...MBA 643-17 April - May 2015 Problem-Solving Skills Assignment One Texas State sales Tax Forecasting Due Date May 22, 2015 A major source of revenue in Texas is a state sales tax on certain types of goods and services. Data are compiled and the state controller uses them to project future revenues for the state budget. One particular category of goods is classified as Retail Trade. Four years of quarterly data (in millions) for one particular area of southeast Texas follows. Quarter | YEAR 1 | YEAR 2 | YEAR 3 | YEAR 4 | 1 | 218 | 225 | 234 | 250 | 2 | 247 | 254 | 265 | 283 | 3 | 245 | 255 | 264 | 289 | 4 | 292 | 299 | 327 | 356 | 1. Compute seasonal indices for each quarter for year 5 based on CMA. Seasonal indices can be calculated using this formula: (sum of average value for Qx divided by number of data). Therefore seasonal indices for quarters in year five will be: Q1 = (88.148 + 88.51 + 87.98)/3 = 88.21% Q2 = (98.68 + 98.51 + 97.29)/3 = 98.16% Q3 = (97.46 + 98.31 + 96.17)/3 = 97.31% Q4 = (115.35 + 114.17 + 117.30)/3 = 115.6% 2. Deseasonalize the data and develop a trend line of the deseasonalized data. Quarter | Sales | Index | Deseasonalised data | 1 | 218 | 0.8821 | 247.1 | 2 | 247 | 0.9816 | 251.6 | 3 | 245 | 0.9716 | 252.2 | 4 | 292 | 1.1561 | 252.6 | 5 | 225 | 0.8821 | 255.1 | 6 | 254 | 0.9816 | 258.8 | 7 | 255 | 0.9716 | 262.5 | 8 | 299 | 1.1561 | 258.6 | 9 | 234 | 0.8821 | 265.3 | 10 | 265 | 0.9816 | 270...
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...analysis………………………………………5 2.1 What is sales forecasting……………….……………………………...5 2.2 Importance of forecasting in a new B2C business………….…………5 2.3 What affects sales forecasting?..............................................................6 2.4 Techniques of sales forecasting…………………….…………………7 2.4.1 Judgmental methods……………………………………….7 2.4.2 Counting methods………………………………………….8 2.4.3 Newer methods…………………………………………….8 2.5 Adapting forecasting to the company……………………………………...9 3. Conclusion……………………………………………………………….….9 References…………………………….………………………………………10 LIST OF FIGURES Figure 1: Elements of sales forecasting………………………………………………………………..7 Figure 2: Forecasting techniques used in practice …………………………………………………….8 1. Introduction This report discusses the importance of sales forecasting to the entrepreneurial start-up firm in B2C market. The previous assignment discussed the case study on the new set up business related to food industry. The business idea was to create a website and a mobile application that allows office people to order healthy food by choosing every ingredient to suit their personal taste. The concept is quite new to the market so the management has to look into the future sales by implementing sales forecasting. So, the aim and objectives of this report are as follows: Aim: · To discuss why sales forecasting is important to the entrepreneurial start-up business in B2C Objectives: * To explain the nature of forecasting and the importance of...
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...Forecasting Project House Sales in USA Presented by: Michelle Deets Ravin Seju Ankan Sinha March 7, 2016 Professor Dawit Zerom ISDS 526 Executive Summary The data in the report “Monthly total houses sold in the United States for the period January 1978 through July 2007” is time series data representing sales in thousands of units. The data has not been seasonally adjusted. Our project was to produce forecasts of housing sales by creating a model using Forecast Pro’s Expert Selection Method. The model was generated by withholding 2 years of data and creating a forecast based upon the data from January 1978 to July 2005. We provided fit measures based upon MAPE and RMSE and evaluated the model’s accuracy MAPE, RMSE, and GMRAE from Forecast Pro’s out-of-sample statistic evaluation table. The MAPE numbers show that the forecast expands from a 7.95% error at the beginning of the holdout period and quickly grows to 32% error within 24 months. The acceptability of this error depends upon which managers are using it. The housing industry touches many fields, from moving to painting to construction to land purchases. This large of an error might could be unacceptable given the amount of risk and resources involved in construction of new single family homes; a manager might prefer to only use the first 6 months of forecasted data to stay within a 10% error range. Looking at the results of the forecast’s graph, the actual data (Exhibit A, represented by the...
