DECISION SUPPORT SYSTEMS

Decision Support Systems

Abstract

Information plays a key role in business management. Qualitative information to provide guidance to the company's management decisions, as well as effective tools for analyzing the performance of the company is necessary components of sustainable development and profitability. Business intelligence (BI) is designed to support management decisions. Through the use of such systems, information from various data sources and Information Systems Company is stored in a convenient form for analysis under a single corporate analytical data warehouse. The objective of this paper is to analyze the concept of Decision Support and Business Intelligence system and their application in an organization.

Table of Contents

Introduction4

Objectives of DSS4

Types of Decision Support Systems5

Management information systems (MIS)5

Executive information systems (EIS)5

Expert systems based on artificial intelligence (SSEE)5

Decision Support Systems Group (DSSG)6

Business Intelligence in the different departments of the company6

Marketing Department6

Purchasing Department6

Production Department7

Sales Department7

Economic and financial department7

Customer Service Department7

Human Resources Department7

Information Systems and Decisions in an organization8

Customer analysis:9

Analysis of stores:9

Analysis of sales and stocks:9

Analysis of progress:10

Analysis of the chains and supply chains:10

Data Base Management System and Logical Data Model10

The Real Business Intelligence11

Conclusion12

References14

Decision Support Systems

Introduction

Decision Support System (DSS) is a business intelligence tool focused on the analysis of data within an organization. In principle, it may seem that the analysis is simple, and easy to get through an application made as sophisticated as DSS (O'brien 2004). The ability to make accurate business decisions quickly has become one of the means for a company to achieve success. However, traditional information systems (like most management programs, custom applications, and even more sophisticated ERP), usually have a very inflexible structure for this purpose. Although its design conforms more or less to manage corporate data, it does not allow obtaining information from them, let alone extrapolating the knowledge stored in the day to day database (Sage 2001). 

Objectives of DSS

DSS is one of the most emblematic of Business Intelligence as it can solve many of the limitations of management programs. These are some of its main features:

Reporting is dynamic, flexible and interactive, so that the user does not have to adhere to predefined lists that were configured at the time of implantation, and does not always respond to real questions (Sage 2001).

No technical knowledge required. A non-technical user can create new charts and reports, and navigate between them, with drag & drop or drill down option (O'brien 2004). Therefore, to examine the data available or create new metrics is essential to seek help at the department.

It has a fast response time even though the underlying database is usually a corporate data warehouse or data mart, star or snowflake data models. Such databases are optimized for the analysis of large volumes of information (Connolly 2008).

Integration between all systems/departments of the company.

Each user has adequate information to their profile and not everyone has access to all information (Power 2000).

Availability of historical information. These systems can compare current data with information from other historical periods of the company, to analyze trends, to set the parameters of business development ...