Days-of-cover per SKU = on-hand / 30D velocity. Surfaces stockout risk before it bites.
At a glance
Per-SKU days-of-cover, computed as Available ÷ avg_units_sold_per_day_30D. The forecasting view of inventory: which variants will OOS in 5 days, 14 days, 30 days, given current velocity?
| What it counts | For each active variant: totalInventory ÷ (units_sold_30D ÷ 30). Variants with zero sales in 30D are excluded (no velocity = undefined cover). The card surfaces a sortable list bucketed by cover-band. |
| VAT / tax treatment | Not applicable, count metric. |
| Shipping | Not applicable. |
| Discounts | Not applicable. |
| Refunds | Sales numerator includes refunded units (the velocity reflects gross demand, not net). For net-velocity, subtract refunded units; on the roadmap. |
| Cancelled / voided orders | Excluded from velocity if Shopify removed them. Included if still in index. |
| Currency | Not applicable. |
| Channels / sources | All channels contribute to velocity. POS draws same as online. |
| Time window | 30D velocity window; cover figure is real-time given current stock |
| Alert trigger | None directly; pair with workspace thresholds (e.g. “alert if any SKU in top-50 has <14 days cover”). |
| Roles | owner, operations |
Calculation
Calculated automatically from your Shopify data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A US apparel DTC brand on Shopify, ~1,800 active variants. 30D window 12 Apr 26 to 12 May 26. Top-by-velocity variants:| Variant | On-hand | 30D units sold | Days cover | Bucket |
|---|---|---|---|---|
| Linen tee, Sand, M | 8 | 240 | 1.0 | Critical (≤7d) |
| Linen tee, Sand, L | 32 | 220 | 4.4 | Critical (≤7d) |
| Wide-leg trouser, Black, 10 | 56 | 180 | 9.3 | At risk (8-14d) |
| Linen tee, White, M | 102 | 195 | 15.7 | Comfortable (15-30d) |
| Bucket hat, Olive, OS | 18 | 35 | 15.4 | Comfortable (15-30d) |
| Wide-leg trouser, Cream, 12 | 240 | 90 | 80.0 | Surplus (>60d) |
| Linen tee, Black, S | 480 | 30 | 480 | Surplus, slow-mover |
- Sand M is the urgent fire. 1.0 day cover; OOS imminent. PO arrival or stock transfer needed today. Cross-reference Inventory Alerts for the live OOS list including this SKU within hours.
- Sand L is on borrowed time. 4.4 days cover at current velocity. Standard reorder lead time is typically 14-21 days; this SKU will OOS before reorder arrives unless emergency stock transfer is arranged.
- The “at risk” bucket is the planning-priority list. 9.3 days cover means OOS in ~10 days; with normal lead times, the action window closes today. This is where ops attention should focus.
- Surplus on Cream 12 is signal. 80 days cover at 90 units/30D means demand is asymmetric across colour-size combinations. Cream 12 is a slow-mover; allocate fewer units in next PO cycle.
- Linen tee Black S has 480 days cover. Either over-ordered (capital tied up) or genuinely a slow-mover that should be marked-down or de-listed. Pair with margin-per-unit to decide clearance vs hold.
- Velocity assumes recent demand continues. Marketing pushes, viral moments, or seasonal peaks invalidate the assumption. Sand M’s 240 units/30D could collapse to 80 next month if the marketing wave passes; cover would extend to ~3 days from a single day. Pair with marketing calendar to forecast better.
Sibling cards merchants should reference together
Stock vs Sales velocity is the forecasting cousin. Companions:| Card | Why pair it with Stock vs Sales |
|---|---|
| Products with Zero/Negative Stock | The OOS list. This card predicts which non-OOS variants will fall onto that list next. |
| Inventory Distribution | The aggregate band view; this card is the per-SKU detail. |
| OOS Spike Alert | The acute-event alert. Stock-vs-sales is the steady forecasting view. |
| Top SKUs | Velocity drill-down by SKU; primary input to this card. |
| Top Products by Revenue | The £-weighted velocity. A high-velocity SKU might not be top-revenue if it’s a low-margin item. |
| Bottom Products | The slow-mover list; surplus-cover variants. |
| Fulfillment Rate | Persistent low-cover on top SKUs eventually drags fulfilment rate. |
Reconciling against the vendor’s own dashboard
Where to look in Shopify Admin: Shopify doesn’t expose days-of-cover natively. Closest reconstructions:- Reports → Inventory → Sell-through rate: shows what % of stock sold in a period; mathematically related but not days-of-cover.
- Apps like Stocky / Inventory Planner / Cogsy: typically expose days-of-cover and reorder forecasting.
- Reports → ABC analysis (Shopify Plus): SKU-velocity classification (A = top, B = middle, C = slow).
| Reason | Direction | Why |
|---|---|---|
| Velocity window | Either | We use 30D; Stocky may default to 14D or 60D. Different windows produce different velocity figures. Configurable in Nerve Centre → Inventory. |
| Lead-time inclusion | They include, we don’t | Stocky often subtracts vendor lead time from days-cover to give “days until OOS net of incoming”. This card is gross days-cover. |
| Trend smoothing | Different methods | We use simple-mean velocity; advanced apps may use exponential weighting or seasonality adjustment. |
| Multi-location | Aggregate | We sum across active locations; some apps split per-location. |
| Sync lag | Either | Inventory updates can lag 5-15 min during heavy write periods. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
| 3PL / WMS forecasting reports | Should align directionally | 3PL forecasts often include lead-time and PO-arrival data which this card doesn’t. |
amazon_sp.amazon_inventory_velocity | Independent | Amazon and Shopify are separate inventory pools unless multi-channel sync is enabled. |
Known limitations / merchant FAQs
What’s a healthy days-of-cover target? Depends on your reorder cadence and lead time:- Fashion DTC with 21-30 day lead times: target 30-45 days cover on top-velocity SKUs.
- Subscription consumables with 14-day fulfilment cycles: target 21-30 days cover.
- Slow-fashion with 60-90 day lead times: target 60-120 days cover.
- Fast-fashion with 7-14 day reorder: 14-30 days suffices.
- Daily ops: scan the Critical (≤7d) bucket. Reorder or transfer immediately.
- Weekly planning: scan At Risk (8-14d) bucket. Confirm POs are in flight; chase suppliers if not.
- Monthly review: scan Surplus (>60d) bucket. Decide markdown, clearance, or de-list.
- Quarterly forecasting: review velocity-by-SKU trends; tighten PO models for chronic over-orders or under-orders.
- Lead-time review: if Critical bucket is regularly populated, lead times are too long for your safety stock policy. Either widen safety stock or shorten lead times.
- Cross-reference with paid media: pause Google Ads / Meta on Critical-bucket SKUs, see Active Ads on OOS.