Altavox Excel Data (1) Week 1 2 3 4 5 6 7 8 9 10 11 12 13 Average Atlanta 33 45 37 38 55 30 18 58 47 37 23 55 40 40 Boston 26 35 41 40 46 48 55 18 62 44 30 45 50 42 Chicago 44 34 22 55 48 72 62 28 27 95 35 45 47 47 Dallas 27 42 35 40 51 64 70 65 55 43 38 47 42 48 Los Angles 32 43 54 40 46 74 40 35 45 38 48 56 50 46 Total 162 199 189 213 246 288 245 204 236 257 174 248 229 222 Altavox Data (2) Week -5 -4 -3 -2 -1 Atlanta 45 38 30 58 37 Boston 62 18 48 40 35 Chicago 62 22 72 44 48
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Eight Steps to Forecasting • Determine the use of the forecast □ What objective are we trying to obtain? • Select the items to be forecast • Determine the time horizon of the forecast □ Short time horizon – 1 to 30 days □ Medium time horizon – 1 to 12 months □ Long time horizon – more than 1 year • Select the forecasting model(s) |Description |Qualitative Approach |Quantitative Approach
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predictions of automobile sales in the US for the month of March 2012. The prediction is to take into account the historic data (provided) and current marketing environment. At first‚ two approaches of the analytical (quantitative) method were used – moving average and exponential smoothing. The objective of doing so was to get an idea of the prediction based on historic data only. Once that was done‚ the marketing environment was taken into consideration - to see how it would effect the predictions made
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DEMAND FORECASTING Demand forecasting is the process of predicting future average sales on the basis of historical data samples and market intelligence. The volatility of demand from an average level is supplied from the safety inventory. Any forecast is likely to be wrong‚ so the focus should be on understanding the range of potential forecast errors and the level of safety inventory that will cater for peak demand. An important additional calculation is forecast bias. This is the cumulative
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5 310 June 6 175 July 7 155 Aug 8 130 Sept 9 220 Oct 10 277.5 Nov 11 235 Dec 12 1. 3 Month Moving Averages: The forecast for April is average of Jan‚ Feb and Mar shipments‚ =(200+135+195)/3‚ enter D5=SUM(C2:C4)/3 in EXCEL file. Copy and paste this column. So‚ forecast for Dec. shipments is 244.17 2. Similarly‚ for Five Month Average will be E7=SUM(C2:C6)/5= 207.4; copy and paste the formula till the end. So‚ forecast for Dec is 203.50 3. EXPONENTIAL
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have risen by a high number of 40% over a two year period and are unpredictable‚ an exponential smoothing method would be most appropriate. This method weights highest on the most recent years sales history. For the detergent intermediates‚ a moving average method would be most appropriate because sales have been stable overall in the past years. There is no need to give the most recent periods a higher weight of importance. For the specialty chemicals division‚ it would be most effective to complete
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Littlefield Technologies Game Strategy- Group 28 I. PROJECT MANAGEMENT: We can apply multiple project management concepts to planning the project‚ scheduling the project‚ and controlling the project. First‚ the project was planned and scheduled by setting a goal of completion. Considering the group’s total allotted time‚ our goal was to have the description of the game strategy completed 48 hours before the deadline‚ and to work collaboratively on the statistical spreadsheet 24 hours before the
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Executive Summary Dumitri Mironescu is the owner of a limousine company in Las Vegas which currently consists of 17 vehicles. During the year of 2012‚ Dumitru decided that it was time to replace three of the company’s 17 vehicles. In addition‚ Dumitru wanted to add two new vehicles to his fleet of limousines. Dumitru submitted a business plan to the bank to finance his purchases. After reviewing his business plan‚ the bank was not comfortable with the company’s revenue forecast and needed further
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ending with week 11‚ forecast registration using a two-week moving average. Moving Average Forecast Ft = ie F3 = = = 21.5. Carrying this down the table through to week 11 gives: Week 1 2 3 4 5 6 7 8 9 10 11 Registrations 22 21 25 27 35 29 33 37 41 37 Forecast 21.5 23 26 31 32 31 35 39 39 (3 marks) c) Starting with week 5 and ending with week 11‚ forecast registrations using a four-week moving average. Moving Average Forecast Ft = ie F5 = = = 23.75. Carrying this down the
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Choose one of the forecasting methods and explain the rationale behind using it in real life. I would choose to use the exponential smoothing forecast method. Exponential smoothing method is an average method that reacts more strongly to recent changes in demand than to more distant past data. Using this data will show how the forecast will react more strongly to immediate changes in the data. This is good to examine when dealing with seasonal patterns and trends that may be taking place. I would
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