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Overdue orders: how to measure and reduce them

The number of overdue orders shows how many customer or internal orders have not been fulfilled within the agreed time after the Promise/Due Date. It is an indicator of supply chain reliability, planning, and execution discipline.

What the metric measures

The presence and depth of delays in the order portfolio. It helps identify bottlenecks (inventory, production, QA, transport) and minimize the impact on OTD/OTIF and customer satisfaction.

Calculation

  • Overdue Orders (units) = No. of open orders where today > Promise/Due Date
  • Overdue Rate, % = Overdue Orders / All open orders × 100
  • Average Days Late and P95 to assess depth
  • Aging buckets: 1–3, 4–7, 8–14, 15–30, 30+ days
  • For partial shipments — count by the unfulfilled balance; for delivery SLAs — by the delivery date

Use promised/confirmed dates, unified calendars/time zones, and correct cut-offs.

Calculation example

420 orders were due in a month and 38 shipped after the promised date. Overdue share = 38 / 420 × 100 = 9%. A breakdown showed 25 of the 38 delays were caused by missing components from one supplier.

Data sources

ERP/1C (orders, promised/requested/ship/delivery dates), WMS/TMS (actuals), CRM (SLA), APS/MES (production plan vs. actual), QA/hold, customer/warehouse/calendar reference data.

Interpretation

  • Growth in overdue orders — shortages, overloaded bottlenecks, delays in approvals or transport
  • Low share — mature S&OP, realistic promises, managed buffers
  • Prioritize large/long delays with the greatest impact on revenue/NPS

Useful breakdowns

  • Customers / channels / regions
  • Warehouses / production sites
  • Categories/SKU; partial vs full shipments
  • Delay reason codes
  • Carriers / Incoterms

Dashboard visualizations

  • Trend of Overdue Count/Rate
  • Aging buckets (stacked)
  • Pareto of delay reasons
  • Top 20 customers/SKUs by overdue amount
  • Map of overdue orders by warehouse/region; status kanban

How to set targets

Set thresholds for Overdue Rate and P95 Days Late, prioritization rules, and SLAs for eliminating root causes; set up alerts and response playbooks, and check the impact on OTD/OTIF.

Common mistakes

  • Using requested instead of promised dates
  • Ignoring partial shipments and the difference between ship vs delivery
  • Including frozen/canceled orders
  • Inconsistent calendars/time zones
  • Incorrect or missing delay reason codes

Questions for discussion

  • Which 3 actions within 14 days will reduce the Overdue Rate the fastest?
  • Where is the "bottleneck": inventory, production, QA, documents, or transport?
  • What is the impact of −5 days in P95 Days Late on OTIF and revenue?

Questions and answers

How do you count overdue orders?

The number of orders completed after the agreed date, and their share, % = overdue / all orders due in the period × 100.

Why do orders become overdue?

Missing materials, overloaded production, unrealistic dates promised during the sale, equipment breakdowns and planning errors.

How do you reduce overdue orders?

Agree dates based on actual load, monitor critical materials, review at-risk orders daily and analyse the causes of delays.