Inventory Optimization Analyst

Ford México; Hermosillo; On-site; MXN 350,000 - 520,000; Full time

Job summary

Ford México is seeking a Supply Chain Inventory Analyst to optimize plant inventory levels, standardize planning parameters, and mitigate shortage risks. You will monitor DOH/BOH, turnover, and KPIs across planning systems, collaborating with Plants to implement action plans and lead digital inventory initiatives.

The role requires a strong background in analytics, MRP/ERP systems, and English communication.

Qualifications

• Bachelor's degree in Industrial engineering, Supply Chain, Logistics, or Data analytics.
• 3+ years of experience in supply chain, material planning, inventory control or logistics analysis.
• Knowledge of MRP/ERP logic and planning modules (SAP, CMMS/SMART, DDL).
• Advanced proficiency in Microsoft Office 365.

Responsibilities

• Analyze and monitor DOH/BOH and inventory turnover to meet targets.
• Identify slow-moving, excess, and obsolete inventory; define and implement actions.
• Collaborate with Plants and Materiel Planners to optimize inventory levels.
• Lead Kaizen and 8D problem-solving for inventory discrepancies and corrective actions.
• Develop and publish KPI dashboards tracking shortage risks and parameter adherence.
• Champion digital inventory tools to enable data-driven decisions.

Skills

English proficiency

Data analytics

Cross-functional collab

Problem solving

Excel/Office

Education

Bachelor’s degree in Industrial engineering, Supply Chain, Logistics or Data analytics

Tools

SAP

CMMS/SMART

DDL

Power BI

Job description

In this role, you will be responsible for optimizing plant inventory levels, standardizing parameters across planning systems, mitigating material shortage risks.

• Analyze and monitor Days of Inventory on Hand (DOH/BOH), inventory turnover to achieve corporate and plant targets.
• Identify slow-moving, non-productive, excess, and obsolete inventory identify root-cause, define and implement action plans.
• Support and partner with Plants to move forward with the activities to optimize inventory.
• Utilize advanced analytics platforms (e.g., Lean DNA, BI dashboards) to proactively identify critical shortages and bottleneck suppliers before line disruptions occur.
• Collaborate with Material Planners, Follow-up teams to take actions based on data.
• Lead continuous review and dynamic adjustment of the Plan for Every Part (PFEP), including safety stock levels, minimum/maximum parameters, order intervals, and batch lot sizes.
• Apply Lean and FPS principles to eliminate waste in material flow and inventory, tracking KPI’s in our control centers.
• Participate in and lead Kaizen and structured problem-solving initiatives (8D, 5-Why, Fishbone) to address inventory discrepancies, record accuracy issues, defining, implementing, and following up on corrective action plans.
• Champion the adoption of digital inventory tools across the MP&L organization to foster in data-driven decision-making.
• Develop, automate, and publish standard visual management reports (KPI dashboards) tracking parameter adherence and shortage risk trends.
• Bachelor’s degree in Industrial engineering, Supply Chain Management, Logistics, Data analytics or related technical field.
• 3+ years of experience in supply chain, material planning, inventory control, or logistics analysis.
• Knowledge of MRP/ERP logic and supply chain planning modules (SAP, CMMS/SMART, DDL, or equivalent).
• Advanced proficiency in Microsoft Office / Microsoft 365.
• Cross-functional collaboration and communication skills with a team-oriented mindset.
• Excellent structured problem-solving mindset.
• Strong verbal and written communication skills in English.

Preferred Qualifications

• Advanced proficiency in data analytics and data visualization tools (Microsoft Excel: Power Query/Pivot Tables; Power BI, QlikSense, SQL database querying, Python).
• Advanced Digital Tools: Direct hands-on experience with modern inventory optimization platforms and prescriptive supply chain software (e.g., Lean DNA, Blue Yonder, ML/AI.

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