The killer average

Let's say you are running a loyalty programme where one of your main objectives is to use points to bring down discounts. Five months into the programme, you discover that average discounts outside the programme are marginally more than those in the programme (let's say, it's 27% inside the programme verses 29% outside the programme).

Worse, when you add the deferred discounts you have to give away as points (let's say, 2%), the discounts run neck to neck.

Worst, when you put in the expenses on running the programme, it seems quite clear that the programme is, effectively, extracting a larger discount.

Or is it?

Perhaps the transactions inside the programme are very different from those outside it. For instance, sales inside the programme can be of high-price, high-margin items; while those outside be of low-price, low-margin products.

The discounts percentages can be coincidentally equal.

The correct comparison would be of the fraction of the margin given away as discount. Better still, one should ask the simple what-if question: What would have the total discounts been had the programme not existed, assuming everything else remained the same?

This sounds obvious and simplistic, yet every day I see numbers being used with the minimum thought about where they came from.

Which brings me to a more fundamental problem. While finding figures for a nation like ours, where inequalities are far higher than people can ever imagine in developed countries, are agencies careful enough to cast their nets wider for data?

Or would we be better off if, while investigating anything to do with economics and money, we divided the world by borders that combined purchasing power with politics?