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B. INFORMATION TECHNOLOGY (IS) CISB434: DECISION SUPPORT SYSTEMS Chapter 1: Introduction to Decision Support Systems LEARNING OUTCOMES Identify information systems for aiding decision making MIS and DSS Types of Decision-Support Systems Components of DSS DSS Applications Web-based Customer DSS 2 INTRODUCTION DEFINITION A Decision Support System (DSS) assists management decision-making by combining data; sophisticated analytical models and tools; and user friendly software a single powerful system that can support semi-structured and unstructured decision making 3 INTRODUCTION TO DECISION SUPPORT SYSTEMS MIS and DSS MANAGEMENT INFORMATION SYS. MIS Earliest applications for supporting management decision Provide information on firm’s performance help managers monitor and control the business Produce fixed, scheduled reports data extracted and analyzed from Transaction Processing System (TPS) 5 MANAGEMENT INFORMATION SYS. TYPICAL MIS REPORT Summarise monthly sales Highlight exceptional conditions e.g. drop of sales quotas below a set level employees have exceeded spending limit in health care Latest MISs offer online access On-demand Intranet and Web-based 6 DECISION-SUPPORT SYSTEMS DSS Provide nonroutine decisions and user control Emphasize change, flexibility and rapid response Easier access to structured information flows Greater emphasis on models, assump-tions, ad hoc queries and display 7 DECISION-SUPPORT SYSTEMS STRUCTURES OF PROBLEMS Problems Solutions Types Solution Provider Structured Known algorithms provide Repetitive and routine solutions MIS No known algorithms. Unstructured Discuss, ruminate, Novel and nonroutine brainstorm to decide DSS Semistructured Midway Midway between the above solution types DSS 8 EXAMPLE OF A STRUCTURED SEMISTRUCTURED PROBLEM Structured problem: How much will I earn after two years if I invest $100,000 in municipal bonds that pay 4 percent per annum tax free? Semistructured problem: If I invest $100,000 in stock XYZ and sell the stock in two years, how much money will I make? How are these problems different? 9 AND EXAMPLES OF STRUCTURED AND SEMISTRUCTURED PROBLEMS 10 INTRODUCTION TO DECISION SUPPORT SYSTEMS Types of Decision Support System TWO TYPES OF DSS MODEL-DRIVEN Stand-alone system Uses models to perform what-if analysis Usually developed in isolation for a particular group Utilizes strong theory or model Good user interface Easy to use 12 TWO TYPES OF DSS MODEL-DRIVEN: EXAMPLE 13 TWO TYPES OF DSS DATA-DRIVEN Analyzes large pools of data from firm’s information systems Allows users to extract useful information Data from Transaction Processing Sys-tems (TPS) are collected in a Data Warehouse Online analytical processing (OLAP) and data mining are used to analyze the data 14 DATA-DRIVEN DSS OLAP Traditional database queries provide onedimensional data analysis OLAP supports multidimensional data analysis, and complex request for information 15 DATA-DRIVEN DSS DATA MINING Data mining offers insights into corporate data by finding hid-den patterns and relationships inferring rules to predict future behaviour Use the patterns and rules to guide decision making forecast the effect of the decisions 16 DATA-DRIVEN DSS DATA MINING INFORMATION Associations occurrences linked to a single event e.g. sales of drinks and crisps increases by 80% when there is a football match Sequences linking of events over time e.g. when a new house is bought, orders for kitchen cabinet happens 65% after two weeks 17 DATA-DRIVEN DSS DATA MINING INFORMATION Classification describe a group to which an item belongs by examining existing items and inferring a set of rules e.g. identify characteristics of customers who are likely to leave, who they are, so as to devise special campaign 18 DATA-DRIVEN DSS DATA MINING INFORMATION Clustering discover different groupings within data e.g. finding affinity groups for bank cards Forecasting Use a series of values to forecast what other values will be e.g forecasting sales figures from prior sales 19 DATA-DRIVEN DSS DATA MINING TOOLS Data mining uses statistical analysis tools neural networks fuzzy logic genetic algorithms rule-based systems 20 DATA-DRIVEN DSS KNOWLEDGE DISCOVERY Data mining offers knowledge disco-very the process of identifying novel and valuable pattern in large volumes of data through selection, preparation and evalua-tion of contents of large databases 21 INTRODUCTION TO DECISION SUPPORT SYSTEMS Components of DSS COMPONENTS OF DSS DSS DATABASE Collection of current or historical data e.g a small database a Data Warehouse Extracts or copies of production database avoids interfering with operational systems 23 COMPONENTS OF DSS DSS SOFTWARE SYSTEM & UI Software tools for data analysis OLAP tools data mining tools mathematical and analytical models User interface easy interactions supports dialogue Web-based 24 COMPONENTS OF DSS MODELS A model is an abstract representation to illustrate the components or relation-ships of a phenomenon DSS is built for a specific set of purpose It has different collections of models 25 COMPONENTS OF DSS SOME DSS MODELS Statistical models full range of statistical functions: mean, median, deviations, etc. ability to project future outcomes help to establish relationships Optimization models use linear programming to determine opti-mal resource allocation, e.g. time or cost 26 COMPONENTS OF DSS SOME DSS MODELS Forecasting models use to forecast sales a range of historical data used to project future conditions and sales Sensitivity analysis what-if analysis determines impact of changes in one or more factors on outcomes 27 INTRODUCTION TO DECISION SUPPORT SYSTEMS DSS Applications DSS APPLICATIONS SUPPLY CHAIN MANAGEMENT Comprehensive examination of supply management chain Searches for most efficient and cost-effective combination Reduces overall costs Increases speed and accuracy of filling customer orders 29 DSS APPLICATIONS CUSTOMER RELATIONSHIP MANAGEMENT Uses data mining to guide decisions Consolidates customer information into massive data warehouses Uses various analytical tools to slice information into small segments 30 DSS APPLICATIONS CUSTOMER RELATIONSHIP MANAGEMENT 31 INTRODUCTION TO DECISION SUPPORT SYSTEMS Web-based Customer DSS WEB-BASED CUSTOMER DSS Customers use multiple sources of in-formation to make purchasing decision A Customer DSS supports the decision-making process of customers provides online access to databases, infor-mation pools and data analysis tools 33 THE END THANK YOU FOR LISTENING