AI IN SUPPLY CHAIN MANAGEMENT

• Instructor introduction
• General housekeeping
• Course & assignment overview

Start off by gaining an understanding of the differences in AI, ML, and Data Science, and learn to identify practical use cases for each within the context of supply chain management.

• Automation & AI in supply chain: history & evolution
• AI-enabled supply chain management benefits
• Basic principles of AI: GenAI, ML, Data Science
• Case study #1: Negotiating With A Chatbot: A Walmart Procurement Case Study

Discover how to approach AI implementation in supply chain management. Cover everything from data collection, identifying use cases, and developing AI solutions.

• Preparing your supply chain for AI
• Identifying AI solutions & selecting appropriate tools
• Integrating AI with supply chain processes 
• Case study #2: Mars optimizes its supply chain with a digital twin

This class will highlight how data informs decisions. Learn to identify the necessary steps to prepare for implementing your AI use cases, such as understanding what insights to extract from data and how to change behavior in the organization.

• Data analysis in AI supply chain management
• Overview of data preprocessing techniques
• Exploratory data analysis (EDA) & supply chain datasets
• Skillset and mindset sourcing
• Demo #1: Data cleaning with AI (ChatGPT)

Assignment #1: Data Integrity Exercise
Using the provided raw data set, students will clean the data with the assistance of ChatGPT.

Explore key ethical and legal considerations in AI, including privacy concerns and areas to avoid. Learn to articulate ethical responsibilities and legal requirements with an understanding of how these regulations vary across different countries.

• Ethical considerations in AI for supply chain management
• Data privacy & security concerns
• Regulations & compliance
• Introducing ethical data analysis principles 

In class 5, you will learn what makes AI applications in demand forecasting a great use case, identify some easy wins with its implementation, and learn how to leverage an “orchestration” platform to achieve comprehensive end-to-end AI capabilities.

• Introduction to AI-driven demand forecasting
• Demand variability management
• Integrating AI with demand planning software

This class will demonstrate how AI can identify issues in inventory management, propose effective solutions, and implement actions to optimize inventory processes.

• AI in inventory management
• Using demand forecasting insights to optimize inventory levels
• Automated replenishment
• AI-driven inventory tracking and monitoring solutions
• Integrating AI with existing systems
• Demo #2: Demand forecasting & inventory optimization with AI

Dive into how AI can help in transport network optimization, reviewing common solutions for consolidation in transportation, and digital twin scenario modeling.

• AI in network optimization
• Solutions for consolidation in transportation
• Personalized network optimization solutions with AI
• Case study #3: DHL Network Digital Twin AI

Gain an understanding of the challenges associated with various modes of transportation and different types of suppliers, as well as the capabilities of service providers to improve solutions. Recognize the critical role of real-time tracking in enabling other AI-driven supply chain solutions.

• Business benefits of real-time tracking with AI
• The IoT sensors & devices
• AI-powered tracking & tracing systems
• Integrating AI tracking systems with existing and ERP systems
• Emerging solutions, compliance challenges & managing your partners
• Scalability

Learn to use Natural Language Processing-based AI solutions to improve customer satisfaction and craft a basic chatbot.

• Customer satisfaction: AI applications
• Natural language processing-based AI solutions
• Virtual assistants & chatbots
• Automating customer service tasks
• Case study #4: The great acceleration: CIO perspectives on generative AI

Assignment #2: Crafting a Chatbot
Set up a basic chatbot to help with customer support tasks.

Explore ways to use AI to check their data, read documents, minimize human error in translation, and digitalize common quality practices.

• AI-enabled analytics
• Predictive maintenance
• Contract reading & redlining AI
• Quality standards testing using AI techniques
• Documentation and digitization using AI capabilities 

Assignment #3: Collecting Data from Documentation with AI
Use Chat GPT to collect data from the provided mock documentation.

Delve into how AI can analyze large data sets to interpret and recommend solutions in the supply chain, helping to mitigate risks and proactively plan for disruption.

• Applications of AI in risk management
• Identifying risks with AI predictive analytics tools
• Assessing and prioritizing risks
• Formulating risk management & mitigation strategies with AI tools
• Demo #3: Using Everstream for risk mitigation

Assignment #4: Predictive Model
Set up a basic predictive model with the help of the AI tool covered in the class.

Understand the physical robotics and software capabilities of using AI to increase efficiency, enable automation, and improve reaction, proactive planning, and service levels.

• AI-powered automation in streamlining supply chain processes
• Supply chain tasks that can be automated with AI
• Process mining & areas for opportunity
• Building a portfolio of AI tools
• Integrating AI with existing systems
• Case study #5: DHL Control Tower process mining

In this class, learn how to deploy, test, and have confidence that an AI solution works, as well as know when to pivot to a different solution, model, or data set.

• Interpreting AI-driven results
• Determining success: goal, data size, tolerance
• Demonstrating value & ROI
• Actionable recommendations
• Communication strategies for stakeholders
• Case study #6: Smart Predictive ETAs at DHL

Assignment #5: Final Project - AI Implementation Plan
Create a pitch deck to demonstrate 3 use cases of AI applications for your business, using a provided framework.

Uncover the areas of opportunity to deploy AI-enabled solutions and how to stay competitive in Supply Chain Management, from exploring emerging trends, refining your resume, mastering interview techniques, and understanding how their current skills align with future AI-driven opportunities in the field.

• Emerging trends & future opportunities
• Resume & career outlook: Interview tips, LinkedIn presence, staying competitive
• Setting up success in AI in Supply Chain Management