...Forecasting Methods for Managers (3BUS0351): Semester B Multiple Choice In-Class Test - Question Paper This test comprises 30 questions on 6 Pages, including this page Instructions The time allowed for the test is 50 minutes. This is a CLOSED BOOK test. No notes or text books are allowed. A paper English dictionary and a university approved calculator may be used. Statistical Tables are not required If you leave the room during the test you may not re-enter. You may not leave within the last 5 minutes of the test On the Answer Sheet provided indicate your answer by circling whichever option A, B, C, D or E applies. There is ONE correct answer for each question. If you select more than one answer then you will receive zero marks for that question, even if one of the answers you have selected is correct. So select only one answer. There are 30 questions on this paper. Each correct answer will gain 1 mark. If you make a mistake, correct the mistake and make sure that your final choice of answer is clearly indicated. If your answer is not clear then marks cannot be awarded. At the end of the test hand your completed Answer Sheet and this Question Paper to the tutor. To prevent cheating, there are many different versions of the test being used. The only way we can tell which paper you have answered is if we receive your Question Sheet at the end of the test...
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... Slide Background Mix 3 4 5 6 7 8 9 10 2 Modeling Predictive Modeling Genius Forecasting Inventory Forecasting Simulations Modeling Decision Tree Conclusion Many companies and businesses use forecasting. Whether its to predict sales growth, consumer demand, profit or plan production, management wants to know how to proceed in making an informed decision about the future. This presentation will examine some of today’s most popular forecasting models by highlighting how leading companies are putting them to use. 3 Mix modeling – Marketing strategy Mix modeling can help with marketing strategies by measuring the potential value of all market input and marketing investments. The goal is a long-term revenue growth. Mix modeling’s multiple-regression technique is conducted based on the number of inputs and how these inputs relate to an outcome. The data that go into creating a marketing mix model includes: • Economic data • Industry data • Category data • Advertising data (including copy testing) Promotional data Competitive data Service data • Product data- Pricing data, Features & performance • Market outcome data- sales, revenue, profits Reference: http://www.decisionanalyst.com/Services/MarketingMixModeling.dai 4 Predictive Modeling for Consumer Demand forecast Predictive modeling is an effective forecasting model for consumer demand. The technique is based on accumulated data regarding consumer behavior. Within...
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...Broadly speaking, there are two approaches to demand forecasting. Survey method and Statistical method are further sub-divided into various methods. The former obtains information about the consumers’ intentions by conducting consumers’ interviews, through collecting experts’ opinions. The later using past experience as a guide and by extrapolating past statistical- relationships suggests the level of future demand. Survey methods are found appropriate for short term forecasting or demand estimation, while statistical methods are more suitable for long term demand forecasting or business and economic forecasting. Either of the methods may be used for forecasting demand for existing products, but the demand for new products, in the absence of any historical data, must be forecast through the survey method only. Under survey methods surveys are conducted about the consumers’ intentions, opinions of experts, survey of managerial plans, or of markets. Data obtained through these methods are analyzed, and forecasts on demand are made. These methods are generally used to make short-run forecast of demand. Survey methods are further sub-divided in to: Consumers’ Survey and Experts’ Opinion and Survey of Managerial Plans. A. Consumers’ Survey: Consumers’ survey involves direct interview of the potential consumers who are contacted by the interviewer and asked how much they would be willing to buy a given product at different prices. Consumers’ survey may take any form...
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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 because it weighs the most recent past data more strongly than more distant past data. This makes it so that 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 find this information very useful when examining the increased production of a product that appears to be in higher demand in recent times than past. Describe how a domestic fast food chain with plans for expanding into China would be able to use a forecasting model. By looking at the data of other companies the fast food chain would be able to put together a forecast to determine if their business venture was viable. They could examine the sales data and determine through a exponential smoothing forecast if it made sense for them to enter into the market. This would show the trends and changes in the data more recently rather than in past time. What is the difference between a causal model and a time- series model? Give an example of when each would be used. The time–series model is based on using historical data to predict future behavior. This method could be used by a retail store, fast food restaurant or clothing manufacturer to predict sales for an upcoming season change. The causal model uses a mathematical correlation...
