If you work in supply chain, retail, or inventory-heavy industries like diamonds, you’ve probably heard these two terms constantly:

• Inventory Turn (or Turnover)
• Inventory Days (or Days Inventory Outstanding)

At first glance, they seem like two ways of saying the same thing. But they actually provide different perspectives on inventory performance.

Let’s break it down clearly.

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What is Inventory Turn?

Inventory Turn = Cost of Goods Sold (COGS) ÷ Average Inventory

What it means:

Inventory turn tells you:

How many times your inventory is sold and replaced over a period (usually a year).

Example (Diamond Industry)

Let’s say:

• Annual sales (COGS): $12M
• Average inventory: $4M

Inventory Turn = 12 / 4 = 3

👉 You are turning your inventory 3 times a year

Interpretation:

• Higher turns = faster-moving inventory
• Lower turns = slow-moving or aging inventory

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What is Inventory Days?

Inventory Days = 365 ÷ Inventory Turn

(or business days like 250, depending on your analysis)

What it means:

Inventory days tells you:

👉 How long (on average) inventory sits before being sold

Example (Same Data)

• Turn = 3

Inventory Days = 365 ÷ 3 = 122 days

👉 On average, a diamond sits for ~4 months before being sold

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The Core Difference (Simple Way to Think)

Metric	Perspective	Question it answers
Inventory Turn	Speed (frequency)	How many times do I sell my inventory?
Inventory Days	Time (duration)	How long does each item sit?

👉 Turn = velocity

👉 Days = waiting time

They are mathematically linked, but mentally different.

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Real-Life Diamond Industry Example

Let’s use your exact context (deployment model):

Scenario A: Strong Performance

• Average deployed inventory: $10M
• Annual sales: $20M

Turn = 2

Days = 365 / 2 = 182 days

👉 Each diamond takes ~6 months to sell

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Scenario B: Weak Performance

• Average deployed inventory: $10M
• Annual sales: $10M

Turn = 1

Days = 365 days

👉 Diamonds are sitting for a full year

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What This Means Operationally

• In Scenario A:
  • Retailers are actively selling
  • Replenishment cycles are healthy
  • Cash flow is strong
• In Scenario B:
  • Inventory is aging
  • Capital is locked
  • You risk markdowns or returns

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Why Both Metrics Matter (Not Just One)

Many people focus only on turn, but that can hide problems.

Example:

Two customers both have Turn = 2

But:

Customer	Pattern
A	Sells steadily every month
B	Sells everything in 2 months, then no sales for 10 months

👉 Same turn, completely different reality.

Now look at inventory days trend over time:

• If days are increasing → replenishment delay or demand drop
• If days are decreasing → improving velocity

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Key Insight: Turn is Outcome, Days is Behavior

👉 Inventory Turn is a result

👉 Inventory Days shows the underlying process

If you want to fix performance:

• Look at days (delay, bottlenecks)
• Measure turn (final outcome)

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Simple Analogy

Think of a restaurant:

• Inventory Turn = how many times tables are used per day
• Inventory Days = how long each customer occupies a table

You can increase turn by:

• Serving faster (reduce days)
• Increasing demand

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Final Takeaway

• Inventory Turn = How often you sell your stock
• Inventory Days = How long it takes to sell it
• They are mathematically linked but operationally different

👉 If you want to improve business:

• Reduce inventory days
• That will naturally increase inventory turns