Inventory VisibilityD2CFMCGOperationsDataIndiaSystems

Inventory Visibility: The Missing Layer in Most Businesses

The business that does not know its real-time inventory position across every channel and location is making production, marketing, and cash flow decisions on data that may be days or weeks old and the decisions made on stale inventory data are consistently more expensive than the cost of the visibility system that would make them accurate.

Nirmal Nambiar

Author

26-04-2026
8 min read
Inventory Visibility: The Missing Layer in Most Businesses

Inventory visibility knowing precisely how many units of every SKU exist, where they are, and how fast they are moving at any given moment is the operational data layer that enables every other inventory management decision to be made correctly. Without it, the reorder decision is made on a number that was accurate two days ago. The marketing decision to scale spend on a SKU is made without knowing the inventory can support the demand. The production planning decision is made on last month's sell-through rather than on current velocity. The working capital forecast is made on an inventory value that has changed since the last count. Each of these decisions made on stale data is either unnecessarily conservative (forgoing revenue to avoid a stockout that would not have occurred) or unnecessarily aggressive (creating a stockout by scaling spend before the inventory can support it).

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The Three Inventory Visibility Gaps Most Common in Indian D2C and FMCG

Gap one: physical warehouse versus system count divergence. The system says 847 units. The physical count says 783. The 64-unit discrepancy is the accumulated result of receiving errors (units that arrived but were miscounted), pick errors (units that were picked but the system was not updated), return processing errors (units that were returned but not correctly received back into inventory), and damaged goods that were disposed of without system update. At 8.2% inventory inaccuracy, every planning decision made from the system count is wrong by 8.2% before the calculation begins. Gap two: multi-location inventory invisibility. The brand with inventory in its own warehouse, in Amazon FBA, in Flipkart FBF, and in a third-party fulfilment centre has units in four locations but often has visibility into only one of them in real time. The FBA inventory is visible in Seller Central. The FBF inventory is visible in Flipkart's portal. Neither is visible in the brand's own inventory management system, which means the total available inventory calculation requires manually checking four systems and adding the results together.Gap three: in-transit inventory blindness. The production run that left the manufacturer's warehouse three days ago is in transit to the brand's warehouse but is not yet in the system as available inventory even though it will be available in two days and affects the reorder decision that is being made today. The purchase order that was placed but not yet shipped is not visible in the system as incoming inventory. The return that is in reverse transit back to the warehouse is not visible as a pending inventory addition. All of these in-transit goods are real inventory that affects the accurate calculation of days-of-cover and future availability and they are invisible in most inventory management systems until the physical goods arrive and are processed.

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Building Real-Time Inventory Visibility

  • Connect every inventory location to the central inventory system via API Amazon FBA, Flipkart FBF, and any third-party fulfilment centre should feed their inventory counts to the brand's central WMS automatically, not require manual export and import
  • Implement barcode scanning at every inventory movement point receiving, pick, pack, return processing to eliminate the manual count errors that produce system-to-physical divergence
  • Add in-transit inventory tracking to the inventory visibility layer outstanding purchase orders with confirmed ship dates, production runs with confirmed dispatch dates, and returns in reverse transit should all be visible as 'expected incoming' inventory with arrival date estimates
  • Conduct monthly cycle counts on the top-20 SKUs by revenue and quarterly full-inventory counts to maintain system-to-physical accuracy with a root cause investigation for any variance above 2% that produces a specific process fix
  • Track inventory accuracy rate as a weekly KPI not just as an audit metric and hold the operations lead accountable for maintaining accuracy above 97%