Decision Making and Decision Support Systems

Introduction to Decision Making
  • Definition of Decision: A choice among alternatives based on facts and judgments.
  • Types of Decisions:
    • Well-Structured: Simple, clear alternatives.
    • Wicked Problems: Unique, complex issues with no clear solutions.
  • Decision Support Systems (DSS):
    • Designed for poorly structured problems.
    • Provide frameworks for analyzing alternatives.
Rational Decision Making
  • Definition of Rationality: Derives from logical reasoning.
  • Information Needs for Rational Decisions:
    • Must include data about alternatives and conditions.
    • Economic rationality is key: optimize costs/profits.
  • Types of Rationality in Decision Making (Figure 2.2):
    • Procedural Rationality: Logistics of decision-making processes.
    • Economic, Political, and Social (Ethical) Rationality: Evaluating choices based on different criteria.
    • Legal Rationality: Ensures decisions comply with legal standards.
Technical Considerations
  • Technical Rationality: Decision-making should align with goals.
  • Importance of including technical criteria in DSS for effective evaluation.
Bounded Rationality and Satisficing
  • Bounded Rationality: Decision-makers operate with limitations in data and methods.
    • Satisficing rather than optimizing decisions.
  • Muddling Through Theory: Preference for incremental changes over bold decisions.
  • Organizational Limitations: Issues like corporate culture and cooperation can impact decision-making capabilities.
Nature of Managers
  • Managers prefer informal, flexible decision processes:
    • Use verbal versus written communication for efficiency.
    • Require access to sources of information.
  • DSS Design Implications:
    • Must facilitate integration of communication and variety of data access.
Appropriate Decision Support
  • DSS as Electronic Memory: Capture and recreate decision processes.
  • Bias in Decision Making: Ensure systems help mitigate selective information perception.
  • Structured information presentation can help avoid overwhelming users.
Information Processing Models
  • Phases of Information Processing: Sensation, attention, and perception.
  • Decision-makers filter information based on relevance and task goals.
  • Novices require structure, while experts require flexibility in decision processes.
Group Decision Making
  • Benefits: Collective intelligence can generate diverse solutions.
  • Challenges: Group dynamics may lead to pressure and incomplete analyses.
  • Improving group decision processes through guided brainstorming and time limitations.
Intuition, Qualitative Data, and Decision Making
  • Significant decisions often rely on intuition despite available data.
  • Integrated Decision-Making Style: Utilizes both analytic and intuitive processes to manage complexity.
Business Intelligence (BI)
  • Definition of BI: Systematic approach to provide timely data insights for decision making.
  • Importance: Essential for navigating competitive business landscapes and regulatory environments.
  • Analytics Role in Decision Making: Crucial for devising strategies that set companies apart.
Competitive Intelligence (CI)
  • Goal of CI: Enhance understanding of the business environment for strategic decision making.
  • Importance of multi-source data gathering for early identification of threats/opportunities.
Conclusion
  • This chapter provided foundational theories on decision making to be explored further in the context of DSS implementation and design.