QUESTION 1 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 a. Using the following, forecast the sales for the months up to January the following year:- i. A simple three month moving average

QUESTION 1 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 a. Using the following, forecast the sales for the months up to January the following year:- i. A simple three month moving average

Contemporary Marketing

18th Edition

ISBN:9780357033777

Author:Louis E. Boone, David L. Kurtz

Publisher:Louis E. Boone, David L. Kurtz

Chapter14: Pricing Strategies

Section14.2: Forecasting Demand

Problem 1LO

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Under what conditions might a firm use multiple forecasting methods?
Trail Questions National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows: Month Sales ('000 units) Feb. 19 Mar. 18 Apr 15 May 20 Jun. 18 Jul. 22 Aug. 20 Forecast September sales volume using each of the following: (1) A linear trend equation. (2) A five-month moving average (3) Exponential smoothing with a smoothing constant equal to .20, assuming a March forecast of 19('000) (4) A weighted average using 0.60 for the most recent month, 0.30 for the next most recent, and 0.10 for the next.
q1(a)Imagine that you need to introduce a new gadget such as the Apple Watch. Determine which forecasting method is appropriate for projecting the future demand of such this gadget. b)ARIMA is mostly used to forecast future values using historical time series data, as we all know. Its primary use is in short-term forecasting with at least 38-40 historical data points and a small number of outliers. If we don't have at least 38 data points, we should consider using another strategy.
Question 1 ) The monthiy sales Of yamizí Battery company are asfollows:- Month Jales 2000 2100 1500 1400 1300 Calcuiate fore cost sales for June using each of the fo llowing method: - i) Naive Method 1M 3 Month Simple moving averoger Ti) Exponentral smoothing using an a =0:3 cand may forecast of 1600 units.
Q1) Forecasting is both art and science. Describe the situations where we use Qualitative forecasting techniques and quantitative forecasting techniques
4. The following data gives the number of battery sales by one of the leading automobile company over the period of last six months. Month Actual Battery Sales January February 39 44 March 40 April May 45 38 June 43 a. Forecast the sales for the month of July using a 3-week moving average method. b. Forecast the sales for the month of July using a 3-week weighted moving average, with weights of 0.5, 0.3 and 0.2. Using 0.5 for the most recent month. c. Compute the forecast for the month of July using exponential smoothing with a = 0.5. (Assume the forecast for January was 39 batteries) d. Compute the errors of the of the forecast based on calculation in c. с.
Tools View Week 3 Bonus Activity- DEMAND FORECASTING CASE STUDY After reviewing the forecasting demonstration and looking over the slides, complete the following case activity and transfer your answers to the appropriate questions in the Canvas activity quiz. You have been hired as a demand planning intern for Hawaiian Island Creations (HIC). They want you to de- velop a forecast for their HIC Papanui style of sun- glasses. The goal is to determine how many pair they will produce to meet retailer demand in July 2021. During your first meeting, you were handed some data to work with and the product team talked about the company's upcoming promotional blitz to support Summer Break '21 in major vacation destinations. Month Forecast Demand January 2021 4.000 3,300 February 2021 4,200 3,900 March 2021 4,500 4,300 April 2021 4.800 4,200 May 2021 5 000 5.400 of 4 P Type here to search 立

Q5) Monthly sales for a six month period are as follows: Month SalesJan 18,000Feb 22,000Mar 16,000Apr 18,000May 20,000June 24,000 Compute the sales forecast for July using the following approaches: (1) Four-month moving average; (2) Weighted three-month moving average using .50 for June, .30 for May and .20 for April;(3) Exponential smoothing with α (smoothing constant) equal to .40, assuming a February forecast of 18,000
Consider the following sales data for Bell, Inc. Month Sales ($ Millions) Jan. 10 Feb. 12 March 14 April 16 May 18 June 23 July 26 Aug. 31 Sept. 27 Oct. 18 Nov. 16 Dec. 14 a. Use a three-month weighted moving average to forecast the sales for the months April through December. Use weights of (3/6), (2/6), and (1/6), giving more weight to more recent data. b. Use exponential smoothing with α = 0.30 to forecast the sales for the months April through December. The forecast for January was $12 million. c. Compare the performance of the two methods by using the bias and MAD as the performance criteria. Which performance method is the most reasonable? Why?
QUESTION 2:The manager of YTL Computers wants to develop next year’s quarterly forecasts of salesrevenue for its brand laptops. The sales are seasonal and the company believes that thefollowing most recent eight quarters of sales should be representative of next year’ssales: Year Quarter Sales (millions of dollars) 1 1 9.2 1 2 5.4 1 3 4.3 1 4 14.1 2 1 10.3 2 2 6.4 2 3 5.4 2 4 16.0 Determine the forecast of next year’s quarterly sales revenue for this line of laptops.Show all your workings.
Q3) Discuss Qualitative forecasting technique. Explain the situations where we use Qualitative methods. Discuss Delphi forecasting method and its challenge.
Question 03 Suppose you sell stylish leather bags targeting young office going people who can use your bags to carry laptops and necessary stuff. You have already launched leather bags in February of this year and now based on the demand results of last 7 months, you want to predict the demand for your bags for the month of September. Hence, you want to select the right forecasting techniques and you are considering 2 period Moving Average, Naive technique and Exponential Smoothing (use any value between .10 - .15 as the value of alpha). Now figure out the better forecasting technique among 2 period Moving Average, Naive technique and Exponential Smoothing by doing the error calculation with the help of MAD, MSE, MAPE. Period Demand 2period Moving Average (Demand forecast) Naive technique (Demand forecast) Exponential Smoothing (Demand forecast) February 70 75 ** ** March 74 78 ** ** April 80 ** ** ** May 88 ** ** ** June…