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Data Analytics for Supply Chain
YOUR PATHWAY TO SUCCESS
This 5-day course provides a practical introduction to data analytics techniques and their application in supply chain management. Participants will learn how to collect, clean, analyze, and visualize data to gain insights into supply chain performance, identify areas for improvement, and make data-driven decisions.
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Course Duration
5 Days
Course Details
This 5-day course provides a practical introduction to data analytics techniques and their application in supply chain management. Participants will learn how to collect, clean, analyze, and visualize data to gain insights into supply chain performance, identify areas for improvement, and make data-driven decisions. The course covers core concepts such as descriptive analytics, predictive analytics, and prescriptive analytics, using relevant software tools and techniques. Through real-world case studies and hands-on exercises, learners will develop the skills to leverage data analytics to optimize supply chain operations, reduce costs, and improve customer service.
The course emphasizes the importance of data-driven decision-making in modern supply chain management and the use of data analytics to gain a competitive advantage. It explores various data analytics tools and techniques, including statistical analysis, data mining, and machine learning. Participants will learn how to identify relevant data sources, clean and prepare data for analysis, apply appropriate analytical methods, and communicate insights effectively.
By the end of this course, learners will be able to:
- Collect and clean supply chain data.
- Apply descriptive analytics to understand supply chain performance.
- Use predictive analytics to forecast demand and anticipate disruptions.
- Apply prescriptive analytics to optimize supply chain decisions.
- Visualize data and communicate insights effectively.
- Use data analytics software and tools.
- Supply chain analysts
- Logistics professionals
- Inventory planners
- Demand planners
- Operations managers
- Anyone involved in analyzing supply chain data
Course Outline
5 days Course
- Introduction to Data Analytics for Supply Chain:
- The role of data analytics in supply chain management.
- Types of data analytics: Descriptive, predictive, and prescriptive.
- Data sources for supply chain analysis.
- Case study: Using data analytics to improve supply chain performance.
- Activity: Group discussion on the challenges and opportunities of data analytics in supply chain.
- Data Collection and Preparation:
- Data collection methods: Surveys, databases, and sensor data.
- Data cleaning and preprocessing: Handling missing data and outliers.
- Data integration and transformation.
- Practical exercise: Cleaning and preparing a supply chain dataset.
- Descriptive Analytics for Supply Chain Insights:
- Calculating key supply chain metrics: Inventory turnover, order fill rate, and on-time delivery.
- Visualizing data using charts and graphs.
- Identifying trends and patterns in supply chain data.
- Practical exercise: Analyzing supply chain performance using descriptive statistics.
- Descriptive Analytics for Supply Chain Insights:
- Predictive Analytics for Supply Chain Forecasting:
- Demand forecasting techniques: Time series analysis and regression modeling.
- Predicting supply chain disruptions.
- Using predictive analytics software and tools.
- Case study: Forecasting demand for a specific product.
- Predictive Analytics for Supply Chain Forecasting:
- Prescriptive Analytics for Supply Chain Optimization:
- Optimization models for supply chain decisions: Network design, inventory optimization, and transportation planning.
- Using prescriptive analytics software and tools.
- Communicating data insights effectively.
- Project: Developing a data analytics plan for a specific supply chain challenge.
- Prescriptive Analytics for Supply Chain Optimization:
