What dead stock actually costs you
Every Indian distributor we have worked with underestimates their dead stock cost by a factor of two. The intuitive number is just the eventual write-down, and that alone is usually 3 to 5% of inventory value per year. The full economic cost is larger because dead stock keeps consuming things even while it sits.
- Capital cost. Money locked in stock that is not turning. At a 12% cost of capital, every ₹1 Cr of dead stock burns ₹12L per year before any other line.
- Warehouse and handling cost. Rack space, insurance, periodic recounts, occasional movement to free up space. Quietly 2-3% of inventory value annually.
- Write-down risk. Goods that lose value because they expire, become obsolete, or get damaged sitting on the rack. Pharma, electronics, and fashion-adjacent SKUs feel this hardest.
- Opportunity cost. The order you could not fulfil because cash was locked in dead SKU A and the moving SKU B went out of stock. The hardest cost to measure and often the largest.
Add the four together for a typical Indian distribution business and the real cost is 8 to 12% of inventory value per year. On a ₹4 Cr average inventory, that is ₹32L to ₹48L quietly bleeding out the bottom of the P&L every year.
How dead stock sneaks up on you
Nobody buys dead stock on purpose. It accumulates through three mechanisms that are individually invisible and only show up in aggregate at year-end.
- Gradual velocity decline. An SKU that used to sell 200 units a month is now selling 60. Still moving, so nobody flags it. Six months later you realise you ordered another 600 units in the meantime.
- Channel shift. General trade was the volume driver, modern trade has taken over, your SKU mix has not caught up. Fast movers in the old channel are slow movers in the new one.
- Supplier overrun. Minimum order quantity from the supplier is 500 cartons, your monthly off-take is 80, you ordered to avoid the next freight charge. Now you have 6 months of cover and demand has softened.
Report 1 - SKU velocity by godown
The foundation report. For each SKU at each godown, units moved in the last 7, 30, and 90 days, with the trend arrow. Run weekly. The point is not the absolute number, the point is the change. An SKU that was a fast mover at the Pune godown three months ago and is now a slow mover there is the earliest possible signal of either a regional demand shift or a stockout-driven distortion.
Most distributors only have this view at the company level, not the godown level. The trap is that an SKU can look healthy at company level while being completely stuck at one spoke godown. Per-godown velocity catches the local issue 6-8 weeks before company-level numbers do.
Report 2 - Age buckets per SKU
For each SKU, how much stock is 0-30 days old, 30-60, 60-90, and 90+, valued at landed cost. The 90+ bucket is the dead stock candidate pile. Anything sitting there for two consecutive weekly readings without depletion deserves an intervention, whether that is a scheme to push it, a return to supplier, or a clearance write-off decision.
The discipline is reading this report every Monday and asking one question per SKU in the 90+ bucket: what changes this week. If the answer is nothing, the SKU is dead and should be moved out of the active inventory plan.
Report 3 - Slow-mover trend
A list of SKUs whose 30-day velocity has dropped more than 30% from their 90-day average. This is the early warning, not the alarm. An SKU on this list for 3 weeks running is on its way to becoming dead stock. Catching it here means there is still demand to clear it through normal channels with a small push, instead of waiting until it sits in the 90+ age bucket and needs a discount or write-off.
Report 4 - Channel shift detection
Sales by SKU split by channel - general trade, modern trade, institutional, online - week over week. The pattern that matters is divergence. An SKU that is growing in modern trade and shrinking in general trade still looks flat at the company level. Without the channel split, you keep ordering for the wrong channel and the wrong pack size, building dead stock in one channel while running short in the other.
Report 5 - Supplier reorder cycle vs lead time
For each supplier and each SKU, your current days of cover versus the supplier's published lead time. The trap is the MOQ-driven over-order. A supplier with a 4-week lead time and an MOQ of 500 cartons forces a 6-month cover for any SKU where your monthly off-take is below 80 cartons. This report flags every SKU where days of cover exceed lead time by more than 3x, which is the pre-condition for dead stock from supplier overrun.
What each report catches and what to do
| Report | Catches | Action it triggers |
|---|---|---|
| SKU velocity by godown | Local demand shifts before company numbers move | Rebalance stock between godowns, adjust spoke ordering |
| Age buckets per SKU | SKUs sitting in the 90+ pile | Push scheme, return to supplier, or write-off decision |
| Slow-mover trend | Velocity drops of more than 30% on a 30 vs 90 day window | Marketing push, dealer scheme, or stop reordering |
| Channel shift detection | SKU growing in one channel, shrinking in another | Re-mix the order plan by channel and pack size |
| Supplier reorder cycle | Days of cover more than 3x lead time | Renegotiate MOQ, change order frequency |
The early warning signal in each report
- Velocity report: an SKU that crosses below 50% of its 90-day rolling average at any single godown for two consecutive weeks.
- Age bucket report: more than 8% of total inventory value sitting in the 90+ age bucket on any Monday read.
- Slow-mover trend: the same SKU appearing on the slow-mover list for 3 consecutive weeks. Signals structural decline, not a blip.
- Channel shift: more than 15 percentage point shift in channel mix for a single SKU month over month.
- Supplier reorder: any SKU with days of cover above 120 days when lead time is under 30 days. Almost guaranteed dead stock candidate.
What this looks like in rupees
A ₹50 Cr distributor running on quarterly inventory reviews typically holds ₹3 to ₹5 Cr of dead stock at any given moment. Running these five reports weekly does not eliminate dead stock, nothing does, but consistently brings it down to ₹50L to ₹1.5 Cr range. That is ₹1.5 to ₹3.5 Cr of working capital that goes back to the active business.
Why these need AI to be sustainable
The reports themselves are not exotic, any competent accountant can build them in Excel from Tally exports. The problem is sustaining the weekly cadence across hundreds or thousands of SKUs and multiple godowns. Manual builds last 4 to 6 weeks before someone gets busy and the discipline lapses.
An AI layer like KolossusAI for trading houses generates these five reports every Monday morning from your Tally data, ranks the SKUs that need attention, and lets your team ask follow-up questions in plain English. The reports become routine instead of a project. See the free 14-day POC for what week 1 looks like on your own data.