In the logistics sector, the meaning of OTIF is “on time, in full”: every order must arrive within the agreed date/slot and with everything the customer purchased, with no shortages or errors. In practice, OTIF measures the ability to meet SLAs and the customer promise, with a direct impact on service costs, loyalty, and brand reputation. The formula is simple: OTIF = Orders delivered on time and complete / Total orders, multiplied by 100.
Peak season risks: what damages OTIF and picking accuracy
During the e-commerce peak season, operational stress amplifies every small inefficiency. There are three typical causes of OTIF decline. The first is courier lead-time variability, which becomes unpredictable exactly when volumes grow; without multi-carrier orchestration and updated assignment rules, orders end up on congested lanes, with delays and storage. The second is inventory data quality: if logical stock does not reflect physical stock, picking suspensions, last-minute substitutions, and backorders multiply, eroding the “In Full.” The third is human error in picking and packing, which rises when teams expand and shifts get longer. All this directly hits order picking accuracy and, consequently, OTIF, because more outbound errors mean more rework, more delays, and more parcels that fail to meet the promise.
Processes and layout to increase order picking accuracy
Order picking accuracy increases when the layout guides the movement and the system guides the choice. A slotting map based on real demand shortens routes and reduces aisle transitions, grouping product families that are frequently sold together. A clear separation between inbound, picking, and packing areas prevents flow interference, while packing stations equipped with weighing and automatic scanning detect weight or barcode mismatches that reveal an error.
Here, Hubrise solutions help make quality repeatable. With One Touch, the operational gesture is standardized by reducing unnecessary steps between systems and peripherals, so operators perform consistently even under pressure. Thanks to Picking, you can orchestrate the picking strategies best suited to your catalog, managing waves, batches, and priorities based on shipping deadlines.
Orchestrating shipments to protect OTIF
A high OTIF doesn’t depend solely on the warehouse; the choice of carrier and service makes the difference between on-time delivery and storage. Orchestration starts from data: historical performance by ZIP code, daily saturation, real first-attempt times, and tracking quality.
Exception handling and returns without impacting KPIs
No peak is perfect; exception events happen, but the difference lies in how quickly you detect them and how effectively you contain them. It’s important not to sacrifice order picking accuracy to recover speed: reworking an error always costs more than shipping thirty minutes late. An effective model includes smart outbound checks, dynamic thresholds on warehouse KPIs, and an operational log that identifies under-target areas in real time. When volumes explode, “managing by sight” is not enough; you need a platform that coordinates roles, priorities, and corrective actions without creating bottlenecks.
The return must also be considered part of OTIF, because incomplete or incorrect orders turn into reverse logistics, refunds, and customer effort. Managing returns without impacting KPIs means bringing the return flow back into the same process framework, with clear rules on inspection, reintegration, and stock updates. Maintaining the integrity of returned stock reduces the need for substitutions and protects the “In Full” of subsequent cycles. In this context, warehouse management ensures inventory alignment throughout the entire cycle, picking stabilizes fulfillment even with extended teams, and One Touch reduces manual steps that, under stress, generate errors and delays.