The document discusses various types of management support systems that can help with managerial decision making, including decision support systems, expert systems, intelligent agents, neural networks, and knowledge management systems. It covers the evolution of these computerized decision aids from early transaction processing to more advanced integrated and hybrid systems. The goal of management support systems is to improve the quality, speed, and consistency of managerial decisions through leveraging data, models, and artificial intelligence technologies.

1. Management Support
Systems
Managers and Decision Making
Decisions and Information Systems
Computerized Support
Decision Support
Expert Systems
Intelligent Agents
Neural Nets
Knowledge Management
Enterprise level support
Hybrid Support
Evolution of Computerized DSS

2. Managers & Decision Making
Opening vignette – read & have answers to
questions
Roles of the manager
 Interpersonal
 Leader, Industry Liason
 Informational
 Monitor, Disseminate, Represent
 Decisional
 Exploit opportunity, handle disturbance,
allocate resources, negotiate

3. Decisions & Information Systems
Goals (outputs)
 Resources – application (inputs) – focus
 Productivity
Focus
 Planning, Organizing, Directing, Controlling
Management – Art or Technology?
 Speed, Competition
 Increasing alternatives from which to choose
 Cost of Errors
 Changing Environment
 Technology, multinational, politics, consumers

4. Computerized Support
Vital to Business
Data Collection (traditional)
 Accounting, operations, manufacturing
 Transactions
 Monitoring
Decision support
 Analytical
 Proactive

5. Decision Support
Speed - Timeliness
Productivity – More decisions/manager
Technical Facility – Bringing resources
together
Quality & Consistency
Competitive Advantage
Cognitive Limits

6. Decision Support Technologies
Management Support Systems (MSS)
Group Support Systems (GSS)
Decision Support Systems (DSS) Enterprise (Executive)
Information Systems (EIS)
Enterprise Resource Planning (ERP) and Supply-
Chain Management (SCM)
Knowledge Management Systems
Expert Systems (ES) (KBS)
Artificial Neural Networks (ANN)
Hybrid Support Systems
Intelligent DSS (IDSS)

7. Framework for Decision Support
Decision making continuum
Unstructured --------------------- Structured
Nonprogrammed ---------------- Programmed
------------- semistrucutured-----------------
Structured – steps to solution are known
Unstructured – intuition, chaos, R&D,
feasibility
Semistructured – a range of alternatives with
some uncertainty

8. Framework for Decision Support (2)
Managerial Activities
Strategic Planning
 What goals?
Management Control
 What resources?
Operational Control
 What tasks and efficiency?

9. Decision Support
Framework
Type of Control
Operational Managerial Strategic
Type of Control Control Control
Decision
Structured
Semistructured
Unstructured
Gorry and Scott Morton 1978, See figure 1.2 p 12
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10. Support for Structured Decisions
Management Science
 Define the problem
 Classify the problem (standard categories)
 Model (math or otherwise)
 Find potential solutions
 Choose the best

11. Three Phase Decision-
making Process (Simon)
Intelligence--searching for conditions that call for
decisions
Design--inventing, developing, and analyzing possible
courses of action
Choice--selecting a course of action from those
available
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
11

12. Decision Support Systems
Concept
DSS are interactive computer-based systems, which help
decision makers utilize data and models to solve unstructured
problems (Scott Morton, 1971).
Decision support systems couple the intellectual resources of
individuals with the capabilities of the computer to improve
the quality of decisions. It is a computer-based support system
for management decision makers who deal with semi-
structured problems (Keen and Scott Morton, 1978).
Content-free expression
There is no universally accepted definition of DSS
Umbrella term vs. narrow definition (specific technology)
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
12

13. Major DSS Characteristics
(DSS In Action 1.5: Houston Minerals Case)
Initial risk analysis (management science)
Model scrutiny using experience, judgment, and intuition
Initial model mathematically correct, but incomplete
DSS provided very quick analysis
DSS: flexible and responsive. Allows managerial intuition
and judgment
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
13

14. Why Use DSS?
Perceived benefits
 decision quality
 improved communication
 cost reduction
 increased productivity
 time savings
 improved customer and employee satisfaction
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
14

15. Major Reasons
Unstable economy
Difficulty in tracking numerous business objectives
Increased competition
Electronic commerce
Existing systems did not support decision making
IS Department is too busy
Special analysis
Need accurate information
Organizational winner
New or timely information needed
Mandated by management
Cost reductions
End-user computing
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
15

16. Other support systems
Group Support (GSS)
Executive (EIS)
Enterprise

17. Expert Systems (ES)
Knowledge Based Systems
(KBS)
Experts solve complex problems
Experts have specific knowledge and experience
“The more unstructured the situation the more specialized the
advice”
Expert systems mimic human experts
ES performance comparable to or better than experts in a
specialized and usually narrow problem area
Expertise transferred from Computer to Human
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
17

18. Intelligent Agents
Help automate various tasks
Increase productivity and quality
Learn how you work
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
18

19. Artificial Neural
Systems
Artificial Neural Networks (ANN):
Mathematical models of the human brain
ANN learn patterns in data
ANN can work with partial, incomplete, or inexact
information
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
19

20. Knowledge Management
Systems (KMS)
Capture and reuse knowledge at the
organizational level
Knowledge repository for storage
Organizational impacts can be dramatic
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
20

21. Cutting Edge Intelligent
Systems
Genetic Algorithms
Work in an evolutionary fashion
Fuzzy Logic
Continuous logic (NOT just True / False)
Intelligent Agents
In search engines, e-mail, electronic commerce
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition.
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
21

22. Hybrid Support Systems
Combines MSS technologies
Use strengths of each
Goal: successful solution of the
managerial problem
Tools support each other
Tools can add intelligence to traditional
MSS
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23. Computerized Decision Aids
Evolution and Attributes
Computerized procedures development
aids decision making (Table 1.2)
DSS supports specific questions (Table 1.3)
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24. Evolutionary View of CBIS
1. Time Sequence
mid-1950s Transaction Processing Systems (TPS)
1960s MIS
1970s Office Automation Systems
DSS
1980s DSS Expanded
Commercial applications of expert systems
Executive Information Systems
1990s Group Support Systems
Neural Computing
Integrated, hybrid computer systems
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25. 2. Computer evolved over time
3. Systemic linkages in how each system processes
data into information
Relationship among these and other technologies
(Figure 1.3)
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26. Relationship Among
Technologies
Each technology unique
Technologies interrelated
Each supports some aspects of managerial decision
making
Ever expanding role of information technology
improving management
Interrelationship and coordination evolving
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27. Summary
DSS has many definitions
Complexity of managerial decision making is
increasing
Computer support for managerial decision
making
Several MSS technologies including hybrids
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