Class-II

Decision Support System

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

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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 authorshave extended the definition of DSS to include any system that might supportdecision making.

DSSs include knowledge-based systems. A properly designed DSS is an interactivesoftware-based system intended to help decision makers compile usefulinformation 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 helpdecision-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 problemthat upper level managers typically face;

2. DSS attempts to combine the use of models or analytic techniques withtraditional 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 theenvironment 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, and3. DSS should be able to respond quickly to the changing needs of decision

makers.

Clyde Holsapple and Andrew Whinston in 1996, identified four characteristics ofDSS.

Turban and Aronson identified 13 characteristics and capabilities of DSS.

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

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

2. Interaction. DSS are computer-based systems designed for interactive useby decision makers or staff users who control the sequence of interactionand 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 beused routinely or used as needed for ad hoc decision support tasks.

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

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

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

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!

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Has been seen to improve collaboration and communication within groups

Reduces training times because the experience of experts is available withinthe 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 decidehow 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 bothinternal and external sources.Planning languages: Two types of planning languages. General purposeplanning languages allow users to perform many routine tasks. Special purpose

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planning languages are more limited in what they can do. But they usually docertain jobs better than the general purpose planning languages.The model base: It is the brain of the DSS because it performs datamanipulations and computation with the date provided to it by the user and thedatabase.

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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.

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A communication-driven DSS supports more than one person working on ashared task; examples include integrated tools like Google Docs or Groove

A data-driven DSS or data-oriented DSS emphasizes access to andmanipulation of a time series of internal company data and, sometimes,external data.

A document-driven DSS manages, retrieves, and manipulates unstructuredinformation in a variety of electronic formats.

A knowledge-driven DSS provides specialized problem-solving expertisestored 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 dataand parameters provided by users to assist decision makers in analyzing asituation; they are not necessarily data-intensive. Decodes is an example ofan open source model-driven DSS generator.[10]

Using scope as the criterion, Power differentiates

Enterprise-wide DSS and

Desktop DSS.

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

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

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

Cost Accounting SystemCapital Budgeting SystemBudget Variance Analysis SystemGeneral Decision Support System

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