Increased forecast accuracy by 106% for shipments from China to 3 different gateways. He used regression and throughput yield concepts to develop a formula by gateway, day of the week, and potential order status to forecast dimensional weight required on each lane each day. Exceeded SMART goal of being 90% accurate 50% of the time. Led a project that reduced average cycle time for a major global manufacturer from order to manufacturing by 31%. Using DMAIC methodology with transactional lean analysis he and his team implemented a number of improvement actions that cut average cycle time from 17.5 to 12 hours. Exceeded his SMART goal of reducing cycle time by 25%. Delivered $1 Million under budget and 4 months early a project with a large US food retailer. He managed the team and project of integrating a new Transportation Management System (TMS) with legacy, ERP, and Warehouse Management Systems (WMS). He analyzed current-state and led team through design of future-state processes and structure using Kaizen facilitation techniques. Exceeded goal of delivering early and under-budget. Identified over $31 Million in yield improvement opportunities. Used a mixed integer program based on activity based costing numbers through an Essbase data cube to analyze infrastructure, emerging markets, shipping lanes, and equipment balancing. Redesigned, standardized, and streamlined logistics processes to consolidate 3 separate organizations into a single unit using a horizontal management model. Analyzed current-state processes & communication maps. Led the team in developing and implementing to-be processes with no go-live issues. Performed key data analysis using JMP and DMAIC methodology for a global company to uncover a more efficient ordering process based on enlightened customer segmentation. Analytical tools used to analyze this normal and non-normal data included distribution analysis, multi-vari analysis, variability gauge, control charts, ANOVA, correlation analysis, and best fit (linear and non-linear analysis) analysis. Met SMART goal of determining the most efficient process.
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