Lecture

Demand Forecasting Methods

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In course

ME-419: Production management

Production management deals with producing goods sustainably at the right time, quantity, and quality with the minimum cost. This course equips students with practical skills and tools for effectively managing demand, supply, and implementing advanced anal ...

Description

This lecture covers the steps involved in demand forecasting, including the purpose of the forecast, data acquisition and analysis, method selection, making the forecast, and monitoring forecast errors. It also delves into the Holt-Winter model for time series analysis, focusing on trend, seasonality, and model initiation steps.

Instructor

Amin Kaboli

Dr. Amin Kaboli is an external lecturer for at the Mechanical Engineering Section at EPFL and teaches Production Management (ME-419), Continuous Improvement (ME-498) to graduate students and Digital Supply Chain, Innovation and Digitization, and Sustainable Change Leadership to business executives and managers at International Institute for the Management of Logistics and Supply Chain (IML). Amin supports many organizations ranging from Fortune 500 corporations to entrepreneurial firms and industries as diverse as Watch, Consumer Goods, Food and Beverage, MedTech, and Pharma. He obtained his Ph.D. in Manufacturing Systems & Robotics, specialized in Supply Chain Management from EPFL. You can watch his TEDx talk on “Leading Change Consciously” here. TEDx talk here.

Official source

Related concepts (32)

Forecasting

Forecasting is the process of making predictions based on past and present data. Later these can be compared (resolved) against what happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis. Prediction is a similar but more general term. Forecasting might refer to specific formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgmental methods or the process of prediction and resolution itself.

Demand forecasting

Demand forecasting refers to the process of predicting the quantity of goods and services that will be demanded by consumers at a future point in time. More specifically, the methods of demand forecasting entail using predictive analytics to estimate customer demand in consideration of key economic conditions. This is an important tool in optimizing business profitability through efficient supply chain management. Demand forecasting methods are divided into two major categories, qualitative and quantitative methods.

Economic forecasting

Economic forecasting is the process of making predictions about the economy. Forecasts can be carried out at a high level of aggregation—for example for GDP, inflation, unemployment or the fiscal deficit—or at a more disaggregated level, for specific sectors of the economy or even specific firms. Economic forecasting is a measure to find out the future prosperity of a pattern of investment and is the key activity in economic analysis.

Weather forecasting

Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given location and time. People have attempted to predict the weather informally for millennia and formally since the 19th century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere, land, and ocean and using meteorology to project how the atmosphere will change at a given place.

Taskbar

The Taskbar is a graphical user interface element that has been part of Microsoft Windows since Windows 95, displaying and facilitating switching between running programs. The Taskbar and the associated Start Menu were created and named in 1993 by Daniel Oran, a program manager at Microsoft who had previously collaborated on Great ape language research with the behavioral psychologist B.F. Skinner at Harvard. The Taskbar is an exemplar of a category of always-visible graphical user interface elements that provide access to fundamental operating system functions and information.

Related lectures (34)

Demand Forecasting: Methods and Models

Explores demand forecasting methods, time series analysis, trend forecasting, and the application of the Holt-Winter model.

Time Series: Forecasting and Long Memory

Explores forecasting in time series analysis, long memory processes, and ARCH models for volatility modeling.

Demand Management: Forecasting Methods

Covers demand management, forecasting methods, and trend analysis in production management.

Time Series: Fundamentals and Models

Explores the fundamentals of time series analysis, including stationarity, linear processes, forecasting, and practical aspects.

Demand Forecasting: Model Initiation