Decision Support Systems, Attributes, Characteristics, Classification, Types, Advantages, Disadvanatages

Decision Support system (DSS) is a computerized program used to support determinations, judgments, and courses of action in an organization or a business. A DSS sifts through and analyzes massive amounts of data, compiling comprehensive information that can be used to solve problems and in decision-making.

Typical information used by a DSS includes target or projected revenue, sales figures or past ones from different time periods, and other inventory- or operations-related data.

A DSS can be used by operations management and planning levels in an organization to compile information and data and synthesize it into actionable intelligence. This allows the end user to make more informed decisions at a quicker pace.

The DSS is an information application that produces comprehensive information. This is different from an operations application, which would be used to collect the data in the first place. A DSS is primarily used by mid- to upper-level management, and it is key for understanding large amounts of data.

For example, a DSS could be used to project a company’s revenue over the upcoming six months based on new assumptions about product sales. Due to the large amount of variables that surround the projected revenue figures, this is not a straightforward calculation that can be done by hand. A DSS can integrate multiple variables and generate an outcome and alternate outcomes, all based on the company’s past product sales data and current variables.

The primary purpose of using a DSS is to present information to the customer in a way that is easy to understand. A DSS system is beneficial because it can be programed to generate many types of reports, all based on user specifications. A DSS can generate information and output it graphically, such as a bar chart that represents projected revenue, or as a written report.

As technology continues to advance, data analysis is no longer limited to large bulky mainframes. Since a DSS is essentially an application, it can be loaded on most computer systems, including laptops. Certain DSS applications are also available through mobile devices. The flexibility of the DSS is extremely beneficial for customers who travel frequently. This gives them the opportunity to be well-informed at all times, which in turn provides them with the ability to make the best decisions for their company and customers at any time.

Process of Decision Support Systems (DSS):

1. Data Input:

Gathering relevant data from various sources, both internal and external.

2. Data Processing:

Analyzing and processing data using models, algorithms, and analytical tools.

3. Knowledge Base:

Utilizing a knowledge base to store relevant information, rules, and decision criteria.

4. User Interface:

Providing a user-friendly interface for querying and interacting with the system.

5. Model Execution:

Executing models and simulations to generate insights and scenarios.

6. Results Presentation:

Presenting results through reports, dashboards, and visualizations.

7. User Feedback:

Gathering feedback from users to improve system performance.

Attributes of a DSS

• Adaptability and flexibility
• High level of Interactivity
• Ease of use
• Efficiency and effectiveness
• Complete control by decision-makers
• Ease of development
• Extendibility
• Support for modeling and analysis
• Support for data access
• Standalone, integrated, and Web-based

Characteristics of a DSS

• Support for decision-makers in semi-structured and unstructured problems.
• Support for managers at various managerial levels, ranging from top executive to line managers.
• Support for individuals and groups. Less structured problems often requires the involvement of several individuals from different departments and organization level.
• Support for interdependent or sequential decisions.
• Support for intelligence, design, choice, and implementation.
• Support for variety of decision processes and styles.
• DSSs are adaptive over time.

Benefits of DSS

• Improves efficiency and speed of decision-making activities.
• Increases the control, competitiveness and capability of futuristic decision-making of the organization.
• Facilitates interpersonal communication.
• Encourages learning or training.
• Since it is mostly used in non-programmed decisions, it reveals new approaches and sets up new evidences for an unusual decision.
• Helps automate managerial processes.

Disadvantages of Decision Support Systems:

• Complex Implementation:

Implementing DSS may require specialized skills and technical expertise.

• High Initial Costs:

The initial investment in DSS development and implementation can be substantial.

• Dependency on Data Quality:

DSS effectiveness heavily relies on the quality and accuracy of input data.

• Resistance to Change:

Users may resist adopting new decision-making processes facilitated by DSS.

• Security Concerns:

DSS may handle sensitive information, raising security and privacy issues.

• Overemphasis on Technology:

Overreliance on technology may overlook the human element in decision-making.

• Limited Flexibility:

Some DSS may lack flexibility to adapt to rapidly changing business environments.

• Integration Challenges:

Integrating DSS with existing systems may pose compatibility and integration challenges.

• Learning Curve:

Users may face a learning curve when adopting new DSS tools and interfaces.

• Maintenance Requirements:

Regular maintenance and updates are necessary to keep DSS effective and up-to-date.

Components of a DSS

(i) Database Management System (DBMS)

To solve a problem the necessary data may come from internal or external database. In an organization, internal data are generated by a system such as TPS and MIS. External data come from a variety of sources such as newspapers, online data services, databases (financial, marketing, human resources).

