A Brief History of Decision Support Systems
version 4.1 or see version 2.8
see version 4.1 in Spanish translated by Maria Ramos
Information Systems researchers and technologists have built and
investigated computerized Decision Support Systems (DSS) for approximately 40 years.
This article chronicles and explores the developments related to building and deploying
DSS. The journey begins with building model-driven DSS in the late 1960s, theory developments in the 1970s, and
implementation of financial planning systems, spreadsheet-based DSS and Group DSS in the early and mid 1980s.
Data warehouses, Executive Information Systems, OLAP and Business Intelligence evolved in the late 1980s
and early 1990s. Finally, the chronicle ends with knowledge-driven DSS and the implementation of
Web-based DSS beginning in the mid-1990s. The field of computerized decision support is expanding to
use new technologies and to create new applications.
Computerized decision support systems became practical with the development of
minicomputers, timeshare operating systems and distributed computing. The history of
the implementation of such systems begins in the mid-1960s. In a technology field as
diverse as DSS, chronicling history is neither neat nor linear. Different people perceive
the field of Decision Support Systems from various vantage points and report different
accounts of what happened and what was important (cf., Arnott & Pervan, 2005; Eom & Lee, 1990b;
McCosh & Correa-Perez, 2006; Power, 2003; Power, 2004a; Silver, 1991). As technology evolved new
computerized decision support applications were developed and studied. Researchers used multiple
frameworks to help build and understand these systems. Today one can organize the history of DSS
into the five broad DSS categories explained in Power (2001; 2002; 2004b), including: communications-driven,
data-driven, document driven, knowledge-driven and model-driven decision support systems.
This hypertext document is a starting point in explaining the origins of the
various technology threads that are converging to provide integrated support for managers working alone,
in teams and in organization hierarchies to manage organizations and make more rational decisions. History
is both a guide to future activity in this field and a record of the ideas and actions of those who have
helped advance our thinking and practice. Historical facts can be sorted out and better understood, but
more information gathering is necessary. This web page is a starting point in collecting more first hand
accounts and in building a more complete mosaic of what was occurring in universities, software companies and in
organizations to build and use DSS.
This document traces decision support applications and research studies related
to model and data-oriented systems, management expert systems, multidimensional data analysis,
query and reporting tools, online analytical processing (OLAP), Business Intelligence, group DSS,
conferencing and groupware, document management, spatial DSS and Executive Information Systems as the
technologies emerge, converge and diverge. All of these technologies have been used to support
decision making. A timeline of major historical milestones relevant to DSS is included in Appendix I.
The study of decision support systems is an applied
discipline that uses knowledge and especially theory from other disciplines.
For this reason, many DSS research questions have been examined because they
were of concern to people who were building and using specific DSS. Hence much
of the broad DSS knowledge base provides generalizations and directions for
building more effective DSS (cf., Baskerville & Myers, 2002; Keen, 1980).
The next section describes the origins of the field
of decision support systems. Section 3 discusses the decision support systems theory
development that occurred in the late 1970s and early 1980s. Section 4
discusses important developments to communications-driven ,
data-driven, document driven, knowledge-driven and model-driven DSS (cf.,
Power, 2002). The final section briefly discusses how DSS practice, research and
technology is continuing to evolve.
II. Decision Support Systems Origins
In the 1960s, researchers began systematically
studying the use of computerized quantitative models to assist in decision
making and planning (Raymond, 1966; Turban, 1967; Urban, 1967, Holt and
Huber, 1969). Ferguson and Jones (1969) reported the first experimental
study using a computer aided decision system. They investigated a production
scheduling application running on an IBM 7094. In retrospect, a major
historical turning point was Michael S. Scott Morton's (1967) dissertation
field research at Harvard University.
Scott Morton’s study involved building, implementing
and then testing an interactive, model-driven management decision system. Fellow
Harvard Ph.D. student Andrew McCosh asserts that the “concept of decision support
systems was first articulated by Scott Morton in February 1964 in a basement
office in Sherman Hall, Harvard Business School” (McCosh email, 2002) in a
discussion they had about Scott Morton’s dissertation. During 1966, Scott
Morton (1971) studied how computers and analytical models could help managers
make a recurring key business planning decision. He conducted an experiment
in which managers actually used a Management Decision System (MDS). Marketing
and production managers used an MDS to coordinate production planning for
laundry equipment. The MDS ran on an IDI 21 inch CRT with a light pen connected
using a 2400 bps modem to a pair of Univac 494 systems.
