Logility announced two artificial intelligence (AI)-native capabilities designed to reimagine supply chain execution.
“At Logility, we’re committed to revolutionizing supply chain management with cutting-edge, AI-first solutions,” says Allan Dow, president and CEO of Logility. “Intelligent Order Response and the continued enhancement of Continuous Network Optimization reflect this commitment by addressing long-standing challenges in new and innovative ways. Traditional, manual, and subjective processes are giving way to strategies that democratize information, elevate human decision making, and allow organizations to rapidly build competitive advantage. We’re proud to help our clients transition from a ‘what happened’ view of the world to one that focuses on what’s coming.”
Key takeaways:
- Intelligent Order Response is an automated order allocation and optimization software application that uses AI to actively scan for and resolve demand-supply imbalances.
- Intelligent Order Response applies an AI-first approach to automate and optimize order fulfillment based on near-term business goals. Eliminating rigid allocation rules and manual processes, it is designed to intelligently allocate available supply of on-hand and incoming inventory to satisfy demand within a defined business window and in accordance with defined business goals.
- The responses provides intelligent matching, AI-first allocation ranking and resolution, accelerated insights, continuous monitoring and optimization and flexible decision support.
- The second is the next phase of enhancement for Logility’s Continuous Network Optimization capability, which will be expanded to provide AI-powered recommendations for incremental supply chain network adjustments and automate the realignment of the operating model.
- Serving as an “oil change” light for an organization’s network, the Continuous Network Optimization application is designed to continuously monitor network conditions and surface alerts when adjustments are needed to achieve defined business outcomes. Continuous Network Optimization is designed to use AI to proactively and continuously identify incremental changes to optimize results. Users can accept or decline recommendations and use automation capabilities to execute the changes.
