Inflating Contributions

How Data and Statistics can be used to lie

Many years back, I attended an internal department town hall and a selected few speakers internal to the organization but external to the department were invited to share about their work. The purpose of which was to expose the technology department to other areas of the business and what others are doing in the company.

One particular presentation irks me enough that until today, more than 6 years later, I still remember it.

$70 million increase in revenue due to analytics

The particular presentation was a showcase by the head of consumer banking data analytics team. He started off with a few slides of introductory materials of benefits of data analytics and how it can be used to understand consumer behavior, particularly in the area of consumer spending. Then, he launched into a single slide boasting of his team’s contributions to the company: an increase of $70 million in revenue.

Now, I don’t really have an issue with someone boasting of their contribution, if the numbers are real; I have an issue if the numbers are not. In this article, I want to use this as an example to show my readers how to think about the statistics that you were given and to be able to see when certain results are highly questionable.

How was this attribution of revenue attributed to the analytics team as claimed by the head? A simple calculation of revenue for the current year minus revenue…