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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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...easily, such as how long a trip would last or how many people were coming. Some things, however, needed a forecast. Was it likely to rain? What would we do if it did rain? The best plans had two essential ingredients: First, everyone worked to the same plan; second, all pertinent information was included in that plan. In the business world, there are many methods of forecasting product demand, and they must include all known information. Extrinsic forecasting methods involve factors such as economic conditions, market trends, competition, government regulations, or the sale of related goods. These techniques look for patterns or correlations linking product demand with these outside factors. Qualitative forecasting techniques most often are used for extrinsic forecasting. They are employed by senior managers and involve using good judgment, intuition, and informal opinions. Qualitative forecasting is necessary for products where no previous sales data exist. Intrinsic forecasting, on the other hand, uses data from previous sales, and the forecast is developed using that sales history. This quantitative forecasting is done by most members of a supply chain, especially those near the final consumer. Many factors can be included in the forecast along with traditional methods to improve forecast reliability. Principle 2: Forecasts must include some measure of error. The forecast is going to be wrong—but by how much? Estimates of forecast error can be made by studying past performance...
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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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...Sample questions 1. Time-series forecasting models: a. | are useful whenever changes occur rapidly and wildly | b. | are more effective in making long-run forecasts than short-run forecasts | c. | are based solely on historical observations of the values of the variable being forecasted | d. | attempt to explain the underlying causal relationships which produce the observed outcome | e. | none of the above | 2. The forecasting technique which attempts to forecast short-run changes and makes use of economic indicators known as leading, coincident or lagging indicators is known as: a. | econometric technique | b. | time-series forecasting | c. | opinion polling | d. | barometric technique | e. | judgment forecasting | 3. The use of quarterly data to develop the forecasting model Yt = a +bYt1 is an example of which forecasting technique? a. | Barometric forecasting | b. | Time-series forecasting | c. | Survey and opinion | d. | Econometric methods based on an understanding of the underlying economic variables involved | e. | Input-output analysis | 4. The variation in an economic time-series which is caused by major expansions or contractions usually of greater than a year in duration is known as: a. | secular trend | b. | cyclical variation | c. | seasonal effect | d. | unpredictable random factor | e. | none of the above | 5. The type of economic indicator that can best be used for business forecasting is the: a. | leading indicator |...
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...TOPIC 1. FUNDAMENTALS OF ECONOMIC FORECASTING TOPIC I TOPIC I. FUNDAMENTALS OF ECONOMIC FORECASTING Contents 1. Meaning of forecasting 2. Features, importance and limitations of forecasting 3. Forecast types 1. Meaning of forecasting Forecast is a likely, scientifically well-grounded opinion about the possible state of the events, objects or processes in the future. Forecasting is a process of making statements about events whose actual outcomes (typically) have not yet been observed. Forecasting is a process of predicting or estimating the future based on past and present data. Economic Forecasting is a process of making forecasts based on analysis of past trends and regularities of the economic processes. Economic forecasts can be carried out at a high level of aggregation – for example for GDP, inflation, unemployment or the fiscal deficit – or at a more disaggregated level, for specific sectors of the economy or even specific companies. Economic forecasting provides information about the potential future events and their consequences for the organization. It may not reduce the complications and uncertainty of the future. However, it increases the confidence of the management to make important decisions. Economic forecasting includes the following steps: 1. Identifying items to be forecast. The items of socio-economic forecasting are the economic processes (for example, inflation, demand, supply), any indicator describing the company activity (for example...
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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...
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...Forecasting: Relying On The Unknown http://www.manufacturing.net/articles/2007/10/forecasting-relying-on-the-unknown September 23, 2007 was the autumnal equinox — the official end of summer. The leaves are beginning to turn colors and the seasons are changing. For some manufacturers, the end of summer could be the end of a busy season, or it could just be the beginning. If you manufacture beach towels or Christmas trees, you’re locked into seasonal demand. How do you adjust your operations to handle your peak time? How much of a peak period will you have? How much capacity will you need? What will be your inventory storage and holding costs? Factors and Consequences There is a lot of variability when it comes to demand — consumer tastes may change, competition could increase, weather patterns could change, etc. “The farther away in time a forecast is from the sales it projects, the less accurate the forecast will be. This stands to reason that the longer the horizon, the more changes will take place between the forecast and the actual sales,” said Jane Lee, Vice President of Supply Chain, Supply Chain Consultants. “Picture a company that makes orange juice,” said Jim LeSage, Executive Vice President with The Facility Group. “They may be producing more at the start of the school year or during cold and flu season, but the oranges are only harvested at a certain time.” That leaves the orange juice company with few options, LeSage explains. The company...
