WeekSpot — Inventory & Risk Supply Chain × Finance

When inventory helps — and when it quietly hurts

1) Carrying Cost

2) Obsolescence / Last-Buy Risk

📦 Inventory Carrying Cost Calculator

Turn “inventory math” into a risk & cash conversation.

Carrying rate: — Annual: —

Average inventory value ($)

Avg units on hand (optional)

Unit cost (optional, $/unit)

Inventory value method

Cost of capital (%/yr)

Storage / space (%/yr)

Insurance + taxes (%/yr)

Shrink / damage (%/yr)

Handling / admin (%/yr)

Other (%/yr)

Optional: add an “obsolescence reserve” into carrying rate

Obsolescence reserve (%/yr)

If your org routinely writes off inventory, treat that as a “reserve rate” and put it here so carrying cost reflects reality.

Quick sensitivity
Slide carrying rate to see what “small %” does in $.

Rate: —

Sensitivity carrying rate (%/yr)

Use this when leadership says “carrying cost is only like 12%”…
and you want to translate that into cash.

Carrying rate

—

Sum of cost components (%/yr)

Annual carrying cost

—

What inventory “costs” just to exist

Monthly / daily

—

Cash drip you don’t notice

Scrollable Cost breakdown (shows your assumptions)

Tip: use this in a slide

Component	Rate	$/year

—

⚠️ Obsolescence / Last-Buy Risk Simulator

Compares policies under uncertainty (demand + obsolescence + lead time).

Risk: — Best policy: —

Horizon (months)

Simulations

Annual demand (units/year)

Demand volatility (stdev as % of mean)

Unit sell price ($)

Unit cost ($)

Lead time (months)

Review cycle (months)

Carrying rate (%/yr)

Stockout penalty ($ per unit unmet)

Obsolescence model

Obsolescence probability (% per year)

Salvage recovery (% of cost if obsolete)

This assumes a “sudden” obsolescence event can occur during the horizon. If it hits, remaining inventory is written down to salvage.

Policies to compare

Keep Inventory: target months of supply

“Keep” approximates a higher buffer / conventional planning.

Lean/JIT-ish: target months of supply

“Lean” cuts exposure but raises stockout risk under volatility.

Last-Buy: one-time buy quantity (units)

“Last-Buy” is a bet: pay carry + obsolescence risk to avoid future stockouts.

Run the simulation
Monte Carlo — results are “expected value” + tail risk.

Tip: If you’re teaching, run once with low volatility (5–10%) then again at 30–40% to show the trade.

Chart = expected profit (higher is better). The spread is explained in the table (P10/P90).

Expected profit

—

Average across simulations

Tail risk

—

10th percentile profit (bad case)

Obsolescence exposure

—

Expected write-down when it hits

Scrollable Policy comparison (profit + drivers)

Higher profit ≠ lower risk

Policy	Exp Profit	P10	P90	Stockouts	Avg Inv	Write-down

Run the simulation to generate an executive-ready explanation.