Information Technology Foundations-BIT 112 CHAPTER 9 Managerial Support Systems

Information Technology Foundations-BIT 112

CHAPTER 9

Managerial Support Systems


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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


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Learning Objectives

• Describe the concepts of management, decision making and computerized support for decision making.

• Describe multidimensional data analysis and data mining

• Describe dashboards

• 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.


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9.1 Managers and Decision Making

• Management – A process by which organizational goals are achieved

through the use of resources (people, money, energy, materials, space, time).

• Managers have three basic roles (Mintzberg 1973)a) Interpersonal roles: figurehead, leader, liaison b) Informational roles: monitor, disseminator, spokespersonc) Decisional roles: entrepreneur, disturbance handler,

resource allocator, negotiator.


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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: (Simon 1977)– Intelligence Phase-the starting point where reality is examined and the

problem is defined. – Design Phase-design and construct a model, or simplified representation of

reality– Choice Phase-selecting a solution to test “on paper.”

• Example, Making A Decision About A New Automobile:– Intelligence—review automobile maintenance records showing chronic

transmission problems. Seek information from dealers, consumer reports and friends about new automobiles.

– Design—Establish objectives and criteria for evaluating automobiles. Establish weights illustrating the relative importance of these criteria. Analyze alternative possibilities.

– Choice— generate summary statistics on the evaluation of each automobile.


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Decision Making Process


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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.


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9.2 BI, Multidimensional Data Analysis, Data Mining, and DSSs

• 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.

• 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


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Multidimensional Data Analysis (or online analytical processing)

• 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.

Figure 4.11


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Data Mining

• Searching for valuable business information in a large database, data warehouse, or data mart.

• Data mining performs two basic operations:– Predicting trends and behaviors– Identifying previously unknown patterns and relationships

Credit card companies often use Data Mining

to check for fraudulent credit

card use.


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Decision Support Systems (DSS)

• Decision support systems– combine models and data in an attempt to solve semi-

structured and some unstructured problems with extensive user involvement.

– A DSS is not a standalone system, usually a collection of computer information systems.

• DSS Analysis capabilities– 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.


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Two Types of Group-based Decision Support Solutions

• Group decision support system (GDSS) – an interactive computer-based system that supports the process

of finding solutions by a group of decision makers. – Decision Room (War Room) is a face-to-face setting for a group

DSS, in which terminals are available to the participants.

• Organizational Decision Support System (ODSS) – a DSS that focuses on an organizational task or activity

involving a sequence of operations and decision makers.– ODSS Characteristics:

• It affects several organizational units or corporate problems.• It cuts across organizational functions or hierarchical layers.• It involves computer-based and (usually) communications

technologies.


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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.


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Sample Performance Dashboard (Figure 9.4)


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Another Example of Dashboard


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9.4 Data Visualization Systems

• Data visualization is the process of presenting data to users in visual formats, thereby making IT applications more attractive and understandable to users.

• 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!”


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New York City Police Department Command Center

Data visualization in action


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Example Of Data Visualization

• 21-minute video that illustrates data visualization

Hans Rosling at the TED Talks

http://video.google.com/videoplay?docid=4237353244338529080&q=%22Hans+Rosling%22&total=65&start=0&num=10&so=0&type=search&plindex=0

http://video.google.com/videoplay?docid=4237353244338529080&q=%22Hans+Rosling%22&total=65&start=0&num=10&so=0&type=search&plindex=0


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Two Types Of Data Visualization Systems

• 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.


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GIS for existing land use


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GISMO

• GISMO is a geographical information system developed for the city of Corvallis, Oregon.

http://gis.esri.com/esriclips/flash.cfm?path=72


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Virtual Reality


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Technology of Data Glove

http://www.tu-berlin.de/uebertu/fotogalerie/forschung_lehre/Sensorhandschuh_TU-Pressestelle.jpg


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Virtual Reality manipulation with data glove


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Driving Simulator

http://www.tu-berlin.de/uebertu/fotogalerie/forschung_lehre/Fahrersimulator_TU-Berlin.jpg


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Virtual Tour Of A Museum


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9.5 Intelligent Systems

• Intelligent systems is a term that describes the various commercial applications of Artificial intelligence (AI).

• 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.


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Expert Systems

• Expert Systems (ESs) attempt to mimic human experts by applying expertise in a specific domain. – Can support decision makers or completely replace them.

• Expertise refers to the extensive, task-specific knowledge acquired from training, reading and experience.

Star Trek Voyager’s doctor: a 24th century expert system


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Four Activities Involved in the Transfer of Expertise from an Expert to Computer and then to a User

• 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.


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The Components of Expert Systems

• Knowledge base – Contains knowledge necessary for understanding, formulating

and solving problems.

• Inference engine – A computer program that provides a methodology for

reasoning and formulating conclusions.

• User interface – Enables users to communicate with the computer

• Blackboard – An area of working memory set aside for the description of a

current problem.

• Explanation subsystem – Explains its recommendations.


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Natural Language Processing & Voice Technologies

• 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.


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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.


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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.


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Chapter Closing Case P. 290

GPS sensor

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Information Technology Foundations-BIT 112 CHAPTER 9 Managerial Support Systems