Days of cover
How many days of forward demand the current stock-on-hand will satisfy at the current sell-through rate — the operator-friendly view of inventory health.
By Oana Bradulet
Days of cover (sometimes days of stock cover or stock cover days) measures how many days of forward demand your current inventory can satisfy at the current sell-through rate.
If a SKU has 1,000 units on hand and is selling 50 a day, days of cover is 20 — meaning the current stock will run out in 20 days unless replenished.
It's the metric operators actually look at. It answers the question "how worried should I be about this SKU?" in a single number.
The formula
Days of Cover = Stock on hand / Average daily demand
Worked example. A SKU has 1,500 units on hand. Looking at the last 4 weeks, demand averaged 350 units/week, or 50 units/day.
Days of cover = 1,500 / 50 = 30 days
That tells the planner: at current sell-through, this SKU lasts 30 days. If the supplier lead time is 35 days, you're already late on the next order.
Days of cover vs DIO
These get confused but answer different questions:
- Days Inventory Outstanding is a backward-looking accounting metric: how many days of past COGS does the average inventory balance represent? Used for financial reporting.
- Days of cover is a forward-looking operational metric: how many days of expected future demand does the current stock satisfy? Used for daily operations.
DIO smooths over short-term swings. Days of cover responds to them immediately. A SKU with growing demand will show declining days of cover before DIO budges.
Sell-through rate matters more than the formula
The maths is trivial. The hard part is choosing which "average daily demand" to use.
- Last 7 days. Most reactive; can swing wildly on noise.
- Last 28 days. Smoother; standard for stable categories.
- Last 13 weeks. Smooths seasonality but lags structural trend changes.
- Forward forecast. Uses your demand plan, not historical actuals. Best for SKUs with seasonality or known upcoming events.
Most planning processes use last-28-days for stable SKUs and a forecast-based view for seasonal or promo-affected ones. Mixing methods within one report is fine — what matters is that each SKU's metric reflects the right denominator for its demand pattern.
Days of cover thresholds
Operationally useful bands, calibrated to lead time:
- Days of cover < lead time → stockout risk; reorder now if not already in flight
- Days of cover ≈ lead time + safety period → on plan; no action needed
- Days of cover > 2× lead time → carrying excess; check whether forecast has dropped or buying ran ahead
- Days of cover > 90 days on consumer goods → likely a slow-mover; investigate write-down or markdown
These bands aren't rules — they're starting points. The right thresholds depend on the SKU's lead time, demand variability, and category lifecycle.
When days of cover misleads
Three traps:
- Promo about to start. A SKU showing 60 days of cover under normal sell-through might be 2 days of cover during a 50% sale. Always check the marketing calendar.
- Recent stockout depressing the denominator. A SKU that ran out 10 days ago will look like it has more days of cover than it actually does, because the recent demand average is artificially low.
- Seasonal SKU at end-of-season. A summer SKU with 30 days of cover entering September is not in danger of stockout — it's about to enter a season where demand collapses. Forecast-based denominator beats trailing-average denominator here.
Each of these is solved by using a forward forecast as the denominator instead of trailing actuals — but only if your forecast is good enough to trust.
Why operators love this metric
Three reasons it dominates the daily planning view:
- Single number per SKU. No interpretation required.
- Direct comparison to lead time. If days of cover < lead time + safety, you're late.
- Trend is meaningful. A SKU dropping from 45 to 30 to 18 days of cover over three weeks is sounding an alarm; the absolute number plus the trajectory tells the story.
Pair days of cover with stockout rate and in-stock rate and you have the trio of metrics that drive most daily replenishment decisions.
Formula
- Stock on hand
- = Current sellable units (excludes damaged, allocated to specific orders, in QC)
- Average daily demand
- = Recent average — usually 28-day trailing for stable SKUs, forecast-based for seasonal
Worked example
1,500 units on hand. Last 28 days averaged 50 units/day demand. Days of cover = 1,500 / 50 = 30 days. If the supplier lead time is 35 days, you're already late on the next order.
Common mistakes
- →Using last-7-days demand on a noisy SKU. The denominator swings too much; the days-of-cover number becomes unreliable.
- →Forgetting that a recent stockout depresses the denominator — making days of cover look healthier than it is.
- →Not checking the marketing calendar before acting on days of cover. A promo can collapse a comfortable cover number to a stockout in a week.
- →Treating days of cover as a planning metric for long-lead inventory. For long-lead, use the forward demand forecast over the lead-time period; days of cover is for short-horizon decisions.
How Lumina handles days of cover for scaling brands
Lumina monitors days of cover per SKU, per location — and flags the products where the cover warrants action, whether that's too little or too much.
Frequently asked questions
What are days of cover?
What's the difference between days of cover and DIO?
What's a healthy days of cover number?
What demand period should I use for the calculation?
Why does my days of cover number jump around?
Related terms
Weeks of supply
How many weeks of forward demand the current stock-on-hand will satisfy — the weekly-cadence equivalent of days of cover, used in retail and wholesale.
Inventory turnover— Inventory Turnover Ratio
How many times you sold through your average inventory over a period — usually a year.
Stockout rate
The percentage of SKUs (or SKU-days) that are out of stock — a direct measure of how often you're disappointing demand.
Reorder point— Reorder Point (ROP)
The stock level at which you trigger the next purchase order, calculated to land replenishment before you run out.