The pioneering work of George Dantzig,
Douglas Engelbart and Jay Forrester likely influenced
the feasibility of building computerized decision support systems. In 1952, Dantzig became a research mathematician at the Rand
Corporation, where he began implementing linear programming on its experimental
computers. In the mid-1960s, Engelbart and colleagues
developed the first hypermedia—groupware system called NLS (oNLine
System). NLS facilitated the creation of digital libraries and the storage and
retrieval of electronic documents using hypertext. NLS also provided for
on-screen video teleconferencing and was a forerunner to group decision support
systems. Forrester was involved in building the SAGE (Semi-Automatic Ground
Environment) air defense system for North America completed in 1962. SAGE is
probably the first computerized data-driven DSS. Also, Professor Forrester
started the System Dynamics Group at the Massachusetts Institute of Technology Sloan
School. His work on corporate modeling led to programming DYNAMO, a general
In 1960, J.C.R. Licklider published his ideas about the future
role of multiaccess interactive computing in a paper titled “Man-Computer Symbiosis.” He saw man-computer
interaction as enhancing both the quality and efficiency of human problem solving and his paper provided
a guide for decades of computer research to follow. Licklider was the architect of Project MAC at MIT
that furthered the study of interactive computing.
By April 1964, the development of the IBM System 360 and
other more powerful mainframe systems made it practical and cost-effective to develop
Management Information Systems (MIS) for large companies (cf., Davis, 1974). These early
MIS focused on providing managers with structured, periodic reports and the information
was primarily from accounting and transaction processing systems, but the systems did
not provide interactive support to assist managers in decision making.
Around 1970 business journals started to publish
articles on management decision systems, strategic planning systems and
decision support systems (cf., Sprague and Watson 1979).. For
example, Scott Morton and colleagues McCosh and
Stephens published decision support related articles in 1968. The first use of
the term decision support system was in Gorry and
Scott-Morton’s (1971) Sloan Management Review article. They argued that
Management Information Systems primarily focused on structured decisions and
suggested that the supporting information systems for semi-structured and
unstructured decisions should be termed “Decision Support Systems”.
T.P. Gerrity, Jr. focused
on Decision Support Systems design issues in his 1971 Sloan Management Review
article titled "The Design of Man-Machine Decision Systems: An Application
to Portfolio Management". The article was based on his MIT Ph.D.
dissertation. His system was designed to support investment managers in their
daily administration of a clients' stock portfolio.
John D.C. Little, also at Massachusetts Institute of
Technology, was studying DSS for marketing. Little and Lodish
(1969) reported research on MEDIAC, a media planning support system. Also, Little (1970) identified criteria for designing models and
systems to support management decision-making. His four criteria included:
robustness, ease of control, simplicity, and completeness of relevant detail.
All four criteria remain relevant in evaluating modern Decision Support
Systems. By 1975, Little was expanding the frontiers
of computer-supported modeling. His DSS called Brandaid
was designed to support product, promotion, pricing and advertising decisions.
Little also helped develop the financial and marketing modeling language known
In 1974, Gordon Davis, a Professor at the University of Minnesota, published his influential
text on Management Information Systems. He defined a Management Information
System as "an integrated, man/machine system for providing information to
support the operations, management, and decision-making functions in an
organization. (p. 5)." Davis's Chapter 12 was titled
"Information System Support for Decision Making" and Chapter 13 was titled
"Information System Support for Planning and Control". Davis’s framework incorporated
computerized decision support systems into the emerging field of management
Peter Keen and Charles Stabell
claim the concept of decision support systems evolved from "the
theoretical studies of organizational decisionmaking
done at the Carnegie Institute of Technology during the late 1950s and early
'60s and the technical work on interactive computer systems, mainly carried out
at the Massachusetts Institute of Technology in the 1960s. (Keen
and Scott Morton, 1978)". Herbert Simon’s books (1947, 1960) and
articles provide a context for understanding and supporting decision making.
In 1995, Hans Klein and Leif Methlie
noted “A study of the origin of DSS has still to be written. It
seems that the first DSS papers were published by PhD students or
professors in business schools, who had access to the first time-sharing
computer system: Project MAC at the Sloan School, the Dartmouth Time Sharing
Systems at the Tuck School. In France, HEC was the first French
business school to have a time-sharing system (installed in 1967), and the
first DSS papers were published by professors of the School in 1970. (p. 112).”
III. Theory Development
In the mid- to late 1970s, both practice and theory
issues related to DSS were discussed at academic conferences including the
American Institute for Decision Sciences meetings and the ACM SIGBDP Conference
on Decision Support Systems in San Jose, CA in January 1977 (the proceeding
were included in the journal Database). The first International Conference on
Decision Support Systems was held in Atlanta, Georgia in 1981. Academic
conferences provided forums for idea sharing, theory discussions and
At about this same time, Keen and Scott Morton’s DSS textbook (1978) provided
the first broad behavioral orientation to decision support system analysis,
design, implementation, evaluation and development. This influential text
provided a framework for teaching DSS in business schools. McCosh
and Scott-Morton’s (1978) DSS book was more influential in Europe.
In 1980, Steven Alter published his MIT doctoral
dissertation results in an influential book. Alter's
research and papers (1975; 1977) expanded the framework for thinking about business
and management DSS. Also, his case studies provided a firm
descriptive foundation of decision support system examples. A number of other
MIT dissertations completed in the late 1970s also dealt with issues related to
using models for decision support.
