Hidden cost of holding stock.

Inventory carrying cost is the annual cost of holding inventory: storage, insurance, obsolescence, damage, and capital tied up. Industry rule of thumb: 20-30% of inventory value annually. Slow-moving inventory can hit 35-50% carrying cost because obsolescence compounds. Fast-moving fresh inventory (food, fashion) can be 30-40% due to spoilage risk.

500,000 average inventory value × 25% carrying cost = 125,000 annual cost. That's the hidden cost of holding inventory. Reducing inventory 25% (to 375k) saves 31,250/year. Most businesses don't see carrying cost as a line item because it's distributed across rent, insurance, write-offs, and opportunity cost - but it's real and material.

Carrying cost breakdown: storage (8-12%), insurance + shrinkage (1-3%), obsolescence/damage (5-15%), capital cost (5-10%). Businesses with high inventory optimization (just-in-time, drop-shipping) carry near zero inventory and sidestep this cost entirely. Full supply-chain visibility software can cut carrying costs 20-30%.

Quick example

With avg inventory value of 500,000 and carrying cost of 25%, the result is 125,000.00. Change any figure and watch the output shift — it's often more useful to see the pattern than to memorise the formula.

Which inputs matter most

You enter Avg Inventory Value and Carrying Cost %. Frequency and unit price pull the total in different directions. The biggest surprise for most people is how small recurring amounts compound into large annual figures — that's where this calculation earns its keep.

What's happening under the hood

Annual carrying cost = inventory value × carrying cost %. Breakdown: storage + insurance + obsolescence + capital. The formula is listed in full below. If the number looks off, you can retrace the calculation by hand — that's the point of showing the working.

What to do with a low result

A disappointing result is information, not a judgement. Pick the single input that dragged the figure down most and focus the next quarter on that one factor. Breadth-first improvement rarely works; depth-first on the worst input usually does.

What this doesn't capture

The score is a composite of the inputs you provide. Life context — job security, family obligations, health, housing — doesn't appear in the math but shapes the real picture. Use the number as a prompt, not a verdict.