Chap 2- Decison Support System(1)
Importance of Decision Making
Levels of Management:
Operational Level: Executes day-to-day activities using structured decisions.
Managerial Level: Evaluates company operations with semi-structured decisions.
Strategic Level: Develops overall strategies with unstructured decisions.
Decision-Making Challenges for Managers
Analyzing Large Amounts of Information:
Globalization increases the variables to consider for decisions.
Example: Choosing discount strategies by analyzing data from 500 hotels.
Quick Decision-Making Required:
Time constraints lead to the necessity of swift decisions.
Example: Handling a reservation for a fully booked hotel.
Applying Analysis Techniques:
Managers need to incorporate strategic frameworks such as Porter's strategies.
Example: Implementing a loyalty program across multiple hotels.
The Decision-Making Process
Six-Step Process:
Problem Identification: Clearly define the problem (e.g., product return issues).
Data Collection: Gather relevant information (facts only).
Solution Generation: Brainstorm multiple possible solutions.
Solution Test: Evaluate feasibility, suitability, and acceptability.
Solution Selection: Choose the best solution for implementation.
Solution Implementation: Carry out the decision, assess its effectiveness.
Decision-Making Essentials
Strategic Level: Handles unstructured decisions related to business strategies.
Managerial Level: Focus on semi-structured decisions to improve operations.
Operational Level: Involves structured decisions for daily operations.
Measuring Organizational Business Decisions
Critical Success Factors (CSFs):
Essential steps to achieving goals (e.g., quality products, low costs).
Key Performance Indicators (KPIs):
Quantifiable metrics to evaluate progress toward CSFs (e.g., employee turnover, customer satisfaction).
Metrics for Evaluation
Efficiency Metrics:
Measure internal performance:
Throughput: Volume of data processed.
Transaction Speed: Time for completing transactions.
System Availability: Operational hours for users.
Information Accuracy: Correctness of repeated transactions.
Effectiveness Metrics:
Measure impact on business:
Usability: User-friendliness of processes.
Customer Satisfaction: Evaluated via feedback and revenue.
Conversion Rates: Effectiveness of customer engagement strategies.
Decision Support Systems (DSS)
Definition: Tools to support managers with decision-making.
Types:
Operational Support Systems: Transaction Processing Systems (TPS) for structured decision-making.
Managerial Support Systems: Decision Support Systems (DSS) for semi-structured situations.
Strategic Support Systems: Executive Information Systems (EIS) for unstructured decisions.
AI in Business Decision Making
Artificial Intelligence (AI): Simulates human intelligence for various applications.
Expert Systems: Model expert reasoning processes to solve specific problems.
Algorithms: Mathematical functions for data analysis.
Genetic Algorithms: Mimic evolutionary processes to improve solutions.
Machine Learning in AI
Types:
Supervised Learning: Requires labeled training data.
Unsupervised Learning: Finds patterns in unlabeled data.
Transfer Learning: Builds on previously learned knowledge.
Managing Business Processes
Value of Business Processes: Comparison of customer-facing vs. business-facing processes.
Business Process Modeling: Use of BPMN to visualize processes.
As-Is vs. To-Be Models: Current state versus improved processes.
Business Process Improvement Techniques
Automation: Implementing digital solutions to streamline processes.
Robotic Process Automation: Using AI to manage repetitive tasks.
Reengineering: Radical redesign of processes to achieve dramatic improvements.
(Additional details streamlined from the original slides for clarity and focus on essential content.)