In the rush to fulfill orders quickly, operators often cut corners on accuracy, leading to significant issues over time. When accuracy is compromised, product availability can be misrepresented, resulting in customer dissatisfaction and operational inefficiency. For example, items marked 'in stock' falsely can lead to order cancellations and increase CS workload due to follow-up discrepancies. Moreover, inaccurate stock levels can disrupt supply chains due to missed replenishment signals. A Shopify store reported a 12% decline in repeat customer purchases after a fulfillment error cascade, all traced back to inaccurate inventory data. The ideal model is where inventory data integrity is prioritized, with clear ownership, proper checks, and SLAs ensuring responsible handling.