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Decision Support Systems Yong Choi School of Business CSU, Bakersfield Type of Decision-makings Structured (Programmed) Unstructured (Nonprogrammed) routine & repetitive, predictable problems standard solutions exist non-routine, unpredictable, “fuzzy” complex problems no cut-and-dried solutions Semistructured (Programmed + Nonprogrammed) non-routine, predictable, Require a combination of standard solution procedures and individual judgement Stages of Decision Making Stage 1: Intelligence identify the problems/opportunities and then, collect data or information Stage 2: Design analyze/develop the possible solutions for the feasibility GO back to stage 1 if there is insufficient data. Stages of Decision Making Stage 3: Choice Choose one alternative Go back to stage 1 or 2 if there are no satisfactory solutions. Stage 4: Implementation Implement the selected alternative Failure of implementation go back to stage 1 or 2 or 3 Ex) Buying a new car Transaction Processing Systems (TPS) Developed in the early1960s Serve the operational management level Performing and recording daily routine and repetitive transactions Primary focus: structured decision-makings Transaction Processing Systems Lifeblood of an organization Provide summarized and organized data in the accounting and finance areas Account receivable and payable Sales transactions Payroll Management Information Systems Developed in the 1960s Intended to serve the operational or middle management level Summary and exception reports monthly production reports Quarterly travel expense reports Difference between expected sales and actual sales of a particular product Primary focus: fairly structured decision-makings Decision Support System (DSS) An interactive computer-based system that helps decision makers in the solution of semi-structured and unstructured problems. Developed in the early 1970s Originally, designed to serve the middle management Primary focus: semi-structured and unstructured decision-makings Decision Support System What is a DSS? DSS Examples A highly flexible and interactive IT system that is designed to support decision making when the problem is not structured. Provide alternative-analysis report investment portfolios Plant expansion See text book for detail examples Three Fundamental Components of a DSS Model management component – consists of both the DSS models and the model management system Data management component – stores and maintains the information that you want your DSS to use User interface management component – allows you to communicate with the DSS Three Fundamental Components Three Fundamental Components of DSS 3. Model management component Data management component User interface management component See the online lecture or the textbook for details 1. 2. Model driven DSS Primarily stand alone systems isolated from major organization's information systems Use models (LP, Simulation) Sensitivity analysis as a main technique What-If analysis Goal Seek Analysis What-if analysis vs. Goal-seek analysis Attempt to check the impact of a change in the assumptions (input data) on the proposed solution What will happen to the market share if the advertising budget increases by 5 % or 10%? Attempt to find the value of the inputs necessary to achieve a desired level of output Use “backward” solution approach A DSS solution yielded a profit of $2M What will be the necessary sales volume to generate a profit of $2.2M? Tools for Model Driven DSS Linear Programming Lindo Gindo Spreadsheet Software Excel Lotus 1-2-3 Quattro Pro Data Driven DSS Many current and the newest DSS Data-driven DSS with On-line Analytical Processing (OLAP) provide the highest level of functionality and decision support that is linked to analysis of large collections of historical data. Discover previously unknown patterns by analyzing large pools of data from data warehouse Data mining as main technique Data Mining • Help managers to find hidden patterns and relationships in large databases to predict future behavior – “If a house is purchased, then new refrigerator will be purchased within two weeks 65% of the time.” Model Driven DSS vs. Data Driven DSS A Model Driven DSS uses various models such as statistical model, simulation model or financial model for decision makings. So, decisions are based on models. A Data Driven DSS emphasizes access to and manipulation of a time-series of internal company data and sometimes external data to aid decision makings. So, decisions are based on analyzed data. Web-based DSS for customers Evaluate and compare real estate prices Evaluate alternative investment in mortgage portfolios fidelity.com (on-line investor center) Evaluate and compare air fares Zillow.com: 10402 Loughton Ave. 93311 travelocity.com Evaluate and compare various automobile prices aotubytel.com Executive Information Systems OR Executive Support Systems Developed in the late 1980s Serve the senior management level Designed mainly to monitor organization’s performance and address decision makings quickly and accurately Very user-friendly, supported by graphics Drill-down capability EIS drill-down interface design The Need of EIS Need for more timely and accurate information for better decision makings Need to access internal/external databases to detect environmental changes Need to be more proactive due to intensive competition Gain computer literacy