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Sales Forecasting is a practical guide for beginning and intermediate sales forecasters. The book does not use complex formulas. Instead, it is designed around the author's application of the learning curve to sales forecasting. Millions of sales forecasts are made by hundreds of thousands of people every year. Sales forecasts for every product and every sales territory in the world are made at least once a year, if not monthly. Then there are various aggregations of these forecasts, such as product to product line to division, and territory to district to region. Further, multiple functional areas across the company make sales forecasts. Sales, marketing, finance and manufacturing are all involved, at least on an annual basis, and often much more frequently. The sad truth is that few forecasters have any formal education or training on the subject. Part of this is because most forecasting books use numerous complex formulas, which are arcane, intimidating and off-putting. Another reason is that sales forecasters are encouraged to place too much trust in forecasting software by vendors who tend to make exaggerated and unsubstantiated claims about forecasting accuracy. Sales Forecasting breaks new ground. It re-invents the process of teaching the subject of sales forecasting. It is designed around the learning curve. The author's experience in day trading, along with decades of sales and marketing consulting, taught him the essential ingredients of sales forecasting. These are provided in Part 1 of the book. The first and most important skill is error measurement. The author makes a clear declaration about the best method and demonstrates its use throughout the book. The second skill is testing, and the author demonstrates how to divide historical sales data into in- and out-samples, calibrate models on the in-sample, and assess model accuracy by forecasting the out-sample. The third and fourth skills are avoiding linear extensions and mastering exponential smoothing. Part 1 is concluded with a description of the whole forecasting process and what is called "five-step forecasting." Part 2 moves into intermediate forecasting. Leading software packages are assessed through the author's research. Very little is published on forecasting software assessment, so this chapter plays an important role. Then ARIMA and ARIMAX are taught and demonstrated through multiple examples. These two methods, combined with exponential smoothing, form the foundation of intermediate forecasting. Perhaps the most exciting chapters in Part 2 involve aggregation. This is a fairly new field and it is growing rapidly. The author identifies some important gaps in the field, then fills them with his own research. Anyone involved in sales forecasting can benefit from these important findings. A chapter is dedicated to demonstrating the application of sound techniques to common forecasting challenges in marketing and sales departments: product planning and quota setting. It becomes quite clear that traditional methods generate far more error than the basic sales forecasting techniques taught in this book. The author also examines the topic of handicapping, or determining how much confidence to place on a forecast. He introduces the concept of "true confidence ranges" and also demonstrates the application of Bayesian probabilities to sales forecasting. To conclude the book, the author explores economic forecasting and closes with a discussion of common forecasting pitfalls to be avoided at all costs.
"Sales Forecasting: A Practical & Proven Guide to Strategic Sales Forecasting" navigates the intricate landscape of sales forecasting, providing a holistic understanding of its intricacies, contemporary significance, and practical applications. From the responsibilities of Sales Managers to the benefits of accurate predictions for strategic planning, resource allocation, and risk mitigation, this guide equips readers with the tools to excel in the dynamic world of business strategy. Real-life case studies, interactive exercises, and workshops bring theoretical concepts to life, fostering active engagement. With a focus on diverse methods, techniques, and addressing common challenges, the book serves as a comprehensive toolkit for refining forecasting strategies. The conclusion encourages continuous learning and adaptation, ensuring readers are poised to navigate the ever-evolving realm of sales forecasting with confidence and mastery.
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.
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. New to This Edition: The author′s well-regarded Multicaster software system demo, previously available on cassette, has been updated and is now available for download from the authors′ Web site New insights on the critical area of qualitative forecasting are presented The results of additional surveys done since the publication of the first edition have been added The discussion of the four dimensions of forecasting management has been significantly enhanced Significant reorganization and updating has been done to strengthen and improve the material for the second edition. Sales Forecasting Management is an ideal text for graduate courses in sales forecasting management. Practitioners in marketing, sales, finance/accounting, production/purchasing, and logistics will also find this easy-to-understand volume essential.
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.
Stressing the concrete applications of economic forecasting, Practical Business Forecasting is accessible to a wide-range of readers, requiring only a familiarity with basic statistics. The text focuses on the use of models in forecasting, explaining how to build practical forecasting models that produce optimal results. In a clear and detailed format, the text covers estimating and forecasting with single and multi- equation models, univariate time-series modeling, and determining forecasting accuracy. Additionally, case studies throughout the book illustrate how the models are actually estimated and adjusted to generate accurate forecasts. After reading this text, students and readers should have a clearer idea of the reasoning and choices involved in building models, and a deeper foundation in estimating econometric models used in practical business forecasting.
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.
This book emphasizes the rationale, application, and interpretation of the most commonly used forecasting techniques in business.