Alter concluded from his research (1980) that decision
support systems could be categorized in terms of the generic operations that
can be performed by such systems. These generic operations extend along a
single dimension, ranging from extremely data-oriented to extremely
model-oriented. Alter conducted a field study of 56 DSS that he categorized
into seven distinct types of DSS. His seven types include:
File drawer systems that provide access to data
Data analysis systems that support the
manipulation of data by computerized tools tailored to a specific task and
setting or by more general tools and operators.
Analysis information systems that provide access to a series
of decision-oriented databases and small models.
Accounting and financial
models that calculate
the consequences of possible actions.
Representational models that estimate the consequences
of actions on the basis of simulation models.
Optimization models that provide guidelines for
action by generating an optimal solution consistent with a series of
Suggestion models that perform the logical
processing leading to a specific suggested decision for a fairly structured or
Donovan and Madnick (1977)
classified DSS as institutional or ad hoc. Institutional DSS support decisions
that are recurring. An ad hoc DSS supports querying data for one time requests.
Hackathorn and Keen (1981) identified DSS in three
distinct yet interrelated categories: Personal DSS, Group DSS and
In 1979, John Rockart of
the Harvard Business School published a ground breaking
article that led to the development of executive information systems (EISs) or executive support systems (ESS). Rockart
developed the concept of using information systems to display critical success metrics
Robert Bonczek, Clyde Holsapple, and Andrew Whinston
(1981) explained a theoretical framework for understanding the issues
associated with designing knowledge-oriented Decision Support Systems. They identified
four essential "aspects" or general components that were common to
all DSS: 1. A language system (LS) that specifies all
messages a specific DSS can accept; 2. A presentation system (PS) for all
messages a DSS can emit; 3. A knowledge system (KS) for all knowledge a DSS
has; and 4. A problem-processing system (PPS) that is the "software
engine" that tries to recognize and solve problems during the use of a
specific DSS. Their book explained how Artificial Intelligence and Expert
Systems technologies were relevant to developing DSS.
Finally, Ralph Sprague and Eric Carlson’s (1982)
book Building Effective Decision Support
Systems was an important milestone. Much of the book further explained the
Sprague (1980) DSS framework of data base, model base and
dialog generation and management software. Also, it provided a practical, and understandable overview of how organizations
could and should build DSS. Sprague and Carlson (1982) defined DSS as "a
class of information system that draws on transaction processing systems and
interacts with the other parts of the overall information system to support the
decision-making activities of managers and other knowledge workers in
organizations (p. 9).”
IV. DSS Applications Development
Beginning in about 1980 many activities associated
with building and studying DSS occurred in universities and organizations that
resulted in expanding the scope of DSS applications. These actions also expanded
the field of decision support systems beyond the initial business and
management application domain. These diverse systems were all called Decision Support
Systems. From those early days, it was recognized that DSS could be designed to
support decision-makers at any level in an organization. Also, DSS could support
operations decision making, financial management and strategic decision-making.
A literature survey and citation studies (Alavi & Joachimsthaler, 1990,
Eom & Lee, 1990a, Eom,
2002, Arnott & Pervan,
2005) suggest the major applications for DSS emphasized manipulating quantitative
models, accessing and analyzing large data bases, and supporting group decision
making. Much of the model-driven DSS research emphasized use of the systems by
individuals, i.e., personal DSS, while data-driven DSS were usually
institutional, ad hoc or organizational DSS. Group DSS research emphasized impacts
on decision process structuring and especially brainstorming.
The discussion in this section follows the broad historical
progression of DSS research. The first subsection examines model-driven DSS,
then the focus turns to data-driven DSS and executive information systems and notes
the growing prominence of such systems beginning in the late 1980s. The origins
of communications-driven DSS are then briefly explored and the bifurcation into
two types of group DSS, model-driven and communications-driven. Developments in
document storage technologies and search engines then made document-driven DSS more
widely available as web-based systems. The last subsection summarizes major developments
in Artificial Intelligence (AI) and expert systems that made suggestion or knowledge-driven
IV.1 Model-driven DSS
Scott-Morton’s (1971) production planning management
decision system was the first widely discussed model-driven DSS, but Ferguson
and Jones’ (1969) production scheduling application was also a model-driven
DSS. Many of the early decision systems mentioned in section 2, e.g., Sprinter,
MEDIAC and Brandaid, are probably model-driven DSS.
A model-driven DSS emphasizes access to and
manipulation of financial, optimization and/or simulation models. Simple quantitative
models provide the most elementary level of functionality. Model-driven DSS use
limited data and parameters provided by decision makers to aid decision makers
in analyzing a situation, but in general large data bases are not needed for
model-driven DSS (Power, 2002). Early versions of model-driven DSS were called
model-oriented DSS by Alter (1980), computationally oriented DSS by Bonczek, Holsapple and Whinston (1981) and later spreadsheet-oriented and
solver-oriented DSS by Holsapple and Whinston (1996).
