Managing Employee Retention

Data Quality:

It is essential to make sure the information you utilize stands. An outlier information point can significantly decrease the fit of a model, so it is crucial that bad information points be moved. In the case of the Store24 information, we will assume that all managers have some experience, so get rid of any data points where the manager experience is zero.

Regression Analysis

First, you should run a full model for profit that consists of both period and website area related variables.

Period related variables are MTenure and CTenure. Website area associated variables are population, variety of competitors, street level exposure, pedestrian access, kind of neighborhood, and whether a store stays open 24 hours. These variables are also defined on page 4 of the case Store24 (A).

First you ought to determine if all variables add to our understanding of the design. Utilize the p-value for each coefficient to choose (a worth of 0.05 is generally utilized to decide whether a variable should be consisted of).

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If any variables are not substantial, copy the worksheet, remove the variable and run the regression once again. In your report you ought to discuss how well the design fits (e.g. explains the factors that affect earnings).

It is not frequently comprehended how to assess the "impact" of the independent variables. The variables have to have a p-value that is substantial (otherwise we can't state there is a relationship), but how little the p-value is does not inform us how important the variable is.

A great way to understand the effect of the variable is to find the variety of values it can take, and after that increase that range by the value of the coefficient. That informs you the maximum impact that the variable can have on the problem.

Next, you must resolve Tom Hart's hypothesis that supervisor period does not have a direct effect on profitability-- that is, that there are reducing go back to manager tenure. To check this, copy the worksheet, then add the variable MTenure2. To do this, insert a column next to the Period column, and then enter the formula =D2 ^ 2 in cell E2 and copy this formula to the remainder of the cells. Now run a regression on this new set of variables and see if the MTenure2 variable is statistically considerable.

What to Submit: You are to write a memo from Sarah Jenkins to Paul Doucette summarizing your results. You should explain your regression results:

• How well the model predicts store performance (r2, p-value of variables and their “impact”)
• How your MTenure2 assesses Tom Hart’s hypothesis. Does it support his hypothesis? You should include a graph that shows contribution to profit of employee tenure over the range of values in the data set. The x-axis should be manager tenure, and the y-axis should be the predicted contribution to store profit.

Finally, your memo should give Paul Doucette a concrete recommendation as to how much Store24 should invest in any new manager retention programs.