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Lecture

Traceability and Forecast Analysis

In courses (2)

MGT-427: Project management and risk analysis

Ce cours a pour objectif de présenter l'approche générale du management de projet en intégrant la gestion du risque dans toutes les étapes du projet. ...

MGT-426: Logistics and demand analysis

La logistique, fonction transversale par excellence, intègre toutes les dimensions des processus industriels à ajout de valeur, de l'approvisionnement à la distribution aux clients et au-delà en intégrant le développement durable. Un focus particulier sera ...

Description

This lecture covers the importance of traceability in logistics and supply chain management, discussing objectives, implementation, and code carriers. It also explores the use of various technologies like RFID and barcodes for traceability, as well as the fight against counterfeiting and fraud. Additionally, it delves into the challenges of forecasting demand, historical inaccuracies in predictions, and the significance of product lifecycle management in the context of globalization and cost optimization.

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Instructor

Philippe Wieser

Philippe Wieser obtained his diploma of engineer in mechanics at the EPFL in 1977 and he received his PhD in 1981. After a few years working in a engineering consulting company, he joined the EPFL as lecturer. His fields of research and teaching deal with logistics, supply chain management, information systems and integrated logistics, health supply chain and project management. Since May 2000, Philippe Wieser is the executive director of IML: International Institute for the Management of Logistics (EPFL - Lausanne and ENPC - Paris). In 2008 he was appointed Professeur titulaire at EPFL. Philippe Wieser teaches in EPFL-Lausanne (Minor, Master and Executive Master MSL), ENPC-Paris (Executive Master) and other European and African Universities. He is author or co-author of more than ninety publications and international conferences.

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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.

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.

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.

Globalization

Globalization, or globalisation (Commonwealth English; see spelling differences), is the process of interaction and integration among people, companies, and governments worldwide. The term globalization first appeared in the early 20th century (supplanting an earlier French term mondialization), developed its current meaning some time in the second half of the 20th century, and came into popular use in the 1990s to describe the unprecedented international connectivity of the post-Cold War world.

Combinatorial optimization

Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the set of feasible solutions is discrete or can be reduced to a discrete set. Typical combinatorial optimization problems are the travelling salesman problem ("TSP"), the minimum spanning tree problem ("MST"), and the knapsack problem. In many such problems, such as the ones previously mentioned, exhaustive search is not tractable, and so specialized algorithms that quickly rule out large parts of the search space or approximation algorithms must be resorted to instead.

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