Transcription of Introduction to Demand Planning & Forecasting
{{id}} {{{paragraph}}}
Example: stock market
Introduction to Demand Planning & Forecasting
MIT Center for Transportation & -Supply Chain & Logistics Fundamentals Introduction to Demand Planning & Forecasting - Supply Chain and Logistics Fundamentals Lesson: Demand Forecasting Basics Demand Process Three Key Questions Demand Planning n Product & Packaging n Promotions n Pricing n Place 2 What should we do to shape and create Demand for our product? What should we expect Demand to be given the Demand plan in place? How do we prepare for and act on Demand when it materializes? Demand Forecasting n Strategic, Tactical, Operational n Considers internal & external factors n Baseline, unbiased, & unconstrained Demand Management n Balances Demand & supply n Sales & Operations Planning (S&OP) n Bridges both sides of a firm Material adapted from Lapide, L. (2006) Course Notes, Logistics Systems. - Supply Chain and Logistics Fundamentals Lesson: Demand Forecasting Basics Forecasting Levels 3 Level Horizon Purposes Quarterly Brand Plans Budgeting Sales Planning Manpower Planning Strategic Year/Years Business Planning Capacity Planning Investment Strategies Ta c t i c a l Months/Weeks Short-term Capacity Planning Master Planning Inventory Planning Operational Days/Hours Transportation Planning Production Planning Inventory Deployment Material adapted from Lapide, L.
• Forecasting is a means not an end • Forecasting Truisms ! Forecasts are always wrong ! Aggregated forecasts are more accurate ! Shorter horizon forecasts are more accurate • Subjective & Objective Approaches ! Judgmental & experimental ! Causal & time series • Forecasting metrics ! Capture both bias & accuracy !
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
Related search queries
OPERATIONS MANAGEMENT, Forecasting, Forecasting Approaches, Time, Series Forecasting, Time series, Approaches, Financial Time Series, Machine Learning Applied to Weather Forecasting, Time se-ries, Series, Spatio-Temporal Graph Convolutional Networks: A, Business Forecasting: Practical Problems and Solutions, Series fore-casting