Group Variation Analyst

Arranging Data for Testing

The data is key, and the GIGO concept holds true: Garbage In Garbage Out. Before looking at the assumptions that must be met in order to run a reliable variation analysis lets discuss the form and kind of data suitable for the analysis.

There are two main situations when we want to analyze performance:

1. To find out differences in internal and external data. The former refers, for instance, to our product only and the latter accounts for competitors as well.
2. To find out differences in spatial and time data, such as several geographic areas and time series.

The picture above shows the different data sets. The four tables show hypothetical data concerning sales performance in several situations. In the top-left region the table shows measurements for the same product in three different geographic areas: area 1, 2 and 3. Each area is made of six zones (or stores if you like), and the data shows sales growth by zone. For instance, the value in cell B2 is obtained by dividing the sales value for Dash in Zone 1 of Area 1 in August 2004 by the sales value in the same zone for July 2004 minus 1.

This test may be of great value to managers, for example when evaluating the effectiveness of promotional actions. Say you want to increase sales in the short run by means of a promotional campaign, and you have doubts concerning which of three concepts should be applied: price discount, increased quantity, or bundling a convenience package. Surveying a sample of consumers could produce the data needed to make an informed decision based on customer preference and profitability, because Variation Analyst supplies values that make clear the advantage of one offer against the others.

You may have noticed there are missing values in two of the tables. Variation Analyst handles such cases without requiring the user to take any action. Read more concerning missing data in the section Technicalities.

The tables in the picture show percent values, but unit or monetary data can also be used. The important thing is that the variances of the groups (columns) are equal or close. In this instance, Variation Analyst produces reliable results. However, if one of the stability assumptions is unmet, it may produce unreliable and, therefore, dangerous results. The section Technicalities supplies information concerning the assumptions underlying the data arrangement for this analytical tool.