Decision Making

Expert Systems

An expert system consists of both an inference engine and a knowledge base and has decision-making abilities.

Learning Objectives

Break down expert systems to the inference engine, the knowledge base, and conversational

Key Takeaways

Key Points

  • In the 1980s, a third component was added to most expert systems: A dialog interface to communicate with users. This ability to conduct a conversation with users was later called “conversational. “
  • In expert system technology, the knowledge base is expressed with natural language rules, such as if-then statements. For example: “If it is living then it is mortal. ” This dialog interface has the advantage of speaking in everyday language, which is very rare in computer science.
  • Knowledge-based systems are artificial intelligent tools working in a narrow domain to provide intelligent decisions with justification. Knowledge is acquired and represented using various knowledge representation techniques, rules, frames and scripts.

Key Terms

  • artificial intelligence: The branch of computer science dealing with the reproduction or mimicking of human-level intelligence, self-awareness, knowledge, conscience, thought in computer programs.
  • knowledge base: A database designed to meet the complex storage and retrieval requirements of computerized knowledge management, especially in support of artificial intelligence or expert systems.

Definition of an Expert System

An expert system has a unique structure, different from traditional computer programs. It is divided into two parts: One fixed and independent of the expert system—the inference (reasoning) engine, and one variable—the knowledge base. To run an expert system, the engine uses the knowledge base in the same way that a human reasons. In the 1980s, a third component was added to most expert systems: A dialog interface to communicate with users. This ability to conduct a conversation with users was later called “conversational. ” In expert system technology, the knowledge base is expressed with natural language rules, such as “if-then” statements. For example: “If it is living then it is mortal. ” This dialog interface has the advantage of speaking in everyday language, which is very rare in computer science (a classic computer program must be written in a specific programming language in order for the computer to understand and carry out instructions).

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Robots Are a Type of Expert System.: Expert systems have decision-making abilities, just like their human counterparts.

Knowledge-based Systems

Knowledge based systems are artificial intelligent tools working in a narrow domain to provide intelligent decisions with justification. Knowledge is acquired and represented using various knowledge representation techniques, rules, frames and scripts. The basic advantages offered by such a system are documentation of knowledge, intelligent decision support, self learning, reasoning and explanation. Knowledge-based systems are systems based on the methods and techniques of artificial Intelligence. Their core components are

  1. Knowledge base
  2. Acquisition mechanisms
  3. Inference mechanisms (reasoning ability)

Knowledge base systems (KBS) go beyond the decision support philosophy to incorporate expert system technology into the decision-making framework. Expert systems (ES) have been the tools and techniques perfected by artificial intelligence (AI) researchers to deduce decision influences based on the codification of knowledge and applying rules, such as if-then statements.

Informed Decisions

Effectively transforming data into actionable information is the key to using information technology to improve decision making.

Learning Objectives

Infer how managing information systems relates to decision-making

Key Takeaways

Key Points

  • The decision-making process involves several steps, which includes the establishment of objectives, classification of objectives by order of importance, and the development of alternative actions.
  • Business organizations utilize management information systems (MIS), which combine the use of information technology, people, and data/information to provide tools used in making decisions.
  • An MIS supports a business’ long-range plans, providing performance analysis reports on areas critical to those plans, with feedback mechanisms that improve guidance for every aspect of the enterprise, including recruitment and training.

Key Terms

  • cost center: A division or project of an organization to which costs can be specifically allocated.

Decision-making Process

Decision making can be regarded as the mental processes (cognitive processes) resulting in the selection of a course of action among several alternative scenarios. Every decision making process produces a final choice. The output can be an action or an opinion of choice. A typical decision-making process involves several steps:

  1. Objectives must first be established;
  2. Objectives must be classified and placed in order of importance;
  3. Alternative actions must be developed;
  4. The alternatives must be evaluated against all the objectives;
  5. The alternative that is able to achieve all the objectives is the tentative decision;
  6. The tentative decision is evaluated for more possible consequences;
  7. The decisive actions are taken and additional actions are taken to prevent any adverse consequences from becoming problems, which can lead to the processes of problem analysis and decision-making to begin all over again.

