Information Systems and Decision Making
Decision making, relating to information systems or any strategic considerations, is a critical managerial
and leadership competency. Often, decisions require accurate and timely information about the
organization, its resources, and its environment. For an organization that has grown too large for any one
individual to be involved in its many initiatives, information can be difficult to access and analyze without
the use of information technology. In these cases, decision support technologies can play a crucial role in
the organization’s success. You will take a look at various types of decision support technologies, or
systems, and examine how they can impact strategic decision making as well as day-to-day decisions.
You will consider whether and how the available decision support models can be used to enhance
strategic decision making.
To be completed:
� Identify various types of decision support systems and how they are used in the organization
� Assess the role of decision support systems in creating superior business strategy
INFORMATION SYSTEMS AND DECISION MAKING 2
Resources;
Course Text
Management Information Systems for the Information Age
Chapter 4, “Decision Support and Artificial Intelligence: Brainpower for Your Business”
This chapter discusses expert systems, neural networks and fuzzy logic, genetic algorithms, and the four
types of agent-based technologies.
Articles
� Fazlollahi, B., & Vahidov, R. (2001). A method for generation of alternatives by decision support
systems. Journal of Management Information Systems, 18(2). Retrieved from ABI/INFORM Global
database.
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Information Systems and Decision Making
Introduction
Decision support systems (DSS) are usually computer-based interactive software whose
main function is to help decision makers through the use of data, knowledge and communication
technologies to complete the decision-making process. Decisions support systems can be broadly
grouped into the four categories below:
Data-driven DSS
Decision support systems that are data-driven are systems that are usually used to query a
database for specific information that is required for a decision to be made. Such systems are
used by managers, staff, and suppliers for purposes such as determining the levels of available
stock so that supply orders can be made and similar decisions (Fazlollahi & Vahidov, 2001).
Examples of such systems are computer-based databases that manage data on customers and
suppliers and the fulfillment of customer orders.
Communication-driven DSS
Communication-driven decision support systems are basically computer-based
communication systems that are mostly used within the organization to facilitate easy
communication between teams (Wiederhold, 2000). An example of the application of such
systems is in the case of multinational corporations that need to coordinate work between
employees in various countries and continents where they implement a system of
teleconferencing or even a webinar type of application to facilitate communication. Other
examples of such systems include instant messaging systems, chats, Skype calls and net-meeting
systems.
Knowledge-driven DSS
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A knowledge-driven DSS is a special type of decision support system that provides
specialized expertise, which is usually stored as facts, procedures, or rule to solve problems
(Edwards, Duan & Robins, 2000). An example of such a system is the clinical decision support
system.
Document-driven DSS
Decision support systems that are document-driven are basically used to manipulate
information that is widely unstructured in various digital formats.
Model-driven DSS
Model-driven decision support systems are usually used to assist decision makers analyze
a particular situation through the manipulation of statistical, simulation or financial models. Such
systems usually rely on data provided by the users and the parameters set for the modeling to
occur (Power, 2007). Such systems include the financial models used by investment experts to
predict the future of stocks.
The role of decision support systems in creating superior business strategy
Decision support systems are being used extensively by businesses to create unique
strategies that are superior to their competitors and set them apart from the rest. An example of
such a corporation is the Canadian National Railway system that implemented a decision support
system that assists the railway in managing the railway tracks. The DSS keeps track of the state
of the railways tracks and identifies any tracks that are worn out or in bad repair after which the
railway company performs maintenance on the tracks and they are restored. Using the DSS, the
CNR was able to reduce the number of train derailments on their tracks, while across the region
other railway companies were actually experiencing a significant increase in the number of
derailments witnessed annually. Another effective application of DSS is within the medical
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industry where the Clinical Decision Support System (CDSS) is extremely effective in
performing medical diagnosis, and has drastically increased the amount of time taken and
resources used in medical diagnosis in the hospitals that use the CDSS. Most businesses use DSS
to represent all the relevant information about the business in summary form using charts such
that managers have an easy time making strategic decisions using the charts that contain all the
necessary information in summarized form.
Conclusion
Decision Support Systems are crucial for businesses as they speed up the speed of the
decision making process while at the same time increasing the personal efficiency of the decision
makers. DSS also facilitates communication between internal teams, staff, and managers and
provides new evidence that was not available without the DSS and the evidence provides enough
reason for the decision makers to make certain strategic decisions.
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References
Fazlollahi, B., & Vahidov, R. (2001). A method for generation of alternatives by decision
support systems. Journal of Management Information Systems, 18(2).
Wiederhold, G. (2000). Information systems that really support decision-making. Journal of
Intelligent Information Systems, 14(2&150;3).
Edwards, J. S., Duan, Y., & Robins, P. C. (2000). An analysis of expert systems for business
decision making at different levels and in different roles. European Journal of
Information Systems, 9(1).
Power, D. J. (2007, March 10). A Brief History of Decision Support Systems.
