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lect3 - Demand Forecasting I Time Series Analysis Chris...

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Demand Forecasting I Time Series Analysis Chris Caplice ESD.260/15.770/1.260 Logistics Systems Sept 2006
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© Chris Caplice, MIT 2 MIT Center for Transportation & Logistics – ESD.260 Agenda Problem and Background Four Fundamental Approaches Time Series Methods “Predictions are usually difficult – especially for the future” Yogi Berra
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© Chris Caplice, MIT 3 MIT Center for Transportation & Logistics – ESD.260 Demand Processes Demand Forecasting Predict what will happen in the future Typically involves statistical, causal or other model Conducted on a routine basis (monthly, weekly, etc.) Demand Planning Develop plans for creating or affecting future demand Results in marketing & sales plans – builds unconstrained forecast Conducted on a routine basis (monthly, quarterly, etc.) Demand Management Make decisions in order to balance supply and demand within the forecasting/planning cycle Includes forecasting and planning processes Conducted on an on-going basis as supply and demand changes Includes yield management, real-time demand shifting, forecast consumption tracking, etc.
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© Chris Caplice, MIT 4 MIT Center for Transportation & Logistics – ESD.260 Four Fundamental Approaches Subjective Judgmental Sales force surveys Delphi techniques Jury of experts Experimental Customer surveys Focus group sessions Test Marketing Simulation Objective Time Series “Black Box” Approach Uses past to predict the future Causal / Relational Econometric Models Leading Indicators Input-Output Models Often times, you will need to use a combination of approaches
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© Chris Caplice, MIT 5 MIT Center for Transportation & Logistics – ESD.260 Cost of Forecasting vs Inaccuracy Cost of Forecasting Forecast Accuracy Cost Cost of Errors In Forecast Total Cost Å Overly Naïve Models Æ Å Excessive Causal Models Æ Å Good Region Æ
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© Chris Caplice, MIT 6 MIT Center for Transportation & Logistics – ESD.260 Time Series The typical problem: Generate the large number of short-term, SKU level, locally disaggregated demand forecasts required for production, logistics, and sales to operate successfully. Predominant use is for: Forecasting product demand of . . . Mature products over a . . .
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  • Fall '06
  • ChrisCapliceesd
  • Time series analysis, Trend estimation, MIT Center, MIT Center for Transportation & Logistics, Chris Caplice

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