Summer 2023

Journal of Business Forecasting Volume 42 | Issue 2 | Summer 2023

This issue dives into the question of why demand planning is slow to adopt machine learning, despite the technology being readily available. The core challenges are discussed, namely that that machine learning was built for the digital world and not the real world, how its outputs are difficult to apply to business decision making, and how the data requirements exceed what many companies can access. A practical pathway to get started in machine learning is provided. Other highlights of this issue include a reshoring case study from a multinational chemicals company which documents the planning implications of repatriating production and useful advice for those looking to take the leap.

Featured Articles:

• Why Aren’t Demand Planners Adopting Machine Learning? Why You Should Take the Leap

  By Olga Gerasymchuk

• 20 Questions With a Planning Leader

  By Sara Park

• Case Study: Fixing Supply Chain Planning for a B2C Services Business

  By Willem van Oppen

• Reshoring Case Study: A Chemical Company Shifts Supply Chain Strategies

  By

  • Patrick Bower
  • Zachary Fisher
• What did Tech Companies Get so Wrong? Forecasting for Subscription-Based Businesses

  By Larry Lapide

• The Alpha & Omega of Product Lifecycle Management

  By Eva Dawkins

• Macroeconomics & Demand — Understanding Seismic Drivers of Change

  By Mark Lawless, ACPF

• The US Economy Proves Incredibly Resilient

  By Nur M. Onvural