E-Commerce Fulfillment Reliability: Quantifying Order Promise Risk Under Inventory Inaccuracy, Pick-Pack Variability, and Carrier Uncertainty

Abstract

This article presents an engineering-oriented framework that models end-to-end promise fulfillment as uncertainty propagation across (i) inventory record confidence and SKU-level availability risk, (ii) pick-pack execution time variability including congestion and exception loops, and (iii) lane-dependent carrier transit time distributions that exhibit heavy tails and disruption regimes. The framework evaluates operational architectures in terms of distributional service outcomes relevant to engineering management, including probability of promise violation, conditional lateness severity, stockout-at-pick cancellation probability, wrong-item defect probability, and cost index under normal and disrupted conditions. A scenario-based quantitative study is developed for a generic multi-node network with two fulfillment centers and one drop-ship node serving standard and expedited commitments, and four architectures are compared: baseline fixed-buffer promise logic, increased automation without governance redesign, distribution-aware (quantile) promise setting with limited inventory control, and a governance-optimized two-tier approach that integrates inventory confidence scoring, staged verification for low-confidence commitments, dynamic routing under congestion risk, and dynamic carrier selection based on lane variance. Results show that reliability gains are driven more by controlling promise tail risk and preventing low-confidence inventory commitments than by improving mean pick rates alone, that adding automation without revising promise governance can increase mispromises during disruptions, and that the two-tier governed architecture reduces promise violations and cancellations while lowering exception-driven defects and stabilizing labor escalation. The article provides three copy-ready tables and complete prompts for scientific, data-driven figures suitable for Techne submission.