The Smart Forecaster
Pursuing best practices in demand planning,
forecasting and inventory optimization
Improve Forecast Accuracy, Eliminate Excess Inventory, & Maximize Service Levels
In this video tutorial Dr. Thomas Willemain, co–Founder and SVP Research at Smart Software, presents Regression Analysis, a specialized statistical modeling technique to identify and harness leading indicators to achieve more accurate forecasts. Regression analysis is a statistical procedure to estimate the relationship between a response variable and one or more predictor variables. Housing starts, for example, might be a good leading indicator of vinyl siding demand. Tom explains how and when to use regression analysis and works through a practical example.
People involved in the supply chain are likely to have questions about various inventory terms and methods used in their jobs. This note may help by explaining these terms and showing how they relate.
Are you confused about what is AI and what is machine learning? Are you unsure why knowing more will help you with your job in inventory planning? Don’t despair. You’ll be ok, and we’ll show you how some of whatever-it-is can be useful.
In this article, we’ll walk you through the process of crafting a spare parts inventory plan that prioritizes availability metrics such as service levels and fill rates while ensuring cost efficiency. We’ll focus on an approach to inventory planning called Service Level-Driven Inventory Optimization. Next, we’ll discuss how to determine what parts you should include in your inventory and those that might not be necessary. Lastly, we’ll explore ways to enhance your service-level-driven inventory plan consistently.