With Bicycle, the retailer unifies inventory, order, and replenishment data to detect stockout risk as it emerges, find the root cause, and act before top SKUs go unavailable.
One of India's largest online grocery retailers.
Across millions of orders a month, availability of top-selling SKUs directly drives revenue, customer satisfaction, and NPS. But out-of-stock events were caught manually or after the fact, and root causes sat buried across disconnected systems.
SKU availability, minimum base quantity, indent requests, and warehouse data sat across multiple systems, making it hard to see which SKUs were at risk of stockout or delayed fulfillment.
Store and replenishment teams identified out-of-stock events manually or only after they happened, leading to delayed interventions and missed orders.
Manual investigation across many systems consumed significant time, slowing replenishment cycles and SLA adherence when it mattered most.
Certain SKUs repeatedly went unavailable due to inaccurate base quantities, skipped indents, stacking delays, or late goods-receipt notes, with no early warning.
The retailer deployed Bicycle to unify inventory, order, and replenishment data across all stores and fulfillment centers, then turn it into real-time detection, root-cause analysis, and prioritized actions, without disrupting existing systems.
Bicycle continuously monitors top SKUs to flag potential stockouts before they happen, not after the order is missed.
Each out-of-stock event is classified into causes such as low base quantity, skipped indents, goods-receipt or stacking delays, and chronic supply-chain bottlenecks.
Early warnings trigger replenishment action so teams can prevent lost sales instead of reacting to them.
Centralized views bring out-of-stock trends, root-cause breakdowns, and SLA metrics into one place for every team.
Recommendations to raise indents, correct base quantities, or reallocate inventory reach the responsible team, and supply, category, and regional teams get self-serve access for data-backed decisions.
From reacting to stockouts to preventing them, one SKU at a time.
The retailer keeps top products on the shelf instead of chasing the orders it already lost.
Continuous monitoring and proactive replenishment keep top-selling products on the shelf, so more orders complete.
Root-cause analysis shifted from daily, after-the-fact reviews to real-time, in-day resolution of stockout risk.
Automated detection and prioritization replaced repetitive manual reporting, freeing engineering and analyst effort for higher-value work.
Category, planning, and supply-chain teams work from one source of truth, making faster, more confident decisions together.
Bring one revenue-critical KPI. We'll show how Bicycle detects the movement, explains the cause, and recommends the next step.