Failure Mode and Effects of IoT in a Global Pharmaceutical Company, Identified and assessed potential failure modes in IoT devices, systematically categorizing risks based on severity and probability to strategically prioritize and implement targeted mitigation efforts, resulting in a 30% reduction in downtime and a 15% increase in device reliability metrics., Applied redundancy measures and predictive maintenance strategies, reducing IoT-related downtime by 30% and improving overall equipment effectiveness (OEE) by 15%. Quality in Practice: Customer Focus at Amazon, Integrated customer feedback into continuous improvement processes, resulting in a 20% increase in customer satisfaction and a 15% reduction in product returns, significantly improving overall performance., Utilized data analytics to achieve a 25% uplift in conversion rates through personalized product recommendations based on customer behavior and preferences. Prediction Using Logistic Regression in R, Developed logistic regression models with an average accuracy of 85% in predicting customer churn, leading to a notable 30% reduction in churn rates and substantial improvement in customer retention metrics., Validated models using cross-validation techniques, achieving a precision of 80% and recall of 75%, optimizing model performance for real-world application.