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Sales forecasting and market analysis are the cornerstones of the planning process. Yet, these two tasks are usually performed by people with only limited training in either area because most firms do not have full-time forecasters/market analysts. The authors acknowledge this situation and attempt to describe the key techniques for forecasting sales and analyzing markets in a format that meets the needs of an audience with limited quantitative skills. In addition to its basic approach, another strength of this book is that it combines the coverage of two key activities--forecasting and market analysis--that are performed by the same person in most middle-sized (and smaller) firms. The book's contents and format were designed with two audiences in mind: persons assigned to develop forecasts and market analyses, but who are not specialists in either area, and persons who will be incorporating these results in their planning and decision making. The major portion of the book is devoted to the three basic categories of forecasting models--time series, causal, and judgmental--emphasizing the most widely used models in each category. Special attention is also given to the sources for obtaining the data needed to make forecasts and analyze markets. The latter part of the book describes procedures for developing market and sales potentials, methods for segmenting markets, and some analytic techniques such as conjoint analysis and cluster analysis, gaining increased usage among market analysts.
Sales forecasting and market analysis are the cornerstones of the planning process. Yet, these two tasks are usually performed by people with only limited training in either area because most firms do not have full-time forecasters/market analysts. The authors acknowledge this situation and attempt to describe the key techniques for forecasting sales and analyzing markets in a format that meets the needs of an audience with limited quantitative skills. In addition to its basic approach, another strength of this book is that it combines the coverage of two key activities--forecasting and market analysis--that are performed by the same person in most middle-sized (and smaller) firms. The book's contents and format were designed with two audiences in mind: persons assigned to develop forecasts and market analyses, but who are not specialists in either area, and persons who will be incorporating these results in their planning and decision making. The major portion of the book is devoted to the three basic categories of forecasting models--time series, causal, and judgmental--emphasizing the most widely used models in each category. Special attention is also given to the sources for obtaining the data needed to make forecasts and analyze markets. The latter part of the book describes procedures for developing market and sales potentials, methods for segmenting markets, and some analytic techniques such as conjoint analysis and cluster analysis, gaining increased usage among market analysts.
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.
"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.
This book is written for all technologists and engineers. To those unfamiliar with forecasting it may appear a somewhat esoteric activity with little relevance to the everyday technical concerns of the reader. This is not so. The aim of this book is to show how forecasting can improve the quality of technical decision making. Furthermore, this can be accomplished without the use of highly sophisticated techniques which can only be applied by specialists. The approaches described in this book can be easily understood and used by all its readers.
Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
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.
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.