Logility’s latest Price and Promotion solution is designed to help consumer goods companies better manage their inventory needs when it comes to promotion activity.
The solution leverages machine learning to predict the impact of promotion activity on inventory, helping planners better understand changes in demand and, in turn, improve replenishment and inventory allocation to meet variances in expected sales.
It’s designed to complement traditional demand planning capabilities by managing pricing scenarios and generating a price-adjusted forecast to align inventory decisions with marketing campaigns. Machine learning and price elasticity models identify the expected lift in demand, allowing users to identify the ideal price while staying within the constraints of supply.
It also features a predictive model and interactive visuals to speed adoption and help planners understand the impact of pricing changes across product category, SKU, region, customer and warehouse location.
“Companies have access to enormous volumes of both structured and unstructured data; however, they lack the systems to harness and turn the information into insights that drive the business,” said Allan Dow, Logility president, in a statement. “Through advances in machine learning, Logility is able to help supply chains gain precision and accelerate better decisions on the impact of price changes and promotions to their supply chain plan.”