Demand Forecasting Best Practices (eBook)

Nicolas Vandeput (Autor)

eBook Download: EPUB

2023
216 Seiten
Manning (Verlag)
978-1-63835-197-9 (ISBN)

Infos

Lead your demand planning process to excellence and deliver real value to your supply chain.In Demand Forecasting Best Practices you'll learn how to: Lead your team to improve quality while reducing workload Properly define the objectives and granularity of your demand planning Use intelligent KPIs to track accuracy and bias Identify areas for process improvement Help planners and stakeholders add value Determine relevant data to collect and how best to collect it Utilize different statistical and machine learning models An expert demand forecaster can help an organization avoid overproduction, reduce waste, and optimize inventory levels for a real competitive advantage. Demand Forecasting Best Practices teaches you how to become that virtuoso demand forecaster. This one-of-a-kind guide reveals forecasting tools, metrics, models, and stakeholder management techniques for delivering more effective supply chains. Everything you learn has been proven and tested in a live business environment. Discover author Nicolas Vandeput's original five step framework for demand planning excellence and learn how to tailor it to your own company's needs. Illustrations and real-world examples make each concept easy to understand and easy to follow. You'll soon be delivering accurate predictions that are driving major business value. About the Technology An expert demand forecaster can help an organization avoid overproduction, reduce waste, and optimize inventory levels for a real competitive advantage. This book teaches you how to become that virtuoso demand forecaster. About the Book Demand Forecasting Best Practices reveals forecasting tools, metrics, models, and stakeholder management techniques for managing your demand planning process efficiently and effectively. Everything you learn has been proven and tested in a live business environment. Discover author Nicolas Vandeput's original five step framework for demand planning excellence and learn how to tailor it to your own company's needs. Illustrations and real-world examples make each concept easy to understand and easy to follow. You'll soon be delivering accurate predictions that are driving major business value. What's Inside Enhance forecasting quality while reducing team workload Utilize intelligent KPIs to track accuracy and bias Identify process areas for improvement Assist stakeholders in sales, marketing, and finance Optimize statistical and machine learning models About the Reader For demand planners, sales and operations managers, supply chain leaders, and data scientists. About the Author Nicolas Vandeput is a supply chain data scientist, the founder of consultancy company SupChains in 2016, and a teacher at CentraleSuplec, France. Table of Contents: Part 1 - Forecasting demand 1 Demand forecasting excellence 2 Introduction to demand forecasting 3 Capturing unconstrained demand (and not sales) 4 Collaboration: data sharing and planning alignment 5 Forecasting hierarchies 6 How long should the forecasting horizon be? 7 Should we reconcile forecasts to align supply chains? Part 2 - Measuring forecasting quality 8 Forecasting metrics 9 Choosing the best forecasting KPI 10 What is a good forecast error? 11 Measuring forecasting accuracy on a product portfolio Part 3 - Data-driven forecasting process 12 Forecast value added 13 What do you review? ABC XYZ segmentations and other methods Part 4 - Forecasting methods 14 Statistical forecasting 15 Machine learning 16 Judgmental forecasting 17 Now it's your turn!

Produkt-Details

• Erscheint lt. Verlag: 25.7.2023
• Sprache: englisch
• Themenwelt: Kunst / Musik / Theater ► Design / Innenarchitektur / Mode
• Themenwelt: Informatik ► Datenbanken ► Data Warehouse / Data Mining
• Themenwelt: Mathematik / Informatik ► Informatik ► Theorie / Studium
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management
• ISBN-10: 1-63835-197-X / 163835197X
• ISBN-13: 978-1-63835-197-9 / 9781638351979