Use Naïve To Start The Exponentialsmoothing Case Study

BUS 260Will AlmonteAssignment 21. The following data are monthly sales of jeans at a local department store. The buyer would like toforecast sales of jeans for the next month, July.a) Forecast sales of jeans for March through June using the naïve method, a two-period movingaverage, and exponential smoothing with an α = 0.2. (Hint: Use naïve to start the exponentialsmoothing process.)MonthSales Naïveb) Compare the forecasts using MAD and decide which is best.Exponential = MAD = Σ | actual – forecast | = 13.73  8+8+4+7/4= 6.75nNaïve = MAD = Σ | actual – forecast | = 8.25  10+10+5+8/4= 8.25n2 period = MAD = Σ | actual – forecast | = 8.25  2.5+15+10+8/4= 8.25nAnswer: Exponential is bestc) Using your method of choice, make a forecast for the
Demand at Nature Trails Ski Resort has a seasonal pattern. Demand is highest during the winter, asthis is the peak ski season. However, there is some ski demand in the spring and even fall months.The summer months can also be busy as visitors often come for summer vacation to go hiking onthe mountain trails. The owner of Nature Trails would like to make a forecast for each season ofthe next year. Total annual demand has been estimated at 4000 visitors. Given the last two years ofhistorical data, what is the forecast for each season of the next year?VisitorsSeason Year 1 Year 2Fall200230Winter14001600Spring520580Summer720831avarageDemand in year 1 = 2840/ 4 = 710Demand in year 2 = 3241/ 4 = 810Season index of year 1:Season index of year 2:Fall = 200 / 710 = 0.28Winter = 1400 / 710 = 1.97Spring = 520 / 710 = 0.73Summer = 720 / 710 = 1.01Average for each seasonFall = 230 / 810 = 0.28Winter = 1600 / 810 = 1.97Spring = 580 / 810 = 0.72Summer = 831 / 810 = 1.03Each season's forecast for next yearFall = (0.28 + 0.28)/2 = .28Winter = (1.97 + 1.97)/2 = 1.97Spring = (0.73 + 0.72)/2 = 0.73Summer = (1.01 + 1.03)/2 =1.02Fall = .28 * 1000 = 280Winter = 1.97 * 1000 = 1970Spring = 0.73 * 1000 = 730Summer = 1.02 * 1000 =
The president of a company was interested in determining whether there is a correlation betweensales made by different sales teams and hours spent on employee training. These figures are shown.Sales (in thousands) Training Hours2510401236125015116a)Compute the correlation coefficient for the data in Minitab. What is your interpretation of thisvalue?5. Custom Computers, Inc. assembles custom home computer systems. The heat sinks needed arebought for $12 each and are ordered in quantities of 1300 units. Annual demand is 5200 heat sinks,the annual inventory holding cost rate is $3 per unit, and the cost to place an order is estimated tobe $50. Calculate the following:a) Average inventory level• EOQ sqrt(2DS)/H• sqrt(2*5200*50/3)= 416b) The number of orders placed per year• 5200/416= 12.5 per yearc) The total annual inventory holding cost• $3x416/2= 624 holding cost(Holding cost of annual inventory times the average inventory dived by 2)d) The total annual ordering cost• Cost to place order is $50 x 4= $200e) The total annual cost• $3 per unit x 1300units= $3,900• $3,900 x 4 times a year = $15,600• Cost to place order is $50 x 4= $200• $15,600+200= $15,800 total annual cost6. A local nursery, Greens, uses 1560 bags of plant food annually. Greens works 52 weeks per year. Itcosts $10 to place an order for plant food. The annual holding cost rate is $5 per bag. Lead time isone week.a) Calculate the economic order quantity.• EOQ sqrt(2DS)/H• Sqrt(2x1560x10)5= 78.9 or 79b)