I led a 14-week supply chain transformation for a $1B+ Consumer Goods client in Mexico, starting with a 1-week impact assessment that secured executive buy-in through a Letter of Proposal. Acting as Engagement Manager across two workstreams, I deployed the first prescriptive control tower on GCP with a BigQuery data foundation and SAP ECC fit-gap mapping—replacing Excel-heavy manual practices. Within six weeks the tower was live with four modules, enabling recurring control-tower meetings, coaching client leaders through their first Steering Committee with Co-Presidents, and delivering $5M realized impact with a $2M pipeline while designing the future-state supply chain blueprint.

I partnered with a $10B+ North American food manufacturer to address the lack of structured cross-functional collaboration and backward-looking analytics. In a 12-week engagement, I built forward-looking KPIs on truck utilization and redeployment costs, deployed a prescriptive control tower within four weeks, and integrated MOJRO’s third-party optimizer to enable multi-stop shipments that respected operational constraints. This provided planners real-time visibility to minimize penalties and reduce redeployment costs. Over 30+ control tower meetings were run, 70+ planners were trained, and the initiatives delivered $4M realized impact with a $15M pipeline opportunity.

I partnered with a $5B US-based EV manufacturer on an 11-week engagement to manage obsolescence risk during a major vehicle phase-out. Through weekly war room meetings, I eliminated risk tied to maintaining EOL safety stock by building a safety stock cockpit and providing leadership with scenario-based insights on obsolescence exposure at different service absorption rates. When data sources switched 10 weeks before cutover, I developed an automated workflow with a 10-second turnaround to convert vehicle sequences into part-level requirements. I also embedded enhancements into the new tracking process, building client analytics capabilities and institutionalizing sustainable obsolescence management.

I served as an expert during a 2-week diagnostic for a $1B US-based packaging and plastics manufacturer, identifying a $30–60M opportunity through network optimization. My analysis highlighted structural inefficiencies in the supply chain footprint and surfaced actionable levers for cost reduction and service improvement, setting the stage for a transformation roadmap.

I partnered with a $2B+ US-based building products distributor facing severe service level issues and inflated inventory after the pandemic. In a 6-week diagnostic, I uncovered root causes across inventory, warehouse operations, network design, systems, and processes, estimating a $1.4B enterprise value unlock. Leading the transformation phase, I pivoted their operations to a hub-and-spoke model, stood up 4 new hub facilities, and redesigned operations at their largest site—driving $70M gross procurement savings. I optimized SKU-location inventory targets, ensured a seamless transition while safeguarding 98% fill rates, and revamped warehouse operations with a mission control room reporting directly to the CEO. By redesigning system architecture, upgrading processes, and building client talent pipelines, the program delivered a 5–7pp fill rate improvement in 3 months and reduced inventory by $100M in 9 months.

I partnered with a $10B US-based alcoholic beverage client for ~1 year, beginning with a Letter of Proposal and driving the design of their future-state supply chain architecture across end-to-end processes. I led the advanced planning system (APS) vendor selection process—from requirements gathering to vendor demos—developing a scoring methodology with cross-functional stakeholders in Business and IT to shortlist vendors for the proof-of-concept phase. I built a bottoms-up business case for APS implementation, presented directly to senior leaders including the SVP of Product, Director of Finance, and Director of IT. To strengthen execution, I created a model to track unplanned cost drivers via the control tower (e.g., order swaps, transfers, imports) and launched a pilot hypercare program at a DC that achieved 100% OTIF while surfacing immediate process improvements. This work laid the foundation for APS adoption, future-state process maps, and solution architecture.

I independently led the design and development of control tower dashboards for the coffee business unit of a $15B US-based beverage company. Working remotely, I supervised and trained a junior analyst, coached client associates and business analysts on supply chain concepts, and demonstrated how to use the tool effectively. The solution provided end-to-end visibility into excess/deficit inventory, rebalancing opportunities, forecasting inaccuracies, production plan adherence gaps, and order cuts—critical given the shelf life of coffee products. To ensure sustainable impact, I conducted capability-building and model transition sessions with the client team, embedding the control tower into daily operations.

