Performance Manager – Logistics Data

优缺点分析

角色解读

• Advance to Senior Performance Manager or Head of Logistics Analytics within Henkel.
• Move into broader supply chain strategy roles, leveraging global exposure and data expertise.
• Develop into a data science or AI specialist focused on logistics optimization.
• Develop and maintain logistics KPI dashboards and performance transparency reports for global leadership.
• Analyze transport and warehouse network data to model scenarios and support optimization decisions.
• Collaborate with regional logistics teams and IT to align data governance and improve data quality.
• Identify improvement opportunities and drive data-driven projects across Henkel's global logistics network.
• Strong data analytics skills: SQL, Power BI, Python, and experience with logistics systems like SAP, TMS, WMS.
• Solid understanding of supply chain and logistics operations, including performance measurement and network modelling.
• Project management capabilities to handle multi-stakeholder initiatives in a matrix organization.
• Excellent communication to translate complex data into actionable business insights.

申请策略

• Tailor your cover letter to show your passion for data-driven logistics and your pioneering mindset.
• Research Henkel's adhesive technologies business and understand how logistics performance impacts their supply chain.
• Emphasize your experience in logistics performance management and KPI development with measurable results.
• Highlight your technical skills: SQL, Power BI, Python, and any network modelling tools (Optilogic, SC Guru).
• Showcase project examples where you turned complex data into business recommendations that led to cost savings or efficiency gains.
• Include your ability to work in a global matrix organization, with examples of cross-functional collaboration.
• If not already proficient, learn one of the network modelling tools (e.g., Optilogic) to strengthen your candidacy.
• Deepen your knowledge of data governance and data quality frameworks, as mentioned in the job description.

面试指南

• For KPI questions: start by identifying business objectives, then propose metrics aligned with those goals, and explain how you would visualize and communicate them.
• For conflict resolution: use a structured approach – acknowledge stakeholders' interests, find common ground, propose data-backed trade-offs, and document decisions.
• For technical questions: describe your process from data extraction, cleaning, analysis, modelling, to insight generation, emphasizing business impact.
• How would you design a KPI dashboard for global logistics performance? Give examples of key metrics.
• Describe a time you used data to drive a significant improvement in logistics operations.
• How do you handle conflicting priorities from different regional stakeholders in a project?
• What experience do you have with transport or warehouse network modelling? Walk us through a project.
• How would you ensure data quality and governance across multiple systems and regions?