Decision Support Systems Overview

Transcription

1 Decision Support Systems Overview Dr Sherif Kamel Department of Management School of Business, Economics and Communication

2 Decision Support Systems Systems designed to support managerial decision-making in unstructured problems Increasing emphasis shifting to inputs from outputs Mechanism for interaction between user and components Usually built to support solution or evaluate opportunities

3 Decision Support Systems A DSS is a methodology that supports decision-making The methodology is flexible adaptive Interactive GUI-based Iterative and employs modeling

4 DSS Definition Little (1970) defines DSS as a model-based set of procedures for processing data and judgments to assist a manager in his decision-making Alter (1980) defines DSS by contrasting them with traditional electronic data processing (EDP) Moore and Chang (1980) defines DSS as extendible systems capable of supporting ad hoc data analysis and decision modeling, oriented toward future planning and used at irregular and unplanned intervals

5 DSS v EDP Dimensions DSS EDP Use Active Passive User Line and staff management Clerical Goal Effectiveness Mechanical efficiency Time Horizon Present and future Past Objective Flexibility Consistency

6 What is a DSS application? DSS application is usually built to support the solution of a certain problem or. evaluate an opportunity It could be used by a simple user through a PC interface or collectively by a group of people through web-based applications

7 Case: DSS Application Reducing Inventories and Improving Performance Cambar Company is distributing industrial, electrical and electronic supplies (half a million products represent the inventory) Objective = how to reduce inventory without compromising customer service (decisions were mainly based on intuition leading to overstock and carrying additional costs) Need is to improve accuracy of demand forecasts (key to inventory reduction) What needs to be done?

8 Case: DSS Application Reducing Inventories and Improving Performance Steps to follow: Analyzing demand data and identifying order rules Develop, test and deploy a prototype for inventory-planning and management system Developing a model whereby Business information is saved Model based on data on the data server built on the application server Approximating lead time demand and rationalize the ordering process which also affects the service level associated Optimizing the model at the optimization and simulation server, results are captured at the application server which are then sent to the web server in the form of reports

9 Multi-tiered Architecture Incorporating optimization, simulation and other models into Web-based DSS Web Browser Optimization Simulation Server Web Server Application Server Data Warehouse DBMS Data Server

10 DSS Characteristics

11 What is Business Intelligence? BI is a collection of technical and process innovations across the data warehousing and business intelligence space Proactive BI focus on accelerating decision-making by leveraging its infrastructure to produce timely, relevant and useful information BI helps the continuous increase in information flow with business related implications through better decision making

12 Components of DSS 1. Data management subsystem It includes a database that contains relevant data for the situation and is managed by a database management system (DBMS) application Connected to the corporate data warehouse (with decision making data) accessed via database web server 2. Model management subsystem Software package that includes financial, statistical, management science, quantitative models providing the analytical capabilities called model base management system (MBMS) usually runs on application server

13 Components of DSS 3. User interface subsystem Users communicate and interact with the DSS Interaction between users (decision-makers) and computing Web browser provides a user-friendly and easy interface 4. Knowledge-based management subsystem Support subsystem providing intelligence for decision makers Known as organizational knowledge base

14 Building Blocks of DSS DBMS MBMS KBMS (optional) User Interface

15 Schematic view of DSS

16 1. Data Management Subsystem A. DSS Database B. Database management system C. Data directory D. Query facility

17 Structure of Database Management System

18 A. DSS Database Interrelated data extracted from various sources, stored for use by the organization, and queried Internal data, usually from TPS External data from government agencies, trade associations, market research firms, forecasting firms Private data or guidelines used by decision-makers Could also share DBMS with other systems

19 B. Database Management System Database is created, accessed and updated by a DBMS Most DSS are built with a standard relational database Captures and extracts data for inclusion in a DSS database Updates (add, delete, edit, change) data records and files Manages data and their relationships

20 C. Data Directory Catalog of all data Contains data definitions Answers questions about the availability of data items Source Meaning Allows for additions, removals, and alterations

21 D. Query Facility Retrieves and accesses data Queries and manipulates data

22 2. Model Base Management Subsystem A. Model base B. Modeling language (tools) C. Model base management system D. Model directory E. Model execution, integration, and command processor

23 A. Model Base Model base contains routine and special statistical, financial, forecasting, management science, quantitative models that provide the analysis capabilities in a DSS Models are divided into 4 main categories Strategic supporting top management decisions Tactical used primarily by middle management to allocate resources Operational supporting daily activities Analytical used to perform analysis of data

24 B. Modeling Language (tools) Models are usually customized because DSS mainly focus on semi-structured and unstructured problems Example: C++, OLAP, Java, Excel

25 C. Model Base Management System Functions of the model-base management system include: Model creation using programming languages Model updates and changes Model data manipulation Generation of new routines

26 D. Model Directory Catalog of models including all the models and other software in the model based (it does the same function as is data directory in the database) Definitions (to demonstrate the capabilities and functions of the model)

27 E. Model Execution, Integration, Command Processor Model execution Controls running of model Model command processor Receives model instructions from user interface Routes instructions to MBMS or module execution or integration functions Model integration Combines several models operations

28 3. User Interface Subsystem Combines all aspects of communication between a user and the DSS Dealing with factors related to ease of use, accessibility and human-machine interactions (web-browser have been recognized as the most effective)

29 User Interface Management System GUI Natural language processor Interacts with model management and data management subsystems Examples Speech recognition Display panel

30 4. Knowledge-Based Management System Expert or intelligent agent system component included Complex problem solving capabilities Enhances operations of other components May consist of several systems Mainly text-oriented DSS

31 User in DSS User represents the decision maker Individual or group Human interaction with DSS is key (capabilities are important for DSS success)

32 DSS Hardware Web server with DBMS: Operates using browser Data stored in variety of databases Can be mainframe, server, workstation, or PC Any network type Access could be through mobile devices

33 DSS Classifications Text-oriented DSS Information is often stored in textual format and must be accessed by decision makers Documents are electronically created, revised and accessed Web-based documents is an example Database-oriented DSS Mainly reflecting elements of report generation and query capabilities Usually of large volume, descriptive and rigidly structured

34 DSS Classifications Spreadsheet-oriented DSS Allowing the use of spreadsheet as a modeling tool for DSS analysis Most common end-user DSS Manipulation of data and the creation of multiplicity of scenarios Solver-oriented DSS Algorithm of procedure written to solve a specific problem Economic order quantity procedure for calculating an optimal ordering quantity

35 Web and DSS Web technologies Internet, intranets, extranets Enterprise software Knowledge management (KM) Enterprise resource planning (ERP) Customer relationship management (CRM) Supply chain management (SCM)