Analytics · 3PL & Warehousing
Inventory aging and dead-stock analytics
A distributor surfaced slow and dead stock across sites to free the cash and space it was consuming.
Microsoft FabricPower BIAzure SQLDAX measures
- Dead stock
- -21%
- illustrative
- Carrying cost
- Quantified
- per SKU
- At-risk stock
- Flagged
- early
- Sites covered
- All
- one view
Illustrative scenario · example figures
The challenge
Slow-moving stock accumulated quietly across sites, tying up cash and space, and nobody saw it until a warehouse ran short of room.
What we built
We built an aging model with days-on-hand, last-movement, and carrying cost by SKU and site, flagging dead and at-risk stock early.
- Aging buckets with days-on-hand and last movement by SKU.
- Carrying cost and space consumed by slow stock.
- Early flags for stock trending toward dead.
Outcomes
- Slow and dead stock is visible before it fills the warehouse.
- Cash and space tied up in excess inventory are recovered.
- Markdown and liquidation decisions are made on time.
Where the data came from
WMSNetSuiteSales historyCost master
Data is drawn from the systems the operation already runs on and delivered in the client’s own tenant.
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