Total purchased cost ==B9*B11 Manufactured cost less?=IF(B14

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Total purchased cost ==B9*B11<br>Manufactured cost less?=IF(B14<B15,1,0)<br>Use a data table, as outlined in the text, to run the simulation 1000 times. From the<br>simulation results, calculate the estimated probability that manufacturing the<br>product in-house will cost less than purchasing from the supplier.<br>Understanding that simulation is random in nature and that your answer may not<br>match any of the answer choices exactly, choose the answer choice that is closest to<br>the estimated probability.<br>29.3%<br>4.5%<br>58.2%<br>44.0%<br>18.5%<br>

Extracted text: Total purchased cost ==B9*B11 Manufactured cost less?=IF(B14
Consider the following spreadsheet for an outsourcing decision model, The analyst is<br>trying to determine whether the product in question should be manufactured in-<br>house, incurring a fixed cost in addition to a cost per unit, or purchased from a<br>secondary supplier. Clouding the decision is uncertainty with regard to the demand<br>for the product and also with regard to the purchase price that will be offered by the<br>potential supplier. The analyst believes that the demand can be modeled by a normal<br>random variable with mean 1000 units and standard deviation of 100. A supervisor<br>asks the analyst to simulate the scenario 1000 times using a normal random variable,<br>with mean of $165 with a standard deviation of $10, for the purchase price. The<br>supervisor asks the analyst to report the probability that manufacturing the product<br>in-house will cost less than purchasing from the supplier.<br>Hint: Copy-and-paste the following into an Excel spreadsheet.<br>Outsourcing Decision Model<br>Data<br>In-House Manufacturing<br>Fixed cost =60000<br>Variable cost per unit = 115<br>Purchased from Supplier<br>Unit cost ==NORM.INV(RAND(),165,10)<br>Demand volume<br>=NORM.INV(RAND(),1000,100)<br>Model<br>Total manufactured cost ==B5+(B6*B11)<br>Total purchased cost ==B9*B11<br>Manufactured cost less?=IF(B14<B15.1.0)<br>

Extracted text: Consider the following spreadsheet for an outsourcing decision model, The analyst is trying to determine whether the product in question should be manufactured in- house, incurring a fixed cost in addition to a cost per unit, or purchased from a secondary supplier. Clouding the decision is uncertainty with regard to the demand for the product and also with regard to the purchase price that will be offered by the potential supplier. The analyst believes that the demand can be modeled by a normal random variable with mean 1000 units and standard deviation of 100. A supervisor asks the analyst to simulate the scenario 1000 times using a normal random variable, with mean of $165 with a standard deviation of $10, for the purchase price. The supervisor asks the analyst to report the probability that manufacturing the product in-house will cost less than purchasing from the supplier. Hint: Copy-and-paste the following into an Excel spreadsheet. Outsourcing Decision Model Data In-House Manufacturing Fixed cost =60000 Variable cost per unit = 115 Purchased from Supplier Unit cost ==NORM.INV(RAND(),165,10) Demand volume =NORM.INV(RAND(),1000,100) Model Total manufactured cost ==B5+(B6*B11) Total purchased cost ==B9*B11 Manufactured cost less?=IF(B14<>

Jun 07, 2022
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