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.
In this blog, the spotlight is cast on the software that creates reports for management, the silent hero that translates the beauty of furious calculations into actionable reports. Watch as the calculations, intricately guided by planners utilizing our software, seamlessly converge into Smart Operational Analytics (SOA) reports, dividing five key areas: inventory analysis, inventory performance, inventory trending, supplier performance, and demand anomalies.
This article is about the real power that comes from the collaboration between you and our software that happens at your fingertips. We often write about the software itself and what goes on “under the hood”. This time, the subject is how you should best team up with the software.
I can’t imagine being an inventory planner in spare parts, distribution, or manufacturing and having to create safety stock levels, reorder points, and order suggestions without using key performance predictions of service levels, fill rates, and inventory costs.