Managing Employee Retention Essay

matchless of the first steps in abbreviation of the data is to make a comparison of the 10 approximately remunerative stores and the 10 least lucrative stores. Hart claimed that the motorbus and crew ten-spoture in the some paid stores was almost four times the level of that in the least economic stores. This analysis is barely based solely on the summary statistics for those ten stores in each category. Taking a closer look at the consequents for the individual stores would stir that the birth is not so simple. For example face at store 47, which is at the bottom of the ten most profitable list, both the crew and manager kick upstairs are very measly in comparison to the early(a)(a) stores in the list. This means that it would not be pass judgment that store 47 would be so profitable if the manager and crew kick upstairs were the only influencing factor on favorableness. In fact, the levels of promote in this store are lower the average of those from the ten last profit stores, which would indicate that very low levels of profit would be expected from the store. A more in-depth analysis is consequently required.There is further demonstrate that neither manager land promote nor employee tenure alone importantly square offs the profitableness of each store. This whitethorn seen in the scatter-plots which are include 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 assumption for manager tenure is 45.3. This mean whitethorn however be meagrely higher than the median would be given that there are some(prenominal) exceedingly high values which would influence the calculation of the mean. A corresponding pattern whitethorn 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 in addition apparent from these plots is that neither variable may significantly explain discrepancy in the profitability of a store. This is evident in the r-squared value, which indicates that only 19.6% of diversity in profitability may be explained by manager tenure alone. Similarly, only 6.7% of this variation may be explained by employee tenure alone. Ittherefore is apparent that there are eightfold variables which may influence profitability.In order to assess whether a manager and employee tenure combine to influence profitability a multiple reasoning backward lesson may be formed using these two variables. The results of this regression may be seen in control board 1.Figure 1 Correlation between manager tenure and store profitabilityFigure 2 Correlation between employee tenure and store profitabilityFrom Table 1 it may be seen that when considering both manager and employee tenure there is still only 21.7% of variation in profitability which these variables may explain. This therefore indicates that there must be other factors which e xert an influence. It would therefore be suitable to construct a multiple regression stumper which takes into account other variables for which data is available. Although it was origin altogethery believed that the relationship may be non-li confining, this still does not significantly join on the r-squared value.Table 1 Regression determine in which manager tenure and employee tenure are included Regression Statistics three-fold R 0.465617551 R straight 0.216799704 Adjusted R Square 0.19504414 Standard Error 80212.7404 Observations 75 Multiple Regression ModelThe first multiple regression simulate which is included is that which includes all of the variables for which data are available. These variables areY ProfitabilityX1 theater director tenureX2 Employee tenureX3 Population near storeX4 Competition near storeX5 Visibility of storeX6 Pedestrian countX7 Residential or industrial areaX8 24 hour accessThe results of the regression model may be seen in Table 2 below. This sh ows that using the model with all eight variables included 63.8% of the variation in profitability may be explained. This suggests that the model may be valid in explaining the touch on profitability. In addition to this, from Table 3 it may be seen that the value of the F-test statistic is 14.53, with a significance of less than 0.05 which also shows that the model is significant. tho by looking at the results in Table 4 it may be seen that not all of the variables which are included in the model may be significantly contributing to the model. As the variable X5, which is the visibleness of the store, has a p-value of more than 0.05 this suggests that the variable is not contributing significantly to the model.This would suggest that removing this variable may further improve the model. In addition to this it would be necessary to remove any variables which were collinear as this could interfere with the results of the regression. subsequently using the program PHStat to analys e the variable inflation factors (VIFs) of the variables these are all below 5, which shows that there is no collinearity between variables. because the improved model would be one which included all variables except X5.The Impact of gain Crew TenureFrom the regression equation which is calculated from the multiple regression model it may be seen that increasing both manager and employee tenure is significant in increasing profitability of stores. Specifically, the model predicts that for every(prenominal) month sum up in manager tenure there would be an increase in profits of near $787 if all other factors were unplowed constant. Also, for every increase of one month in employee tenure there is predicted to be an increase in profitability of around $963 if all other factors were kept constant. It was suggested that the relationship between tenure and profitability may be bloodsucking on the length of tenure, i.e. a non-linear relationship. However the fitting of a impetus li ne to the scatter-plot suggests that a non-linear relationship does not fit the data significantly better than a linear trend line. Therefore it would be predicted that an increase in employee tenure of 1.38 months would result in an increase in profitability of around $1330.Validity of the DataThe data on which the above analyses are based contains information taken from 2000, which is now eight years old. Therefore it is possible that the financial implications of increasing crew tenure have changed somewhat. It would however be considered valid to use the data to provide an estimate of the financial implications as the factors which would influence the regression model used would be for the most part the same. Although the data also included only the data from 75 of the 82 stores, this is a large enough sample to be considered representative of the mountain range as a whole. It wouldtherefore be expected that while these other stores may not follow the model precisely, it shou ld still provide an recital of the influence of tenure on profitability of these stores.RecommendationsBased on the analysis of the data it would be recommended that increasing both manager and employee tenure may significantly increase profitability of stores. In particular, the current bonus jut would be profitable to the company if the amount of bonus offered were less than around $1330, as this is the increase in profitability which would result. However, it is also possible that offer these bonuses would increase manager tenure, which would then further increase profitability. It would however be suggested that this alone may not be sufficient to largely increase the profitability of some stores, as the overall profitability of stores is a result of an interplay of both site-location and people factors.BibliographyBerenson, M.L., Levine, D.M. & Krehbiel, T.C. (2008) Basic Business Statistics. 11th Edition. Philadelphia, PA learner Hall.Kazmier, L.J. (2003) Schaums Outline o f 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.