Chapter 10  2000 by Prentice Hall Information Systems for Managerial Decision Making Uma Gupta Introduction to Information Systems

 2000 by Prentice Hall.10-2 Learning Objectives After studying this chapter, you will be able to:  Explain how different types of information systems aid decision makers  Outline how transaction processing systems support operational decision making  Specify how management information systems help managers make tactical decisions  Discuss how intelligent support systems support mid- and top-level managerial decision making

 2000 by Prentice Hall.10-3 The Three Types of Systems That Support Employee Decision Making Transaction Processing Systems Management Information Systems Intelligent Support Systems ORGANIZATION’S INFORMATION NEEDS All three types of systems support decision making

 2000 by Prentice Hall.10-4 Transaction Processing System (TPS)  A system that records company transactions, in which a transaction is defined as an exchange between two or more business entities.

 2000 by Prentice Hall.10-5 Intelligent Support Systems  A set of systems that help managers integrate data, judgement, and intuition with their decision-making models and captures and preserves the knowledge of a company’s employees.

 2000 by Prentice Hall.10-6 Steps in Processing a Transaction Enter data Step 1 Validate data Step 2 Process the data into information Step 3 Store the processed data Step 4 Generate output Step 5 Support user queries Step 6

 2000 by Prentice Hall.10-7 Source Documents  Documents generated where and when a transaction occurs; the source of data for the transaction processing system.

 2000 by Prentice Hall.10-8 On-Line Transaction Processing (OLTP)  Transaction data that are processed instantaneously.

 2000 by Prentice Hall.10-9 Batch Processing  Transactions are accumulated over a certain period of time and processed at periodic intervals.

 2000 by Prentice Hall On-Line versus Batch Transaction Processing On-line Data input device is linked to the transaction processing system, so data are processed as soon as they are generated. Data are updated at certain intervals, such as daily, weekly monthly, and so on. Batch

 2000 by Prentice Hall Characteristics of a Transaction Processing System  Records internal and external transactions that take place in a company  Is used mostly by lower-level managers to make operational decisions  Stores data that are frequently accessed by other systems  Is ideal for routine, repetitive tasks  Records transactions in batch mode or on-line  Requires six steps to process a transaction— data entry, validation, data processing, storage, output generation, and query support

 2000 by Prentice Hall Management Information Systems (MIS)  A group of general-purpose, well-integrated systems that monitor and control the internal operations of an organization.

 2000 by Prentice Hall Management Information Systems for Decision Making  Management information systems (MIS) provide middle managers with the information necessary to make semistructured decisions  The main input to an MIS is usually the transaction processing system and other internal company sources  Summary and exception reports are the most common output of a MIS

 2000 by Prentice Hall Summary Report  A report that accumulates data from several transactions and presents the results in a condensed form.

 2000 by Prentice Hall Exception Report  A report that outlines any deviations between actual output and expected output.

 2000 by Prentice Hall Relationship between a TPS and MIS Goal: Record and Process Transactions Type of Decision Supported: Operational TRANSACTION PROCESSING SYSTEM Goal: Produce Summary and Exception Reports Type of Decision Supported: Tactical MANAGEMENT INFORMATION SYSTEM TPS output becomes MIS input

 2000 by Prentice Hall Intelligent Support Systems  Systems that augment a manager’s intelligence and expertise are called intelligent support systems (ISS)  Decision support systems (DSS)  Executive information systems (EIS)  Artificial intelligence and expert systems (ES)

 2000 by Prentice Hall Decision Support Systems  A set of interactive software programs that provide managers with data, tools, and models to make semistructured decisions.

 2000 by Prentice Hall Components of a Decision Support System  Database management system (DBMS)  Model management system  Support tools

 2000 by Prentice Hall A Simple Decision-Making Model Internal Data External Data Decision-making Models What-if Analysis Goal Seeking Problem Solving Generate Alternatives Assess Risk

 2000 by Prentice Hall Decision Models  Statistical Models  Financial and Accounting Models  Production Models  Marketing Models  Human Resource Models

 2000 by Prentice Hall Group Decision Support Systems (GDSS)  Computer-based systems that enhance group decision making and improve the flow of information among group members.

 2000 by Prentice Hall Key GDSS Features  Electronic questionnaires  Filled out on computers rather than paper  Electronic brainstorming tools  Tools that allow anonymous expression and sharing of ideas using computers  Idea organizers  Tools that allow groups to coordinate, compile, and prioritize  Voting tools  Tools that allow people to vote for an idea from a set of choices

 2000 by Prentice Hall Executive Information Systems (EIS)  Software that analyzes and presents information to executive decision makers in a useful, friendly, and customized format.

 2000 by Prentice Hall DSS and EIS Characteristics  DSS and EIS provide middle and top managers with decision support.  Both DSS and EIS are intuitive, interactive, user-friendly systems.  DSS and EIS are menu-driven and often have excellent color and graphic capabilities.  Both systems use internal and external data to solve problems.  A DSS uses internal and external data and different decision- making models to provide managers with alternatives to a given problem. An EIS provides managers with expert information in the form of analysis and reports.  Both systems are equipped with decision-making tools such as “what-if” analysis and ‘goal seeking”. EIS is also equipped with drill-down capabilities.  A DSS can support both individual and group decision making. DSS that support group decision making are known as group decision support systems (GDSS).

 2000 by Prentice Hall Artificial Intelligence (AI) and Expert Systems (ES)  Artificial intelligence is a field of computer science that studies the design and development of computer systems that mimic human intelligence.  Expert systems are computer programs that capture the knowledge of a human expert and use it to solve complex problems.

 2000 by Prentice Hall Components of an Expert System User Interface Knowledge Base (captures expert’s knowledge) Inference Engine (software that helps the system apply knowledge to solve problems)

 2000 by Prentice Hall Characteristics of an Expert System  An expert system is a software program that captures the knowledge and problem-solving skills of a human expert.  Expert systems are not targeted at any one level of management.  Expert systems are ideally suited for problems that require knowledge, intuition, and judgment.  Expert systems, unlike DSS and EIS, can replace the decision maker.  The three main components in an expert system are the knowledge base, the inference engine, and the user interface.

 2000 by Prentice Hall Business Guidelines for TPS, MIS, and ISS Success  Get the Commitment of Top Management  The CIO must convince top management of the link between IS and quality managerial decision making  The More Integrated the System, the Greater the Benefits  Without integrated systems, decisions will be made in isolation and the net impact will be delayed and often confused decisions

 2000 by Prentice Hall Business Guidelines for TPS, MIS, and ISS Success (cont.)  Benefits Are More than Just Bottom Line  In some cases a simple cost-benefit analysis may not be sufficient to make the investment decision  Business Drives the Choice of Information Systems Technology, Not the Other Way Around  Investing in technology for the sake of technology is a disaster waiting to happen  T Is for Trust  Trust develops when the IS department delivers successful and meaningful IS and IT services