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...Introduction to Management Science, 10e (Taylor) Chapter 15 Forecasting 1) A trend is a gradual, long-term, up or down movement of demand. Answer Diff: 1 Page Ref: 682 Main Heading: Forecasting Components Key words: trend, forecasting components 2) A seasonal pattern is an up-and-down repetitive movement within a trend occurring periodically. Answer Diff: 2 Page Ref: 682 Main Heading: Forecasting Components Key words: seasonal pattern, forecasting components 3) Random variations are movements that are not predictable and follow no pattern. Answer Diff: 2 Page Ref: 682 Main Heading: Forecasting Components Key words: random variations, forecasting components 4) The basic types of forecasting methods include time series, regression, and qualitative methods. Answer Diff: 2 Page Ref: 683 Main Heading: Forecasting Components Key words: types of forecasting methods 5) Time series is a category of statistical techniques that uses historical data to predict future behavior. Answer Diff: 1 Page Ref: 683 Main Heading: Forecasting Components Key words: time series analysis 6) Regression methods attempt to develop a mathematical relationship between the item being forecast and factors that cause it to behave the way it does. Answer Diff: 2 Page Ref: 683 Main Heading: Forecasting Components Key words: regression methods 7) Qualitative methods use management judgment, expertise, and opinion to make...
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...MEASURING FORECASTING ERROR (The students are advised to refer to the book under reference for details.) Because quantitative forecasting techniques frequently involve time series data, a mathematical notation is developed to refer to each specific time period. The letter Y will be used to denote a time series variable unless there is more than one variable involved. The time period associated with an observation is shown as a subscript. Thus Y1 refers to the value of the time series at time period t. The quarterly data for the Outboard Marine Corporation presented in Example 3.5 (see p. 73) would be denoted Y1 = 147.6,Y2 = 251.8, Y3 = 273.1, ... , Y52 = 281.4. Mathematical notation must also be developed for distinguishing between an actual value of time series and the forecast value. A^ (hat) will be placed above a value to indicate that it is being forecast. The forecast value for Yt is Yt^. The accuracy of a forecasting technique is frequently judged by comparing the original series Y1, Y2, ... with the series of forecast values Y^1, Y^ 2, .... Basic Forecasting Notation Basic forecasting notation is summarized as follows. Yt = value of time series at period t t = forecast value of Yt et = Yt - Yt^ = residual, or forecast error Several methods have been devised to summarize the errors generated by a particular forecasting technique. Most of these measures involve averaging some function of the difference between...
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...Forecasting Methods Genius forecasting - This method is based on a combination of intuition, insight, and luck. Psychics and crystal ball readers are the most extreme case of genius forecasting. Their forecasts are based exclusively on intuition. Science fiction writers have sometimes described new technologies with uncanny accuracy. There are many examples where men and women have been remarkable successful at predicting the future. There are also many examples of wrong forecasts. The weakness in genius forecasting is that its impossible to recognize a good forecast until the forecast has come to pass. Some psychic individuals are capable of producing consistently accurate forecasts. Mainstream science generally ignores this fact because the implications are simply to difficult to accept. Our current understanding of reality is not adequate to explain this phenomena. Trend extrapolation - These methods examine trends and cycles in historical data, and then use mathematical techniques to extrapolate to the future. The assumption of all these techniques is that the forces responsible for creating the past, will continue to operate in the future. This is often a valid assumption when forecasting short term horizons, but it falls short when creating medium and long term forecasts. The further out we attempt to forecast, the less certain we become of the forecast. The stability of the environment is the key factor in determining whether trend extrapolation is an appropriate forecasting...
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...CHAPTER SEVEN Discussion Questions 1. What role does forecasting play in the supply chain of a build-to-order manufacturer such as Dell? Although Dell builds to order, they obtain PC components in anticipation of customer orders and therefore they rely on forecasting. This forecast is used to predict future demand, which determines the quantity of each component needed to assemble a PC and the plant capacity required to perform the assembly. 2. How could Dell use collaborative forecasting with its suppliers to improve its supply chain? Collaborative forecasting requires all supply chain partners to share information regarding parameters that might affect demand, such as the timing and magnitude of promotions. Dell could share with their components suppliers all of the promotions, e.g., holiday, back-to-school, etc., they have planned. These suppliers could, in turn, notify their suppliers of discrete components that a spike in demand is anticipated. These demand forecasts for end items determine the demand for components and coupled with knowledge of fabrication times, allows all members of the supply chain to provide the right quantity at the right time to their customers. 3. What role does forecasting play in the supply chain of a mail order firm such as LL Bean? LL Bean has historically operated almost exclusively in a make-to-stock mode and with very few exceptions, stocked products that did not go out of style as rapidly as many other clothing...