The first commercial tool for building model-driven
DSS using financial and quantitative models was called IFPS, an acronym for
interactive financial planning system. It was developed in the late 1970's by
Gerald R. Wagner and his students at the University of Texas. Wagner’s company, EXECUCOM
Systems, marketed IFPS until the mid 1990s. Gray’s Guide to IFPS (1983)
promoted the use of the system in business schools. Another DSS generator for
building specific systems based upon the Analytic Hierarchy Process (Saaty, 1982), called Expert Choice, was released in 1983.
Expert Choice supports personal or group decision making. Ernest Forman worked
closely with Thomas Saaty to design Expert Choice.
In 1978, Dan Bricklin and
Bob Frankston co-invented the software program VisiCalc (Visible Calculator).
VisiCalc provided managers the opportunity for hands-on computer-based analysis
and decision support at a reasonably low cost.
VisiCalc was the first "killer" application for personal
computers and made possible development of many model-oriented, personal DSS
for use by managers. The history of microcomputer spreadsheets is described in
Power (2000). In 1987, Frontline Systems founded by Dan Fylstra
marketed the first optimization solver add-in for Microsoft Excel.
In a 1988 paper, Sharda,
Barr, and McDonnell reviewed the first 15 years of model-driven DSS research.
They concluded that research related to using models and financial planning
systems for decision support was encouraging but certainly not uniformly
positive. As computerized models became more numerous, research focused on
model management and on enhancing more diverse types of models for use in DSS
such as multicriteria, optimization and simulation
The idea of model-driven spatial decision support
system (SDSS) evolved in the late 1980’s (Armstrong, Densham, and
Rushton., 1986) and by 1995 the SDSS concept had become
firmly established in the literature (Crossland,
Wynne, and Perkins, 1995). Data-driven spatial DSS are also common.
IV.2 Data-driven DSS
In general, a data-driven DSS emphasizes access to
and manipulation of a time-series of internal company data and sometimes
external and real-time 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 (cf., Codd et al., 1993) provide the
highest level of functionality and decision support that is linked to analysis
of large collections of historical data. Executive Information Systems are
examples of data-driven DSS (Power, 2002). Initial examples of these systems
were called data-oriented DSS, Analysis Information Systems (Alter, 1980) and
retrieval-only DSS by Bonczek, Holsapple
and Whinston (1981).
One of the first data-driven DSS was built using an
APL-based software package called AAIMS, An Analytical Information Management System.
It was developed from 1970-1974 by Richard Klaas and
Charles Weiss at American Airlines (cf. Alter, 1980).
As noted previously, in 1979 John Rockart’s research stimulated the development of executive
information systems (EIS) and executive support systems (ESS). These systems evolved
from single user model-driven decision support systems and from the development
of relational database products. The first EIS used pre-defined information
screens maintained by analysts for senior executives. For example, in the Fall of 1978, development of an EIS called Management
Information and Decision Support (MIDS) system began at Lockheed-Georgia (cf., Houdeshel and Watson, 1987).
The first EIS were developed in the late 1970s by Northwest
Industries and Lockheed “who risked being on the ‘bleeding edge’ of technology ….
Few even knew about the existence of EIS until John Rockart
and Michael Treacy’s article, ‘The CEO Goes On-line,’
appeared in the January-February 1982 issue of the Harvard Business Review. (Watson, Houdeshel and Rainer, 1997, p. 6)” Watson and colleagues.
further note “A major contributor to the growth of EIS was the appearance of
vendor-supplied EIS software in the mid-1980s. Pilot Software’s Command Center and Comshare’s
Commander EIS made it much easier for firms to develop an EIS by providing capabilities
for (relatively) easy screen design, data importation, user-friendly front
ends, and access to news services. (p. 6)” In a related development in 1984, Teradata’s parallel processing relational database
management system shipped to customers Wells Fargo and AT&T.
In about 1990, data warehousing and On-Line
Analytical Processing (OLAP) began broadening the realm of EIS and defined a
broader category of data-driven DSS (cf., Dhar
and Stein, 1997). Nigel Pendse (1997), author of the
OLAP Report, claims both multidimensional analysis and OLAP had origins in the APL programming language and in
systems like Express and Comshare’s System W. Nylund (1999) traces the developments associated with
Business Intelligence (BI) to Procter & Gamble’s efforts in 1985 to build a
DSS that linked sales
information and retail scanner data. Metaphor Computer Systems, founded by
researchers like Ralph Kimball from Xerox’s Palo Alto Research Center (PARC),
built the early P&G data-driven DSS. Staff from Metaphor later founded many
of the Business Intelligence vendors: The term BI is a popularized, umbrella
term coined and promoted by Howard Dresner of the
Gartner Group in 1989. It describes a set of concepts and methods to improve
business decision making by using fact-based support systems. BI is sometimes
used interchangeably with briefing books, report and query tools and executive
information systems. In general, business intelligence systems are data-driven
Bill Inmon and Ralph
Kimball actively promoted decision support systems built using relational
database technologies. Barry Devlin (Devlin and Murphy, 1988) defined IBM's data warehouse architecture and promoted it. For many Information Systems practitioners, DSS built using Oracle or DB2
were the first decision support systems they read about in the popular
computing literature. Ralph Kimball was "The Doctor of DSS" and Bill Inmon was the "father of the data warehouse”. By 1995,
Wal-Mart’s data-driven DSS had more than 5 terabytes of on-line storage from Teradata that expanded to more than 24 terabytes in 1997.
