Manager’s Guide to Forecasting by David M. Georgoff and Robert G. Murdick Harvard Business Review Reprint 86104 J A N U A RY– F E B R U A RY 1 9 8 6 HBR Manager’s Guide to Forecasting David M. Georgoff and Robert G. Murdick E arly in 1984‚ the Houston-based COMPAQ Computer Corporation‚ manufacturer of IBMcompatible microcomputers‚ faced a decision that would profoundly affect its future. Recognizing that IBM would soon introduce its version of the portable computer and threaten
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Chapter FORECASTING Discussion Questions 1. Qualitative models incorporate subjective factors into the forecasting model. Qualitative models are useful when subjective factors are important. When quantitative data are difficult to obtain‚ qualitative models may be appropriate. 2. Approaches are qualitative and quantitative. Qualitative is relatively subjective; quantitative uses numeric models. 3. Short-range (under 3 months)‚ medium-range (3 months to 3 years)‚ and long-range (over
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TYPES OF FORECASTING METHODS Qualitative methods: These types of forecasting methods are based on judgments or opinions‚ and are subjective in nature. They do not rely on any mathematical computations. Quantitative methods: These types of forecasting methods are based on quantitative models‚ and are objective in nature. They rely heavily on mathematical computations. QUALITATIVE FORECASTING METHODS Qualitative Methods Executive Opinion Market Research Delphi
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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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Howard 05/28/2012 Apple Forecasting‚ Budgets‚ &MRP A. Forecasting Technique I. Time Series Analysis A) Trend Projections-Fits a mathematical trend line to the data points and projects it into the future. B) Apple forecasting – Company is progressively stronger over past 10 years C) Current market demand requires trend forecasting B. Budgets I. Constant Workforce a) Monthly Calculations
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Eight Steps to Forecasting • Determine the use of the forecast □ What objective are we trying to obtain? • Select the items to be forecast • Determine the time horizon of the forecast □ Short time horizon – 1 to 30 days □ Medium time horizon – 1 to 12 months □ Long time horizon – more than 1 year • Select the forecasting model(s) |Description |Qualitative Approach |Quantitative Approach
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PORTFOLIO ASSIGNMENT Due date: Complete assignment due Week 9 PART 1: HUMAN RESOURCE FORECASTING Reference: Adapted from Human Resource Forecasting Assignment‚ pp 108 – 110 in Nkomo‚ S. M.‚ Fottler‚ M. D.‚ McAfee‚ R. B. (2008) Human Resource Management Applications: Cases‚ Exercises‚ Incidents‚ and Skill Builders‚ 6th Edition Due date: Week 9 LEARNING OBJECTIVES • Practice in forecasting an organisation’s people needs • To familiarize you with some of the factors that affect an
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The Policy Process Part II Lenue Richardson HCS/455 March 14‚ 2013 University of Phoenix The Policy Process Part II Introduction The development of policy is not something that can be done in an efficient manner. However; there are times when policies are very burdensome and can be a very big challenge‚ one that is loaded with all sorts of committees and everything else‚ it is truly an experience. Although the creating of a policy is a very different experience it is necessary
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1) Raw data‚ not seasonalized 2) Seasonal Adjustment used: Census II X-12 multiplicative (MASA): Used because of the presence of seasonal variations that are increasing with the level of my series. Increasing degree of variability overtime… TX non seasonalized and seasonalized 3) Combined seasonally adjusted with non-seasonally adjusted De-seasonalizing the data helped with the removal of seasonal component that creates higher volatility in model. Now‚ variations
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ANC Introduction: Headlines: • Typhoon ‘Lawin’ gets stronger‚ heads far northern Luzon • Eye of ’Lawin’ to spare northern Luzon: PAGASA • CebuPac cancels 4 Caticlan flights • ’Lawin’ slightly weakens Reporter 1: Typhoon ‘Lawin’ gets stronger‚ heads far northern Luzon Typhoon “Lawin” sped up slightly as it continued its movement towards the northern Philippines‚ the state weather bureau said. At 4 p.m. Wednesday‚ the eye of the supertyphoon was plotted by satellite and surface data at
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