1. Managerial Support Systems
CHAPTER 9
Managerial Support Systems

2. CHAPTER OUTLINE 9.1 Managers and Decision Making
9.2 Business Intelligence, Multidimensional Data Analysis, Data Mining, and Decision Support Systems
9.3 Digital Dashboards
9.4 Data Visualization Technologies
9.5 Intelligent Systems

3. LEARNING OBJECTIVES
Describe the concepts of management, decision making and computerized support for decision making.
Describe multidimensional data analysis and data mining
Describe dashboards

4. LEARNING OBJECTIVES (continued)
Describe data visualization, and explain geographical information systems and virtual reality.
Describe artificial intelligence (AI).
Define an expert system and identify its components.
Describe natural language processing and natural language generation, and neural networks.

5. Chapter Opening Case

6. 9.1 Managers and Decision Making
Management is a process by which organizational goals are achieved through the use of resources (people, money, energy, materials, space, time).

7. The Manager’s Job and Decision Making
Managers have three basic roles (Mintzberg 1973)
Interpersonal roles
Informational roles
Decisional roles
Managers have three basic roles:
Interpersonal roles: figurehead, leader, liaison
Informational roles: monitor, disseminator, spokesperson
Decisional roles: entrepreneur, disturbance handler, resource allocator, negotiator.

8. The Manager’s Job & Decision Making (continued)
Decision refers to a choice that individuals and group make among two or more alternatives.
Decision making is a systematic process composed of three major phases: intelligence, design and choice (Simon 1977)
Implementation phase was added later.

9. Decision Making Process

10. Why Managers Need IT Support
The number of alternatives to be considered constantly increases.
Decisions must be made under time pressure.
Decisions are more complex
Decision makers can be in different locations and so is the information.

11. A Framework for Computerized Decision Analysis
Lower-level managers usually perform the structured and operational-control oriented
tasks in cells 1, 2, and 4. (Blue color above).
Middle managers and staff usually perform the tasks in cells 3, 5, and 7. (Orange color above).
Senior executives usually perform the tasks in cells 6, 8, and 9. (Yellow color above.)

12. Problem Structure
The first dimension deals with the problem structure, where does the decision making processes fall along the continuum ranging from highly structured to highly unstructured decisions.
Structured
Unstructured
Semistructured
Structured problems are routine and repetitive problems for which standard solutions exist.
Unstructured problems are fuzzy, complex problems for which there are no cut-and-dried
solutions.
Semistructured problems are problems in which only some of the decision process phases
are structured.

13. The Nature of Decisions
The second dimension of decision support deals with the nature of decisions
Operational control
Management control
Strategic planning
Operational control involves executing specific tasks efficiently and effectively.
Management control involves decisions concerning acquiring and using resources efficiently
in accomplishing organizational goals.
Strategic planning involves decisions concerning the long range goals and policies for growth
and resource allocation.

14. 9.2 BI, Multidimensional Data Analysis, Data Mining, and DSSs
Business Intelligence (BI)
Two types of BI Systems:
Those that provide data analysis tools
Multidimensional data analysis (or online analytical processing)
Data mining
Decision support systems
Those that provide information in structured format
Dashboards
Business Intelligence (BI) refers to applications and technologies for consolidating,
analyzing, and providing access to vast amounts of data to help users make better
business and strategic decisions.

15. How Business Intelligence Works (Figure 9.3)

16. Multidimensional Data Analysis
Provides users with a look at what is happening or what has happened.
Allows users to analyze data in such a way that they can quickly answer business questions.

17. Data Mining
Searching for valuable business information in a large database or data warehouse.
Data mining performs two basic operations:
Predicting trends and behaviors
Identifying previously unknown patterns and relationships

18. 9.2 Decision Support Systems (DSS)
DSS capabilities
Sensitivity analysis
What-if analysis
Goal-seeking analysis
Decision support systems (DSSs) are computer-based information systems that
combine models and data in an attempt to solve semistructured and some unstructured
problems with extensive user involvement.
Sensitivity analysis is the study of the impact that changes in one (or more) parts of a model
have on other parts.
What-if analysis is the study of the impact of a change in the assumptions (input data) on the
proposed solution.
Goal-seeking analysis is the study that attempts to find the value of the inputs necessary to
achieve a desired level of output.

19. Group Decision Support Systems (GDSS)
Group decision support system (GDSS) is an interactive computer-based system that supports the process of finding solutions by a group of decision makers.
Decision Room is a face-to-face setting for a group DSS, in which terminals are available to the participants.

20. Organizational Decision Support System (ODSS)
Organizational Decision Support System (ODSS) is a DSS that focuses on an organizational task or activity involving a sequence of operations and decision makers.
Organizational Decision Support System (ODSS) provide the following:
It affects several organizational units or corporate problems;
It cuts across organizational functions or hierarchical layers;
It involves computer-based and (usually) communications technologies.

21. 9.3 Digital Dashboards Dashboards:
Provide rapid access to timely information.
Provide direct access to management reports.
Are very user friendly and supported by graphics.

