Decision Support Systems
A decision support system (DSS) is a computerised programme that enables decisions, assessments, and acts inside a firm or organization. A DSS sorts and analyses massive data sets before compiling specific information for use in decision-making and problem-solving.
A DSS often includes objective or expected revenue, historical sales data from multiple time periods, and inventory or operational data.
A DSS may be used by an organization’s planning and operations management levels to collect and integrate data and information to provide actionable insight. As a consequence, the user may make decisions more rapidly and with better understanding.
The DSS is an information application that produces detailed data. This is not the same as an operations application, which is used to collect data initially. A DSS is mostly used by mid- to upper-level management to interpret massive amounts of data.
A DSS, for example, might be used to anticipate a company’s revenue for the next six months in response to altered product sales forecasts. Because of the multiple factors surrounding the expected income predictions, this is not an easy computation to accomplish by hand. Based on the company’s previous product sales data and current factors, a DSS may combine several variables to provide one result as well as alternate outcomes.
The primary purpose of using a DSS is to provide clients with information that is easily comprehensible. One benefit of a DSS system is that it may be customized to provide a variety of reports based on user needs. A DSS may produce textual reports or visually represent data in the form of a bar chart displaying predicted revenue.
The usage of large, heavy mainframes for data processing is becoming less popular as technology advances. A DSS may be installed on the majority of computer systems, even laptops, since it is simply an application. Mobile devices can also access certain DSS apps. Customers that travel regularly benefit greatly from the DSS’ flexibility. This gives them constant access to information, allowing them to make the best choices for their company and clientele at any moment.
Characteristics of DSS
- Flexibility and Adaptability
- Increased degree of interaction
- Utilization ease
- Effectiveness and Efficiency
- Those in control exercise absolute command.
- Development’s easiness
- Extendibility
- help with analysis and modeling.
- Assistance with data access.
- Web-based, integrated, or standalone
- DSS features let decision-makers address both unstructured and semi-structured challenges.
- Assistance for managers at all levels of management, from CEOs to lower-level managers.
- Assistance to individuals and organizations. Less structured issues usually need the cooperation of numerous persons from different organizational levels and departments.
- Supports sequential or interrelated judgments.
- Assistance in implementation, design, decision making, and intelligence.
- Support for various decision-making methods and ideologies.
- DSSs may vary with time.
- Advantages of DSS
- improves the speed and efficacy of decision-making.
- enhances the organization’s ability to make future-oriented decisions, as well as its control and competitiveness.
- Promotes interpersonal communication.
- encourages education or training.
Because it is mostly used for non-programmed judgments, it delivers innovative tactics and new evidence for an unusual decision.
facilitates the automation of management responsibilities.
The components of a DSS
I Information Management System (DBMS)
The information required to address an issue might come from an external or internal database. TPS and MIS systems generate internal data inside a company. External data (finance, marketing, human resources) may be obtained from a variety of sources, including newspapers, internet data providers, and databases.
Model Management System (ii) stores and accesses decision-making models used by managers. These models are used to forecast demand for a product or service, assess an organization’s financial health, design production facilities, and so on.
(iii) Assistance Instruments
Online assistance, pull-down menus, user interfaces, graphical analysis, and error correction methods are examples of support technologies that facilitate user interaction with the system.
DSS classification
There are several techniques of categorising DSS. Hoi Apple and Whinstone divide the DSS into the following categories:
I DSS with Text Focus
It comprises textual information that may impact a decision. It allows you to electronically produce, amend, and study documents as required.
Database-oriented DSS (ii) requires well-structured data.
Spreadsheet-based DSS (iii)
Spreadsheets with data that allow for the generation, viewing, and update of procedural knowledge, as well as instructions that instruct the system to do autonomous activities, are provided. The most popular applications are Lotus 1-2-3 and Excel.
(iv) DSS with a solver focus.
Its cornerstone is a solver, which is an algorithm or procedure that performs specified calculations and is compatible with a specific kind of software.
(v) Rule-based DSS.
It follows precise processes specified as recommendations.
(vi) DSS with Rules.
Procedures are used in a rule-based DSS. The example is the export system.
(vii) DSS Compound.
It is made up of two or more of the five structures listed above.
DSS Types
I System for Status Inquiry
It supports in making operational, managerial, or intermediate-level management choices, such as daily machine work schedules or machine operators.
(ii) System for Data Analysis
It necessitates comparative analysis and uses formulae or algorithms like as inventory, cash flow, and so forth.
The Information Analysis System (iii) analyzes data and creates information reports. For example, examine market analysis, accounts receivable systems, and sales analysis.
(iii) The Accounting Framework.
It analyzes financial and accounting data, such as final accounts, accounts payable, accounts receivable, and so on, which follow the company’s primary operations.
(v) System based on models
Decision-making models based on optimization or simulation are infrequently utilized and generate broad operational or management recommendations.