TRC

By Rajan Sambandam

Satiscan™ is a directed search algorithm that was developed to conduct key driver analysis in a way that regression is not capable of doing. Traditional regression analysis considers the direct impact of each independent variable on the dependent variable, but has no way of identifying relationships among independent variables. As a consequence, if there are complex relationships between independent variables, the inability to specify them will cause incorrect estimation of the relative importance of each independent variable.

For example, independent variable A may be important both because of its direct impact on the dependent variable X and because of its impact on another independent variable B that in turn affects the dependent variable. In this situation, traditional regression analysis will underestimate the total importance of A.

The practical effects of this can be quite important. Most often, the results of key driver analysis are used to make decisions about where to allocate service improvement resources. Ordinarily, only some of the independent variables in a key driver analysis are subject to direct manipulation – perhaps only a few of them. Consequently, failure to appreciate the true importance of a driver can result in lost opportunities and/or serious misallocation of service improvement resources.

In contrast to traditional regression analysis, Satiscan™ uses a directed search algorithm to model all relationships among variables. It systematically searches all of the possible path models to find the one that is most consistent with the data.

The next few pages show an actual example, a case where the same data was analyzed using traditional regression analysis on one hand and Satiscan™ on the other. Figure 1 shows the traditional regression analysis, with the impact of each independent variable expressed as a Beta weight. (Beta weights measure the importance of each variable in determining another variable. In this case, for example, "called back when rep said" is only about a fifth as important as "satisfaction with service rep" in determining "satisfaction with the call experience.")

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