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Practical Guide to Business Forecasting

Practical Guide to Business Forecasting
Author: Chaman L. Jain & Jack Malehorn
Publisher: Institute of Business Forec
Total Pages: 516
Release: 2005
Genre: Business forecasting
ISBN: 9780932126757

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Practical Sales Forecasting

Practical Sales Forecasting
Author: William Copulsky
Publisher: AMACOM Div American Mgmt Assn
Total Pages: 36
Release: 1970
Genre: Business & Economics
ISBN: 0814421326

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Textbook on the methodology of forecasting consumer demand for consumer goods and on the use of economic models and sector analysis to forecast the economy.


Sales Forecasting

Sales Forecasting
Author: Mark Blessington
Publisher: Createspace Independent Publishing Platform
Total Pages: 0
Release: 2015-10-10
Genre: Sales forecasting
ISBN: 9781505536843

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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

Sales Forecasting: A Practical & Proven Guide to Strategic Sales Forecasting
Author: Gerard Assey
Publisher: Gerard Assey
Total Pages: 103
Release: 2024-01-08
Genre: Business & Economics
ISBN:

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"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.


Practical Sales Forecasting

Practical Sales Forecasting
Author: Edwin John Davis
Publisher:
Total Pages: 291
Release: 1988
Genre: Sales forecasting
ISBN:

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Business Forecasting

Business Forecasting
Author: Michael Gilliland
Publisher: John Wiley & Sons
Total Pages: 435
Release: 2021-05-11
Genre: Business & Economics
ISBN: 1119782473

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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.


Business Forecasting

Business Forecasting
Author: Michael Gilliland
Publisher: John Wiley & Sons
Total Pages: 417
Release: 2015-12-15
Genre: Business & Economics
ISBN: 1119228298

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A comprehensive collection of the field's most provocative, influential new work Business Forecasting compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative ideas from forecasting researchers and practitioners, on topics including accuracy metrics, benchmarking, modeling of problem data, and overcoming dysfunctional behaviors. Its coverage includes often-overlooked issues at the forefront of research, such as uncertainty, randomness, and forecastability, as well as emerging areas like data mining for forecasting. The articles present critical analysis of current practices and consideration of new ideas. With a mix of formal, rigorous pieces and brief introductory chapters, the book provides practitioners with a comprehensive examination of the current state of the business forecasting field. Forecasting performance is ultimately limited by the 'forecastability' of the data. Yet failing to recognize this, many organizations continue to squander resources pursuing unachievable levels of accuracy. This book provides a wealth of ideas for improving all aspects of the process, including the avoidance of wasted efforts that fail to improve (or even harm) forecast accuracy. Analyzes the most prominent issues in business forecasting Investigates emerging approaches and new methods of analysis Combines forecasts to improve accuracy Utilizes Forecast Value Added to identify process inefficiency The business environment is evolving, and forecasting methods must evolve alongside it. This compilation delivers an array of new tools and research that can enable more efficient processes and more accurate results. Business Forecasting provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes.


Sales Forecasting

Sales Forecasting
Author: Gerard Assey
Publisher: Collection Skills
Total Pages: 0
Release: 2024-01-08
Genre: Business & Economics
ISBN: 9788196720261

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"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.


Demand Prediction in Retail

Demand Prediction in Retail
Author: Maxime C. Cohen
Publisher: Springer Nature
Total Pages: 166
Release: 2022-01-01
Genre: Business & Economics
ISBN: 3030858553

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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.