(ii) Model Management System

It stores and accesses models that managers use to make decisions. Such models are used for designing manufacturing facility, analyzing the financial health of an organization, forecasting demand of a product or service, etc.

(iii) Support Tools

Support tools like online help; pulls down menus, user interfaces, graphical analysis, error correction mechanism, facilitates the user interactions with the system.

Classification of DSS

There are several ways to classify DSS. Hoi Apple and Whinstone classifies DSS as follows:

(i) Text Oriented DSS

It contains textually represented information that could have a bearing on decision. It allows documents to be electronically created, revised and viewed as needed.

(ii) Database Oriented DSS

Database plays a major role here; it contains organized and highly structured data.

(iii) Spreadsheet Oriented DSS

It contains information in spread sheets that allows create, view, modify procedural knowledge and also instructs the system to execute self-contained instructions. The most popular tool is Excel and Lotus 1-2-3.

(iv) Solver Oriented DSS

It is based on a solver, which is an algorithm or procedure written for performing certain calculations and particular program type.

(v) Rules Oriented DSS

It follows certain procedures adopted as rules.

(vi) Rules Oriented DSS

Procedures are adopted in rules oriented DSS. Export system is the example.

(vii) Compound DSS

It is built by using two or more of the five structures explained above.

Types of DSS

(i) Status Inquiry System

It helps in taking operational, management level, or middle level management decisions, for example daily schedules of jobs to machines or machines to operators.

(ii) Data Analysis System

It needs comparative analysis and makes use of formula or an algorithm, for example cash flow analysis, inventory analysis etc.

(iii) Information Analysis System

In this system data is analyzed and the information report is generated. For example, sales analysis, accounts receivable systems, market analysis etc.

(iv) Accounting System

It keeps track of accounting and finance related information, for example, final account, accounts receivables, accounts payables, etc. that keep track of the major aspects of the business.

(v) Model Based System

Simulation models or optimization models used for decision-making are used infrequently and creates general guidelines for operation or management.

Decision Support Systems Role in Decision making process

1. Data Aggregation and Analysis:

   • Role of DSS:
     • Gathers and aggregates relevant data from various sources.
     • Analyzes data using advanced modeling and analytical techniques.
   • Impact on Decision Making:
     • Provides decision-makers with a comprehensive view of relevant information.
     • Enables in-depth analysis for better-informed decisions.

2. Scenario Simulation:

   • Role of DSS:
     • Allows for the creation and simulation of different decision scenarios.
     • Models the potential outcomes of various decision options.
   • Impact on Decision Making:
     • Assists decision-makers in understanding the consequences of different choices.
     • Supports proactive decision-making by exploring potential scenarios.

3. Decision Modeling and Optimization:

   • Role of DSS:
     • Utilizes mathematical models to represent decision problems.
     • Optimizes decision variables to achieve the best outcomes.
   • Impact on Decision Making:
     • Provides decision-makers with quantifiable and objective insights.
     • Optimizes resource allocation and decision parameters.

4. Access to Real-Time Information:

   • Role of DSS:
     • Integrates with systems to provide real-time data updates.
     • Ensures decision-makers have access to the latest information.
   • Impact on Decision Making:
     • Enables timely decision-making based on current and relevant data.
     • Supports agility and responsiveness in dynamic business environments.

5. User-Friendly Interfaces:

   • Role of DSS:
     • Provides intuitive and user-friendly interfaces for interaction.
     • Allows users to easily input queries and interact with the system.
   • Impact on Decision Making:
     • Reduces the learning curve for users, fostering widespread adoption.
     • Enhances accessibility for decision-makers across different levels.

6. Collaboration Support:

   • Role of DSS:
     • Facilitates collaboration by allowing multiple users to interact with the system.
     • Supports shared decision-making processes.
   • Impact on Decision Making:
     • Encourages teamwork and collective decision-making.
     • Improves communication and coordination among decision-makers.

7. Information Presentation:

   • Role of DSS:
     • Presents insights through visualizations, reports, and dashboards.
     • Transforms complex data into easily understandable formats.
   • Impact on Decision Making:
     • Enhances comprehension by presenting information in a digestible manner.
     • Supports quick and effective decision-making.

8. Risk Assessment and Mitigation:

   • Role of DSS:
     • Assesses potential risks associated with decision options.
     • Recommends strategies to mitigate identified risks.
   • Impact on Decision Making:
     • Helps decision-makers make informed choices while considering potential risks.
     • Supports the development of risk-conscious decision-making strategies.

9. Feedback Mechanism:

   • Role of DSS:
     • Establishes a feedback loop for continuous improvement.
     • Collects feedback from users to enhance system performance.
   • Impact on Decision Making:
     • Enables continuous learning and improvement in decision-making processes.
     • Incorporates user insights for refining decision support functionalities.