Store 24
Case Study: Managing Employee Retention
Relationship Between Employee and Manager Tenure and Store Performance
One of the first steps in analysis of the data is to make a comparison of the 10 most profitable stores and the 10 least profitable stores. Hart claimed that the manager and crew tenure in the most profitable stores was almost four times the level of that in the least profitable stores. This analysis is however based solely on the summary statistics for those ten stores in each category. Taking a closer look at the results for the individual stores would suggest that the relationship is not so simple. For example looking at store 47, which is at the bottom of the ten most profitable list, both the crew and manager tenure are very low in comparison to the other stores in the list. This means that it would not be expected that store 47 would be so profitable if the manager and crew tenure were the only influencing factor on profitability. In fact, the levels of tenure in this store are lower the average of those from the ten lowest profit stores, which would indicate that very low levels of profit would be expected from the store. A more in-depth analysis is therefore required.
There is further evidence that neither manager tenure nor employee tenure alone significantly influences the profitability of each store. This may seen in the scatter-plots which are included below as Figure 1 and Figure 2. It appears clear from Figure 1 that most managers have been at their store for less than 50 months, and the mean which is given for manager tenure is 45.3. This mean may however be slightly higher than the median would be given that there are several exceedingly high values which would influence the calculation of the mean. A similar pattern may be seen in Figure 2, where it is clear that most employees have lower than 20 months retention, with the mean given as 13.9 months.
What is also apparent from these plots is that neither variable may
Relationship Between Employee and Manager Tenure and Store Performance
One of the first steps in analysis of the data is to make a comparison of the 10 most profitable stores and the 10 least profitable stores. Hart claimed that the manager and crew tenure in the most profitable stores was almost four times the level of that in the least profitable stores. This analysis is however based solely on the summary statistics for those ten stores in each category. Taking a closer look at the results for the individual stores would suggest that the relationship is not so simple. For example looking at store 47, which is at the bottom of the ten most profitable list, both the crew and manager tenure are very low in comparison to the other stores in the list. This means that it would not be expected that store 47 would be so profitable if the manager and crew tenure were the only influencing factor on profitability. In fact, the levels of tenure in this store are lower the average of those from the ten lowest profit stores, which would indicate that very low levels of profit would be expected from the store. A more in-depth analysis is therefore required.
There is further evidence that neither manager tenure nor employee tenure alone significantly influences the profitability of each store. This may seen in the scatter-plots which are included below as Figure 1 and Figure 2. It appears clear from Figure 1 that most managers have been at their store for less than 50 months, and the mean which is given for manager tenure is 45.3. This mean may however be slightly higher than the median would be given that there are several exceedingly high values which would influence the calculation of the mean. A similar pattern may be seen in Figure 2, where it is clear that most employees have lower than 20 months retention, with the mean given as 13.9 months.
What is also apparent from these plots is that neither variable may
Bibliography: Berenson, M.L., Levine, D.M. & Krehbiel, T.C. (2008) Basic Business Statistics. 11th Edition. Philadelphia, PA: Prentice Hall. Kazmier, L.J. (2003) Schaum’s Outline of Business Statistics. New York: McGraw-Hill. Levine, D.M., Stephan, D.F., Krehbiel, T.C. & Berenson, M.L. (2007) Statistics for Managers Using Microsoft Excel. Philadelphia, PA: Prentice Hall.