peiyan ye

Led data-driven last-mile logistics operations across Massachusetts, managing DSP performance to achieve over 98% 24-hour on-time delivery and a 15% improvement in customer satisfaction. Built data-driven performance monitoring using Excel, SQL, and Tableau to evaluate DSP metrics such as completion rate, on-time delivery, return rate, and customer complaints, enabling informed operational and management decisions. Optimized exception parcel handling by improving SOPs for failed deliveries; analyzed root causes including address inaccuracies and system-identified positioning errors to reduce re-delivery costs and service delays. Streamlined workflows and strengthened upstream and pre-dispatch controls by monitoring parcel inbound timeliness and sorting accuracy, collaborating cross-functionally to drive continuous process improvements and scalable operational solutions.

Provided data support to optimize operations, ensuring the timeliness and accuracy of data across multiple departments, including manufacturing, logistics, and sales. Conducted daily data verification and analysis, identified and resolved data discrepancies, and facilitated cross-departmental information flow to enhance operational efficiency. Collaborated proactively with manufacturing and logistics teams to optimize data collection processes; performed data cleansing and variance analysis using Excel to ensure data consistency; communicated with sales and project teams to verify information and prepared data visualization reports for management decision-making. Significantly improved data accuracy and cross-departmental collaboration efficiency, streamlined information transmission, and delivered reliable data support to aid company operational decisions.

• Responsible for analyzing trends in public discourse on the Nestlé brand and making a problem structuring visually check out what is the trend and producing daily reports to feedback to Nestlé. • Employed data collection techniques to capture customer feedback on brand products, contributing to the generation of valuable insights into customer requirements and preferences.

• Collected and analyzed data related to competing products. This included an in-depth study of customer evaluations of these products. • I conducted comprehensive customer research initiatives, engaging with the customer base to gather feedback and opinions regarding the company's products. This data collection and analysis provided valuable insights into the specific needs, preferences, and pain points of our customers. Based on the feedback I help the company to select new products to be developed next. • By identifying commonalities and distinctive characteristics among the products, I was able to discern and capture emerging market trends, allowing for proactive decision-making in response to market shifts.

Relevant Coursework: Fall 2023: MISM6200 : Intro To Business Analytics MISM6202 : Foundations of Data Analysis for Business MISM6205 : Data Wrangling for Business BUSN6200 : Career Management Spring 2024: MISM6206 : Modeling for Business MISM6210 : Information Visuals and Dashboards for Business MSIM6212 : Data Mining and Machine Learning for Business MISM6213 : Business Information Design, Quality and Strategy Summer1 2024: MISM6214 : Business Analytics Capstone Fall 2024: MKTG6200 : Creating and Sustaining Customer Markets MKTG6234 : Marketing Analytics