Business Analytics Notes

Business Analytics Notes

Introduction to Business Analytics

  • Business Analytics (BA) defined as the scientific process of transforming data into insight for better decision-making.
  • Importance of BA in decision making is influenced by three developments:
    • Technological Advances: Enhanced data collection technologies.
    • Methodological Developments: Advancements in data analysis methods.
    • Increase in Computing Power: Improved software and hardware capabilities.

Decision Making

  • Process of decision making includes:
    1. Identify and define the problem.
    2. Determine criteria for evaluating solutions.
    3. Identify alternatives.
    4. Evaluate alternatives.
    5. Select an alternative.
  • Types of decisions:
    • Strategic Decisions: Long-term goals and direction of the organization (3-5 years).
    • Tactical Decisions: Mid-term decisions affecting how strategic goals will be achieved (1 year).
    • Operational Decisions: Day-to-day operations management decisions.

Business Analytics Defined

  • A key advantage in decision making is overcoming uncertainty and analyzing vast amounts of alternatives.
  • BA can help:
    • Create insights from data.
    • Improve forecasting.
    • Quantify risks.
    • Yield better alternatives through analysis and optimization.

Categorizing Analytical Methods

  1. Descriptive Analytics: Techniques that describe historical data. Utilizes data queries, reports, dashboard visualization, and descriptive statistics.
    • Example: Sales reports, historical data.
  2. Predictive Analytics: Techniques that predict future outcomes based on historical data. Includes regression analysis, forecasting, time-series analysis, and simulation.
  3. Prescriptive Analytics: Techniques that suggest optimal actions. Involves optimization algorithms and decision analysis tools.

Big Data and Analytics

  • Big Data: Larger data sets that require advanced methods and tools for analysis beyond traditional data processing applications.
  • Companies are increasingly hiring data scientists due to the complexity of big data.

Applications of Business Analytics

  • Various Industries: Financial Analytics, HR Analytics, Marketing Analytics, Health Care Analytics, Supply Chain Analytics, and more.
  • Real-world applications demonstrate significant cost savings and performance improvements across sectors.

Financial Analytics

  • Use of predictive models for forecasting financial outcomes.
  • Optimization models assist in portfolio management and capital budgeting.

Human Resource Analytics

  • Support for hiring and retaining high-quality talent through predictive analytics on employee data.

Marketing Analytics

  • Understanding consumer behavior to optimize advertising, pricing strategies, and customer satisfaction.

Health Care Analytics

  • Improving patient care and optimizing operational efficiency through data analysis.

Conclusion

  • Business analytics presents comprehensive tools and methodologies for effective decision-making.
  • Emphasizes the need to adapt to data-driven approaches for competitive advantage.