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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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...SUBJECT: Forecasting and Sales for our Widget Manufacturing line As we have discussed earlier in the day, we have a 60 % accuracy with our sales forecast rate and we are reviewing ways to close the gap between 60% and 100%. In this memo I have written out what our current outlook looks like from the beginning to end of our production cycle and what forecasting methods I believe we can use to improve forecasting accuracy. Our current process: Components Vendor C On Site in Factory Vendor A Vendor B Steel for Widget takes 4 weeks Widget is made 1 week Plastic cover 3 weeks Card Board shipping box 4 weeks Packaging Packaging Department Shipping Receives the covers and applies them and puts the product in the packaging takes 1 day Shipping takes 3 Weeks Time Stamp: The customer places his order on 01/01/2015 and does not need it to be at his business until 03/31/2015. 01/01/2015 Customer places order 02/02/2015 Steel for the Widgets is ordered 01/09/2015 Ordered Card Board Shipping boxes 01/09/2015 Ordered Plastic covers 03/02/2015 Make the widgets 03/09/2015 • widgets are finished, • plastic covers come in • boxes come in, • apply boxes and plastic covers to the widgets • prepare to ship 03/10/2015 Ship Widgets to customer 03/31/2015 Customer receives the widgets The Steel was ordered in early February and planned to be at the Manufacturing plant in time to complete the widget assembly for the beginning of the second week in March. Packaging and shipping...
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...packaged goods. There are no magical algorithms, forecasting tools, or proprietary process solutions that offer much more than a "like as" or analog-based planning solution. The companies that do the best job in forecasting new ¡Hnáucts work the details in a methodical way, challenge underlying assumptions, and examine all available data to givei: PATRICK BOWER Mr. Bower is Senior Director of Corporate Planning & Customer Service at Combe Incorporated, producer of high-quality personal care products. He is a frequent writer and speaker on supply chain subjects, and is a self-professed "S&OP geek." Prior to Combe, he was with a consulting firm where he worked for clients such as Diageo, Bayer, Glaxo Smith Kline, Pfizer, Foster Farms, Farley's and Sather, Cabot Industries, and American Girl. His experience also includes employment at Cadbury, Kraft Foods, Unisys, and Snapple. He has been twice recognized as a "Pro to Know" by Supply atid Detnand Chain Executive magazine. He is also the recipient of the IBF 2012 award for "Excellence in Business Forecasting & Planning." His expertise includes S&OP, demand planning, inventory, network optimization, and production scheduling. Copyright ©2013 Journal of Business Forecasting 1 All Rights Reserved I Winter 2012-2013 ne of the toughest demand planning tasks is forei goods world. Why? First, we don't really have good math tg^nnelp us. It would be great if there were a forecasting algorithm that reads consurriefs'' minds, but there...
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...NOVA SOUTHEASTERN UNIVERSITY The Wayne Huizenga Graduate School of Business and Entrepreneurship-Master's ProgramS Assignment for Course: QNT 5040- Business Modeling Submitted to: Dr. Tom Griffin Submitted by: Prince A. Storr ps44@nova.edu Date of Course Meeting: November 18, 2011 Date of Submission: November 18, 2011 Title of Assignment: Greaves Brewery: 10 Month Forecasting CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and any assistance that I received in its preparation is fully acknowledged and disclosed in the paper. I have also cited any sources from which I used data, ideas, or words, either quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course. Student Signature: Prince A Storr Instructor(s Grade on Assignment: Instructor(s Comments: Greaves Brewery: Ten Month Sales Forecasting Case Synopsis Alex Benson, purchasing manager for Greaves Brewery in Trinidad was faced with a dilemma in early 2004. He encountered difficulty in forecasting sales for 2004; particularly because of the 2003 slump, government excise taxes and other factors such as decreased numbers in both tourist arrivals to the Caribbean island and beer exports to the U.S. As purchasing manager, Benson’s prime responsibility was maintaining adequate inventory levels for all goods and materials used in the company’s production processes, including the purchase of new bottles and...
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...leader is manufacturing plastic with customers which “include automotive parts manufacturers, aircraft manufacturers, the Department of Defense, beverage makers and bottlers, and appliance manufacturers”(Riordan, 2005.) A review of Riordan Manufacturing will include the company’s manufacturing strategy, process flow chart for the electric fan supply, metrics to evaluate the electric supply chain, and how the supplier relationship and the effects on the supply chain. Additionally, the review will also explain the lean production schedule, forecasting techniques, aggregate production plan, master schedule, and materials requirement schedule. Riordan Manufacturing Strategy The manufacturing strategy which best fits Riordan’s manufacturing strategy is a stable workforce. Stable workforce is the best manufacturing strategy because “it schedules production of fans to meet the forecasted sales and the forecast is calculated by taking the average of sales for the last three years and extrapolating it into the next year” (Riordan, 2005). Another indication can be found in the employee turnover report for 2009-2012. The percentage of involuntary separations decreased from 3.4% in 2009 to 2.0% in 2012. The decrease in involuntary turnovers indicates maintenance of a stable workforce. The stability of the workforce benefits the company because “this strategy provides workforce continuity and avoids many of the emotional and tangible costs of hiring and firing associated with the chase strategy”...
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