Days of Inventory on Hand (DOH): Formula, the Lead-Time Threshold, and When to Act
Compare accounting inventory days with operational stock coverage and understand the limits of average-demand and decay models.
Jainul Vaghasia/Published /Updated /7 min read
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In a closed-loop procurement platform — where demand signals, purchase orders, supplier replies, receiving, and inventory updates all stay in one connected record — the most useful question is not "how much do I have?" but "how long will it last?" Days of inventory on hand (DOH) answers that second question. It is the number of days current on-hand stock will cover at the current rate of consumption before an item runs out.
Quick answers
What is days of inventory on hand? DOH is the number of days current on-hand inventory is expected to last at the current consumption rate. When DOH reaches zero, the item will stock out.
What is the DOH formula? Two formulas exist. The real-time formula — the one that matters for procurement decisions — is:
The two measure different things. Real-time DOH tells you when an item will run out. Accounting DOH tells you how capital-efficient your inventory position was over the past year.
What is the critical DOH threshold? When DOH drops below , the item will run out before the next order can arrive — the stockout window is open. Including a safety buffer, the real alert threshold is .
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How does DOH relate to reorder point?Reorder point (ROP) is an inventory quantity: the on-hand unit count that triggers a new order. DOH is a time duration expressing the same risk. They are two views of the same threshold: ROP ≈ DOH_threshold × daily consumption rate. Both require consumption rate as the shared input.
On-hand quantity is the actual stock count — units physically in possession that have not been committed to open orders or allocated to production.
Daily consumption rate is how fast the item is used per day: sales units per day plus any decay or shrinkage loss. For items with a POS integration, this is computed from a rolling average of actual sales. For recipe ingredients, it is derived from recipe usage multiplied by daily production volume.
Worked example
A specialty retailer carries 80 units of whole-bean coffee. Sales run at 12 units per day.
Real-time DOH = 80 ÷ 12 = 6.7 days
The item will run out in 6.7 days under current conditions. The procurement question is immediate: is 6.7 days enough coverage given this supplier's lead time?
This says the business carried about 46 days of inventory value relative to what it sold — a capital-efficiency measure. Useful for investor analysis and year-over-year benchmarking. Not useful for knowing whether any individual item will stock out this week.
Accounting DOH is the arithmetic inverse of inventory turnover: Inventory Turns = COGS ÷ Average Inventory, so DOH = 365 ÷ Turns. If turns = 8, accounting DOH = 45.6 days. Use inventory turns when benchmarking capital efficiency across periods or comparing to industry norms; use per-item real-time DOH when making replenishment decisions.
The critical threshold: DOH versus lead time
The key operational insight is the comparison:
If DOH < lead time → stockout window is open
If real-time DOH on an item is 6.7 days and the supplier delivers in 4 days, you have 2.7 days of buffer — probably fine. If the supplier takes 8 days, you are already inside the stockout window: an order placed today will not arrive before the item runs out.
The correct alert threshold accounts for lead-time variability and service-level confidence:
Safety DOH threshold = lead time + safety stock days
safety stock days = safety stock units ÷ daily consumption rate
where safety stock in units is z × σ × √(lead time) and z is the z-score for the target service level (1.65 for 95%, 1.28 for 90%, 0.67 for 75%).
Worked example with safety buffer
A retailer: daily consumption 12 units, lead time 4 days, daily-demand σ = 3 units, 95% service level target (z = 1.65).
Safety stock = 1.65 × 3 × √4 = 9.9 units
Safety stock days = 9.9 ÷ 12 = 0.83 days
Safety DOH threshold = 4 + 0.83 = 4.83 days
When DOH falls below 4.83 days, the item is in reorder territory. This is mathematically equivalent to the reorder point: ROP = (12 × 4) + 9.9 = 57.9 units. DOH and ROP are two expressions of the same threshold — DOH in days, ROP in units.
Coverage with a fractional-loss assumption
A loss-only expression I(t) = I0 × (1 − d)^t never reaches zero for 0 < d < 1. To estimate coverage with ongoing use, include consumption explicitly:
I(t + 1) = (1 − d) × I(t) − c
This is the recurrence used by the current planning calculation. Estimate the time until modeled usable stock is exhausted, keeping fractional days and rounding conventions explicit. For d = 0 and positive c, it reduces to on-hand / c.
The loss rate is a scenario input, not a shelf-life or food-safety decision. Confirm the product’s actual expiry and storage requirements separately. With zero consumption, a finite depletion date may not be meaningful; show insufficient evidence rather than an arbitrary forecast.
DOH and demand variability
For items with high demand volatility, the DOH number is itself uncertain. An item with a coefficient of variation (CV²) above 0.49 has erratic demand: the average consumption rate might be 12 units per day, but realized daily demand fluctuates enough that 6.7 days of DOH could be consumed in 4 days during a spike or stretched to 10 during a slow stretch.
This is why the Syntetos–Boylan Classification (SBC) framework matters: erratic and lumpy items need larger safety buffers (higher z in the safety stock formula) to achieve the same service level as smooth-demand items. Their effective DOH threshold should be wider, not tighter. For smooth-demand items (CV² ≤ 0.49), the DOH number is reliable enough to use directly in reorder logic.
Set coverage from the actual replenishment problem
Use SKU demand, relevant incoming orders, supplier lead time, committed demand and usable-stock limits. Portfolio accounting days and operational days of supply answer different questions; one category average cannot set every item’s reorder policy.
Why accounting DOH misleads operators
The accounting DOH formula is often the first version operators encounter — in financial coaching sessions, accounting software dashboards, or industry benchmarking reports. It is useful for capital-efficiency analysis across the full inventory base. It fails in three ways when applied to procurement decisions:
It is backward-looking. It measures the past year, not current stock. A business that built holiday inventory in November and burned it by February will show a reasonable aggregate DOH for the year while specific items run critically low in March.
It aggregates across all SKUs. A 120-day item averaging with a 2-day item produces a 61-day aggregate that hides both the over-stocked slow mover and the stockout risk. Procurement decisions require per-item DOH, not a portfolio average.
It uses cost value, not units. A high-cost, slow-moving item inflates aggregate DOH while a low-cost, high-velocity essential may be simultaneously at risk. Cost-weighted averages do not surface that mismatch.
Operational, per-item DOH from current consumption rates resolves all three problems.
Apply this to a real purchasing record
LineNow's purchasing workflow connects purchase orders, supplier replies, receiving and accounting handoff. In a demonstration, inspect usable on-hand, the daily usage estimate, confirmed inbound timing and an item with insufficient history.
Use the result to agree the fields, decision owner and exception process. A linked purchasing record supplies evidence for this analysis; it does not by itself prove a particular dashboard, financial outcome or automatic approval policy.