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...PRODUCTION AND OPERATIONS MANAGEMENT BUS3020 COURSE CONTENT WEEK THREE TOPIC: FORECASTING • Different Methods of Forecasting – Formal and Informal, • Qualitative and Quantitative Methods • Causal methods auto projection methods of forecasting. What is forecasting? Forecasting is the art and science of predicting future events. As a science it uses historical data and projects them into the future using mathematical models. As an art it uses intuition or judgment to predict the future. Why forecast? Done to minimize uncertainty and evaluate risk relating to future events caused by dynamism of the environment within which organizations operate. Such dynamisms includes: a) Changes in legislation b) Stiff competition c) Demographic changes. Forecasting is important for planning and control of functional areas such as; marketing, finance, operations e.t.c.In the public sector, forecasts are used to plan on: Health, Education, Social services e.t.c. Types of forecasts • Demand forecasts – projections of demand for a company’s products or services. • Economic forecasts – predicts inflation rates, money supplies e.t.c • Technological forecasts.- concerned with the rate of technological progress. Forecasting Horizons a) Short – range forecasts: Covers from a few days to 6 months. It concerns issues like purchase forecasts, job scheduling, workforce levels, job assignments, production levels e.t.c. b) Medium range forecasts: Covers usually from 3 months...
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...Questions: 1,7, and 15 1: (a) What is forecasting? Why is it so important in the management of business firms and other enterprises? (b) What are the different types of forecasting? (c) How can the firm determine the most suitable forecasting method to use? a) Forecasting is used to try and predict the economic activity of a firm’s future. It aims to reduce risk/uncertainty that is faced in the short-term operational decision making. It is also used to plan for the firm’s long-term growth. Forecasting helps make decisions by using macroforecasts of the general economic activity as inputs for their microforecasts of the industry’s and firm’s demand and sales. Forecasting helps decide a firm’s marketing strategy, production needs, sales forecast, and helps predict financial needs such as cash flow, profits, and outside financing. Furthermore, it helps make personal based decisions, as well as assist for the long-term future of the firm (Salvatore, 2012). b) Forcasting types range from expensive to inexpensive, as well as simple to complex. Forecasting techniques can be qualitative, and others can be quantitative. Salvatore focuses on qualitative forecasts. These forecasts include: time-series, smoothing techniques (moving averages), barometric forecasts with leading indicators, econometric forecasts, and input-output forecasts. c) A firm determines the most suitable forecasting method to use by using the following criterion: ...
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...CASE Merriwell Bag Company Merriwell Bag Company is a small, family owned corporation located in Seattle, Washington. The stock of the company is equally divided among five members of the Merriwell family (husband, wife, and three sons), but the acknowledged leader is the founder and patriarch, Ed Merriwell. Ed Merriwell formed the company 20 years ago when he resigned as a mill supervisor for a large paper manufacturer. Ironically, the same manufacturer formed a container division five years ago and is presently one of Merriwell’s competitors. Company Strategy The family attributes the success of Merriwell Bag Company to the fact that it has found a market niche and has no “serious” competition. Merriwell supplies stock bags to many small chain stores scattered over a wide geographical area. It ships the bags directly to small regional warehouses or drop ships directly to the individual stores. The family reasons that the large bag manufacturers cannot profitably provide service to accounts on that small of a scale. In fact, Ed Merriwell formed the business with one second-hand bagging machine to provide bags for a small discount store chain and a regional chain of drug stores. These two organizations have grown tremendously over the years, and Ed Merriwell proudly points out that the Bag Company has grown with them. Today, these two original clients are Merriwell’s largest customers. The Merriwell family does not want its business to be too...
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...Study Guide for Chapter 5: 1. What does the acronym CPFR represent? a. | Coordinated planning and forecasting relationships | b. | Collaborative planning, forecasting, and replenishment | c. | Centralized purchasing and forecasting relationships | d. | Collaborative purchasing, forecasting, and receivables | 2. Some measures of forecasting accuracy include mean absolute deviation, mean absolute percentage error, and mean squared error. The formula for each is dependent on the forecast error, which is calculated by using the equation: a. | Actual demand for period t divided by the forecasted demand for period t | b. | Actual demand for period t plus the forecasted demand for period t | c. | Actual demand for period t minus the forecasted demand for period t | d. | The average of Actual demand for period t and forecasted demand for period t | Data Set E1 Period | Sales Volume | 1 | 10000 | 2 | 12400 | 3 | 14250 | 4 | 15750 | 5 | 20500 | 6 | 18500 | 7 | 15750 | 8 | 20500 | 9 | 21500 | 10 | 22550 | 3. Using Data Set E1, what would be the forecast for period 7 using a four period moving average: (Choose the closest answer.) a. | 17625 | b. | 15225 | c. | 15300 | d. | 17250 | 4. Using Data Set E1, what would be the forecast for period 6 using a five period weighted moving average? The weights for each period are 0.05, 0.10, 0.20, 0.30, and 0.35 from the oldest period to the most recent period, respectively...
