The Covid 19 pandemic exposed firsthand the critical challenges facing today’s distribution supply chains.
Unprecedented velocity, complexity, and uncertainty amplified an already daunting disconnect between traditional demand and inventory planning, where obsolete deterministic demand forecasts lead to inaccurate supply decisions for the world’s most essential commodities.
Unable to rely on conventional supply chain management methods due to the absence of historical data, supply and demand became impossible to predict or manage.
Without a fundamental shift in how distribution is strategically planned and executed, global enterprises remain at risk of exponentially increasing shortages, delays, and financial losses.
SCAS for Distribution Supply Chain Planning
SCAS, Seeloz’ Supply Chain Automation Suite, addresses these critical Distribution challenges through artificial intelligence, behavioral learning, and autonomous execution of replenishment and transfer orders. Here’s how:
- Rapid Diagnostic: An ERP-agnostic solution, SCAS connects to existing ERP modules to extract historical data.
- Cross Supply Chain View: Data from the ERP is used to generate a holistic cross supply chain view based on demand, inventory, and supply, factoring in supply chain constraints as well as relevant external data.
- Behavioral Learning: Through a once-initiated, frequently-refined behavioral training exercise, SCAS generates hundreds of millions of probable scenarios which cover all possible supply chain movements, learning to beat each scenario with precisely timed replenishment and transfer orders.
- AI Model: The output of behavioral learning exercises is an AI model which is effectively an optimized playbook, equipped to handle all possible supply chain behaviors.
- Scoring Engine: Continuously leveraging the AI Model, SCAS' scoring engine dynamically evaluates the current state of the supply chain to generate planned replenishment orders and optimized cross-warehouse movements
- Autonomous Execution: Outputs from the scoring engine are which are then pushed to the ERP for execution.
- Continuous Optimization: This ongoing cycle of learning, modeling, scoring, and execution enables continuous optimization of supply chain performance with no need for separately-generated forecasts or inventory planning parameters.
Through this AI-driven approach to Distribution Supply Chain Planning, SCAS effectively replaces DRPs and autonomously delivers the right quantities, to the correct locations, through optimal suppliers, at precisely the right time.
Benefits & ROI
In transforming supply chain planning, SCAS autonomously unlocks value throughout the supply chain, delivering tangible benefits to P&Ls and balance sheets.
For a billion dollar outbound supply chain with 100 million in average inventory and eight annual turns, SCAS reduces inventory by up to 25%, stockouts by up to 50%, and transportation costs by up to 40%.
These AI-enabled operational efficiencies result in 12 million in annual savings to the bottom line, 30 million in annual increase to the top line, and 14 days reduction in cash to cash cycle, drastically improving financial performance across outbound supply chains.
Get in Touch
To learn more about how SCAS is transforming global distribution supply chains with AI, watch this video and contact us to set up a demo.