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Demand Prediction in Retail by Maxime C. Cohen,Paul-Emile Gras,Arthur Pentecoste,Renyu Zhang Pdf
From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture. This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.
Author : John E. Boylan,Aris A. Syntetos Publisher : John Wiley & Sons Page : 403 pages File Size : 40,5 Mb Release : 2021-06-02 Category : Medical ISBN : 9781119135302
Intermittent Demand Forecasting by John E. Boylan,Aris A. Syntetos Pdf
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.
This book addresses the challenging task of demand forecasting and inventory management in retailing. It analyzes how information from point-of-sale scanner systems can be used to improve inventory decisions, and develops a data-driven approach that integrates demand forecasting and inventory management for perishable products, while taking unobservable lost sales and substitution into account in out-of-stock situations. Using linear programming, a new inventory function that reflects the causal relationship between demand and external factors such as price and weather is proposed. The book subsequently demonstrates the benefits of this new approach in numerical studies that utilize real data collected at a large European retail chain. Furthermore, the book derives an optimal inventory policy for a multi-product setting in which the decision-maker faces an aggregated service level target, and analyzes whether the decision-maker is subject to behavioral biases based on real data for bakery products.
Consumption-Based Forecasting and Planning by Charles W. Chase Pdf
Discover a new, demand-centric framework for forecasting and demand planning In Consumption-Based Forecasting and Planning, thought leader and forecasting expert Charles W. Chase delivers a practical and novel approach to retail and consumer goods companies demand planning process. The author demonstrates why a demand-centric approach relying on point-of-sale and syndicated scanner data is necessary for success in the new digital economy. The book showcases short- and mid-term demand sensing and focuses on disruptions to the marketplace caused by the digital economy and COVID-19. You’ll also learn: How to improve demand forecasting and planning accuracy, reduce inventory costs, and minimize waste and stock-outs What is driving shifting consumer demand patterns, including factors like price, promotions, in-store merchandising, and unplanned and unexpected events How to apply analytics and machine learning to your forecasting challenges using proven approaches and tactics described throughout the book via several case studies. Perfect for executives, directors, and managers at retailers, consumer products companies, and other manufacturers, Consumption-Based Forecasting and Planning will also earn a place in the libraries of sales, marketing, supply chain, and finance professionals seeking to sharpen their understanding of how to predict future consumer demand.
Sales Forecasting Management by John T. Mentzer,Mark A. Moon Pdf
Incorporating 25 years of sales forecasting management research with more than 400 companies, Sales Forecasting Management, Second Edition is the first text to truly integrate the theory and practice of sales forecasting management. This research includes the personal experiences of John T. Mentzer and Mark A. Moon in advising companies how to improve their sales forecasting management practices. Their program of research includes two major surveys of companies' sales forecasting practices, a two-year, in-depth study of sales forecasting management practices of 20 major companies, and an ongoing study of how to apply the findings from the two-year study to conducting sales forecasting audits of additional companies. The book provides comprehensive coverage of the techniques and applications of sales forecasting analysis, combined with a managerial focus to give managers and users of the sales forecasting function a clear understanding of the forecasting needs of all business functions.
Author : Nicolas Vandeput Publisher : Walter de Gruyter GmbH & Co KG Page : 338 pages File Size : 45,6 Mb Release : 2021-03-22 Category : Business & Economics ISBN : 9783110671209
Data Science for Supply Chain Forecasting by Nicolas Vandeput Pdf
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. 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; Spyros Makridakis, professor at the University of Nicosia and director of the Institute For the Future (IFF); and Edouard Thieuleux, founder of AbcSupplyChain, discuss the general issues and challenges of demand forecasting and provide insights into best practices (process, models) and discussing how data science and machine learning impact those forecasts. The event will be moderated by Michael Gilliland, marketing manager for SAS forecasting software: https://youtu.be/1rXjXcabW2s
What is the value of a bricks-and-mortar store? As retailers move to a multichannel world where the winners must overcome the challenges of pricing transparency, personalized marketing, and supply chain controls, most sales still occur in the physical site. Behavior Analytics is the science of studying the behavior of people. Schedule to Demand is a subset of Behavior Analytics, a method that correlates between traffic, sales and labor data, in order to optimize the productivity of employees and position them where they matter most. In Behavior Analytics for Retail, we will introduce the core metrics of Schedule to Demand; design the requirements for a Customer Service Model of the store, inside the store, and at the checkout; present technology options and accuracy requirements; and offer insights through case studies. Regardless of how the future will shape retail, the physical store will continue to exist, and thrive. We propose a framework for retailers, and others, on how to optimize store operations and profitability, and enhance the shopping experience by measuring, monitoring and predicting the behavior of employees and customers.
Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications by Abhishek Majumder,Joy Lal Sarkar,Arindam Majumder Pdf
Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications captures the state of the art in usage of artificial intelligence in different types of recommendation systems and predictive analysis. The book provides guidelines and case studies for application of artificial intelligence in recommendation from expert researchers and practitioners. A detailed analysis of the relevant theoretical and practical aspects, current trends and future directions is presented. The book highlights many use cases for recommendation systems: · Basic application of machine learning and deep learning in recommendation process and the evaluation metrics · Machine learning techniques for text mining and spam email filtering considering the perspective of Industry 4.0 · Tensor factorization in different types of recommendation system · Ranking framework and topic modeling to recommend author specialization based on content. · Movie recommendation systems · Point of interest recommendations · Mobile tourism recommendation systems for visually disabled persons · Automation of fashion retail outlets · Human resource management (employee assessment and interview screening) This reference is essential reading for students, faculty members, researchers and industry professionals seeking insight into the working and design of recommendation systems.
The coming of the AI revolution in brick-and-mortar retail In AI for Retail: A Practical Guide to Modernize Your Retail Business with AI and Automation, Francois Chaubard, AI researcher and retail technology CEO, delivers a practical guide for integrating AI into your brick-and-mortar retail business. In the book, you’ll learn how to make your business more efficient by automating inventory management, supply chain, front-end, merchandising, pricing, loss prevention, e-commerce processes, and more. The author takes you step by step from no AI Strategy at all to implementing a robust AI playbook that will permeate through your entire organization. In this book, you will learn: How AI works, including key terminology and fundamental AI applications in retail How AI can be applied to the major functions of retail with detailed P&L analysis of each application How to implement an AI strategy across your entire business to double or even triple Free Cash Flow AI for Retail is the comprehensive, hands-on blueprint for AI adoption that retail managers, executives, founders, entrepreneurs, board members, and other business leaders have been waiting for.
Machine Learning and Data Analytics for Solving Business Problems by Bader Alyoubi,Chiheb-Eddine Ben Ncir,Ibraheem Alharbi,Anis Jarboui Pdf
This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods – such as blockchain, big data, artificial intelligence, and cloud computing – so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.
Perishable Inventory Systems by Steven Nahmias Pdf
A perishable item is one that has constant utility up until an expiration date (which may be known or uncertain), at which point the utility drops to zero. This includes many types of packaged foods such as milk, cheese, processed meats, and canned goods. It also includes virtually all pharmaceuticals and photographic film, as well as whole blood supplies. This book is the first devoted solely to perishable inventory systems. The book’s ten chapters first cover the preliminaries of periodic review versus continuous review and look at a one-period newsvendor perishable inventory model. The author moves to the basic multiperiod dynamic model, and then considers the extensions of random lifetime, inclusion of a set-up cost, and multiproduct models of perishables. A chapter on continuous review models looks at one-for-one policies, models with zero lead time, optimal policies with positive lead time, and an alternative approach. Additional chapters present material on approximate order policies, inventory depletion management, and deterministic models, including the basic EOQ model with perishability and the dynamic deterministic model with perishability. Finally, chapters explore decaying inventories, queues with impatient customers, and blood bank inventory control. Anyone researching perishable inventory systems will find much to work with here. Practitioners and consultants will also now have a single well-referenced source of up-to-date information to work with.
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
This work presents a comprehensive model of supply chain management. Experienced executives from 20 companies clearly define supply chain management, identifying those factors that contribute to its effective implementation. They provide practical guidelines on how companies can manage supply chains, addressing the role of all the traditional business functions in supply chain management and suggest how the adoption of a supply chain management approach can affect business strategy and corporate performance.
Next Generation Demand Management by Charles W. Chase Pdf
A practical framework for revenue-boosting supply chain management Next Generation Demand Management is a guidebook to next generation Demand Management, with an implementation framework that improves revenue forecasts and enhances profitability. This proven approach is structured around the four key catalysts of an efficient planning strategy: people, processes, analytics, and technology. The discussion covers the changes in behavior, skills, and integrated processes that are required for proper implementation, as well as the descriptive and predictive analytics tools and skills that make the process sustainable. Corporate culture changes require a shift in leadership focus, and this guide describes the necessary "champion" with the authority to drive adoption and stress accountability while focusing on customer excellence. Real world examples with actual data illustrate important concepts alongside case studies highlighting best-in-class as well as startup approaches. Reliable forecasts are the primary product of demand planning, a multi-step operational supply chain management process that is increasingly seen as a survival tactic in the changing marketplace. This book provides a practical framework for efficient implementation, and complete guidance toward the supplementary changes required to reap the full benefit. Learn the key principles of demand driven planning Implement new behaviors, skills, and processes Adopt scalable technology and analytics capabilities Align inventory with demand, and increase channel profitability Whether your company is a large multinational or an early startup, your revenue predictions are only as strong as your supply chain management system. Implementing a proven, more structured process can be the catalyst your company needs to overcome that one lingering obstacle between forecast and goal. Next Generation Demand Management gives you the framework for building the foundation of your growth.