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...Distribution and Channel Management MT211 The main aim of my essay is to show my understanding of the main principles and concepts of distribution and channel management through the use of notes on Moodle, information I gathered from attending lectures and also from literature that I have read on this topic. The Supply Chain is the sequence of suppliers that contribute to the creation and delivery of a good or service to end customers, meanwhile Supply Chain Management is organizing the cost effective flow and storage of materials, in-process inventory, finished goods and related information from point of origin to point of consumption to satisfy customer requirements. A major element of the supply chain is the use of logistics which is the management of the storage and flow of goods, services and information throughout your organisation. Logistics can be broken down into three major elements, Firstly, materials management which is the sourcing and receiving of raw materials or unfinished products for subsequent use. Secondly, material flow system which can be defined as the ability to locate and schedule material through to end production and disposition, and finally the physical distribution which is the delivery of finished goods to customers. The main aim of a supply chain management is to evolve a company’s supply chain into an optimally efficient, customer-satisfying process, where the effectiveness of the whole supply chain is more important than the effectiveness of...
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...The Accuracy of Demand Forecasting Between Point of Sale and Order History Supply Chain Management TBS908 Table of Contents 1. Executive Summary 4 2. Company Profile 4 3. Demand 5 3.1 Demand Forecasting 6 3.2 Demand Forecasting Methods 6 3.2.1 Opinion Polling / Qualitative Method (subjective): 6 3.2.2 Statistical Methods/Quantitative Approach (objective): 6 4. Order History Vs. Point-of-sale 8 5. Planning Promotions 8 5.1 Promotion Planning and Supply Chain Contracting in a High-Low Pricing Environment 9 5.1.1 Basic Household Inventory Model: 9 6. Types of demand forecast in GCC and UAE 10 7. Objective 10 8. Methodology 11 Table 3 13 Figure 1 13 9. Result 14 10. Recommendations 14 11. Conclusion: 15 11. References 16 12. Appendixes 17 Appendix I 17 Appendix II 19 1. Executive Summary Demand forecasting is essentially anticipating future prospects by reviewing historical data in the most calculated way in an uncontrollable environment. Foreseeing what and when buyers will purchase has never been a simple procedure for producers or retailers. Troubled by the overwhelming undertaking of correctly coordinating supply with interest, makers are always enhancing procedures to accomplish the most noteworthy estimate exactness that will guarantee when the customer enters a store, the item they are searching for is on the rack. This is getting significantly tricky as the uncertainty level increase. In the below report the demand...
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...ForecastX Software (There will be additional ForecastX notes for subsequent chapters) 1. Insert disk and install a. Note: you will have to do this every time you use a campus computer, but the process should only take a minute or two. b. Insert disk. If a McGraw Hill screen pops up, just agree to what it is asking you, and then reduce the window. c. Double click on “My computer” d. Select (click once on) cdrom drive (or whatever the listing is for the drive into which you have inserted your disk), right click over the shaded area, select “open” from the menu, click on “forecast x installer”, click on “setup.exe” (You may find there are two “setup” files, if so, choose the top one, but try the bottom one if the top one doesn’t work.) 2. Add in the forecast x add-in. a. Open excel b. Click on the following: File, options, add-ins. You should see “Forecastx7Toolbar” underneath “Active Application Add-Ins”. To make sure that ForcastX is installed, click on “go” at the bottom of the page, and make sure that there is a check in the check box next to ForecastX in the pop up box that appears, then click on OK. Then close out of Excel, and reopen Excel. You should find ForecastX when you select the Add-Ins bar at the top of the page. c. If you do not see ForecastX in the pop up box, click ok and close Excel. Then close Excel and do step 2b again. If you still do not see ForecastX in the pop up box, Click on...
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