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- Under what conditions might a firm use multiple forecasting methods?The following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LOA newly operated company producing household items would want to forecast its sales volume for the next month. It has been in operation for ten (10) months now. For the past ten (10) months, forecast and sales data for its top selling Item A are as follow: Time Period Forecasted Value Actual Sales (Quantity) 10th month 405 345 9th month 400 380 8th month 410 400 7th month 370 375 6th month 330 360 5th month 320 325 4th month 320 315 3rd month 305 300 2nd month 290 295 1st month 300 280 The operations manager observes the fluctuations on the sales quantity over the 10-month period that the company is in operation. To forecast for the 11th month, the team decided to evaluate options on what forecasting method to use. Their options are: To use the Moving Average Method using the sales data for the past 10 months, To use the Exponential Smoothing Average assigning a smoothing constant of .6 and To use the Trend-adjusted Exponential Smoothing assigning smoothing constants α =…
- Which type of analytics is used to know the effect of product price on sales. OA) predictive OB) forecast C) prescriptive D) descriptiveFollowing data on the demand for sewing machines manufactured by Taylor and Son Co. have been compiled for the past 10 years. Year 1971 1972 1973 1974 1975 78 1976 1977 1978 1979 99 1980 106 Demand 58 65 73 76 87 88 93 in (1000 units) Please estimate the value of demand for next 3 years using trend analysis.The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES 1 215 2 240 3 205 4 190 5 160 6 195 7 150 8 140 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to 1 decimal place.
- A company has the following demand history by seasons over a two-year period. The production planner deseasonalizes the data first. Then, using the exponential smoothing method with a = 0.30 and F= 80, she forecasts the demand for the first season of 2021. Finally, the planner reseasonalizes her forecast. What is her final forecast for the first season of 2021? 2019 2020 Season 1 84 88 Season 2 76 71 Season 3 93 97 Season 4 46 51 Season 5 77 73 O a. 87.50 O b. 77.57 Oc. 79.87 O d. 75.98 O e. 86.43Smart Phone covers sales for the past 12 months is given below. Management forecast's for the months of March, April, May, and June are listed Month Unit Sales Management's Forecast Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 100 95 95 112 126 118 95 85 101 94 89 110 122 114 108 112 a) What is the MAD for the forecast developed by management sales (round your response to two decimal places) What in the MAPE for the forecast developed by management % (round your response to two decimal places). %3D1) Describe a scenario that you have encountered recently as a consumer where a business has either under forecast or iver forecast demand for a product that you were planning to purchase. You will generally notice under forecasting if the product is out of stock or over forecasting if there is excess inventory for the item. Describe the imolications to the retailer,manufacturer, and broader supply chain. You can present your response through thr lens of your own discpline (accounting,mafketing,etc.) if you wish. 2) Give three examples from your life in which you may forecast the future. Highlight the importance of accurate forecasting in the three examples you provide.
- The number of patients coming to the Healthy Start Maternity clinic has been increasing steadily over the past eight months. You are provided with some historical data as follows:Month Clinic attendance (in thousands) 1 3.42 3.93 4.54 5.05 5.86 5.97 6.58 6.7a. Identify and give a brief explanation of the:-i. Dependent variableii. Independent variable b. Use simple linear regression to forecast annual demand for months 9 and 10 by using the tabular method to:-i. Derive the values for the intercept and slope. ii. Derive the linear regression equation.iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.The following equation summarizes the trend portion of quarterly sales of condominiums over a long cycle. Sales also exhibit seasonal variations. Using the information given, prepare a forecast of sales for each quarter of next year (not this year), and the first quarter of the year following that.Ft = 40 – 6.5t + 2t2whereFt = UnitSales t = 0 at, the first quarter of last yearQuarter Relative1 1.12 1.03 .64 1.3Please answer parts i, ii and iii of the below question. The table below shows the sales figures for a brand of shoe over the last 12 months. Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 Using the following, forecast the sales for the months up to January the following year:- i) A simple three month moving average. ii) A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. iii) Exponential Smoothing when α= .6 and the forecast for March is 350.