OTIF looks like a single, simple percentage — until you compare the number your ERP reports internally with the number on your retailer's scorecard. In food and beverage, that gap is exactly where penalties, chargebacks, and eventually delisting conversations start. Here's the real formula, the four ways F&B companies actually calculate it, and the five root causes that quietly break it.
(Order lines delivered OTIF / Total order lines) x 100One row per customer sales order line — customer × product × site × requested delivery date
Orders_Delivered_OTIF = shipments confirmed on-time AND in-full AT CUSTOMER RECEIPT.
dispatch confirmations, partial deliveries rounded up, shelf-life exceptions waived by CS.
in chilled dairy and ultra-fresh, 'on time' means within a 30-min dock booking window — not the calendar day. A truck arriving 47 minutes late is off-slot, regardless of the date.
Measures confirmed customer receipt, not supplier dispatch. The gap between OTIF (dispatch) and DIFOT (receipt) isolates transit and receiving failures. When to use it: As the primary external measure for calculating retailer penalties and managing customer relationships. This is the number your customer uses.
Each order's OTIF status is weighted by its financial value or case volume. A failure on a large promotional order has a greater impact than a failure on a small replenishment order. When to use it: To align operational priorities with commercial impact. A 95% blended OTIF that hides 80% on your top 3 customers is a major financial risk.
Segment OTIF performance for promotional SKUs versus the core range. Failures on promotional lines often carry contractual penalties 3-10x higher than base SKU misses. When to use it: During S&OP and demand control meetings to assess the true risk of promotional plans and allocate scarce inventory or capacity correctly.
Adds a third condition: order must be On-Time, In-Full, AND meet the retailer's minimum days-of-life requirement at receipt. A delivery can be OTIF but still rejected if the product is short-coded. When to use it: Mandatory for any chilled, fresh, or short shelf-life product category. This is the most accurate reflection of service level for perishable goods.
ATP logic includes QA-held stock as 'available'. The ERP's Available-to-Promise (ATP) calculation includes physically produced but legally unshippable stock, allowing planners to confirm orders against inventory that will fail its final lab release.
In the ERP (e.g., SAP CO09), check ATP for a batch on QA hold. If it shows as available, the configuration is wrong. Cross-reference average QA release time in the LIMS; if it's >24h, this is a critical failure point.
'Stock on Hand: 1,200 cases' in the ERP looks green. It doesn't distinguish between the 800 cases ready to ship and the 400 pending micro clearance.
Static transit times in TMS ignore seasonality. The Transport Management System (TMS) uses a single average transit time for a lane, failing to account for peak season port congestion or winter weather, leading to systematically late deliveries.
In the TMS, pull the last 12 months of 'planned transit time' vs 'actual POD time' for key lanes. If the variance exceeds 15% in peak months (e.g., July, November), the master data is wrong.
'Planned Delivery Date: 15-Nov' in the order confirmation looks achievable because it's based on a flawed, static lead time that doesn't reflect peak season reality.
WMS allocation logic is not strictly FEFO. The Warehouse Management System (WMS) is configured to pick for location efficiency, not strict First-Expiry-First-Out (FEFO), sending product with less remaining life to customers with strict shelf-life SLAs.
Run a WMS pick-list report for 10 recent orders of a short shelf-life SKU. Compare the expiry date of the picked batch against other available batches in the warehouse. If an older batch was left behind, FEFO is not being enforced.
'Warehouse pick efficiency: 110 cases/hour' looks great. It hides the fact that pickers are grabbing the most convenient pallet, not the one with the correct expiry date, creating a shelf-life failure downstream.
Sales allocation override bypasses ERP pick sequence. A senior Sales manager, under pressure to hit a key account target, verbally instructs the DC to re-allocate stock from a confirmed order to their priority customer, causing an In-Full failure for the original order.
This is often invisible to systems. Spot it by comparing the ERP's original 'confirmed order' list from 72 hours pre-dispatch with the final WMS 'shipped order' list. Unexplained discrepancies for non-priority customers are a red flag.
'Key Account Volume: 105% of target' is celebrated in the sales meeting. The cost of the service failure and penalty invoice for the customer who was short-shipped is booked to the supply chain P&L.
No logistics capacity check in the S&OP demand sign-off. The S&OP process approves a consensus demand plan without a binding sign-off from Logistics confirming that transport capacity is available and contracted for the planned volume, especially during peaks.
Review the S&OP meeting minutes and demand control template. If there is no mandatory sign-off field for 'Logistics Capacity Confirmed', the process is flawed. Confirm by checking if 'On-Time' failures spike predictably during every promotional period.
'S&OP Plan Accuracy: 96%' looks solid. This metric confirms the business built a great plan, but it doesn't confirm the plan was executable in the physical world.
Isolate QA-Held Stock from ATP. ERP ATP calculation includes non-releasable stock → Configure ERP to exclude all 'QA-Hold' storage locations from the ATP calculation → 'In-Full' failures due to promising phantom stock drop within 7 days.
Update TMS Transit Time Master Data. TMS uses outdated, static transit times → Run analysis of actual carrier POD data for the last 6 months and update master data for top 20 lanes → 'On-Time' failures due to unrealistic planning reduce immediately.
Mandate FEFO-compliance Reporting. WMS allows non-FEFO picking for efficiency → Create a daily exception report flagging any pick where an older batch was available but not selected → Reduces risk of short shelf-life rejections.
Reallocate OTIF Penalty Cost to Commercial P&L. Sales confirms unserviceable promotions, but Supply Chain carries the penalty cost → CFO signs off on a new rule: all OTIF penalties resulting from a promotional forecast error >15% are allocated to the relevant Sales channel's P&L → Commercial team is forced to balance volume ambition with operational reality.