Management Information Systems

Information technology refers to the convergence of audio-visual and telephone networks with computer networks through a single cable or link system that unifies signal distribution and management. Business organizations utilize management information systems (MIS), which combine the use of information technology, people, and data/information to provide tools used in making decisions. Management information systems are distinct from other information systems in that they are designed to be used to analyze and facilitate strategic and operational activities in the organization. An MIS supports a business’ long-range plans, providing performance analysis reports on areas critical to those plans, with feedback mechanisms that improve guidance for every aspect of the enterprise, including recruitment and training. MIS not only indicates how various aspects of a business are performing, but also why and where. MIS reports include near-real-time performance of cost centers and projects with detail sufficient for individual accountability.

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Smartphones Make It Easier for Individuals to Make Informed Decisions.: Technology enables fast access to vast quantities of information, which can lead to better decision-making.

Information and Risk Trade-Off

IT risk relates to the business risk associated with the use, ownership, operation, involvement, and adoption of IT within an enterprise.

Learning Objectives

Explain how organizations can measure and control IT risk

Key Takeaways

Key Points

  • IT risk encompasses, not only the negative impact on operations and service delivery which can bring destruction or reduction of the organization’s value, but also the benefit \value enabling risk associated with missed opportunities to use technology or the improper management of IT projects.
  • The measure of IT risk can be determined as a product of threat, vulnerability and asset values or Risk = Threat * Vulnerability * Asset Value.
  • IT risk management can be considered a component of a wider enterprise risk management (ERM) system. Some organizations have a comprehensive enterprise risk management methodology, which addresses four objective categories: strategy, operations, financial reporting, and compliance.

Key Terms

  • COSO: Committee of Sponsoring Organizations of the Treadway Commission (COSO) is a voluntary private-sector organization dedicated to providing thought leadership to executive management and governance entities on aspects of organizational governance, business ethics, internal control, enterprise risk management, fraud and financial reporting.
  • likelihood: The probability of a specified outcome; the chance of something happening; probability; the state of being probable.

Measuring IT Risk

Information technology (IT) risk involves the business risk associated with the use, ownership, operation, involvement, influence and adoption of IT within an enterprise. IT encompasses not only the negative impact on operations and service delivery, but also the benefit and/or value enabling risk associated with missed opportunities to use technology to enable or enhance the business (including improper management of IT projects). The negative impact can cause destruction or reduction of the organization’s value. The benefit and/or enabling risk can result in overspending or late delivery of projects that lead to adverse business results.

Risk is the product of the likelihood of an occurrence times its impact (Risk = Likelihood x Impact). The measure of IT risk can be determined as a product of threat, vulnerability, and asset values (Risk = Threat x Vulnerability x Asset Value).

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Possible Business Risks: This chart represents a list of the possible risks involved in running an organic business. Risks such as these affect sales, which in turn affect the amount of operating leverage a company should utilize.

IT and Enterprise Risk Management

IT risk management can be viewed as a component of a wider enterprise risk management (ERM) system. Some organizations have a comprehensive enterprise risk management methodology in place. The four objective categories addressed in an ERM, according to COSO, are:

  1. Strategy – high-level goals, aligned with and supporting the organization’s mission
  2. Operations – effective and efficient use of resources
  3. Financial Reporting – reliability of operational and financial reporting
  4. Compliance – compliance with applicable laws and regulations

IT risk transverses all four of the aforementioned categories and should be managed within the framework of enterprise risk management. Risk appetite and risk sensitivity of the whole enterprise should guide the IT risk management process. ERM should provide the context and business objectives on the management of IT risk.

Information and Knowledge

Knowledge is acquired through the use of and access to information.

