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Previous material review
Assignments 
• Microstrategy case study 
• Microsoft BI tools
Decision Making, Systems, 
Modeling, and Support
Decision Making: Introduction 
Decision Making System includes: 
• How decision making is practiced 
• Some of the underlying theories 
• Models of decision making
Definition of Decision making 
• “It is a process of choosing among two or more alternative courses of action for 
the purpose of attaining a goal or goals.” 
 Characteristics of Decision Making 
• Individuals are involved 
• There may be 100’s of alternatives 
• Needs data and analysis with understanding to make a good decision 
• Past results may not be sufficient to predict future results 
• Decisions are interrelated 
• There may be several conflicting objectives 
• May decisions involve risk. Diff people have different appetite for risk 
• Groupthink can lead to bad decision. 
• Decision makers are interested in evaluating what- if scenarios. 
• Experimentation with a real system-trial and error-may result in failure. 
Continued……
• Experimentation with a real system is possible 
only for one set of conditions at a time and can 
be disastrous. 
• Changes in the decision making environment 
may occur continuously, lending to invalidating 
assumptions about a situations. 
• Collecting information and analyzing a problem 
takes time and can be expensive. 
• There may not be sufficient information to make 
an intelligent decision.
Decision Making And Problem Solving 
• Problem occurs when: a system does not meet 
it’s established goals, does not yield the 
predicted results,or does not work as planned. 
• Some consider the entire process of decision 
making as problem solving while other view 
phase 1-3 as formal decision making, ending 
with a recommendation. 
• Additionally includes the actual 
implementation of the recommendation.
Decision Style 
• The manner in which decision makers think and react 
to problems. 
• Vary from individual to individual and situation to 
situation. 
• Although the process is similar, the application is not 
always linear. 
• As a result, people make decision in different ways. 
• Heuristic and analytical 
• Autocratic vs democratic 
• Consultative 
• Decision situation as well style for system to help. 
Hence it should be flexible
Decision Making Models 
“A model is a simplified representation or 
abstraction of reality.” 
• Iconic(Scale)Models: Physical replica of system 
• Analog Models: Symbolic representation of 
reality. 
• Mental Models: Descriptive representation of 
decision making situations. 
• Mathematical(Quantitative)Models: 
Mathematical description of abstract model
Phases of The Decision Making 
(Decision making process)
Simon’s Four Phases of Decision Making 
• Intelligence 
• Design 
• Choice 
• Implementation
The Intelligence phase 
• Involves scanning the environment, includes 
several activities aimed at identifying problem 
situations or opportunities. 
• Intelligence phase includes: 
1.Problem(or opportunity) Identification 
2.Problem Classification 
3.Problem Decomposition 
4.Problem Ownership
The Decision Phase 
• Involves finding or developing and analyzing possible 
courses of action. 
• Includes understanding the problems and testing 
solutions for feasibility. 
• A model of the decision-making is constructed, tested 
and validated. 
• Models include: normative(best amongst available 
amongst all available), suboptimisation, descriptive 
model(simulation, cognitive) and satisifying 
• Measuring outcome, risk and scenarios
The Choice Phase 
• Choice is critical act of decision making. 
• The choice phase is the one in which the 
actual decision is made & the commitment to 
follow a certain course of action. 
• Includes the search for, evaluation of, and 
recommendation of an appropriate solution. 
• A solution is a specific set of values for the 
decision variables in a selected alternatives.
The Implementation Phase 
• Putting a recommended solution to work.
Decision Support Systems 
Concepts, Methodologies, And technologies
Concept of DSS 
• A system intended to support managerial 
decision makers in semi structured and 
unstructured decision situations. 
• Adjuncts to decision makers to extend their 
capabilities but not to replace their 
judgments.
DSS Configuration 
• Depend on nature of management-decision 
situation and specific technology used. 
• These technologies are assembled from four 
basic components: Data, models, user 
interface, and knowledge. 
• These components are managed by software 
that is either commercially available or 
programmed for specific task.
DSS Application 
• Built to support the solution of a certain problem 
or to evaluate an opportunity. 
• DSS typically have their own database and are 
developed to solve a specific problem or set of 
problems. Therefore they are called DSS 
applications. 
• A DSS is an approach for supporting decision 
making. 
• Uses an interactive, flexible, adaptable computer-based 
information system CBIS developed for 
supporting the solution to a specific 
nonstructured management problem.
Characteristic And Capabilities of DSS
Characteristics And Capabilities 
• Support for decision makers in semistructured 
and unstructured problems. 
• Support for all managerial levels. 
• Support for individuals and groups. 
