A Decision Support System (DSS)
A Decision Support System (DSS) is an interactive computer-based system or subsystem intended to help decision makers use communications technologies, data, documents, knowledge and/or models to identify and solve problems, complete decision process tasks, and make decisions.
Decision Support System is a general term for any computer application that enhances a person or group’s ability to make decisions.
Also, Decision Support Systems refers to an academic field of research that involves designing and studying Decision Support Systems in their context of use. In general, Decision Support Systems are a class of computerized information system that support decision-making activities. Five more specific Decision Support System types include:
Communications-Driven DSS is a type of DSS that emphasizes communications, collaboration and shared decision-making support. A simple bulletin board or threaded email is the most elementary level of functionality. The comp.groupware FAQ defines groupware as "software and hardware for shared interactive environments" intended to support and augment group activity. Groupware is a subset of a broader concept called Collaborative Computing. Communications-Driven DSS enable two or more people to communicate with each other, share information and co-ordinate their activities. Group Decision Support Systems or GDSS is a hybrid type of DSS that allows multiple users to work collaboratively in groupwork using various software tools. Examples of group support tools are: audio conferencing, bulletin boards and web-conferencing, document sharing, electronic mail, computer supported face-to-face meeting software, and interactive video.
Communications-Driven DSS software has at least one of the following characteristics:
- Enables communication between groups of people
- Facilitates the sharing of information
- Supports collaboration and coordination between people
- Supports group decision tasks
Key research issues for Communications-Driven DSS include impacts on group processes and group awareness, multi-user interfaces, concurrency control, communication and coordination within the group, shared information space and the support of a heterogenous, open environment which integrates existing single-user applications. Communications-Driven Decision Support Systems are often categorized according to the time/location matrix using the distinction between same time (synchronous) and different times (asynchronous), and between same place (face-to-face) and different places (distributed).
Data-Driven DSS Resources
This web page contains links to many sites that contain information related to Data-driven DSS, especially Data Warehousing (DW) and On-line Analytical Processing (OLAP).
Data-driven DSS is a type of DSS that emphasizes access to and manipulation of a time-series of internal company data and sometimes external data. Simple file systems accessed by query and retrieval tools provide the most elementary level of functionality. Data warehouse systems that allow the manipulation of data by computerized tools tailored to a specific task and setting or by more general tools and operators provide additional functionality. Data-driven DSS with On-line Analytical Processing (OLAP) provides the highest level of functionality and decision support that is linked to analysis of large collections of historical data. Executive Information Systems (EIS) and Geographic Information Systems (GIS) are special purpose Data-Driven DSS.
A Data Warehouse is a database designed to support decision making in organizations. It is batch updated and structured for rapid online queries and managerial summaries. Data warehouses contain large amounts of data. A data warehouse is a subject-oriented, integrated, time-variant, nonvolatile collection of data in support of management's decision making process.
On-line Analytical Processing (OLAP) software is used for manipulating data from a variety of sources that has been stored in a static data warehouse. The software can create various views and representations of the data. For a software product to be considered an OLAP application it must contain three key features: 1. multidimensional views of data; 2. complex calculations; and 3. time oriented processing capabilities.
Executive Information Systems (EIS) are computerized systems intended to provide current and appropriate information to support executive decision making for managers using a networked workstation. The emphasis is on graphical displays and an easy to use interface that present information from the corporate database. They are tools to provide canned reports or briefing books to top-level executives. EIS offer strong reporting and drill-down capabilities.
A Geographic Information System (GIS) or Spatial DSS is a support system that represents data using maps. It helps people access, display and analyze data that have geographic content and meaning.
Document-Driven DSS Resources
Description and Definition
Document-Driven DSS is a relatively new field in Decision Support. Document-Driven DSS is focused on the retrieval and management of unstructured documents. Documents can take many forms, but can be broken down into three categories: Oral, written, and video. Examples of oral documents are conversations that are transcribed; video can be news clips, or television commercials; written documents can be written reports, catalogs, letters from customers, memos, and even e-mail.
Jane Fedorowicz (1996) estimated that American businesses store almost 1.3 trillion documents which can use up to 50% of their floor space. Yet only 5 to 10 percent of these documents are available to managers for use in decision making. Fedorowicz defined document as a "chunk" of information. Unfortunately documents are not standardized in a uniform pattern or structure. Managers and IT/IS staff need a way to transform these documents into usable formats that can be compared and processed to support decision making. New information technology and software is making this concept into a reality.
Information Retrieval
Examples of information retrieval systems are Lexis-Nexis, InfoSys, and UNCOVER. Web search engines such as WebCrawler, Alta Vista and Lycos help web users to define searches based on "keyword" inputs. Cognitive Modeling, such as "My Yahoo" integrates knowledge of the user into retrieval tools. Retrieval can even be based on AI fuzzy theory models that use parameters for searches based on relative commonality or reason to the keyword.
