What Is Decision Support System?

DSS can be defined as use of computer application that can help managers, staff members, or people who interact within the organization to make decisions and identify problems by using available data and communication technology.

Origin Of DSS

In 1960 J. C. R. Licklider wrote a paper on his observation of how the interaction between man and computer can improve the quality and competency in recognising and problem solving. His paper proved to be like a guide to many future researches on DSS. In 1962 with use of hypertext online system helped in storage and retrieval of documents and creation of digital libraries. SAGE (Semi Automatic Ground Environment) built by Forrester is probably the first data driven computerised DSS. In 1964 Scott Morton built up an interactive model driven management decision system which could help managers make important management decisions. In 1970 John D.C. Little noted that the requirement for designing models and system to make a management decision was completeness to data, simplicity, ease of control and robustness, which till date are relevant in improving and evaluating modern DSS’s. By 1975 he built up a DSS called Brandaid which could support promotion, advertising, pricing and product related decisions. In 1974 the focus was on giving managers with information which was from accounting and transaction processing system with use if MIS(Management Information Systems) but MIS was found to not helping out managers with making key decisions. Hence in 1979 Scott Morton and Gorry argued that MIS just primarily focused on structured decisions and hence the system which also supports unstructured and semi-structured decision should be termed as Decision support systems.

In s nutshell developments:-

1960ƒ  Building model-driven DSS

1970 ƒ  Theory developments

Mid 80’s ƒ Implementation of financial planning systems, spreadsheet DSS and Group DSS.

Early 90’s ƒ  Evolving of Data warehouses, Executive Information Systems, OLAP and Business Intelligence.

Mid 90’s ƒ Knowledge-driven DSS and the implementation of Web-based DSS

Types Of DSS:

Model Driven DSS

`Quantitative models provide the most basic level of functionality. Model driven DSS’s use small data and parameters provided by the DSS’s users usually managers to help them in analysing a problem and generate statistical, financial report and simulation model to help the decision makers. Model driven DSS’s question can help organisational processes to answer the “WHAT IF” question and thus help them forecast the effects of changes in business process.

Ferguson and Jones’ production scheduling application was also a model-driven DSS but Scott-Morton’s in 1971, production planning management decision system was the first widely discussed model-driven DSS.

Data Driven DSS

Data driven DSS are systems which makes use of company’s mostly internal data and sometimes external and real time data to help organisations make decisions. Usually the data comes in form of databases or data warehouse which allows queries and data retrieval tools and analysis to make decisions.

Richard Klaas and Charles Weiss at American Airlines developed one of the first data-driven DSS. An example of data driven DSS can be use of digital maps or the GIS( Geographic Information System).

Communication Driven DSS

Communication Driven DSS helps in decision making to internal group of people by sharing of information and enabling communication between them. Most basic example can be the threaded email between a group and complex example can be video conferencing. In communication driven DSS communication technologies is most important component of its working architecture. In recent years internet provided vast possibilities to communication driven DSS.

Groupware bulletin video and audio conferencing are few of the technologies used for communication Driven DSS.

Document Driven DSS

Document driven DSS uses the organisations documents such as policies, procedures, processes, specifications, historical, stored documents and processing technologies to give documental analysis and enhance decision making. This type is system is usually targeted at larger base of users.

Internet greatly increases the availability of all required documents and hence helps in development of document driven DSS.

Knowledge Driven DSS

Knowledge Driven DSS are used usually by managers to help them with management advice or to choose products or services. These DSS’s can be just a standalone computers with applications which are expert in particular domain along with its understanding so as to solve the problems of that particular domain. Artificial intelligence is vastly used by such application to help Knowledge driven DSS’s.

Now a day’s Knowledge Driven DSS coupled with intelligence systems are used at medical diagnostic centre’s, fraud detection and scheduling manufacturing operations.

Web-based DSS

Computerized DSS’s capabilities were extended with emergence of internet and world-wide web. With passing time HTML developed and TAGS and tables further helped in enhancing Web-based DSS. With all these developments web-based DSS became main platform for all types of DSS to develop. Corporate have started using intranet for knowledge management and support information exchange between various departments. The server that is having the DSS application is connected to the computer by a network through the TCP/IP protocol. Recently application service provider’s introduced enterprise knowledge portals that combined information portals, knowledge management, business intelligence and communications-driven DSS in an integrated Web environment.

Benefits of DSS

Improves efficiency

Helps in faster problem solving

Helps in interpersonal communication

Promotes learning

Increases organizational control

Provides new evidence in support of a decision

Creates a competitive advantage over competition

Encourages exploration and discovery on the part of the decision maker

Reveals new approaches to thinking about the problem space

Helps automate the managerial processes.

Cost reduction and enhance profit.

Disadvantages of DSS

Over dependency for Decision making

Assuming it to be correct.

Unanticipated effects

Deflect personal responsibilities

Information overload.

Conclusion

DSS is still and evolving technology. The types of DSS mentioned are just few of the many DSS which are around and help organization in decision making. Many of the types of DSS are subsets of previously researched and created DSS with added functionality and/or requirements.

A very brief span of historical data has been used to portray DSS evolution and growth in early years. All the scientists, researchers and professors then set up a base for future DSS to develop and build upon to enhance and simplify decision making.

By understanding how DSS evolved over the period of time and how its still being developed helps us in understanding how and where the future DSS’s are heading and what to expect next in this fast emerging technology. Of the types discussed Web based is the most rapidly growing and improving DSS. Recent developments in internet, computers and communication devices are helping Web-based DSS application to divulge into various other fields.

DSS and DSS application continues to take advantage of any and all emerging technologies in artificial intelligence, databases, data warehouses, human interaction with computers which can help improve it more and simplify decision making.

Sources/References::

http://www.bestpricecomputers.co.uk/glossary/decision-support-systems.htm

http://searchcio.techtarget.com/definition/decision-support-system

http://en.wikipedia.org/wiki/Decision_support_system

http://dssresources.com/history/dsshistory.html