Learning Objectives

Explain the process of transforming information into knowledge

Key Takeaways

Key Points

  • Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Information seeking is related to, but different from, information retrieval.
  • Retrieving information is an integral part of information gathering and with today’s technology it can involve searching for documents, for information within documents, and for metadata about documents,. It may also involve searching structured storage, relational databases, and the Internet.
  • Both information access and information architecture can facilitate user access to vast quantities of information and the use of it.

Key Terms

  • relational database: A database consisting of separate tables, having explicitly defined relationships, and whose elements may be selectively combined as the results of queries.
  • metadata: Data that describes other data, serving as an informative label.
  • database: a collection of information in a regular structure, usually, but not necessarily in a machine-readable format accessible by a computer

Using and Managing Information

Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Information seeking is related to, but different from, information retrieval. Retrieving information is an integral part of information gathering and with today’s technology it can involve searching for documents, for information within documents, and for metadata about documents. Receiving information can also involve searching structured storage, relational databases, and the Internet. Information management (IM) is the collection and management of information from one or more sources and the distribution of that information to one or more audiences. Sometimes this involves those who have a stake in, or a right to that information. Management means the organization of and control over the structure, processing and delivery of information.

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Information Presented in a Software Application: Well-organized information improves knowledge and decision making.

Knowledge Through Information

Knowledge is acquired through the use of and access to information. An area of research known as information access aims to automate the processing of large and unwieldy amounts of information and to simplify users’ access to it. Applicable technologies include information retrieval, text mining, machine translation, and text categorization. Information architecture (IA) is the art and science of organizing and labeling websites, intranets, online communities and software to support information use. It is an emerging discipline and community of practice focused on bringing together principles of design and architecture to the digital landscape. Typically it involves a model or concept of information which is used and applied to activities that require explicit details from complex programs and information systems. These activities include library systems and database development.

Data and Information

Data consists of nothing but facts, which can be manipulated to make it useful; the analytical process turns the data into information.

Learning Objectives

Explain the process of turning data into information

Key Takeaways

Key Points

  • Data are the numbers, characters, or symbols on which operations are performed by a computer, being stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media.
  • In order to be processed by a computer, data needs to be first converted into a machine readable format. Once data is in digital format, various procedures can be applied on the data to get useful information.
  • Data processing may involve various processes, including: data summarization, data aggregation, data validation, data tabulation, and statistical analysis.

Key Terms

  • primary data: information collected by the investigator conducting the research
  • tabulation: A table displaying data in compact form.
  • statistical analysis: The process of examining data to draw conclusions or insights, and determine cause-and-effect patterns between events; for example determining the safety and efficacy of new drugs by drawing out a probability as to whether the fact that a patient got better (or worse) was due to the drug or some other (perhaps random) factor.
  • secondary data: information collected by someone other than the user of the data

Forms of Computer Data

Data are the numbers, characters, or symbols on which operations are performed by a computer, being stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media. A program is a set of data that consists of a series of coded software instructions to control the operation of a computer or other machine. While program files are referred to as executable files, they may also contain data which is built into the program. For example, some programs have a data segment, which contains constants and initial values. Binary files (readable by a computer but not a human) are sometimes called “data” and are distinguishable from human-readable data, referred to as “text”.

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Changing Technology Has Improved The Way Data Is Organized.: Computer systems make it easier to turn data into useful information.

Data vs. Information

Data consists of nothing but facts (organized or unorganized) which can then be manipulated into other forms to make it useful and understandable, turning the data into information. The process of manipulating facts to information is referred to as “processing. ” In order to be processed by a computer, data needs to first be converted into a machine readable format. Once data is in digital format, various procedures can be applied on the data to get useful information. Data processing may involve various processes, including:

  1. Data summarization
  2. Data aggregation
  3. Data validation
  4. Data tabulation
  5. Statistical analysis

Data processing may or may not be distinguishable from data conversion, which involves changing data into another format, and does not involve any data manipulation. During processing, raw data is used as an input to produce information as an output, typically in the form of reports and other analytical tools.