In more recent years,
vendors added tools to create web-based dashboards and scorecards.
IV.3 Communications-driven DSS
Communications-driven DSS use network and
communications technologies to facilitate decision-relevant collaboration and communication.
In these systems, communication technologies are the dominant architectural component.
Tools used include groupware, video conferencing and computer-based bulletin boards
Engelbart's 1962 paper "Augmenting
Human Intellect: A Conceptual
Framework" is the anchor for much of the later work related
to communications-driven DSS. In 1969, he demonstrated the first hypermedia/groupware
system NLS (oNLine System) at the Fall Joint Computer
Conference in San Francisco. Engelbart
invented the both the computer mouse and groupware.
Joyner and Tunstall’s
article (1970) reporting testing of their Conference Coordinator
computer software is the first empirical study in this research area. Murray Turoff’s (1970) article introduced the concept of
Computerized Conferencing. He developed and implemented the first Computer Mediated
Communications System (EMISARI) tailored to facilitate group communications.
In the early 1980s, academic researchers developed a
new category of software to support group decision-making called Group Decision
Support Systems abbreviated GDSS (cf., Gray, 1981; Huber, 1982; Turoff and Hiltz, 1982). Mindsight from Execucom Systems, GroupSystems developed at the University of Arizona and the SAMM system
developed by University of Minnesota researchers were early
matured into a commercial product. Jay Nunamaker, Jr.
and his colleagues wrote in 1992 that the underlying concept for GroupSystems had its beginning in 1965 with the development
of Problem Statement Language/Problem Statement Analyzer at Case Institute of
Technology. In 1984, the forerunner to GroupSystems
called PLEXSYS was completed and a computer-assisted group meeting facility was
constructed at the University of Arizona. The first Arizona facility, called the PlexCenter, housed a large U-shaped conference table with
16 computer workstations.
On the origins of SAMM, Dickson, Poole and DeSanctis (1992) report that Brent Gallupe,
a Ph.D. student at the University of Minnesota, decided in 1984 "to
program his own small GDSS system in BASIC and run it on his university’s VAX
DeSanctis and Gallup (1987) defined two
types of GDSS. Basic or level
1 GDSS are systems with tools to reduce communication barriers, such as large
screens for display of ideas, voting mechanisms, and anonymous input of ideas
and preferences. These are communications-driven DSS. Advanced or level 2 GDSS provide problem-structuring techniques,
such as planning and modeling tools. These are model-driven group DSS. Since the mid-1980s, many
research studies have examined the impacts and consequences of both types of group
DSS. Also, companies have
commercialized model-driven group DSS and groupware.
Kersten (1985) developed NEGO, a computerized group tool to
support negotiations. Bui and Jarke (1986) reported developing Co-op, a system for
cooperative multiple criteria group decision support. Kraemer and King (1988)
introduced the concept of Collaborative Decision Support Systems (CDSSs). They defined them as interactive computer-based
systems to facilitate the solution of ill-structured problems by a set of
decision makers working together as a team.
1989, Lotus introduced a groupware product called Notes and broadened the focus
of GDSS to include enhancing communication, collaboration and coordination among
groups of people. Notes had its roots in a product called PLATO Notes, written
at the Computer-based Education Research Laboratory (CERL) at the University of Illinois in 1973 by David R. Woolley.
In general, groupware, bulletin boards, audio and
videoconferencing are the primary technologies for communications-driven
decision support. In the past few years, voice and video delivered using the
Internet protocol have greatly expanded the possibilities for synchronous communications-driven
IV.4 Document-driven DSS
A document-driven DSS uses computer
storage and processing technologies to provide document retrieval and analysis.
Large document databases may include scanned documents, hypertext documents,
images, sounds and video. Examples of documents that might be accessed by a
document-driven DSS are policies and procedures, product specifications,
catalogs, and corporate historical documents, including minutes of meetings and
correspondence. A search engine is a primary decision-aiding tool associated
with a document-driven DSS (Power, 2002). These systems have also been called text-oriented
DSS (Holsapple and Whinston,1996).
The precursor for this type
of DSS is Vannevar Bush’s (1945) article titled
"As We May Think". Bush wrote "Consider a future device for
individual use, which is a sort of mechanized private file and library. It
needs a name, and to coin one at random, ‘memex’ will
do”. Bush’s memex is a much broader vision than that
of today’s document-driven DSS.