• Support for Interdependent or sequential 
decision. 
• Support in all phases of decision making process. 
• Adaptable and flexible. 
continued…..
• User friendly, Interactive. 
• Improvement of effectiveness rather than 
efficiency. 
• Support and not to replace the decision maker 
• Easy development by end users. 
• Models are used to analyze decision making. 
• Data access 
• Can be employed as standalone tool or can be 
integrate with other DSS.
Components of DSS
A DSS application composed of: 
• The Data Management Subsystem 
• The Model Management Subsystem 
• The User Interface Subsystem 
• The Knowledge-Based Management System
The Data Management Subsystem
Data management subsystem is composed of 
following elements: 
• DSS database: Is a collection of interrelated data, 
organized to meet the needs and structure of an 
organization, used by one or more applications. 
• DBMS: A database is created, accessed , and 
updated by DBMS. 
• The Directory: Is a catalog of all data in a 
database. 
• The Query Facility: Necessary to access, 
manipulate, and query data. 
• Key issues: quality, scalability, security, integration
The Model Management Subsystem
The model management subsystem is composed 
of following elements: 
• Model base: Contains routine & special statistical, 
financial, forecasting, management science, and 
other quantitative models. 
• Types: strategic, operational, tactical, analytical. 
• The Model Base Management System: 
Interrelating models with appropriate linkage 
through a database. 
• Model Directory: Catalog of all the models and 
other software in the model base. 
• Model Execution, integration, and Command
The User Interface Subsystem
• Covers all aspects of communication between 
a user and the DSS or any MSS. 
• It includes not only the hardware and 
software but also factors that ease to use, 
accessibility, and human-machine interactions. 
• It is the source of many of the power, 
flexibility, and ease-of-use characteristics of 
MSS. 
• The user interface is managed by software 
called the user interface management system.
The knowledge based management 
subsystem 
• Use to get the solution of complex 
unstructured and semistructured problems. 
• Supply the required expertise for solving 
some aspects of the problem 
• Provide knowledge that can enhance the 
operation of other DSS components. 
• The knowledge component consists of one or 
more intelligent systems.
The Decision Support System User 
• The person or people primarily responsible for 
making decision, provides expertise in guiding 
the development and use of a DSS. 
• Two broad classes of users: 
1.Managers 
2.Staff specialists 
Includes Financial analysts, production 
planners, and market researchers.
Decision Support System Classification 
Classification categories are as follows: 
• Communication-driven and group DSS 
• Data-driven DSS 
• Document-driven DSS 
• Knowledge-driven DSS, data mining, and 
• management ES applications 
• Model-driven DSS 
• Compounded (hybrid)

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Decision making systems

  • 2. Assignments • Microstrategy case study • Microsoft BI tools
  • 3. Decision Making, Systems, Modeling, and Support
  • 4. Decision Making: Introduction Decision Making System includes: • How decision making is practiced • Some of the underlying theories • Models of decision making
  • 5. Definition of Decision making • “It is a process of choosing among two or more alternative courses of action for the purpose of attaining a goal or goals.”  Characteristics of Decision Making • Individuals are involved • There may be 100’s of alternatives • Needs data and analysis with understanding to make a good decision • Past results may not be sufficient to predict future results • Decisions are interrelated • There may be several conflicting objectives • May decisions involve risk. Diff people have different appetite for risk • Groupthink can lead to bad decision. • Decision makers are interested in evaluating what- if scenarios. • Experimentation with a real system-trial and error-may result in failure. Continued……
  • 6. • Experimentation with a real system is possible only for one set of conditions at a time and can be disastrous. • Changes in the decision making environment may occur continuously, lending to invalidating assumptions about a situations. • Collecting information and analyzing a problem takes time and can be expensive. • There may not be sufficient information to make an intelligent decision.
  • 7. Decision Making And Problem Solving • Problem occurs when: a system does not meet it’s established goals, does not yield the predicted results,or does not work as planned. • Some consider the entire process of decision making as problem solving while other view phase 1-3 as formal decision making, ending with a recommendation. • Additionally includes the actual implementation of the recommendation.
