Calculate line fill rate by dividing order lines shipped complete by total order lines. Measure SKU-level fulfillment performance.
Line fill rate measures the percentage of individual order lines that are shipped complete from available stock. Each order line represents a single SKU-quantity pair on a customer order. If an order has 5 lines and 4 are shipped in full, the line fill rate for that order is 80%.
Line fill rate sits between unit fill rate and order fill rate in terms of granularity. It is more detailed than order fill rate (which only records complete/incomplete) but more aggregated than unit fill rate (which counts every individual unit). This makes it an excellent diagnostic metric for identifying which SKUs or product categories are causing fulfillment problems.
Enter the number of order lines shipped complete and total order lines to calculate your line fill rate.
Supply-chain managers, warehouse operators, and shipping coordinators rely on precise line fill rate data to maintain efficiency and control costs across complex distribution networks. Revisit this calculator whenever conditions change to keep your logistics plans aligned with real-world performance.
Line fill rate is the best metric for diagnosing inventory fulfillment issues at the SKU level. While order fill rate tells you that orders are incomplete, line fill rate tells you how many lines are failing — and analyzing those failed lines points directly to the SKUs that need better stocking. It is the bridge between high-level service targets and actionable inventory improvements.
Line Fill Rate = (Lines Shipped Complete / Total Lines) × 100 Where: Lines Shipped Complete = order lines where full requested quantity was available and shipped Total Lines = all order lines received during the measurement period
Result: Line Fill Rate = 94.00%
Line Fill Rate = (4,700 / 5,000) × 100 = 94.00%. Out of 5,000 order lines, 4,700 were shipped in full. The 300 incomplete lines (6%) indicate SKU-level availability issues.
When order fill rate is below target, line fill rate tells you how bad the problem is. If order fill rate is 88% but line fill rate is 97%, it means a small number of failed lines are scattered across many orders. If line fill rate is also 88%, the problem is more pervasive.
Export all order lines that were not fully shipped and analyze by SKU, category, supplier, and warehouse. A Pareto chart of failed lines by SKU often reveals that 10-20 items cause 80% of the failures. These are the items that need immediate attention.
A good starting framework: A-items (high value, high velocity) → 99% line fill rate. B-items → 96%. C-items → 92%. These targets reflect the differentiated inventory investment strategy from ABC analysis and align service commitments with inventory economics.
Third-party logistics contracts often include line fill rate SLAs. A typical 3PL commitment is 98-99% line fill rate, with penalties for sustained performance below target. Clear measurement methodology and data sharing are essential for fair SLA management.
Line fill rate is the percentage of order lines shipped complete from available stock. An order line is a single SKU-quantity pair. If 4,700 out of 5,000 lines are fully fulfilled, line fill rate is 94%.
Line fill rate is always ≥ order fill rate. An order with 10 lines where 9 are complete has 90% line fill rate, but 0% order fill rate (since the order is not fully complete). Line fill rate gives a more detailed picture.
Unit fill rate counts individual units; line fill rate counts lines. A line with 100 units ordered and 99 shipped is 99% at the unit level but 0% at the line level (not fully complete). Unit fill rate ≥ line fill rate.
Common causes include inaccurate demand forecasting, insufficient safety stock, long supplier lead times, inventory count errors, and poor allocation logic in the WMS. Use this calculator to model different scenarios and find the best approach.
Focus on the SKUs that appear most often in failed lines. Increase their safety stock, improve their forecast accuracy, or find faster replenishment sources. A Pareto analysis of failed lines often reveals that a few SKUs cause most problems.
Unit fill rate ≥ line fill rate ≥ order fill rate. Each successive metric is more stringent. Improving line fill rate lifts order fill rate, and improving unit fill rate lifts line fill rate.
Yes. Unit fill rate shows overall inventory availability. Line fill rate diagnoses SKU-level issues. Order fill rate reflects the customer experience. Together, they give a complete service picture.
Yes. Modern WMS and OMS systems can calculate line fill rate at the point of allocation or pick release, providing real-time visibility into service performance by shift, day, or wave.