Introduction:

This 5-day training course focuses on the various models and strategies for inventory optimization, providing participants with the tools and techniques to enhance inventory management, reduce holding costs, minimize stockouts, and improve overall supply chain performance. Participants will explore the different types of inventory optimization models, including deterministic and probabilistic models, and how to apply them effectively in real-world settings. The course will also emphasize the integration of technology, data analytics, and forecasting tools to support inventory optimization.

Objectives:

By the end of this training course, participants will be able to:

1. Understand the importance of inventory optimization and its impact on cost reduction and service levels.
2. Apply various inventory optimization models to different business scenarios.
3. Use demand forecasting and lead time analysis to improve inventory decision-making.
4. Develop strategies for balancing inventory costs with customer service levels.
5. Utilize data-driven techniques and software tools to enhance inventory optimization.
6. Evaluate the performance of inventory systems using key metrics and KPIs.
7. Integrate advanced inventory optimization models with supply chain strategies.

Who Should Attend:

This course is ideal for professionals involved in inventory management, supply chain, logistics, and operations who want to deepen their understanding of inventory optimization techniques. It is particularly beneficial for:

• Inventory and Supply Chain Managers
• Operations Managers
• Logistics Coordinators
• Demand Planners
• Procurement and Purchasing Professionals
• Business Analysts focused on inventory or supply chain optimization
• Anyone responsible for inventory control, stock management, and forecasting in an organization

Day 1: Introduction to Inventory Optimization

Morning Session:

1. Course Overview and Objectives
   • Icebreaker activity
   • Review of course structure, goals, and expectations
2. The Basics of Inventory Optimization
   • What is inventory optimization?
   • Key concepts in inventory management: safety stock, reorder points, and order quantities
   • The trade-off between holding costs, ordering costs, and stockout costs

Afternoon Session:

1. The Role of Inventory Optimization in Supply Chain Management
   • How inventory optimization supports overall supply chain efficiency
   • Linking inventory optimization with demand forecasting, procurement, and distribution
2. Types of Inventory Models
   • Introduction to deterministic vs. probabilistic models
   • The role of demand variability and lead time in optimization models

Case Study:

• A review of real-world examples where inventory optimization improved business performance

Day 2: Deterministic Inventory Models

Morning Session:

1. Economic Order Quantity (EOQ) Model
   • Key components of the EOQ model: demand rate, order cost, and holding cost
   • How to calculate and implement EOQ to minimize total inventory costs
   • Advantages and limitations of EOQ in different business contexts
2. Reorder Point and Safety Stock Calculations
   • How to calculate reorder points based on lead time and demand
   • Determining safety stock levels to buffer against variability
   • Balancing customer service levels with inventory holding costs

Afternoon Session:

1. Lot Sizing and Batch Ordering
   • Techniques for determining optimal lot size in production and distribution environments
   • Batch ordering and its application in inventory optimization
2. Just-In-Time (JIT) Inventory Optimization
   • How JIT strategies align with inventory optimization goals
   • Implementing JIT in warehouses and production environments to reduce waste and improve efficiency

Workshop:

• Hands-on calculation of EOQ, reorder points, and safety stock for a sample product

Day 3: Probabilistic Inventory Models

Morning Session:

1. The Newsvendor Model
   • Introduction to the Newsvendor Model for single-period inventory problems
   • Balancing the costs of overstock and understock
   • Using the model for products with uncertain demand (e.g., seasonal products)
2. Demand Forecasting and its Impact on Inventory Optimization
   • The importance of demand forecasting in probabilistic models
   • Methods for demand forecasting: moving averages, exponential smoothing, and regression analysis

Afternoon Session:

1. Multi-Period Inventory Models
   • Managing inventory over multiple periods using probabilistic models
   • The role of dynamic programming in multi-period optimization
2. Service Level and Inventory Optimization
   • Setting service levels: customer demand expectations and cost trade-offs
   • Determining optimal inventory levels to meet service goals while minimizing costs

Case Study:

• Applying the Newsvendor Model and multi-period models to a real-world scenario

Day 4: Advanced Inventory Optimization Models and Techniques

Morning Session:

1. Advanced Forecasting Techniques for Inventory Optimization
   • Time series analysis and machine learning for accurate demand forecasting
   • Integrating Artificial Intelligence (AI) and Machine Learning (ML) in inventory optimization
2. Inventory Optimization in the Context of Supply Chain Networks
   • Multi-echelon inventory optimization: coordinating inventory across multiple levels of a supply chain (suppliers, warehouses, and distribution centers)
   • Collaborative inventory management with suppliers and customers

Afternoon Session:

1. Stochastic Inventory Models
   • Introduction to stochastic models: managing uncertainty in demand and lead time
   • How to incorporate probabilistic factors into inventory decision-making
2. Inventory Optimization Software and Tools
   • Overview of software solutions for inventory optimization (e.g., ERP systems, specialized inventory management software)
   • Implementing and integrating these tools into your inventory management processes

Hands-on Exercise:

• Using a software tool to model inventory optimization for a multi-location warehouse setup

Day 5: Performance Measurement and Implementation of Inventory Optimization Models

Morning Session:

1. Key Performance Indicators (KPIs) for Inventory Optimization
   • Defining and using KPIs to monitor inventory efficiency (e.g., inventory turnover, stockout rate, order cycle time)
   • Continuous monitoring and reporting to ensure the optimization model is effective
2. Inventory Performance Analytics
   • Techniques for analyzing inventory performance using data analytics tools
   • Identifying bottlenecks and inefficiencies in the inventory process

Afternoon Session:

1. Implementing Inventory Optimization Models
   • Steps for implementing the most appropriate inventory optimization model based on business type and goals
   • Overcoming common challenges when transitioning to optimized inventory management systems
2. Future Trends in Inventory Optimization
   • The impact of emerging technologies like blockchain, IoT, and robotics on inventory optimization
   • The role of sustainability and circular economy principles in future inventory strategies

Final Project:

• Presenting an inventory optimization strategy for a sample company, including the choice of model, key assumptions, and expected outcomes

Closing Remarks:

• Review of key takeaways from the course
• Certification and next steps for applying inventory optimization models to real-world business challenges

Certification:

Upon successful completion of the course, participants will receive an Inventory Optimization Models Certification.