IT Knowledge Class-II Decision Support System

Class-II

Decision Support System

A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e. Unstructured and Semi-Structured decision problems. Decision support systems can be either fully computerized, human-powered or a combination of both.

While academics have perceived DSS as a tool to support decision making process, DSS users see DSS as a tool to facilitate organizational processes. Some authors have extended the definition of DSS to include any system that might support decision making.

DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, and personal knowledge, or business models to identify and solve problems and make decisions.

What are characteristics of a decision support system?

DSS are interactive computer-based systems and subsystems intended to help decision-makers. These definitions include a number of characteristics.

Sprague in 1980, identifies 4 characteristics of DSS:

1.     DSS tends to be aimed at the less well structured, underspecified problem that upper level managers typically face;

2.     DSS attempts to combine the use of models or analytic techniques with traditional data access and retrieval functions;

3.     DSS specifically focuses on features which make them easy to use by non-computer people in an interactive mode; and

4.     DSS emphasizes flexibility and adaptability to accommodate changes in the environment and the decision making approach of the user.

Alter in, 1980identified three major characteristics of DSS:

1.     DSS are designed specifically to facilitate decision processes,

2.     DSS should support rather than automate decision making, and

3.     DSS should be able to respond quickly to the changing needs of decision makers.

ClydeHolsapple and Andrew Whinston in 1996, identified four characteristics of DSS.

Turban and Aronson identified 13 characteristics and capabilities of DSS.

Considering the above we have summarized a list of the characteristics of a DSS as follows:

1.     Facilitation. DSS facilitate and support specific decision-making activities and/or decision processes.

2.     Interaction. DSS are computer-based systems designed for interactive use by decision makers or staff users who control the sequence of interaction and the operations performed.

3.     Ancillary. DSS can support decision makers at any level in an organization. They are NOT intended to replace decision makers.

4.     Repeated Use. DSS are intended for repeated use. A specific DSS may be used routinely or used as needed for ad hoc decision support tasks.

5.     Task-oriented. DSS provide specific capabilities that support one or more tasks related to decision-making, including: intelligence and data analysis; identification and design of alternatives; choice among alternatives; and decision implementation.

6.     Identifiable. DSS may be independent systems that collect or replicate data from other information systems OR subsystems of a larger, more integrated information system.

7.     Decision Impact. DSS are intended to improve the accuracy, timeliness, quality and overall effectiveness of a specific decision or a set of related decisions.

Advantages of DSS

• Improves performance and effectiveness of the user
• Allows for faster decision-making
• Reduces the time taken to solve problems
• These combine to save money!
• Has been seen to improve collaboration and communication within groups
• Reduces training times because the experience of experts is available within the programs algorithms
• Provides more evidence in support of a decision
• May increase decision-maker satisfaction
• Providing different perspectives to a situation
• Helps automate various business systems

Disadvantages

• Too much emphasis/control given to the machines.
• May reduce skill in staff because they become dependent on the computers
• Reduction in efficiency because of information overload
• Shift of responsibility - easy to blame computer!
• Disgruntled employees who feel they are now only doing clerical work
• False sense of being objective - humans still feed information in and decide how exactly to process it.

Components of DSS:

Four basic components –

The users: The user of a decision support system is usually a manager with anunstructured or semi-structured problem to solve.

Databases: Databases contain both routine and non-routine data from both internal andexternal sources.

Planning languages: Two types of planning languages. General purpose planninglanguages allow users to perform many routine tasks. Special purpose planninglanguages are more limited in what they can do. But they usually do certain jobs betterthan the general purpose planning languages.

The model base: It is the brain of the DSS because it performs data manipulations andcomputation with the date provided to it by the user and the database.

Types of DSS:
Using the relationship with the user as the criterion, Haettenschweiler differentiates
Passive,
Active, and
Cooperative DSS.
A passive DSS is a system that aids the process of decision making, but that cannot bring out explicit decision suggestions or solutions.
An active DSS can bring out such decision suggestions or solutions.
A cooperative DSS allows the decision maker (or its advisor) to modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation. The system again improves, completes, and refines the suggestions of the decision maker and sends them back to them for validation. The whole process then starts again, until a consolidated solution is generated.

Another taxonomy for DSS has been created by Daniel Power. Using the mode of assistance as the criterion, Power differentiates

Communication-driven DSS,                                                            

Data-driven DSS,
Document-driven DSS,
Knowledge-driven DSS, and
Model-driven DSS.

• A communication-driven DSS supports more than one person working on a shared task; examples include integrated tools like Google Docs or Groove
• A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.
• A document-driven DSS manages, retrieves, and manipulates unstructured information in a variety of electronic formats.
• A knowledge-driven DSS provides specialized problem-solving expertise stored as facts, rules, procedures, or in similar structures.^[8]
• A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data-intensive. Decodes is an example of an open source model-driven DSS generator.^[10]

Using scope as the criterion, Powerdifferentiates
Enterprise-wide DSS and
Desktop DSS.

An enterprise-wide DSS is linked to large data warehouses and serves many managers in the company.

A desktop, single-user DSS is a small system that runs on an individual manager's PC.

Examples of Decision Support Systems in Accounting (page no.-42)

Cost Accounting System

Capital Budgeting System

Budget Variance Analysis System

General Decision Support System