"1Business Analytics – BU609 Fall 2016 (Term 2) & Winter 2017 (Term 3) Final Examination 2Table of ContentsQuestion 1 Harmon Foods, Inc. Case Questions3Question 2 Merton Truck Company Case Questions 11Question 3 Lawsuit Decision Making 18References 21 3Question 1 Harmon Foods, Inc. Case QuestionsAnswer(i)Forecast for Seasonally Adjusted Case Shipments:The case study refers to Harmon Foods Inc. which sales Treat, a ready-to-eat breakfast cereal asone of its products with considerable market share. Treat is the main product the companymanufactures. The sales manager of the company, John MacIntyre, is having difficulty inforecasting sales of the product, as actual sales of the product have varied between 50% to 200%during last few months. The production schedule of the company is made on the basis of forecastsales. The difficulty in making forecast sales is affecting making of production schedule,employing adequate skilled labor, ordering raw materials, maintaining delivery schedule, andother business operations, and reduces the effectiveness of the company’s advertisementexpenditure for Treat. Correct forecast is also necessary as the company’s long-term dividendpolicy and corporate expansion plan also depend upon the sales forecasts.A 12 month moving average of sales data shows that there is a trend or rising sales of theproduct. Carswell believes seasonal factors might be of crucial importance in explainingdifficulty in making accurate forecasting. During November and December sales go down asinventories of the stores and the jobbers are drawn from year-end inventories. During summersales are down as a result of plant shutdown and vacationing sales personnel. Data madeavailable by National Association of Cereal manufacturers reveals seasonal effects on shipmentof breakfast cereals in the US. The actual monthly case shipments data of Treat for a period from January 1984 to December1987, and seasonal indices for Treat shipments are provided. The index for a month remainssame for the same month on all the 4 years. In this part of the answer the actual shipments have 4been converted into seasonally adjusted case shipment value and from that forecast of seasonallyadjusted case shipment values are determined in excel spreadsheet. The relevant excel spread- sheet is attached with this word file. The formula used can be seen in the excel formula bar. Harmon Foods, Inc.Month Case Shipments *PeriodJan-84 4250751Feb-84 3153052Mar-84 3672863Apr-84 4294324May-84 3478745Jun-84 4355296Jul-84 2994037Aug-84 2965058Sep-84 4267019Oct-84 32972210Nov-84 28178311Dec-84 16639112Jan-85 62940213Feb-85 26346714Mar-85 39832015Apr-85 37656916May-85 44440417Jun-85 38698618Jul-85 41431419Aug-85 25349320Sep-85 48436521Oct-85 30598922Nov-85 31540723Dec-85 18278424Jan-86 65574825Feb-86 27048326Mar-86 36505827Apr-86 31313528May-86 52821029Jun-86 37985630Jul-86 47205831Aug-86 25451632Sep-86 55135433 5Oct-86 33582634Nov-86 32040835Dec-86 27690136Jan-87 45513637Feb-87 24757038Mar-87 62220439Apr-87 42933140May-87 45315641Jun-87 32010342Jul-87 45177943Aug-87 24948244Sep-87 74458345Oct-87 42118646Nov-87 39736747Dec-87 26909648 Seasonally Forecastadjusted Month case shipment seasonally adjusted case shipmentvalueJan-84376172.5664 335319.4928Feb-84321739.7959 333652.9832Mar-84360084.3137 336612.6362Apr-84401338.3178 336415.4574May-84292331.0924 332473.6981Jun-84418777.8846 338374.0994Jul-84279815.8879 332749.4372Aug-84366055.5556 340226.6797Sep-84377611.5044 339763.1266Oct-84339919.5876 338099.918Nov-84296613.6842 340280.2824Dec-84255986.1538 347380.6696Jan-85556992.9204 359718.5933Feb-85268843.8776 338920.7214Mar-85390509.8039 349907.482Apr-85351933.6449 347353.6719May-85373448.7395 349379.5538Jun-85372101.9231 348899.9324Jul-85387209.3458 348587.6987Aug-85312954.321 346201.9537Sep-85428641.5929 354178.3759 6Oct-85315452.5773 346109.6785Nov-85332007.3684 354425.4837Dec-85281206.1538 361328.7215Jan-86580307.9646 377774.6411Feb-86276003.0612 344772.7152Mar-86357900 361899.1304Apr-86292649.5327 366390.5988May-86443873.9496 384811.4109Jun-86365246.1538 374885.4585Jul-86441175.7009 380571.9773Aug-86314217.284 369667.7228Sep-86487923.8938 388222.6246Oct-86346212.3711 364941.6505Nov-86337271.5789 376447.5119Dec-86426001.5385 394038.8351Jan-87402775.2212 387415.024Feb-87252622.449 387312.7712Mar-87610003.9216 447510.0024Apr-87401243.9252 372632.2304May-87380803.3613 369209.2906Jun-87307791.3462 376532.5535Jul-87422223.3645 437964.7672Aug-87308002.4691 452414.39Sep-87658923.0088 593960.3907Oct-87434212.3711 432271.6858Nov-87418281.0526 418281.0526Dec-87413993.8462 #DIV/0!(ii) Forecasts for Actual Case ShipmentsIn this part of the answer forecast of the actual case shipment values are found out from theforecast of seasonally adjusted case shipment values as found out in (i) above. The formula usedin finding out forecast of actual case shipment values; Forecast for actual case shipment values =Seasonally adjusted case shipment values multiplied by index divided by hundred. The "