Table of Contents
Choose a Global Fortune 500 or a Fortune 500 company. You can also select from the Fortune 500 in Europe and the Fortune 500 Southeast Asia.
After selecting a company, read the annual or 10K reports. You can find reports and industry information on the following sites: SEC, Mergent, Mintel.
Analyze how the company leverages AI to enhance its products/services. Use time series forecasting to forecast future trends and offer strategic recommendations. Each group (or individual) will deliver a 15-20 minute presentation to the class, showcasing your insights and strategic recommendations.
Instructions
1. Company and Strategy
First, research your company to identify its current strategy. How does the company generate revenue? Which types of products and services does it offer? The best place to start is the company’s annual reports, which give a complete overview of its strategy, financial reality, and plans.
2. Provide Recommendations
After analyzing the yearly reports, analyze how the company uses AI in its products and services and try to generate recommendations.
Please don’t take AI answers at face value. For example, let’s ask for recommendations for AI integration at Adidas:
All of Adidas’s recommendations are irrelevant. The company already uses AI in waste, fabric tracing, and tracking and has been experimenting with AR try-ons since 2019. Every Fortune 500 company already does sentiment analysis, a basic AI application. Dynamic pricing, real-time inventory tracking, and personalization are also cornerstones of Adidas’ strategy.
AI bots are not always good at giving strategic recommendations because they might not know enough real-time data and context around a company to make business decisions. A better strategy is correctly understanding your company and its industry and developing creative ideas for additional AI integration or creating AI-driven products or services.
See, for example, an idea for Adidas ExZones.
3. Data gathering and forecasting.
After researching your company’s strategy and brainstorming ideas, please gather data for time-series forecasting.
The type of data you will collect will depend on what you suggest. Suggestions generally fall into two categories: revenue generation and cost savings. Each approach involves setting up one or more key variables and a timeframe in a CSV file.
For the first approach, revenue generation, consider how AI could forecast total sales/revenue for a company. This involves tracking a variable like sales/revenue over time to predict future sales patterns. Gather the data and store it in a CSV file. In your CSV file, include the sales variable in a time-based format, such as monthly or quarterly.