Decision Support Systems: Types, Functions, and Limitations Analysis

This report provides a comprehensive overview of Decision Support Systems (DSS). It begins by highlighting the role of DSS in assisting managers with decision-making, improving their ability to make informed and balanced decisions, and providing user-friendly interfaces for real-time responses. The report then explores different types of DSS, including model-based, data-based, and those utilizing Online Analytical Processing and Data Mining. The key functions of DSS are discussed, including data quantification, model manipulation, and information management. Furthermore, the report differentiates between structured, semi-structured, and unstructured decisions, detailing the components and characteristics of each. Finally, the limitations of DSS are examined, such as challenges faced by small businesses, difficulties in data analysis, and the importance of understanding the assumptions underlying the systems. This information is crucial for anyone seeking to understand the practical application and potential drawbacks of DSS in a business context.

Role of Decision Support Systems
Managers are able to get information through
decision support systems which help them in
making decisions.
Managers’ ability to make correct and balanced
decisions are increased with the use of decision
support systems.
 There is an interactive interface associated with
a decision support system which makes it user-
friendly and gives a real-time response to the
queries of the user.

Types of Decision Support Systems
Model-based DSS is used for generating simulation
models, execution of planning to improve production
and scheduling, and creation of the financial report
and statistical.
Data based DSS analyzes huge amount of data from
various sources, like data from the web,
organizational data and data collected from the
enterprise.
Online Analytical Processing helps in getting a fast
response regarding the queries related to complex
business requests.
Data Mining extract significant data that help in
predicting behaviour and future trends.

Key functions of Decision Support Systems
There are three functions on which the DSS is based
that are data quantification, model manipulation and
information management.
Information management mentioned to the retrieval,
storage and reporting of detailed data in an appropriate
format according to the convenience of the user.
Through data quantification, a large amount of data are
condensed and systematically operated into a few core
measurement that removes the quintessence of
information.
Model manipulation helps in constructing and resolving
the different type of scenarios to response "what if”
questions.

Structured, semi-structured and unstructured
decisions
The structured decisions consist of three components
that are a process, data and evaluation. It is carried
out on a regular basis in order to develop a rigid
framework that will allow making decisions.
The unstructured decisions also consist of the same
components that are a process, data and evaluation.
However, nature may not match with each other.
The semi-structured decisions characterized as some
agreements on the process, data and evaluation but
also taking into account the efforts for retaining
some judgement of individuals in the decision
making process.

Limitations of Decision Support Systems
The small businesses due the lack of technical
knowledge faces problems in implementing the
decision support systems.
The decision makers sometime faces problems in
analyzing data due to the complexities associated
with mathematical calculations.
The decision makers faces problems when they
are not fully aware of the retractions or
suppositions of the decision support system.