1.1: Introduction to Economics 1 - economic flow

1. Course Introduction:

  • Focuses on managing businesses using data.
  • Course taught by multiple instructors: GV (Venkatesh), Sureshbabu (economics professor), and Milind Gandhe (IIIT Bangalore).
  • Case studies from multiple industries: e-commerce (Flipkart), manufacturing, HR (Mercer), and Fintech (PayPal).

2. Learning Objectives:

  • Similar to an introduction to the world of computing, but from the perspective of a data scientist.
  • Introduces students to the world of business using data as the lens.
  • Understanding business consumption patterns, production, and optimization.
  • Analysis of business data, profit/loss statements, balance sheets, and industry competition.

3. Key Topics Covered:

  • Economics (First 4 Weeks):
    • Understand consumer consumption patterns, demand, and elasticity.
    • Examine production costs and firm-level optimization.
  • Firm and Industry Analysis:
    • Evaluating financial health through accounting data.
    • Understanding competition, supplier/customer pressures, and market threats.
  • Industry Context:
    • Positioning firms within their industry.
    • Understanding firm growth, profitability, and cash management.

4. Case Studies (Remaining 7 Weeks):

  • Practical case studies from Flipkart, Mercer, PayPal, and manufacturing.
  • Analysis of real data from business operations in sales, accounting, and production.

5. Business Functions and Data Management:

  • Focus on using data dashboards to manage business KPIs.
  • Raw data from various departments like manufacturing, sales, and accounting.
  • Data organization using spreadsheets and pivot tables.
  • Visual representation through charts to derive business insights.

6. Practical Skills Developed:

  • Emphasis on organizing, processing, and presenting data using Excel/Google Sheets.
  • Assignments to work on datasets with small to medium entries (~1000-3000).
  • No deep statistics, mainly data handling through spreadsheets.

7. Course Delivery:

  • Mix of conceptual lectures (first four weeks), case studies, and working illustrations.
  • Frequent assignments to reinforce learning.
  • Final project requiring students to collect and organize field data from a small enterprise.

8. Comprehensive Learning:

  • Draws material from multiple fields: economics (micro and macro), finance, marketing, production operations, and management information systems.
  • By the end of the course, students will have an understanding of business structures, data generation, and data-driven decision-making for business management.

The provided content lays out a comprehensive and diverse course structure, focusing on both theoretical concepts and practical case studies. It begins with an introduction to the course, explaining the diverse range of topics covered and the lack of a single textbook reference. The course involves significant use of spreadsheets and covers both microeconomic and macroeconomic topics, including demand, consumption, production, and market structures.

Here’s a breakdown of the key components:

1. Weeks 1 and 2: Macroeconomics Concepts

  • Introduction to spreadsheets (Google Sheets, etc.).
  • Focus on the interaction between consumers (households) and producers (firms).
  • Circular flow of goods, services, capital, and labor.
  • Key topics: consumption, production, exchange, price mechanisms, utility (cardinal and ordinal), demand and supply curves, elasticity, and production cost curves.

2. Weeks 3 and 4: Data Analysis

  • Week 3: Analysis of firm-level performance (using companies like Ultratech, Page Industries, Nestle, and TCS).
  • Week 4: Industry-level performance and classification using NIC codes, IIP data, PMI data, and Porter's five forces model.
  • Assignments: Apply learned methods to analyze specific companies, requiring students to generate reports based on financial and industry data.

3. Case Studies (Weeks 5 to 10):

  • Case Study 1: Fabmart (e-commerce)

    • Focus on real-world e-commerce data (based on Flipkart).
    • Key analyses: revenue Pareto, volume Pareto, scatter plots, inventory management, stockout avoidance.
    • Assignment: Sales and inventory analysis.

  • Case Study 2: Ace Gears (Manufacturing)

    • Automotive industry and manufacturing processes.
    • Topics: production schedules, raw material purchases, scrap analysis, unit-level profitability, and safety stock/reordering.
    • Assignment: Prepare reports on revenue trends and operational efficiency.

  • Case Study 3: Tech Enterprises (HR & Recruitment)

    • HR management and recruitment processes.
    • Two caselets: internal sourcing and external recruitment.
    • Focus on unstructured data and candidate ranking.

  • Case Study 4: FinTech (PayPal)

    • Insights into data from the FinTech world.
    • The data is anonymized and adapted from PayPal's real operations, with further details likely covered in future weeks.

Overall, this course offers a mix of theory and hands-on data analysis, preparing students to engage with real-world economic and business challenges across multiple industries. Each segment is supported by practical assignments to ensure that students apply theoretical knowledge to actual data.

1.2: Introduction to Economics 2 - demand and supply

The lecture introduces key economic principles related to business data management, focusing on micro and macroeconomics.

  1. Basic Economic Activities: The economy operates through five activities: production, consumption, exchange, distribution, and investment. These activities are interconnected, and any disruption in one can impact the others.

  2. Agents in the Economy: The economy consists of three main agents: households (consumers), firms (producers), and the government. Households make decisions about consumption and savings, while firms focus on resource allocation for production.

  3. Microeconomics vs. Macroeconomics:

  4. Microeconomics examines individual decision-making at the household or firm level, such as consumption choices and resource allocation.

  5. Macroeconomics looks at broader aggregates, such as industry, state, or national economic factors, including savings rates, investments, and GDP.

  6. Role of Price: Price plays a critical role in linking micro and macroeconomic concepts. It impacts individual welfare at the micro level and inflation at the macro level.

  7. Data in Economics: Data is crucial for understanding decision-making processes. Firms rely on data to analyze resource allocation, efficiency, and trade-offs. Economic analysis of both production and consumption requires data-driven insights, especially to assess efficiency and opportunity costs.

The lecture emphasizes how understanding these economic activities, agents, and data helps inform business decisions.