19 Aug Case: Employee Retention at Bierrenbach & Austin (B&A)
Case: Employee Retention at Bierrenbach & Austin (B&A)
Demand for systems analysts in the consulting industry is greater than ever. Graduates with a combination of business and computer knowledge— some even from liberal arts programs—are getting great offers from consulting companies. Once these people are hired, they frequently switch from one company to another, as competing companies lure them away with even better offers. One consulting company, B&A, has collected data on a sample of systems analysts with undergraduate degrees they hired several years ago. The data are in an attached file. The variables are as follows:
• Starting Salary: employee’s starting salary at B&A
• On Road Percentage: percentage of time employee has spent on the road with clients
• State University: whether the employee graduated from State University (B&A’s principal source of recruits)
• CIS Degree: whether the employee majored in Computer Information Systems (CIS) or a similar computer-related area
• Stayed 3 Years: whether the employee stayed at least three years with B&A
• Tenure: tenure of employee at B&A (months) if he or she moved before three years
Data in attached file.
B&A is trying to learn everything it can about retention of these valuable employees. You can help by solving the following problems and then, based on your analysis, presenting a report to B&A
1. Although starting salaries are in a fairly narrow band, B&A wonders whether they have anything to do with retention.
a. Calculate a 95% confidence interval for the mean starting salary of all employees who stay at least three years with B&A. Do the same for those who leave before three years. Then calculate a 95% confidence interval for the difference between these means
b. Among all employees whose starting salary is below the median ($37,750), calculate a 95% confidence interval for the proportion who stay with B&A for at least three years. Do the same for the employees with starting salaries above the median. Then calculate a 95% confidence interval for the difference between these proportions.
2. B&A wonders whether the percentage of time on the road might influence who stays and who leaves. Repeat the previous problem, but now do the analysis in terms of percentage of time on the road rather than starting salary. (The median percentage of time on the road is 54%.)
3. Find a 95% confidence interval for the mean tenure (in months) of all employees who leave B&A within three years of being hired. Why is it not possible with the given data to calculate a confidence interval for the mean tenure at B&A among all systems analysts hired by B&A?
4. State University’s students, particularly those in its nationally acclaimed CIS area, have traditionally been among the best of B&A’s recruits. But are they relatively hard to retain? Calculate one or more relevant confidence intervals to help you make an argument one way or the other
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