MedicTronix is a startup company that manufactures medical devices for use in hospital clinics. Inspired by experiences with family members who have battled cancer, MedicTronixss founders have developed a prototype for a new device that limits health care workers exposure to chemotherapy treatments while they are preparing, administering, and disposing of these hazardous medications. This new device features an innovative design and has the potential to capture a substantial share of the market. MedicTronix would like an analysis of the first-year profit potential of the device. MedicTronixs has identified the key parameters in determining first-year profit: selling price per unit (p), first-year administrative and advertising costs (ca), direct labor cost per unit (cl), parts cost per unit (cp), and first-year demand (d). After conducting market research and a financial analysis, MedicTronix estimates with a high level of certainty that the devices selling price will be $2,495 per unit, and the first-year administrative and advertising costs will total $5,000,000. MedicTronix is not certain about the values for the cost of direct labor, the cost of parts, and the first-year demand. At this stage of the planning process, MedicTronixs base estimates of these inputs are $1400 per unit for the direct labor cost, $350 per unit for the parts cost, and 25,000 units for the first-year demand (with a standard deviation of 10% of demand). NOTEyou should not use 10% in the STD Dev, but 10% of 25,000. MedicTronix is interested in what happens if the estimates of the direct labor cost per unit, parts cost per unit, and first-year demand do not turn out to be as expected under the basecase scenario. For instance, suppose that MedicTronix believes that direct labor costs could range from $1200 to $1600 per unit, the parts cost could range from $250 to $500 per unit, and the first-year demand could range from 0 to 50,000 units. Because MedicTronixs models the direct labor cost per unit with a discrete probability distribution, the direct labor cost per unit can only take on a value of $1200, $1300, $1400, $1500, or $1600. Costs per unit probability is 10% for $1200, 21% for $1300, 38% for $1400, 21% for $1500, and 10% for $1600. Part A. Using these ranges, develop a base-case simulation. For your chart, make sure that you can see a frequency distribution. Hint: For your Bin column, start around 5-6 Million and increase each row by a factor of 1 Million. Part B. Marketing has seen your baseline simulation and has informed you that their administrative and advertising forecast costs have increased to $5.5 Million. Therefore, you have increased your selling price per unit to $2795. Inflation has been determined to increase price costs 10% for both boundaries of parts costs. Demand is expected to be 27000 with a 5 % deviation. With the inflation, all costs per unit have increased $100. the direct labor cost per unit can only take on a value of $1300, $1400, $1500, $1600, or $1700. Costs per unit probability is 10% for $1300, 21% for $1400, 38% for $1500, 21% for $1600, and 10% for $1700.

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