Dead stock and inventory turnover: what your ERP is hiding

The fastest way to find ₹10–30 L of locked working capital in most SMBs is to look at their slow-moving inventory. The numbers are sitting in the ERP. Nobody pulls them.

Here is a working method for inventory turnover and dead stock identification: pragmatic, runnable on any ERP that has stock items and stock movement vouchers.

The two numbers that actually matter

Forget the textbook ratios for a moment. For an owner running a real business, two numbers carry most of the signal:

1. Days of inventory on hand (DoIH) per SKU: at the current consumption rate, how many days before this SKU runs out?
2. Last-movement date per SKU: when was this SKU last sold or consumed?

Together, these tell you what is moving (low DoIH), what is fine (medium DoIH, recent movement), and what is dead (no movement in months OR DoIH > 365).

How to compute it

Pull two things from your ERP:

• Current stock per SKU, per location.
• Outward movement per SKU, per day, for the last 180 days (sales + branch transfers out + consumption for manufacturing).

Then per SKU:

avg_daily_outward = sum(last_90_days_outward) / 90
DoIH = current_stock / avg_daily_outward          # ∞ if no movement
last_movement = max(date) where outward > 0

Two extra fields:

• velocity_band: bucket DoIH into bands: <30 fast, 30–90 normal, 90–180 slow, >180 very slow, ∞ dead.
• value_locked: current_stock × cost_per_unit. Sort dead/slow SKUs by this.

A typical 5,000-SKU distributor finds that 12–18% of SKUs by count carry 30–45% of the locked capital. That is the list.

Definitions that actually work in India

Be deliberate about the cutoffs; they matter:

• Dead stock: zero outward movement in the last 180 days AND current stock value > ₹5,000. The value cutoff prevents the list from being polluted by ₹50 SKUs that just happen to have been quiet.
• Slow-moving: DoIH > 180 days, but had at least one movement in the last 90 days.
• Excess: DoIH > 90 days for an A-class SKU (top 20% by revenue). Usually a buying mistake.

These are starting cutoffs. Tune them for your industry. Pharma SMBs use 60/120 thresholds because batches expire; steel traders use 365/730 because slow-moving is normal.

What you do once you find it

The dashboard is the easy part. What you do next:

1. Group dead stock by category and branch: usually one branch or one buyer is responsible for most of it. That is a process problem, not a stock problem.
2. Compute value at cost and value at NRV (net realisable value, what you can actually sell it for now). The gap is the real loss.
3. Decide per item: return to supplier, transfer to another branch where it moves, discount and clear, write off.
4. Set a rule: any SKU with no movement for X days enters the clearance queue automatically next month. Otherwise it accumulates again.

The discipline is what makes the dashboard pay back. Without it, the same dead stock list shows up six months later, slightly longer.

Inventory turnover (the ratio)

If you want the headline ratio:

inventory_turnover = COGS_annual / avg_inventory_value

For Indian SMB benchmarks:

• Pharma distribution: 8–12
• FMCG distribution: 10–15
• Steel/building materials: 4–7
• Electronics retail: 6–10
• Apparel: 3–6 (seasonality)

A turnover ratio below the band for your sector means working capital is sitting still.

Doing this with AnalytAI

Inventory analysis is one of the standard reports we ship for Tally and ERP customers. Connect once, see SKU-level DoIH, value-locked and the dead-stock list within the first afternoon. Drill from a category to the branch to the SKU to the last voucher.

Book a 20-minute demo and bring one Tally company. We will run the dead-stock report on it during the call.

Related reads:

• Branch-wise profitability
• Cash flow forecasting from Tally