You are the new Vice President of Sales for Penske Motors, one of America's leading automotive...

 

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You are the new Vice President of Sales for Penske Motors, one of America's leading automotive dealership groups that operates over 100 individual dealerships across the country. While you are an experienced marketer, you are new to the automotive business. Naturally, given Murphy's Law, one of your first recommendations will involve a decision about how the sales operation for all of the company's dealerships will be structured-and passionate opinions abound on both sides of this issue. Repeated surveys across many years have shown that the U.S. car-buying public hates the traditional new-car buying experience. Typically, this experience involves a great deal of bargaining between the buyer and the salesperson, who usually doesn't have the authority to make a final decision on the price of the vehicle but must check repeatedly with a sales manager. Consequently, different buyers often end up paying different prices for the same vehicle depending on a number of factors. Most potential customers find this process demeaning, upsetting, and time-wasting. In response, some dealers have begun selling their products in a way that is more agreeable to most Americans: they simply mark the price on the car and the potential buyer either pays that price or doesn't buy the car. Penske's California dealerships have been testing this new "flat pricing" policy, while its dealerships in other parts of the country have maintained the traditional, "bargaining" approach. You have a meeting with Roger Penske, himself, next week to recommend which of these sales policies the company should employ (which should give you an idea of the magnitude of this decision since Mr. Penske rarely involves himself in details of the company's business anymore). Once, long ago at SJSU, you were a good student of a certain Market Research professor and, if nothing else, you learned to let facts and data help you make better decisions. The question here is which data? The key for the company is what sells the most vehicles, but your company has dealerships of all different sizes and a dozen different brands. Finally, it hits you: one of the most important tools in evaluating salesperson performance is the so-called "closing percentage;" that is, the percentage of customer visits that result in a sales "close" (i.e., the sale of a vehicle). Yelling for your SJSU intern, you quickly send her off to select a random sample of the company's California dealerships and another of the company's dealerships elsewhere in the U.S. In each case, your intern is to provide data on the number of customer visits and the number of vehicle sales. This will enable you to calculate a "closing percentage" for each approach and make a recommendation. You have decided to make one of the following recommendations: (1) the new "flat pricing" approach if its "closing percentage" is higher than the traditional "bargaining" approach; (2) the "bargaining" approach if it has a higher "closing percentage" than "flat pricing;" or (3) if the "closing percentages" are statistically equal, maintain both approaches, but expand the test of the "flat pricing" approach to all west coast dealerships and collect customer data nationwide to see which approach leads to more satisfied customers. The data your intern provided is given below. Using an alpha of .05 and the 5-step hypothesis-testing process, what will you recommend? Sample of California Dealerships Dealership Number of Number of Customer Vehicle ID # Visits Sales 002 005 008 011 014 017 020 023 026 029 032 035 038 041 044 443 1,017 168 532 326 609 1,254 471 585 790 839 392 503 921 254 100 226 47 133 84 152 311 115 59 198 170 165 123 209 66 Sample of Other U.S. Dealerships Dealership ID # 103 107 111 115 119 123 127 131 135 139 143 147 151 155 159 163 167 171 175 102 106 110 114 118 122 Number of Number of Customer Vehicle Visits Sales 861 576 328 222 499 1,183 137 713 484 255 370 448 616 1,301 1,527 769 423 352 554 635 700 878 829 386 941 215 144 72 57 136 289 35 178 120 61 93 107 154 265 324 172 100 85 119 138 141 186 163 75 200 You are the new Vice President of Sales for Penske Motors, one of America's leading automotive dealership groups that operates over 100 individual dealerships across the country. While you are an experienced marketer, you are new to the automotive business. Naturally, given Murphy's Law, one of your first recommendations will involve a decision about how the sales operation for all of the company's dealerships will be structured-and passionate opinions abound on both sides of this issue. Repeated surveys across many years have shown that the U.S. car-buying public hates the traditional new-car buying experience. Typically, this experience involves a great deal of bargaining between the buyer and the salesperson, who usually doesn't have the authority to make a final decision on the price of the vehicle but must check repeatedly with a sales manager. Consequently, different buyers often end up paying different prices for the same vehicle depending on a number of factors. Most potential customers find this process demeaning, upsetting, and time-wasting. In response, some dealers have begun selling their products in a way that is more agreeable to most Americans: they simply mark the price on the car and the potential buyer either pays that price or doesn't buy the car. Penske's California dealerships have been testing this new "flat pricing" policy, while its dealerships in other parts of the country have maintained the traditional, "bargaining" approach. You have a meeting with Roger Penske, himself, next week to recommend which of these sales policies the company should employ (which should give you an idea of the magnitude of this decision since Mr. Penske rarely involves himself in details of the company's business anymore). Once, long ago at SJSU, you were a good student of a certain Market Research professor and, if nothing else, you learned to let facts and data help you make better decisions. The question here is which data? The key for the company is what sells the most vehicles, but your company has dealerships of all different sizes and a dozen different brands. Finally, it hits you: one of the most important tools in evaluating salesperson performance is the so-called "closing percentage;" that is, the percentage of customer visits that result in a sales "close" (i.e., the sale of a vehicle). Yelling for your SJSU intern, you quickly send her off to select a random sample of the company's California dealerships and another of the company's dealerships elsewhere in the U.S. In each case, your intern is to provide data on the number of customer visits and the number of vehicle sales. This will enable you to calculate a "closing percentage" for each approach and make a recommendation. You have decided to make one of the following recommendations: (1) the new "flat pricing" approach if its "closing percentage" is higher than the traditional "bargaining" approach; (2) the "bargaining" approach if it has a higher "closing percentage" than "flat pricing;" or (3) if the "closing percentages" are statistically equal, maintain both approaches, but expand the test of the "flat pricing" approach to all west coast dealerships and collect customer data nationwide to see which approach leads to more satisfied customers. The data your intern provided is given below. Using an alpha of .05 and the 5-step hypothesis-testing process, what will you recommend? Sample of California Dealerships Dealership Number of Number of Customer Vehicle ID # Visits Sales 002 005 008 011 014 017 020 023 026 029 032 035 038 041 044 443 1,017 168 532 326 609 1,254 471 585 790 839 392 503 921 254 100 226 47 133 84 152 311 115 59 198 170 165 123 209 66 Sample of Other U.S. Dealerships Dealership ID # 103 107 111 115 119 123 127 131 135 139 143 147 151 155 159 163 167 171 175 102 106 110 114 118 122 Number of Number of Customer Vehicle Visits Sales 861 576 328 222 499 1,183 137 713 484 255 370 448 616 1,301 1,527 769 423 352 554 635 700 878 829 386 941 215 144 72 57 136 289 35 178 120 61 93 107 154 265 324 172 100 85 119 138 141 186 163 75 200