Knowledge-Driven DSS
Most of the material on Knowledge-Driven DSS is in the Subscriber Zone.About Knowledge-Driven DSS
Knowledge-Driven DSS can suggest or recommend actions to managers. These DSS are person-computer systems with specialized problem-solving expertise. The "expertise" consists of knowledge about a particular domain, understanding of problems within that domain, and "skill" at solving some of these problems. A related concept is Data Mining. It refers to a class of analytical applications that search for hidden patterns in a database. Data mining is the process of sifting through large amounts of data to produce data content relationships. Tools used for building Knowledge-Driven DSS are sometimes called Intelligent Decision Support methods (cf., Dhar and Stein, 1997).Model-Driven DSS
Most of the material on Model-Driven DSS is in the DSSResources.COM Subscriber Zone.About Model-Driven DSS
Model-Driven DSS emphasize access to and manipulation of a model, for example, statistical, financial, optimization and/or simulation models. Simple statistical and analytical tools provide the most elementary level of functionality. Some OLAP systems that allow complex analysis of data may be classified as hybrid DSS systems providing both modeling and data retrieval and data summarization functionality. In general, model-driven DSS use complex financial, simulation, optimization or multi-criteria models to provide decision support. Model-driven DSS use data and parameters provided by decision makers to aid decision makers in analyzing a situation, but they are not usually data intensive, that is very large data bases are usually not need for model-driven DSS. Early versions of Model-Driven DSS were called Computationally Oriented DSS by Bonczek, Holsapple and Whinston (1981). Such systems have also been called model-oriented or model-based decision support systems.Key Terms
Decision Analysis tools - DA tools help decision makers decompose and structure problems. The aim of these tools is to help a user apply models like decision trees, multi-attribute utility models, bayesian models, Analytical Hierarchy Process (AHP), and related models.Forecasting Support System - A computer-based system that supports users in making and evaluating forecasts. Users can analyse a time series of data.
Linear Programming - A mathematical model for optimal solution of resource allocation problems.
Simulation - A technique for conducting one or more experiments that test various outcomes resulting from a quantitative model of a system.
Web-Based DSS
Most of the material on Web-based DSS at DSSResources.COM is in the Subscriber Zone.About Web-based DSS
Web-Based DSS deliver decision support information or decision support tools to a manager or business analyst using a "thin-client" Web browser like Netscape Navigator or Internet Explorer that is accessing the Global Internet or a corporate intranet. The computer server that is hosting the DSS application is linked to the user's computer by a network with the TCP/IP protocol. Web-Based DSS can be communications-driven, data-driven, document-driven, knowledge-driven, model-driven or a hybrid. Web technologies can be used to implement any category or type of DSS. Web-based means the entire application is implemented using Web technologies; Web-enabled means key parts of an application like a database remain on a legacy system, but the application can be accessed from a Web-based component and displayed in a browser.Symbol
/Meaning
/ Terminal Block (Oblong) - Shows the beginning and the end of the process./ Process Block – Shows actions in the process. An operation is performed whenever some change in an item/service occurs.
/ Decision Point – Shows a point in the process where a decision is made that leads to different processing steps.
/ Document-Shows a document introduced into the process or created by the process. The flowchart should show the disposition of all documents.
/ On-Page Connector – Continues the flow on the same page. On-page connectors are defined with an alpha character starting with A.
/ Off-Page Connector – Continues the flow to another page. Off-page connectors are defined with an alpha character and the reference to the page to which the flow is going, or the page from which the flow has come, depending on the nature of the connector.
/ Direction of Flow – Denotes the direction and order of the process steps.
/ Electronic Connection/Flow - Denotes flow of data from an activity to an electronic database or system.
/ Off-line Storage-Denotes a storage location, generally for hard-copy documents, such as a filing cabinet. It may also be used to represent a temporary storage such as a drawer or even a clipboard.
/ Annotation – Used to add additional notes to the flowchart and reference the notes to a symbol on the flowchart.
/ Unit Separator – Use to separate units or individuals performing tasks.
/ System – Represents a computer system. Generally this symbol is used to denote a manual interface with an automated system, typically an application.
/ Note Symbol – The note number symbol references notes in the left-hand margin of the flowchart.
/ Product Symbol – This symbol denotes physical product entering the process.
/ Hyperlink Symbol – This symbol indicates a hyperlink to another file, document, website, etc.
Input and Output Symbols
Data
(I/O) The Data flowchart shape indicates inputs to and outputs from a process. As such, the shape is more often referred to as an I/O shape than a Data shape.
Document Pretty self explanatory – the Document flowchart symbol is for a process step that produces a document.
Multi-Document Same as Document, except, well, multiple documents. This shape is not as commonly used as the Document flowchart shape, even when multiple documents are implied.
Display Indicates a process step where information is displayed to a person (e.g., PC user, machine operator).
