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Author: Nicolas Vandeput Publisher: Simon and Schuster ISBN: 163835197X Category : Computers Languages : en Pages : 292
Book Description
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 CentraleSupélec, 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!
Author: Nicolas Vandeput Publisher: Simon and Schuster ISBN: 163835197X Category : Computers Languages : en Pages : 292
Book Description
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 CentraleSupélec, 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!
Author: Colleen Crum Publisher: J. Ross Publishing ISBN: 1932159010 Category : Business & Economics Languages : en Pages : 257
Book Description
Effective demand management is becoming critical to acompany's profitability. Demand Management BestPractices: Process, Principles, and Collaborationprovides best practice solutions that will improveoverall business performance for supply chain partnersand all functions within a company impacted by the demandmanagement process. The ......
Author: John E. Boylan Publisher: John Wiley & Sons ISBN: 1119135303 Category : Medical Languages : en Pages : 403
Book Description
INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits. No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software. “Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —Spyros Makridakis, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC). “We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.” —Suresh Acharya, VP, Research and Development, Blue Yonder. “As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.” —Thomas R. Willemain, Professor Emeritus, Rensselaer Polytechnic Institute.
Author: Stephan Kolassa Publisher: Business Expert Press ISBN: 1606495038 Category : Business & Economics Languages : en Pages : 214
Book Description
Most decisions and plans in a firm require a forecast. Not matching supply with demand can make or break any business, and that's why forecasting is so invaluable. Forecasting can appear as a frightening topic with many arcane equations to master. For this reason, the authors start out from the very basics and provide a non-technical overview of common forecasting techniques as well as organizational aspects of creating a robust forecasting process. The book also discusses how to measure forecast accuracy to hold people accountable and guide continuous improvement. This book does not require prior knowledge of higher mathematics, statistics, or operations research. It is designed to serve as a first introduction to the non-expert, such as a manager overseeing a forecasting group, or an MBA student who needs to be familiar with the broad outlines of forecasting without specializing in it.
Author: Rob J Hyndman Publisher: OTexts ISBN: 0987507117 Category : Business & Economics Languages : en Pages : 380
Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author: Nicolas Vandeput Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3110671123 Category : Business & Economics Languages : en Pages : 310
Book Description
Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method which includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting. This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework. Part I focuses on statistical "traditional" models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves. This hands-on book, covering the entire range of forecasting—from the basics all the way to leading-edge models—will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting.
Author: Charles W. Chase Publisher: John Wiley & Sons ISBN: 0470531010 Category : Business & Economics Languages : en Pages : 335
Book Description
Praise for Demand-Driven Forecasting A Structured Approach to Forecasting "There are authors of advanced forecasting books who take an academic approach to explaining forecast modeling that focuses on the construction of arcane algorithms and mathematical proof that are not very useful for forecasting practitioners. Then, there are other authors who take a general approach to explaining demand planning, but gloss over technical content required of modern forecasters. Neither of these approaches is well-suited for helping business forecasters critically identify the best demand data sources, effectively apply appropriate statistical forecasting methods, and properly design efficient demand planning processes. In Demand-Driven Forecasting, Chase fills this void in the literature and provides the reader with concise explanations for advanced statistical methods and credible business advice for improving ways to predict demand for products and services. Whether you are an experienced professional forecasting manager, or a novice forecast analyst, you will find this book a valuable resource for your professional development." —Daniel Kiely, Senior Manager, Epidemiology, Forecasting & Analytics, Celgene Corporation "Charlie Chase has given forecasters a clear, responsible approach for ending the timeless tug of war between the need for 'forecast rigor' and the call for greater inclusion of 'client judgment.' By advancing the use of 'domain knowledge' and hypothesis testing to enrich base-case forecasts, he has empowered professional forecasters to step up and impact their companies' business results favorably and profoundly, all the while enhancing the organizational stature of forecasters broadly." —Bob Woodard, Vice President, Global Consumer and Customer Insights, Campbell Soup Company
Author: Nicolas Vandeput Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3110673991 Category : Business & Economics Languages : en Pages : 305
Book Description
In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . . . Vandeput is at the forefront of a new and better way of doing supply chains, and thanks to a richly illustrated book, where every single situation gets its own illustrating code snippet, so could you. --Joannes Vermorel, CEO, Lokad Inventory Optimization argues that mathematical inventory models can only take us so far with supply chain management. In order to optimize inventory policies, we have to use probabilistic simulations. The book explains how to implement these models and simulations step-by-step, starting from simple deterministic ones to complex multi-echelon optimization. The first two parts of the book discuss classical mathematical models, their limitations and assumptions, and a quick but effective introduction to Python is provided. Part 3 contains more advanced models that will allow you to optimize your profits, estimate your lost sales and use advanced demand distributions. It also provides an explanation of how you can optimize a multi-echelon supply chain based on a simple—yet powerful—framework. Part 4 discusses inventory optimization thanks to simulations under custom discrete demand probability functions. Inventory managers, demand planners and academics interested in gaining cost-effective solutions will benefit from the "do-it-yourself" examples and Python programs included in each chapter. Events around the book Link to a De Gruyter Online Event in which the author Nicolas Vandeput together with Stefan de Kok, supply chain innovator and CEO of Wahupa; Koen Cobbaert, Director in the S&O Industry practice of PwC Belgium; Bram Desmet, professor of operations & supply chain at the Vlerick Business School in Ghent; and Karl-Eric Devaux, Planning Consultant, Hatmill, discuss about models for inventory optimization. The event will be moderated by Eric Wilson, Director of Thought Leadership for Institute of Business Forecasting (IBF): https://youtu.be/565fDQMJEEg
Author: Michael Gilliland Publisher: John Wiley & Sons ISBN: 1119782473 Category : Business & Economics Languages : en Pages : 435
Book Description
Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.
Author: Nicolas Vandeput
Author: Nicolas Vandeput
Author: Colleen Crum
Author: Chaman L. Jain
Author: John E. Boylan
Author: Stephan Kolassa
Author: Rob J Hyndman
Author: Nicolas Vandeput
Author: Charles W. Chase
Author: Nicolas Vandeput
Author: Michael Gilliland