A key step to better analytics is move more of your reports/metrics to a common language so different opportunities are cross-comparable. A quick way to get started is to use a common denominator in your monthly category reports. For example, here is what a typical monthly report looks like for a retailer:

 Growth Rate Furniture 20% Mattresses 4% Appliances 3% Total 4.4%

This report tells retail executives that the furniture merchant is doing a great job. In fact, her category is the only one performing above the company's total growth rate. While this may be true, there are typically two common errors that make this implied assumption wrong.

First, what is the industry growth rate for each category? Most of the story here could just be due to different industry dynamics (however, let's put that aside for now and focus on second issue for this blog post).

The second most common error is caused by different denominators. Different denominators prevent you from correctly comparing performances across categories. While it is fair to measure furniture's performance over time to see if the 20 percent is higher or lower than last year's, comparing furniture with any other category is highly misleading. In fact, it is voodoo math. Here is what is really happening:

 Last Year Sales Growth Rate Absolute Growth % of Company Growth Furniture: \$100K 20% \$20K 27% (\$20/\$74) Mattresses: \$600K 4% \$24K 32% (\$24/\$74) Appliances: \$1,000K 3% \$30K 41% (\$30/\$74) Total \$1,700K 4.4% \$74K 100%

Although furniture has the highest category growth rate, its small denominator means that its absolute growth in dollars is also the smallest. After converting all category growth rates to absolute terms, it becomes clear that appliances are driving the bulk (41%) of total growth. Though the concept is simple, misleading metrics due to different denominators are rampant in the retail industry.

We have recently seen this firsthand with a retailer that was debating whether it should focus on Category A or Category B (actual categories are masked due to client confidentiality). The retailer was convinced that their future lay with Category A. Why? The main reason was because it had a higher percentage growth rate. Consequently, they ran an advertising campaign that resulted in 10% growth in Category A and only 8% growth in Category B. The hallways quickly filled with chatter that Category A is driving more business.

Here is the issue: Category A and B have completely different denominators. This retailer sells \$4 in Category B for every \$1 they sell in Category A. You simply can't compare the percentage increase over different denominators when discussing overall impact on the business. In school, we learn to not add fractions with different denominators, and this rule still applies today. You must first convert numbers to a common denominator before comparisons can be made.

The easiest way to get to a common denominator is to convert metrics to absolute sales growth. For the retailer above, Category A lifted sales by \$300K, while Category B lifted sales by \$950K. This works out to 76% [\$950 / (\$300+ \$950) = 76%] of the total lift coming from Category B. Comparing metrics with different denominators led to the wrong initial insight that it was Category A that contributed to overall success, which led to misguided implications for the retailer. With a more accurate report using one common denominator across categories, the retailer now has a clear view on what is driving their business and has since corrected its course.