Text and document management
emerged in the 1970s and 1980s as an important, widely used computerized means
for representing and processing pieces of text (Holsapple
and Whinston, 1996). The first scholarly article for
this category of DSS was written by Swanson and Culnan
(1978). They reviewed document-based systems for management planning and
control. Until the mid-1990s little progress was made in helping managers find
documents to support their decision making. Fedorowicz
(1993, 1996) helped define the need for such systems. She estimated in her 1996
article that only 5 to 10 percent of stored business documents are available to
managers for use in decision making. The World-wide web technologies significantly
increased the availability of documents and facilitated the development of
IV.5 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 (Power, 2002). These
systems have been called suggestion DSS (Alter, 1980) and knowledge-based DSS (Klein
& Methlie, 1995). Goul,
Henderson, and Tonge (1992) examined Artificial
Intelligence (AI) contributions to DSS.
In 1965, a Stanford University research team led by Edward Feigenbaum
created the DENDRAL expert system. DENDRAL led to the development of other
rule-based reasoning programs including MYCIN, which helped physicians diagnose
blood diseases based on sets of clinical symptoms. The MYCIN project resulted
in development of the first expert-system shell (Buchanan and Shortliffe, 1984).
Bonczek, Holsapple and Whinston’s
(1981) book created interest in using these technologies for DSS. In 1983, Dustin Huntington
established EXSYS. That company and product made it practical to use PC based tools to
develop expert systems. By 1992, some 11 shell programs were available for the MacIntosh
platform, 29 for IBM-DOS platforms, 4 for Unix platforms, and 12 for dedicated mainframe
applications (National Research Council, 1999). Artificial Intelligence systems have been
developed to detect fraud and expedite financial transactions, many additional medical
diagnostic systems have been based on AI, expert systems have been used for scheduling
in manufacturing operation and web-based advisory systems. In recent years, connecting
expert systems technologies to relational databases with web-based front ends has broadened
the deployment and use of knowledge-driven DSS.
V. Web-based DSS
Beginning in approximately
1995, the World-wide Web and global Internet provided a technology platform for
further extending the capabilities and deployment of computerized decision
support. The release of the HTML 2.0 specifications with form tags and tables
was a turning point in the development of web-based DSS.
In 1995, a number of papers were presented on using the Web and Internet for decision support at the
3rd International Conference of the International Society for Decision Support Systems (ISDSS). In addition
to Web-based, model-driven DSS, researchers were reporting Web access to data warehouses. DSS Research Resources
was started as a web-based collection of bookmarks. By 1995, the World-Wide Web (Berners-Lee, 1996) was
recognized by a number of software developers and academics as a serious platform for implementing
all types of Decision Support Systems (cf., Bhargava & Power, 2001).
In November 1995, Power, Bhargava and Quek submitted the Decision Support Systems Research
page for inclusion in ISWorld. The goal was to provide a useful starting point for accessing Web-based material
related to the design, development, evaluation, and implementation of Decision Support Systems. Nine
months later, a DSS/WWW Workshop organized by Power and Quek was held as part of the IFIP Working Group 8.3 Conference
on “Implementing Systems for Supporting Management Decisions: Concepts, Methods and Experiences”,
July 21-24, 1996 in London, UK.
In 1996-97, corporate intranets were developed to support information exchange and knowledge
management. The primary decision support tools included ad hoc query and reporting tools,
optimization and simulation models, online analytical processing (OLAP), data mining and data
visualization (cf., Powell, 2001). Enterprise-wide DSS using database technologies were
especially popular in Fortune 2000 companies (Power, 1997). Bhargava, Krishnan
and Müller (1997) continued to discuss and experiment with electronic markets for
In 1999, vendors introduced new Web-based analytical applications. Many DBMS vendors shifted their focus
to Web-based analytical applications and business intelligence solutions. In 2000, application service
providers (ASPs) began hosting the application software and technical infrastructure for decision
support capabilities. 2000 was also the year of the portal. More sophisticated "enterprise knowledge
portals" were introduced by vendors that combined information portals, knowledge management, business
intelligence, and communications-driven DSS in an integrated Web environment (cf., Bhargava and Power, 2001).
Power (1998) defined a Web-based decision support system as a computerized system that delivers
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. The computer server that
is hosting the DSS application is linked to the user's computer by a network with the TCP/IP protocol.
practice, research and technology continue to evolve. By 1996, Holsapple and Whinton had
identified five specialized types of DSS, including text-oriented DSS, database-oriented
DSS, spreadsheet-oriented DSS, solver-oriented DSS, and rule-oriented DSS.