I led the workstream to design the future supply chain network for a $3.5B US-based apparel giant, independently owning model development, stakeholder syndication, and alignment with McKinsey leadership—delivered remotely during the COVID-19 outbreak in India. My analysis identified that to reduce costs and accelerate e-commerce fulfillment, the client needed to transition to a multi-location SKU network, shift inventory toward the East Coast, and expand its East Coast facility by 2x. This strategy is projected to unlock $100M in working capital savings by 2026 and $375M by 2031 compared to the momentum case, creating a long-term competitive advantage.

I independently led the design and development of control tower dashboards for two companies in Dominican republic, enabling the client to proactively manage exceptions during control tower meetings. The dashboards allowed prescriptive actions such as cancelling, delaying, expediting, or creating new purchase orders, giving the client real-time visibility into their supply chain. This solution improved inventory management, reduced inefficiencies, and embedded a sustainable mechanism for exception-based decision-making.

I partnered with a $3B medical device client under pressure to release $60M from working capital, strengthen planning maturity, and improve service levels amid COVID-related disruptions. The client faced complexity from 60+ ERP instances, SKU proliferation, quarter-end merchandising volatility, poorly planned launches, and limited cross-functional collaboration. I developed a future-state operating system, guided technology selection, and defined the technical solution blueprint. Leading the holistic planning transformation, I drove process upgrades, capability building, and change management, while deploying Kinaxis RapidResponse as the core planning solution. The program delivered ~$60M inventory reduction and a 15pp increase in forecast accuracy.

I partnered with one of Mexico’s largest retailers to deliver a 35% reduction in logistics costs while simultaneously improving service levels. Following the merger of two enterprises, I optimized the network design using Llamasoft Supply Chain Guru, improved transport utilization, streamlined warehouse operations, and reduced duplicate flows and costly store-to-store transfers. The initiative unlocked significant cost savings and operational efficiency, positioning the retailer for scalable, post-merger growth.

In 2018, I partnered with a $7B Latin American aerospace OEM to reduce inventory through the deployment of a digital control tower. Over 52 weekly control tower meetings, I identified and executed 200+ prescriptive actions that improved supply chain decision-making and visibility. The initiative unlocked an additional $80M in impact value while embedding a sustainable governance model for ongoing inventory optimization.

In 2017, I optimized the supply chain network of a $15B US-based beverage company using Llamasoft’s Supply Chain Guru X. The engagement involved designing optimal roles for facilities—whether as distribution centers, cross-docks, or double bottoms—across a highly complex network of 13 manufacturing plants, 85 distribution centers, 24 cross-docks, 43 double bottoms, 12,443 customers, and 21 product families. The recommendations enabled more efficient flows, reduced logistics costs, and improved service reliability at scale.

I developed predictive models using machine learning algorithms (CART and Random Forest) to forecast post-installation service visits at a customer level for a major UK telecommunications provider. Covering nearly 10 million customers, the models predicted the likelihood of a service visit within a two-month horizon and identified installation process issues that most frequently triggered callbacks. These insights enabled the client to proactively address root causes, reduce unnecessary service visits, and improve customer experience.

I optimized the supply chain network for a major European healthcare OEM by modeling all customer and inter-facility flows to evaluate baseline and alternative network scenarios. Factoring in freight, handling, brokerage, and other qualitative costs, I recommended new location strategies that minimized total costs. One of the recommended alternatives delivered potential savings of up to €1M, while strengthening the client’s network design and long-term resilience.

I conducted a Marketing ROI analysis and developed monthly retail forecasts for the Ford Ecosport in India, applying statistical models to capture both internal drivers (volume, variable and fixed marketing spend) and external drivers (online traffic and Google Trends). I provided insights on optimal marketing spend allocation through competitive benchmarking, which led the client to increase variable marketing spend by ₹10,000 per unit in December 2014—driving a 41.4% month-on-month increase in retail sales. The work was reported directly to the Executive Director of Marketing, Sales & Service for Ford India, providing both measurable impact and first-hand exposure to executive-level decision-making.