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Supply Chain Planning and Control: The Demand Of TV Equipment In The European Markets - Essay Example

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Supply Chain Planning and Control By Name Presented to Institution Instructor Course Date Supply Chain Planning and Control Question One In order to forecast the demand of TV equipment in the European Markets, we use regression analysis and adjust it for seasonal variation owing to the fact that the demand for TV equipment has been increased during certain times of the year (Gorr, Olligschlaeger, & Thompson, 2003; Goodwin, 2005)…
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Supply Chain Planning and Control: The Demand Of TV Equipment In The European Markets
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Download file to see previous pages In general form y=a + bx where y is the dependent variable and x is the independent data variable; Month = x where x=1, 2, 3.......42 Demand = y To find a and b, we use the following formula: Using the above formula into the existing data, the following was the value for b: b= -98.04 Using the formula to find a: a = 10631.82 Using the above values for a and b into the formula, a value for demand (y) can be derived for a specific month of the year. Data forecasting for the month of March in the year 2013 can be calculated as follows: For March 2013, x = 43 = 6416.1 This value then has to be adjusted for seasonal variations because there are times of the month when the sales are lower than other months. For month 7, actual value is 5000 Value of trend line for demand D = = 9945.54 The seasonal factor = = 1.99 For month 19, actual value is 5000 Value of trend line for demand D = = 8769.06 The seasonal factor = = 1.75 For month 31, actual value is 3000 Value of trend line for demand D = = 7592.58 The seasonal factor = = 1.51 The average for the above three factors: = = 1.75 The forecast for March 2013 is then adjusted using this value: = 3666.34 Using the above method, the factors for the remaining months were calculated as follows: April 2013 = 6318.06 The adjusted factor is calculated and found to be: = 2.53 When the initial value of 6318.06 is adjusted with a seasonal variation of 2.53 the resulting demand level is 2497.25. May 2013 = 6220.02 The adjusted factor is calculated and found to be: = 2.02 When the initial value of 6220.02 is adjusted with a seasonal variation of 2.02 the resulting demand level is 3079.22. June 2013 = 6121.98 The adjusted factor is calculated and found to be: = 1.31 When the initial value of 6121.98 is adjusted with a seasonal variation of 1.31 the resulting demand level is 8019.79. The value for June is adjusted upwards because looking at previous trends; it has been the norm that the demand for the product increases from mid-year to the end of the year. Hence the demand for the following months can be forecast as follows: Month Forecast demand March 3000 April 3000 May 3000 June 8000 Question Two Calculated Demand and Supply In order to determine the employee schedule, the following table is used No. of Hours per month No. of phones one employee can make in a month Total no. of employees Total No. of phones that can be made in six month (8 hrs. per day * 20 hrs. per month) = 160 hrs. (10 phones per hour * 160 hrs. per month) = 960 phones 1,250 (1250 * 960 * 6) = 7,200,000 Based on these figures, the total supply for phones in these six months would be 7,600,000. The total supply according to the projected demand is 7,500,000 phones allowing a 100,000 surplus from the supply in these six months. Cost of Carrying inventory Month Forecast demand Total Phones produced Phones remaining Inventory Cost July 1,600,000 1,600,000 0 0 August 900,000 1,200,000 300,000 900,000 September 1,100,000 1,200,000 400,000 1,200,000 October 800,000 1,200,000 800,000 2,400,000 November 1,400,000 1,200,000 600,000 1,800,000 December 1,750,000 1,200,000 100,000 300,000 Total 7,500,000 Cost of Production Month Cost of producing phones Cost of employees Cost of inventory Total cost July 24,000,000 32,000,000 0 56000000 August 24,000,000 32,000,000 900,000 56900000 September 24,000,000 32,000 ...Download file to see next pagesRead More
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