7 New Business Forecasting Books Reshaping Industry in 2025

Unlike most business forecasting books that dwell on theory, Nicolas Vandeput’s Demand Forecasting Best Practices dives into the practical challenges you face leading demand planning teams. Drawing from his experience founding SupChains and teaching at CentraleSupélec, Vandeput shares a five-step framework that helps you improve forecast quality while cutting workload, using intelligent KPIs and blending statistical with machine learning models. You’ll get concrete guidance on defining objectives, capturing unconstrained demand, and collaborating across sales and finance. If you manage supply chains or demand planning, this book equips you with tools to deliver predictions that truly impact operations and reduce waste.

Steve Clarke, with his background in manufacturing and supply chain management, brings a fresh lens to forecasting by integrating lean principles typically reserved for production environments. You’ll learn how to trim excess inventory, shorten lead times, and improve forecast accuracy without relying on complex software. Clarke’s approach favors straightforward tools and real-world examples that help you navigate demand variability and optimize safety stock management. If your goal is to reduce waste and boost supply chain responsiveness, this book offers clear, pragmatic insights tailored for managers and analysts alike. It’s a practical guide for anyone tasked with making forecasting more efficient and value-driven.

This tailored book explores the latest breakthroughs reshaping business forecasting in 2025, focusing on the most current developments and discoveries. It examines how new analytical techniques, machine learning advancements, and evolving data patterns are transforming forecasting accuracy and demand planning. By addressing your specific interests and goals, this personalized guide helps you stay ahead of emerging trends and cutting-edge insights relevant to your background. The content reveals practical applications of recent research in supply chain forecasting, sales predictions, and forecasting model innovation, providing a focused and enthusiastic learning experience. This tailored approach ensures you gain knowledge precisely aligned with your pursuit of the newest business forecasting methods.

What if everything you knew about time series forecasting needed a fresh update? Galit Shmueli and Julia Polak bring recent advances to the forefront, particularly through their use of the R fable package, to guide you in applying a range of forecasting methods including ARIMA, neural networks, and ensemble techniques. You’ll gain hands-on skills in linking forecasting techniques directly to business objectives, evaluating model performance, and handling real-world data challenges. This book suits those involved in operations research, supply chain, marketing, and finance who want to harness open-source tools for predictive analytics with practical case studies and exercises to sharpen your expertise.

What started as a need to clarify forecasting for decision-makers became a guide that demystifies demand forecasting for executives and professionals. Stephan Kolassa, Bahman Rostami-Tabar, and Enno Siemsen present forecasting through an accessible lens, covering everything from time series basics to advanced models like ARIMA and machine learning. You’ll learn not only technical methods but also how human judgment fits into interpreting forecasts, making this book practical for managers overseeing forecasting teams or anyone looking to grasp forecasting without a heavy math background. Chapters with worked examples make complex ideas approachable, though if you're deeply technical, some content might feel introductory.

During the evolving landscape of sales management, Gerard Assey offers a focused exploration of strategic sales forecasting that goes beyond basic predictions. You’ll find detailed discussions on how accurate forecasting can impact everything from resource allocation to risk mitigation, backed by real-world case studies and interactive exercises that bring concepts into practice. The book dives into various forecasting methods and tackles common challenges sales teams face, making it a useful tool if you're directly involved in shaping sales strategy. While concise at just over 100 pages, it’s particularly suited for those looking to refine their approach with contemporary insights rather than beginners seeking broad overviews.

This tailored book explores the evolving landscape of business forecasting by focusing on resilient and adaptive strategies that match your background and interests. It examines the latest 2025 developments, integrating emerging research to keep your forecasting skills ahead of the curve. The content reveals how to navigate new challenges and uncertainties, helping you build forecasts that respond dynamically to shifting market conditions. By concentrating on your specific goals and areas of focus, this personalized guide provides a clear pathway through complex, rapidly changing forecasting environments, ensuring you remain agile and insightful. Its tailored approach makes advanced concepts accessible and relevant, enhancing your ability to anticipate and prepare for future scenarios.

Abhishek Sharma challenges the conventional wisdom that business forecasting must be complex and inaccessible. This book distills key forecasting concepts specifically for management students, focusing on practical applications within business analytics. You gain insights into fundamental forecasting techniques tailored for MBA and PGDM curricula, including understanding data trends and predictive modeling basics. With its concise 70-page format, it suits those seeking a focused introduction rather than exhaustive theory. If you want to grasp essential forecasting tools to support managerial decision-making without wading through dense jargon, this book fits your needs well.

While working as a data scientist in top tech firms, Greg Rafferty noticed that many forecasting tools fell short in handling complex seasonal patterns and holiday effects. In this book, he guides you through building and fine-tuning time series models using Prophet, an open-source tool developed at Facebook. You'll learn practical skills like adding regressors, handling outliers, and running diagnostics to evaluate your models' performance. The book is well-suited for professionals seeking to improve forecasting accuracy with concise Python or R code, especially those managing business data with seasonal fluctuations and special events.