22. Sample Performance Dashboard (Figure 9.4)

23. Another Example of Dashboard

24. Executive Dashboard Demo

25. A Bloomberg Terminal (Figure 9.5)

26. Management Cockpit (Figure 9.6)

27. Management Cockpit
A strategic management room that enables top-level decision makers to pilot their businesses better.
The environment encourages more efficient management meetings and boosts team performance via effective communication.
Key performance indicators and information relating to critical success factors are displayed graphically on the walls of the meeting room.
External information can be easily imported to the room to allow competitive analysis.

28. Halliburton’s CyberWell (IT’s About Business 9.3)
3D image similar to that produced by CyberWell

29. 9.4 Data Visualization Systems
The Power of Visualization
Even though a picture is “worth a thousand words,” we have to be very careful about just what we are seeing.
Remember, on the Internet, it is “user beware!”
Data visualization is the process of presenting data to users in visual formats, thereby
making IT applications more attractive and understandable to users.

30. New York City Police Department Command Center
Data visualization in action

31. Example of data visualization
Hans Rosling at the TED Talks
This is an outstanding 21-minute video that illustrates data visualization.

32. Types of data visualization systems
Geographical Information Systems
Virtual Reality
Geographical Information Systems: a computer-based system for capturing, integrating,
manipulating, and displaying data using digitized maps.
Virtual Reality: interactive, computer-generated, three-dimensional graphics delivered to
the user via a head-mounted display.

33. Geographic Information System

34. GIS for existing land use

35. GISMO
GISMO is a geographical information system developed for the city of Corvallis, Oregon.
Clicking on the link above will present an interactive demonstration of GISMO.

36. Virtual Reality

37. Technology of Data Glove

38. Virtual Reality manipulation with data glove

39. Driving Simulator

40. Flight Simulator
Internal view
External view

41. VR Head-Mounted Display at Dentist’s Office

42. Virtual Tour of a museum

43. Virtual Reality (continued)

44. The VirtuSphere
VirtuSphere provides a mechanical basis for truly immersive virtual reality environments,
permitting the user to move about in virtual space by simply walking.
The device consists of a large hollow sphere which is mounted on a specially designed platform
that allows the sphere to rotate freely as the user walks in any direction. (Note that the open
hatch in the picture above is closed during use.) The user wears a head-mounted display, which
provides the virtual environment. Sensors under the sphere provide subject speed and direction
to the computer running the simulation. Users can even interact with objects in virtual space
using a special manipulator.

45. VR Body Suit

46. 9.5 Intelligent Systems Intelligent systems
Artificial intelligence (AI)
Intelligent systems is a term that describes the various commercial applications of AI.
Artificial intelligence (AI) is a subfield of computer science concerned with:
* studying the thought processes of humans
* recreating those processes via machines, such as computer and robots.

47. Expert Systems Expertise Expert systems (ESs)
Star Trek Voyager’s doctor:
a 24th century expert system
Expertise refers to the extensive, task-specific knowledge acquired from training, reading
and experience.
Expert systems (ESs) attempt to mimic human experts by applying expertise in a specific
domain. Can support decision makers or completely replace them.

48. Expert Systems (continued)
The transfer of expertise from an expert to a computer and then to a user involves four activities:
Knowledge acquisition
Knowledge representation
Knowledge inferencing
Knowledge transfer
Knowledge acquisition: Knowledge is from experts or from documented sources.
Knowledge representation: Acquired knowledge is organized as rules or frames
(objective-oriented) and stored electronically in a knowledge base.
Knowledge inferencing: Given the necessary expertise stored in the knowledge base,
the computer is programmed so that it can make inferences. The reasoning function is
performed in a component called the inference engine, which is the brain of ES.
Knowledge transfer: The inferenced expertise is transferred to the user in the form of
a recommendation.

49. The Components of Expert Systems
Knowledge base
Inference engine
User interface
Blackboard
Explanation subsystem
Knowledge base contains knowledge necessary for understanding, formulating and solving problems.
Inference engine is a computer program that provides a methodology for reasoning and formulating conclusions.
User interface enables users to communicate with the computer
Blackboard is an area of working memory set aside for the description of a current problem.
Explanation subsystem explains its recommendations.

50. Structure and Process of an Expert System

51. Natural Language Processing & Voice Technologies
Natural language processing (NLP)
Natural language understanding / speech (voice) recognition
Natural language generation/voice synthesis
Natural language processing (NLP): Communicating with a computer in English or whatever
language you may speak.
Natural language understanding/speech (voice) recognition: The ability of a computer
to comprehend instructions given in ordinary language, via the keyboard or by voice.
Natural language generation/voice synthesis: Technology that enables computers to
produce ordinary language, by “voice” or on the screen, so that people can understand
computers more easily.

52. Neural Networks
Neural network is a system of programs and data structures that approximates the operation of the human brain.
Neural networks are particularly good at recognizing subtle, hidden and newly emerging patterns within complex data as well as interpreting incomplete inputs.

53. Neural Network

54. Fuzzy Logic
Fuzzy logic deals with the uncertainties by simulating the process of human reasoning, allowing the computer to behave less precisely and logically than conventional computers do.
Involves decision in gray areas.
Uses creative decision-making processes.

55. Chapter Closing Case
GPS sensor