Chapter 3: Decision Support Systems Concepts, Methodologies, and Technologies

Question 1

Business Intelligence System

Answer 1

A system that monitors situations and identifies problems and/or opportunities using analytic methods.

Question 2

Decision Support System (DSS) Applications

Answer 2

An approach (or methodology) for supporting decision making on certain problems or evaluation of opportunities. Typically uses its own databases.

Question 3

Business Analytics Systems

Answer 3

Business intelligence systems that include analytical tools.

Question 4

Business Analytics (BA)

Answer 4

The use of models and data to improve an organization’s performance or competitive posture.

Question 5

Web Analytics

Answer 5

An approach to using business analytics tools on real-time Web information to assist in decision making.

Question 6

Predictive Analytics

Answer 6

The business analytics method of forecasting problems and opportunities rather than simply reporting them as they occur.

Question 7

Key Characteristics and Capabilities of DSS

Answer 7

1. Support for decision makers, mainly in semistructured and unstructured situations, by bringing together human judgment and computerized information. Such problems cannot be solved (or cannot be solved conveniently) by other computerized systems or through use of standard quantitative methods or tools. Generally, these problems gain structure as the DSS is developed. Even some structured problems have been solved by DSS.
2. Support for all managerial levels, ranging from top executives to line managers.
3. Support for individuals as well as groups. Less-structured problems often require the involvement of individuals from different departments and organizational levels or even from different organizations. DSS support virtual teams through collaborative Web tools. DSS have been developed to support individual and group work, as well as to support individual decision making and groups of decision makers working somewhat independently.
4. Support for interdependent and/or sequential decisions. The decisions may be made once, several times, or repeatedly.
5. Support in all phases of the decision-making process: intelligence, design, choice, and implementation.
6. Support for a variety of decision-making processes and styles.
7. The decision maker should be reactive, able to confront changing conditions quickly, and able to adapt the DSS to meet these changes. DSS are flexible, so users can add, delete, combine, change, or rearrange basic elements. The are also flexible in that they can be readily modified to solve other, similar problems.
8. User-friendliness, strong graphical capabilities, and a natural language interactive human-machine interface can greatly increase the effectiveness of DSS. Most new DSS applications use Web-based interfaces.
9. Improvement of the effectiveness of decision making (e.g., accuracy, timeliness, quality) rather than its efficiency (e.g., the cost of making decisions). When DSS are deployed, decision making often takes longer, but the decisions are better.
10. The decision maker has complete control over all steps of the decision-making process in solving a problem. A DSS specifically aims to support, not to replace, the decision maker.
11. End users are able to develop and modify simple systems by themselves. Larger systems can be built with assistance from information systems (IS) specialists. Spreadsheet packages have been utilized in developing simpler systems. OLAP and data mining software, in conjunction with data warehouses, enable users to build fairly large, complex DSS.
12. Models are generally utilized to analyze decision-making situations. The modeling capability enables experimentation with different strategies under different configurations. In fact, the models make a DSS different from most MIS.
13. Access is provided to a variety of data sources, formats, and types, including GIS, multimedia, and object-oriented data.
14. The DSS can be employed as a stand-alone tool used by an individual decision maker in one location or distributed throughout an organization and in several organizations along the supply chain. It can be integrated with other DSS and/or applications, and it can be distributed internally and externally, using networking and Web technologies.

Question 8

Decision Support System Classifications

Answer 8

The type of DSS, which determines the design process, operation, and implementation of the DSS. (p79)
● Most DSS fit into the Association for Information Systems Special Interest Group on Decision Support Systems (AIS SIGDSS) classification scheme categories
● Other classification systems include Holsapple and Whinston’s Classification and Alter’s Output Classification
● Other DSS categories include institutional and ad hoc DSS; personal, group, and organizational support; individual support system versus GSS; and custom-made systems versus ready-made systems

