Wednesday, May 1, 2024

Decision Support Systems (DSS). Basis of AI May 2024

Back in the 1980's and 1990's I was involved in the development of a few decision support systems for major corporations which are the backbones of AI today (2020's).



Decision support systems can be broken down into categories, each based on their primary sources of information.

  • Data-driven DSS. ...
  • Model-driven DSS. ...
  • Communication-driven and group DSS. ...
  • Knowledge-driven DSS. ...
  • Document-driven DSS

What is a Decision Support System (DSS)?

A decision support system (DSS) is an information system that aids a business in decision-making activities that require judgment, determination, and a sequence of actions. The information system assists the mid- and high-level management of an organization by analyzing huge volumes of unstructured data and accumulating information that can help to solve problems and help in decision-making. A DSS is either human-powered, automated, or a combination of both.

Decision Support System (DSS) - The words decision support system embossed on binary code

Purpose of a Decision Support System

A decision support system produces detailed information reports by gathering and analyzing data. Hence, a DSS is different from a normal operations application, whose goal is to collect data and not analyze it.
In an organization, a DSS is used by the planning departments – such as the operations department – which collects data and creates a report that can be used by managers for decision-making. Mainly, a DSS is used in sales projection, for inventory and operations-related data, and to present information to customers in an easy-to-understand manner.
Theoretically, a DSS can be employed in various knowledge domains from an organization to forest management and the medical field. One of the main applications of a DSS in an organization is real-time reporting. It can be very helpful for organizations that take part in just-in-time (JIT) inventory management.
In a JIT inventory system, the organization requires real-time data of their inventory levels to place orders “just in time” to prevent delays in production and cause a negative domino effect. Therefore, a DSS is more tailored to the individual or organization making the decision than a traditional system.

Components of a Decision Support System

The three main components of a DSS framework are:

1. Model Management System

The model management system S=stores models that managers can use in their decision-making. The models are used in decision-making regarding the financial health of the organization and forecasting demand for a good or service.

2. User Interface

The user interface includes tools that help the end-user of a DSS to navigate through the system.

3. Knowledge Base

The knowledge base includes information from internal sources (information collected in a transaction process system) and external sources (newspapers and online databases).

Decision Support System - Components

Types of Decision Support Systems

  • Communication-driven: Allows companies to support tasks that require more than one person to work on the task. It includes integrated tools such as Microsoft SharePoint Workspace and Google Docs.
  • Model-driven: Allows access to and the management of financial, organizational, and statistical models. Data is collected, and parameters are determined using the information provided by users. The information is created into a decision-making model to analyze situations. An example of a model-driven DSS is Dicodess – an open-source model-driven DSS.
  • Knowledge-driven: Provides factual and specialized solutions to situations using stored facts, procedures, rules, or interactive decision-making structures like flowcharts.
  • Document-driven: Manages unstructured information in different electronic formats.
  • Data-driven: Helps companies to store and analyze internal and external data.

Advantages of a Decision Support System

  • A decision support system increases the speed and efficiency of decision-making activities. It is possible, as a DSS can collect and analyze real-time data.
  • It promotes training within the organization, as specific skills must be developed to implement and run a DSS within an organization.
  • It automates monotonous managerial processes, which means more of the manager’s time can be spent on decision-making.
  • It improves interpersonal communication within the organization.

Disadvantages of a Decision Support System

  • The cost to develop and implement a DSS is a huge capital investment, which makes it less accessible to smaller organizations.
  • A company can develop a dependence on a DSS, as it is integrated into daily decision-making processes to improve efficiency and speed. However, managers tend to rely on the system too much, which takes away the subjectivity aspect of decision-making.
  • A DSS may lead to information overload because an information system tends to consider all aspects of a problem. It creates a dilemma for end-users, as they are left with multiple choices.
  • Implementation of a DSS can cause fear and backlash from lower-level employees. Many of them are not comfortable with new technology and are afraid of losing their jobs to technology.

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