These last four types of DSS match up with some of Alter’s
(1980) categories. Arnott and Pervan
(2005) traced the evolution of DSS using seven sub-groupings of research and
practice: personal DSS, group support systems, negotiation support systems,
intelligent DSS, knowledge management-based DSS, executive information
systems/business intelligence, and data warehousing. These sub-grouping overlap, but reflect the
diverse evolution of prior research.
chapter used an expanded DSS framework (Power, 2001, 2002) to retrospectively discuss
the historical evolution of decision support systems. In recent years, the Web has had a significant
impact on the variety, distribution and sophistication of DSS, but handheld PCs,
wireless networks, expanding parallel processing coupled with very large data
bases and visualization tools are continuing to encourage the development of
innovative decision support applications.
use two approaches to extrapolate the past to the future: reasoning by analogy and
projection of trends. In many ways, computerized decision support systems are
analogous to airplanes, coming in various shapes, sizes and forms, technologically
sophisticated and a very necessary tool in many organizations. Decision support
systems research and development will continue to exploit any new technology
developments and will benefit from progress in very large data bases,
artificial intelligence, human-computer interaction, simulation and
optimization, software engineering, telecommunications and from more basic research
on behavioral topics like organizational decision making, planning, behavioral
decision theory and organizational behavior.
Trends suggest that data-driven DSS will use
faster, real-time access to larger, better integrated databases. Model-driven
DSS will be more complex, yet understandable, and systems built using simulations
and their accompanying visual displays will be increasingly realistic.
Communications-driven DSS will provide more real-time video communications
support. Document-driven DSS will access larger repositories of unstructured
data and the systems will present appropriate documents in more useable
formats. Finally, knowledge-driven DSS will likely be more sophisticated and
more comprehensive. The advice from knowledge-driven DSS will be better and the
applications will cover broader domains.
Current researchers should remember that Decision Support Systems pioneers came from a wide variety of
backgrounds and faced many challenges that they successfully overcame to demonstrate the
value of using computers, information technologies and specific decision support software
to enhance and in some situations improve decision making. The DSS pioneers created
particular and distinct streams of technology development and research that serve as
the foundation for much of today’s interest in building and studying computerized
decision support systems. The legacy of the pioneers must be preserved. Please check the
Decision Support Systems Pioneers list at
The future of decision support systems will
certainly be different than the opportunistic and incremental innovations seen
in the past. Decision support systems as an academic discipline is likely
to follow a path similar to computer architecture and software engineering and
become more rigorous and more clearly delineated and possibly renamed. DSS consulting, teaching and
research can be mutually supportive and each task can help establish a niche
for those interested in building and studying DSS whether in Colleges of
Information, Business or Engineering.
The history of Decision Support Systems covers a
relatively brief span of years, and the concepts and technologies are still evolving. Today it is still
possible to reconstruct the history of Decision Support Systems (DSS) from retrospective accounts from
key participants as well as from published and unpublished materials. Many of the early innovators and
early developers are retiring but their insights and actions can be captured to guide future innovation
in this field. It is hoped this web article leads to email and retrospective accounts that can help us
understand the "real" history of DSS. The Internet and Web have speeded-up developments in decision
support and have provided a new means of capturing and documenting the development of knowledge in
this research area. Decision support pioneers include many academic researchers from programs at MIT,
University of Arizona, University of Hawaii, University of Minnesota and Purdue University. The DSS
pioneers created particular and distinct streams of technology development and research that serve as
the foundation for much of today’s work in DSS.
If you are interested in learning about decision support systems, prospective
students can receive a business intelligence certification
to enhance their knowledge of computer databases.
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Appendix I. DSS Timeline
Bush proposed Memex
Simon book titled
Dantzig joined RAND and continued
research on linear programming
Environment (SAGE) project at M.I.T. Lincoln Lab uses first light pen; SAGE completed
1962, first data-driven DSS
Forrester started System
Dynamics Group at the M.I.T. Sloan School
Simon book The New Science
of Management Decision; Licklider article on
Licklider architect of Project MAC program at M.I.T.;
Iverson’s book A Programming Language (APL); Engelbart's
paper "Augmenting Human Intellect: A Conceptual Framework"
Englebart established Augmentation Research Center at SRI
Stanford team led by Feigenbaum created DENDRAL expert system; Problem
Statement Language/Problem Statement Analyzer (PSL/PSA) developed at Case
Institute of Technology
UNIVAC 494 introduced; Tymshare founded and Raymond article on computer
time-sharing for business planning and budgeting
Scott Morton’s dissertation
completed on impact of computer-driven visual display devices on management
decision-making process; Turban reports national survey on use of
mathematical models in plant maintenance decision making
Scott Morton and McCosh article; Scott Morton and Stephens article; Englebart demonstrated hypermedia—groupware system NLS (oNLine System) at Fall Joint Computer Conference in San Francisco
Ferguson and Jones article on lab study of a production
scheduling computer-aided decision system running on an IBM 7094; Little and Lodish MEDIAC, media planning model; Urban new product
model-based system called SPRINTER
Little article on decision
calculus support system; Joyner and Tunstall
article on Conference Coordinator computer software; IRI Express, a
multidimensional analytic tool for time-sharing systems, becomes available; Turoff conferencing system
Gorry and Scott Morton SMR article first published use of
term Decision Support System; Scott Morton book Management Decision Systems; Gerrity article Man-Machine decision systems; Klein and Tixier article on SCARABEE
PLATO Notes, written at the
Computer-based Education Research Laboratory (CERL) at the University of Illinois by David R. Woolley
Davis’s book Management Information Systems; Meador and Ness
article DSS application to corporate planning
Alter completed M.I.T.