Question 9

The AIS SIGDSS Classification for DSS

Answer 9

● Communications-Driven and Group DSS (GDSS)
○ Include DSS that use computer, collaboration, and communication technologies to support groups in tasks that may or may not include decision making
○ DSS that support any kind of group work fall into this category, such as knowledge management systems (KMS) for collaborative work, or those that support meetings, design collaboration, or supply chain management
● Data-Driven DSS
○ Include DSS that are primarily involved with data and processing them into information and presenting the information to a decision maker
○ Many DSS developed in OLAP and data-mining software systems fall into this category, as well as database-oriented DSS
○ Minimal emphasis on the use of mathematical models
● Document-Driven DSS
○ Include DSS that rely on knowledge coding, analysis, search, and retrieval for decision support
○ Main objective of document-driven DSS is to provide support for decision making using documents in various forms such as oral, written, and multimedia
○ Essentially all DSS that are text-based fall into this category, including nearly all knowledge management systems (KMS)
○ Minimal emphasis on the use of mathematical models
● Knowledge-Driven DSS, Data Mining, and Management Expert Systems Applications
○ Include DSS that involve the application of knowledge technologies to address specific decision support needs
○ Almost all artificial intelligence-based DSS fall into this category, along with those that use symbolic storage
○ Benefits of knowledge-based DSS (intelligent DSS) can be very significant
○ These DSS are utilized in the creation of automated decision-making systems
● Model-Driven DSS
○ Include DSS that are primarily developed around one or more (large-scale/complex) optimization or simulation models and typically include significant activities in model formulation, model maintenance, model management in distributed computing environments, and what-if analyses
○ Many large-scale applications fall into this category
○ These systems focus on using models to optimize one or more objectives, such as profit
● Compound DSS (Hybrid DSS)
○ A compound/hybrid DSS includes two or more of the major categories listed above

Question 10

Holsapple and Whinston’s Classification

Answer 10

● Text-Oriented DSS
○ same as the Document-Driven DSS category (AIG SIGDSS)
● Database-Oriented DSS
○ same as the Data-Driven DSS category (AIG SIGDSS)
● Spreadsheet-Oriented DSS
○ similar to the Model-Driven DSS category (AIG SIGDSS) but focusing on the use of spreadsheets and their add-in programs
● Solver-Oriented DSS
○ same as the Model-Driven DSS category (AIG SIGDSS)
● Rule-Oriented DSS
○ includes most DSS that fit into the Knowledge-Driven DSS category (AIG SIGDSS)
● Compound DSS
○ same as the Compound/Hybrid DSS category (AIG SIGDSS)

Question 11

Alter’s Output Classification

Answer 11

● Classification is based on the extent to which system outputs can directly support or determine the decision
● Categories include file drawer systems, data analysis systems, analysis information systems, accounting models representational models, optimization models, suggestion models

Question 12

Institutional DSS

Answer 12

DSS that deal with decisions of a recurring nature, such as portfolio management systems (PMS). Can be developed and refined as it evolves over the years.

Question 13

Ad Hoc DSS

Answer 13

DSS that deal with specific problems that are usually neither anticipated nor recurring, often involving strategic planning issues and sometimes management control problems. It may be hard to justify an ad hoc DSS because of its limited use.

Question 14

Personal, Group, and Organizational Support

Answer 14

● Support given by a DSS can fall into three distinct, interrelated categories
○ Personal Support
■ focus is on individual user performing an activity in a discrete task or decision
○ Group Support
■ focus is on a group of people who are engaged in separate, highly interrelated tasks
○ Organizational Support
■ focus is on organizational tasks or activities involving a sequence of operations, different functional areas, possibly different locations, and massive resources

Question 15

Group Support System (GSS)

Answer 15

A DSS that is focused on supporting collaboration of a group, which may be local or remote and deployed over the web.