Manual Input Manual Input flowchart shapes show process steps where the operator/ user is prompted for information that must be manually input into a system.
Card This is the companion to the punched tape flowchart shapes. This shape is seldom used.
Punched Tape If you’re very good at stretching all the life out of a machine, you may still have use for the Punched Tape symbol – used for input into old computers and CNC machines.
File and Information Storage Symbols
Stored Data A general Data Storage flowchart shape used for any process step that stores data (as opposed to the more specific shapes to follow next in this table).
Magnetic Disk (Database) The most universally recognizable symbol for a data storage location, this flowchart shape depicts a database.
Direct Access Storage Direct Access Storage is a fancy way of saying Hard Drive.
Internal Storage Used in programming flowcharts to mean information stored in memory, as opposed to on a file.
Sequential Access Storage
(Magnetic Tape) Although it looks like a ‘Q’, the symbol is supposed to look like a reel of tape.
Data Processing Symbols
Collate The Collate flowchart shape indicates a process step that requires organizing data, information, or materials according into a standard format or arrangement.
Sort Indicates the sorting of data, information, materials into some pre-defined order.
Branching and Control of Flow Symbols
Flow Line
(Arrow, Connector) Flow line connectors show the direction that the process flows.
Terminator
(Terminal Point, Oval) Terminators show the start and stop points in a process. When used as a Start symbol, terminators depict a trigger action that sets the process flow into motion. Decision Indicates a question or branch in the process flow. Typically, a Decision flowchart shape is used when there are 2 options (Yes/No, No/No-Go, etc.)
Connector (Inspection) Flowchart: In flowcharts, this symbol is typically small and is used as a Connector to show a jump from one point in the process flow to another. Connectors are usually labeled with capital letters (A, B, AA) to show matching jump points. They are handy for avoiding flow lines that cross other shapes and flow lines. They are also handy for jumping to and from a sub-processes defined in a separate area than the main flowchart.
Process Mapping: In process maps, this symbol is full sized and shows an Inspection point in the process flow.
Off-Page Connector Off-Page Connector shows continuation of a process flowchart onto another page. When using them in conjunction with Connectors, it’s best to differentiate the labels, e.g. use numbers for Off-Page Connectors and capital letters for Connectors. In actual practice, most flowcharts just use the Connect shape for both on-page and off-page references. Merge
(Storage) Flowchart: Shows the merging of multiple processes or information into one.
Process Mapping: commonly indicates storage of raw materials.
Extract (Measurement) Flowchart: Shows when a process splits into parallel paths. Also commonly indicates a Measurement, with a capital ‘M’ inside the symbol.
Process Mapping: commonly indicates storage of finished goods.
Or The logical Or symbol shows when a process diverges – usually for more than 2 branches. When using this symbol, it is important to label the out-going flow lines to indicate the criteria to follow each branch.
Summing Junction The logical Summing Junction flowchart shape is shows when multiple branches converge into a single process. The merge symbol is more common for this use, though. This symbol and the Or symbol are really more relevant in data processing flow diagrams than in process flowcharts.
SWOT analysis is a strategic planning method used to evaluate the Strengths, Weaknesses, Opportunities, and Threats involved in a project or in a business venture.
It involves specifying the objective of the business venture or project and identifying the internal and external factors that are favorable and unfavorable to achieve that objective.
The technique is credited to Albert Humphrey, who led a convention at Stanford University in the 1960s and 1970s using data from Fortune 500 companies.
A SWOT analysis must first start with defining a desired end state or objective. A SWOT analysis may be incorporated into the strategic planning model. Strategic Planning has been the subject of much research.[citation needed]
- Strengths: characteristics of the business or team that give it an advantage over others in the industry.
- Weaknesses: are characteristics that place the firm at a disadvantage relative to others.
- Opportunities: external chances to make greater sales or profits in the environment.
- Threats: external elements in the environment that could cause trouble for the business.
Identification of SWOTs is essential because subsequent steps in the process of planning for achievement of the selected objective may be derived from the SWOTs.
First, the decision makers have to determine whether the objective is attainable, given the SWOTs. If the objective is NOT attainable a different objective must be selected and the process repeated.
The aim of any SWOT analysis is to identify the key internal and external factors that are important to achieving the objective. These come from within the company's unique value chain. SWOT analysis groups key pieces of information into two main categories:
- Internal factors – The strengths and weaknesses internal to the organization.
- External factors – The opportunities and threats presented by the external environment to the organization. -
The internal factors may be viewed as strengths or weaknesses depending upon their impact on the organization's objectives. What may represent strengths with respect to one objective may be weaknesses for another objective. The factors may include all of the 4P's; as well as personnel, finance, manufacturing capabilities, and so on. The external factors may include macroeconomic matters, technological change, legislation, and socio-cultural changes, as well as changes in the marketplace or competitive position. The results are often presented in the form of a matrix.