Ph.D. dissertation "A Study of Computer Aided Decision Making in
Organizations"; Keen SMR article on evaluating computer-based decision
aids; Boulden book on computer-assisted planning
Sprague and Watson article
"A Decision Support System for Banks"; Grace paper on Geodata Analysis and Display System
Alter article "A
Taxonomy of Decision Support Systems", Klein article on Finsim; Carlson and Scott Morton chair ACM SIGBDP
Conference DSS Conference
Development began on
Management Information and Decision Support (MIDS) at Lockheed-Georgia; Keen
and Scott Morton book; McCosh and Scott Morton
book; Holsapple dissertation completed; Wagner
founded Execucom to market IFPS; Bricklin and Frankston created Visicalc
(Visible Calculator) microcomputer spreadsheet; Carlson from IBM, San Jose
plenary speaker at HICSS-11; Swanson and Culnan
article document-based systems for management planning
Rockart HBR article on CEO data needs
Sprague MISQ article on a
DSS Framework; Alter book; Hackathorn founded MicroDecisionware
Conference on DSS, Atlanta, Georgia; Bonczek, Holsapple, and Whinston book;
Gray paper on SMU decision rooms and GDSS
Computer named the “Man” of
the Year by Time Magazine; Rockart and Treacy article “The CEO Goes On-Line” HBR; Sprague and
Carlson book; Metaphor Computer Systems founded by Kimball and others from
Xerox PARC; ESRI launched its first commercial GIS software called ARC/INFO;
IFIP Working Group 8.3 on Decision Support Systems established
Inmon Computerworld article on relational DBMS; IBM DB2
Decision Support database released; Student Guide to IFPS by Gray; Huntington established Exsys; Expert
Choice software released
PLEXSYS, Mindsight and SAMM GDSS; first Teradata
computer with relational database management system shipped to customers
Wells Fargo and AT&T; MYCIN expert system shell explained
Procter & Gamble use
first data mart from Metaphor to analyze data from checkout-counter scanners;
Whinston founded Decision Support Systems journal; Kersten developed NEGO
Houdeshel and Watson article on MIDS; DeSanctis
and Gallupe article on GDSS; Frontline Systems
founded by Fylstra, marketed solver add-in for
Turban DSS textbook; Pilot
Software EIS for Balanced Scorecard deployed at Analog Devices
Gartner analyst Dresner coins term business intelligence; release of
Lotus Notes; International Society for Decision Support Systems (ISDSS)
founded by Holsapple and Whinston
Inmon book Using Oracle to Build Decision Support
Systems; Eom and Lee co-citation analysis of DSS
Inmon books Building the Data Warehouse and Database
Machines and Decision Support Systems; Berners-Lee’s World Wide Web server
and browser, become publicly available
Codd et al. paper defines online analytical processing
HTML 2.0 with form tags and
tables; Pendse’s OLAP Report project began
The Data Warehousing
Institute (TDWI) established; DSS journal issue on Next Generation of
Decision Support; Crossland, Wynne, and Perkins
article on Spatial DSS; ISWorld DSS Research pages
and DSS Research Resources
InterNeg negotiation software renamed Inspire;
Wal-Mart and Teradata created then world’s largest production data
warehouse at 24 Terabytes (TB)
ACM First International
Workshop on Data Warehousing and OLAP
First AIS Americas
Conference mini-track on Decision Support Systems
Association for Information
Systems (AIS) Special Interest Group on Decision Support, Knowledge and Data
Management Systems (SIG DSS) founded
International Society for
Decision Support Systems (ISDSS) merged with AIS SIG DSS
J. Power is a Professor of Information Systems and Management at the College of
Business Administration at the University of Northern Iowa, Cedar Falls, Iowa
and the editor of DSSResources.COM, the Web-based knowledge repository about
computerized systems that support decision making, the editor of
PlanningSkills.COM, and the editor of DSS News, a bi-weekly e-newsletter. Dan
writes the column "Ask Dan!" in DSS News.
Power's research interests include the design and development of Decision
Support Systems and how DSS impact individual and organizational decision
behavior. Since 1982, Power has
published more than 40 articles, book chapters and proceedings papers. He was
founding Chair of the Association for Information Systems Special Interest
Group on Decision Support, Knowledge and Data Management Systems (SIG DSS).
Thanks for visiting. If you have any suggestions for improving this brief history of DSS,
I'd like to hear from you. I'm trying to collect retrospective reports for my "Brief History of Decision
Support Systems" hypertext document at DSSResources.COM. I'm including recollections, reflections
and comments of those involved in the various DSS "threads" and I'm trying to correct any errors of
omission or misinterpretation.
How to cite A Brief History of
Decision Support Systems should be cited as:
Power, D.J. A Brief History of Decision Support
Systems. DSSResources.COM, World Wide Web, http://DSSResources.COM/history/dsshistory.html,
version 4.0, March 10, 2007.