BUS 305 Practice Exam 3 1) Assume the following time series data representing the number of sales per day your company’s employees make. Year-Quarter | t | Yt | 2001-1 | 1 | 17 | 2001-2 | 2 | 26 | 2001-3 | 3 | 21 | 2001-4 | 4 | 15 | 2002-1 | 5 | 19 | 2002-2 | 6 | 18 | 2002-3 | 7 | 21 | 2002-4 | 8 | 23 | a) Use Applet #16 to calculate the seasonal index numbers for the four quarters. b) Interpret what each of the four indices you computed in (a)
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FORECASTING METHODS Qualitative forecasting methods are based on educated opinions of appropriate persons 1. Delphi method: forecast is developed by a panel of experts who anonymously answer a series of questions; responses are fed back to panel members who then may change their original responses a- very time consuming and expensive b- new groupware makes this process much more feasible 2. Market research: panels‚ questionnaires‚ test markets‚ surveys‚ etc. 3. Product life-cycle analogy: forecasts
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[Other Resource] Why Forecast ? ․ To plan for the future by reducing uncertainty. ․ To anticipate and manage change. ․ To increase communication and integration of planning teams. ․ To anticipate inventory and capacity demands and manage lead times. ․ To project costs of operations into budgeting processes. ․ To improve competitiveness and productivity through decreased costs and improved delivery and responsiveness to customer needs. - 3 - Demand Forecasting. [Other Resource]
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groups tend to be more accurate than forecasts for individuals • Forecast accuracy declines as time horizon increases Elements of a Good Forecast • Timely • Accurate • Reliable (should work consistently) • Forecast expressed in meaningful units • Communicated in writing • Simple to understand and use Steps in Forecasting Process • Determine purpose of the forecast • Establish a time horizon • Select forecasting technique • Gather and analyze the appropriate data • Prepare the
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Chapter 1 Introduction to Operations Management True/False 1. Operations managers are responsible for assessing consumer wants and needs and selling and promoting the organization’s goods or services. Answer: False Page: 4 Difficulty: Easy 2. Often‚ the collective success or failure of companies’ operations functions will impact the ability of a nation to compete with other nations. Answer: True Page: 4 Difficulty: Easy 3. Companies are either producing
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risks of material misstatement of accounting estimates made in the current period financial statements. However‚ the review is not intended to call into question the judgments made in the prior periods that were based on information available at the time. A42 The auditor may judge that a more detailed review is required for those accounting estimates that were identified during the prior period audit as having high estimation uncertainty‚ or for those accounting estimates that have changed significantly
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Introduction Examples • Why forecast? • Why understand uncertainty of forecast? • What information to use in forecast? STAT 443: Forecasting Example: Accidental deaths Reza Ramezan Introduction Examples • Many examples are time series– forecast what happens in future • Example: monthly number of accidental deaths in USA- 1973-79 • Look at structure of data STAT 443: Forecasting Example: Accidental deaths
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Types of Forecasts: Judgmental Time Series Associative Models Judgmental Forecasts: Executive opinions Sales force Composite Consumer surveys Outside opinion Opinions of managers/staff Delphi technique Time Series Forecasts Level-Long-term “base” of the data Trend- long-term upward or downward movement in data Seasonability- short-term regular variations in data at constant time intervals Cyclicity- long term variations due to economic cycle Random variations- Caused by chance. Unpredictable-
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Index Cover Page 1 1. Executive Summary 3 2. Background 3 3. Issue Statement 4 4. Analysis of the problem 4-9 1. Moving Average 4-6 2. Holt Winters’ Exponential Smothing 6-7 3. Simple Average 7 3. Exponential Smothing 8-9 5. Recommandations 10 6. References 11 Executive Summary In the given case study‚ Snow the revenue manager of the Hamilton hotel has to make a decision which is to accept the group of not for 22nd August. As it is a business hotel and generally it
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PERENCANAAN & PENGENDALIAN PRODUKSI TIN 4113 Pertemuan 2 • Outline: – – – – – Karakteristik Peramalan Cakupan Peramalan Klasifikasi Peramalan Metode Forecast: Time Series Simple Time Series Models: • Moving Average (Simple & Weighted) • Referensi: – Smith‚ Spencer B.‚ Computer Based Production and Inventory Control‚ Prentice-Hall‚ 1989. – Tersine‚ Richard J.‚ Principles of Inventory and Materials Management‚ Prentice-Hall‚ 1994. – Pujawan‚ Demand Forecasting Lecture Note‚ IE-ITS‚ 2011
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