average.  As a decision maker you receive a report that shows on average each tire is properly inflated and assume the car is running fine.   However, if you are then told that three of the tires are inflated to 35 psi, which means 1 tire only has 15 psi, does that change how you think the car will run?

A colleague of mine, Kathy Lange, uses this example to get the same point across: if you put one hand in boiling water and one hand in ice cold water then on average you are ok, right?    This is one reason why your data scientists or statisticians tend to ask for more details and shy away from aggregated information since it sometimes hides patterns that could point to new opportunities or identify potential problems.

Unfortunately, since we have to deploy or "deliver" analytic insight to others through reports, one can see why BA is sometimes lumped in with BI because the report format may look the same. The difference is in the value that is delivered.   As a result we may need to actually produce two reports, one with analytic insight in it and one without, and then show them side by side in order to allow them to "see" the difference or come to their own conclusions, which is better.