Job Description
- Collect and analyze operational and business data;
including performance metrics, process flows, and business or finance related information, to identify trends, patterns, and areas of improvement. Utilize solid analysis techniques and tools to draw meaningful insights from the data. Provide insights and recommendations based on data analysis to support decision-making processes.
- Develop and implement performance metrics and key performance indicators (KPIs) to measure the efficiency, and quality of logistics services. Monitor and track these metrics regularly to identify areas for improvement and compare performance against organizational goals.
- Conduct root cause analysis to identify the underlying reasons for inefficiencies, bottlenecks, and operational challenges. Collaborate with cross-functional teams to investigate and address the root causes, implementing corrective actions and process improvements.
- Identify opportunities for process optimization and reengineering to streamline operations, reduce costs, and improve productivity. Collaborate with stakeholders to implement process changes, utilizing lean methodologies and best practices.
- Develop and present regular reports and dashboards to communicate operational performance. Highlight key findings, challenges, and recommendations to management and other relevant stakeholders.
- Identify and utilize appropriate technology solutions and analytical tools to automate data collection, analysis, and reporting processes. Stay up-to-date with industry trends and advancements in data analytic and performance measurement.
Job Requirement
- Bachelor's or Master's degree in business analytic, logistics, or a related field.
- Proven experience in business intelligence, data analysis, or supply chain operations.
- Strong analytical and problem-solving skills, with proficiency in data analysis and statistical techniques.
- Proficient in using data visualization and reporting tools, such as Tableau or Power BI.
- Advanced skill in SQL and other data science related programming like R or Python is preferred.
- Experience with forecasting and predictive analytic, machine learning, and other advanced analytic techniques.
- Excellent communication and presentation skills, with the ability to convey complex information in a dear and concise manner.
- Strong attention to detail and ability to manage multiple projects and priorities.
- Ability to work collaboratively in a team environment and influence stakeholders at various levels.