Question 16

Components of Decision Support Systems

Answer 16

● Data Management Subsystem
● Model Management Subsystem
● User Interface Subsystem
● Knowledge-Based Management Subsystem

Question 17

The Data Management Subsystem

Answer 17

● The data management subsystem includes a database that contains relevant data for the situation and is managed by software called the database management system (DBMS)
● Can be interconnected with the corporate data warehouse, a repository for corporate relevant decision-making data
● The data management subsystem is composed of the following elements:
○ DSS Database (p90)
■ A collection of interrelated data organized to meet the needs and structure of an organization that can be used by more than one person for more than one application
■ Data are extracted from internal and external sources, along with personal data belonging to users
■ Extraction is a process by which data is captured from several sources to create or load a DSS database or data warehouse
○ DBMS (p92)
■ Creates, accesses, and updates the database
○ Data Directory (p93)
■ A catalog of all of the data in a database that contains data definitions
■ Main function is to answer questions about the availability of data items, their source, and their exact meaning
○ Query Facility (p93)
■ Accesses, manipulates, and queries data
■ Accepts requests for data from other DSS components, determines how the requests can be filled (consulting the data directory), formulates detailed requests, and returns results to request issuer
● Key database and database management system issues
○ Data Quality (p93)
○ Data Integration (p94)
○ Scalability (p95)
○ Data Security (p95)

Question 18

The Model Management Subsystem

Answer 18

● The model management subsystem is a software package that includes financial, statistical, management science, or other quantitative models that provide the system’s analytical capabilities and appropriate software management
○ This software is often called model base management system (MBMS)
● The model management subsystem is composed of the following elements:
○ Model Base (p96)
■ Contains routine and special statistical, financial, forecasting, management science, and other quantitative models that provide the analysis capabilities in a DSS
■ Strategic models are used to support top managers’ strategic planning responsibilities
■ Tactical models are mainly used by middle managers to assist in allocating and controlling the organization’s resources
■ Operational models are used to support the day-to-day working activities of the organization
■ Analytical models are used to perform analysis on data
■ Model building blocks include software elements used to build computerized modes
○ Model Base Management System (p99)
■ MBMS has four main functions
● Model creation, using programming languages, DSS tools and/or subroutines, and other building blocks
● Generation of new routines and reports
● Model updating and changing
● Model data manipulation
○ Modeling Language
■ Modeling languages include AMPL and GAMS
○ Model Directory (p99)
■ Similar role to the database directory
■ A catalog of all the models and other software in the model base
○ Model Execution, Integration, and Command Processor (p99)
■ Model Execution: The process of controlling the actual running of the model
■ Model Integration: Combining the operations of several models when needed or integrating the DSS with other applications

Question 19

The User Interface Subsystem

Answer 19

● All aspects of communication between a user and the DSS or any MSS, including hardware, software, ease of use, accessibility, and human-machine interactions
● User Interface Management System (UIMS): The software that manages the user interface subsystem
○ also called the dialog generation and management system
● The user interface component includes a natural language processor or can use standard object (such as pull-down menus) through a graphical user interface
○ DSS are typically accessed through a web browser, which provides a portal or dashboard to access the system
○ For more information on specific DSS web tools, see pages 102-104

Question 20

The Knowledge-Based Management Subsystem

Answer 20

● Can support any of the other subsystems or act as an independent component
● Provides intelligence to augment the decision maker’s
● Can be interconnected with the organization’s knowledge repository (organizational knowledge base)
● Unlike the DBMS, MBMS, and user interface, the KBMS is an optional DSS component

Question 21

Decision Support System User

Answer 21

The person faced with a decision that an MSS is designed to support (p106)
● also called the manager or the decision maker
● provides the human intellect component of the DSS

Question 22

Intermediary

Answer 22

A person who allows a manager to benefit from a DSS without actually having to use the keyboard. (p107) There are several types of intermediary:
● Staff assistants have specialized knowledge about management problems and experience with DSS
● Expert tool users are skilled in the application of one or more types of specialized problem-solving tools
● Business (system) analysts have a general knowledge or the application area, a formal business administration education, and considerable skill in DSS construction skills
● Facilitators in a GSS control and coordinate the use of software to support the work of people working in groups