Optimal Origin — Reshape the cost geometry from the source
Objective: minimize cost-to-serve and stockouts while improving delivery promise reliability.
What is Optimal Origin?
Algorithm that selects the best fulfillment node (DC, Store, Delivery Station) considering stock availability, distance, fleet capacity and promised delivery date.
Key KPIs
Split shipments
On-time
Rejects due to OOS
Cost of delivery
Fleet capacity
Stakeholders
Ops: Inventory managers & DC dispatch
Stores & Delivery Stations
Product / DS / Eng / UX
Finance: savings validation
Expected Benefits
Structural impact: reduce cost-to-serve from origin
Fewer splits / distance: better promise reliability
Synergy with OR: two flagship products for Supply Chain
Roadmap & Milestones
0M3M12M24M
Mockups
Baseline KPIs
Usability tests
Algorithm v1 → Pilot ready
Pilot in major city → Beta (city scale)
Execute Beta full-city (3M)
National rollout
Phase 1
Phase 2
Phase 3
● milestone