Pros
Hands-on exposure to supply chain operations — got direct experience identifying bottlenecks and optimizing procurement processes. Practical data analysis work — applied Python, Excel forecasting, and QCDM analysis on real import and delivery data. Impactful outcomes — reduced inefficiencies by 17% and presented findings to senior leadership, gaining visibility. Tool proficiency — gained practical use of MS Excel, Power BI, and automation scripts for ETL processes. Mentorship & access to data — learned from the HOD and senior team, and worked on live datasets rather than simulated ones.
Cons
Limited cross-department exposure — most work was within the purchase domain, with fewer opportunities to explore manufacturing or operations directly. Short duration — only two months, which restricted the depth of long-term project involvement. Process rigidity — corporate procedures sometimes slowed down experimentation with new ideas. Data dependency — certain analyses relied on data availability/quality, which occasionally limited scope.