Blinkit Posts ₹102 Cr Adjusted EBITDA Despite ₹308 Cr Inventory Loss
Eternal’s quick-commerce business Blinkit reported ₹102 crore in positive adjusted EBITDA in Q1 FY27, while inventory expiry, damage, transit losses and theft accounted for 1.8% of ₹17,132 crore net order value—about ₹308 crore.
What happened
Blinkit, Eternal’s largest business, reported Rs 102 crore adjusted EBITDA profit in Q1 FY27. The quick-commerce platform disclosed inventory-related losses
Key facts
- Rs 102 crore positive adjusted EBITDA in Q1 FY27
- 1.8% of net order value lost to expired inventory, damaged goods, in-transit losses and theft
- Rs 17,132 crore quarterly net order value
- Approximately Rs 308 crore inventory-related loss
Why this matters
Blinkit’s scale and positive adjusted EBITDA strengthen its strategic value, but any partnership or acquisition case should price in substantial shrink-related costs and mitigation capabilities.
What to watch
- Inventory-loss rate as a percentage of net order value, especially whether it falls below 1.5% while order volume grows.
- Adjusted EBITDA margin and whether gains persist after accounting for shrink, new-store costs and customer incentives.
- Number and maturity mix of dark stores; a rising share of newly opened stores would raise execution risk.
- Changes in fresh and grocery assortment mix, which may increase perishability exposure.
- Management commentary on theft, expiry, transit damage, vendor recoveries and cold-chain controls.
- Competitive discounting or delivery-fee changes from Zepto and Swiggy Instamart that could force reinvestment of margin gains.
- Deploy store- and SKU-level shrink dashboards, with tighter controls for fresh, dairy, frozen and high-theft categories.
- Reduce expiry risk through smaller, more frequent replenishment cycles and demand-led assortment rationalization.
- Shift more inventory risk upstream through vendor terms, sale-or-return arrangements, packaging standards and damage claims.
- Increase use of dynamic markdowns and near-expiry promotions to recover value before write-offs.
- Link dark-store manager incentives to availability, waste, damage and theft metrics rather than order throughput alone.
- Prioritize expansion into clusters where mature-store operating processes can be replicated before adding complex long-tail assortment.