  • 8. Decision Style • The manner in which decision makers think and react to problems. • Vary from individual to individual and situation to situation. • Although the process is similar, the application is not always linear. • As a result, people make decision in different ways. • Heuristic and analytical • Autocratic vs democratic • Consultative • Decision situation as well style for system to help. Hence it should be flexible
  • 9. Decision Making Models “A model is a simplified representation or abstraction of reality.” • Iconic(Scale)Models: Physical replica of system • Analog Models: Symbolic representation of reality. • Mental Models: Descriptive representation of decision making situations. • Mathematical(Quantitative)Models: Mathematical description of abstract model
  • 10. Phases of The Decision Making (Decision making process)
  • 11. Simon’s Four Phases of Decision Making • Intelligence • Design • Choice • Implementation
  • 12. The Intelligence phase • Involves scanning the environment, includes several activities aimed at identifying problem situations or opportunities. • Intelligence phase includes: 1.Problem(or opportunity) Identification 2.Problem Classification 3.Problem Decomposition 4.Problem Ownership
  • 13. The Decision Phase • Involves finding or developing and analyzing possible courses of action. • Includes understanding the problems and testing solutions for feasibility. • A model of the decision-making is constructed, tested and validated. • Models include: normative(best amongst available amongst all available), suboptimisation, descriptive model(simulation, cognitive) and satisifying • Measuring outcome, risk and scenarios
  • 14. The Choice Phase • Choice is critical act of decision making. • The choice phase is the one in which the actual decision is made & the commitment to follow a certain course of action. • Includes the search for, evaluation of, and recommendation of an appropriate solution. • A solution is a specific set of values for the decision variables in a selected alternatives.
  • 15. The Implementation Phase • Putting a recommended solution to work.
  • 16. Decision Support Systems Concepts, Methodologies, And technologies
  • 17. Concept of DSS • A system intended to support managerial decision makers in semi structured and unstructured decision situations. • Adjuncts to decision makers to extend their capabilities but not to replace their judgments.
  • 18. DSS Configuration • Depend on nature of management-decision situation and specific technology used. • These technologies are assembled from four basic components: Data, models, user interface, and knowledge. • These components are managed by software that is either commercially available or programmed for specific task.
  • 19. DSS Application • Built to support the solution of a certain problem or to evaluate an opportunity. • DSS typically have their own database and are developed to solve a specific problem or set of problems. Therefore they are called DSS applications. • A DSS is an approach for supporting decision making. • Uses an interactive, flexible, adaptable computer-based information system CBIS developed for supporting the solution to a specific nonstructured management problem.
  • 21. Characteristics And Capabilities • Support for decision makers in semistructured and unstructured problems. • Support for all managerial levels. • Support for individuals and groups. • Support for Interdependent or sequential decision. • Support in all phases of decision making process. • Adaptable and flexible. continued…..
  • 22. • User friendly, Interactive. • Improvement of effectiveness rather than efficiency. • Support and not to replace the decision maker • Easy development by end users. • Models are used to analyze decision making. • Data access • Can be employed as standalone tool or can be integrate with other DSS.
  • 24. A DSS application composed of: • The Data Management Subsystem • The Model Management Subsystem • The User Interface Subsystem • The Knowledge-Based Management System
  • 25. The Data Management Subsystem
  • 26. Data management subsystem is composed of following elements: • DSS database: Is a collection of interrelated data, organized to meet the needs and structure of an organization, used by one or more applications. • DBMS: A database is created, accessed , and updated by DBMS. • The Directory: Is a catalog of all data in a database. • The Query Facility: Necessary to access, manipulate, and query data. • Key issues: quality, scalability, security, integration
  • 27. The Model Management Subsystem
  • 28. The model management subsystem is composed of following elements: • Model base: Contains routine & special statistical, financial, forecasting, management science, and other quantitative models. • Types: strategic, operational, tactical, analytical. • The Model Base Management System: Interrelating models with appropriate linkage through a database. • Model Directory: Catalog of all the models and other software in the model base. • Model Execution, integration, and Command
  • 29. The User Interface Subsystem
  • 30. • Covers all aspects of communication between a user and the DSS or any MSS. • It includes not only the hardware and software but also factors that ease to use, accessibility, and human-machine interactions. • It is the source of many of the power, flexibility, and ease-of-use characteristics of MSS. • The user interface is managed by software called the user interface management system.
  • 31. The knowledge based management subsystem • Use to get the solution of complex unstructured and semistructured problems. • Supply the required expertise for solving some aspects of the problem • Provide knowledge that can enhance the operation of other DSS components. • The knowledge component consists of one or more intelligent systems.
  • 32. The Decision Support System User • The person or people primarily responsible for making decision, provides expertise in guiding the development and use of a DSS. • Two broad classes of users: 1.Managers 2.Staff specialists Includes Financial analysts, production planners, and market researchers.
  • 33. Decision Support System Classification Classification categories are as follows: • Communication-driven and group DSS • Data-driven DSS • Document-driven DSS • Knowledge-driven DSS, data mining, and • management ES applications • Model-driven DSS • Compounded (hybrid)