Integrated Planning – Module 2 1 Agenda • Forecasting‚ • Factors influencing Demand • Basic Demand Patterns • Basic Principles of Forecasting • Principles of Data Collection • Basic Forecasting Techniques‚ Seasonality • Sources & Types of Forecasting Errors Forecasting can be conducted at various levels Strategic Required for • Product life cycle • Long-term capacity planning • Capital asset/equipment/ human resource management Examples • Product line transitions • Annual volume out
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demand. The frequency distribution of historical errors is then compiled across items‚ for new and never out items separately‚ to form a probability distribution. The probability distribution is then used to predict errors for the future. The second step involves calculating the contribution margin if the unit is demanded and the loss if the unit has to be calculated. This is done to calculate the critical fractile for the demand which can be calculated by Gain/ (Gain+ Loss). The critical fractile
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Marriott Rooms Forecasting Executive Summary In the case of the Hamilton hotel‚ Snow needs to make a decision as to if 60 additional rooms reservations should be accepted which could lead to overbooking (Weatherford & Bodily‚1990). It is a problem of capacity utilization that is being faced in this particular case where revenue maximization is aimed while minimizing customer dissatisfaction. In this report the case is put forward and various methods have been chosen to come to a sensible conclusion
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WEATHER ANALYSIS & FORECASTING ** Weather Analysis: process of collecting‚ compiling‚ analyzing and transmitting the observational data of atmospheric conditions *this data & analysis is then used to forecast future weather conditions * Types of data: * Each weather station‚ 10‚000 around the world‚ collects the same data at the same time‚ at least 4 times per day(0000‚ 0600‚1200‚ 1800 GMT) * Most US stations also collect data continuously or at least every hour
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Forecasting "Best Practices" "Effective demand planning and sales forecasting across the supply chain can bring a host of benefits. Specifically‚ it can help improve labor productivity‚ reduce head count‚ cut inventories‚ and speed up production flows‚ and increase revenues and profits. -Edward J. Marien To find the "best practices" for forecasting‚ our team researched many cases of forecasting success‚ and found five companies with a common theme. Rayovac‚ the Coca-Cola Bottling Company
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Forecasting: The McDonald ’s Way McDonald’s is a well-known worldwide franchise and has been around since the 1950s. Serving customers for over 50 years successfully entails a strong inventory and operations management system. “McDonald ’s is the world ’s #1 fast-food company by sales‚ with more than 33‚500 restaurants serving burgers and fries in 119 countries” (University of Phoenix [UOP]‚ 2012‚ p. 2). To maintain and continue a successful franchise operation‚ quality food items‚ and highly successful
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tactics implemented by management in order to become more competitive and world-class in their operations. Hard Rock Café has clearly made great strides in modernizing their business venue by utilizing sophisticated POS systems with the latest forecasting trends. Some tactics they have implemented include an extensive Point-of-sale system (POS)‚ which captures transaction data on nearly every person who walks through a cafe’s door. The sale of each entrée represents one customer. They forecast monthly
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UNIT 6 DEMAND ESTIMATION AND FORECASTING Objectives By studying this unit‚ you should be able to: identify a wide range of demand estimation and forecasting methods; apply these methods and to understand the meaning of the results; understand the nature of a demand function; identify the strengths and weaknesses of the different methods; understand that demand estimation and forecasting is about minimising risk. Structure 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 Introduction Estimating Demand Using
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Case Forecasting Beer Demand at Anadolu Efes Murat Köksalan Department of Industrial Engineering‚ Middle East Technical University‚ Ankara 06531‚ Turkey koksalan@ie.metu.edu.tr Selin Özpeynirci ˙ ˙ Department of Industrial Systems Engineering‚ Izmir University of Economics‚ Izmir 35330‚ Turkey‚ selin.ozpeynirci@ieu.edu.tr Haldun Süral Department of Industrial Engineering‚ Middle East Technical University‚ Ankara 06531‚ Turkey sural@ie.metu.edu.tr Key words: forecasting; regression
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CHAPTER 1 INTRODUCTION Demand forecasting refers to the prediction or estimation of a future situation under given constraints. Demand Forecasting is the activity of estimating the quantity of a product or service that consumers will purchase. Demand forecasting involves techniques including both informal methods‚ such as educated guesses‚ and quantitative methods‚ such as the use of historical sales data or current data from test markets. Demand forecasting may be used in making pricing decisions
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