Transaction Processing System (TPS)

1. Transaction Processing System (TPS) • A transaction is a business event that generates or modifies data stored in an information system. • A TPS collects and stores data about transactions and sometimes controls decisions made as part of a transaction. • A TPS focuses on record keeping and control of repetitive clerical processes. (Source: Alter, 1999)

2. TPS (Contd.) • Design of a TPS is based on • execution details of the transactions; • data content and format; and • rules and policies to be enforced. • TPSs are capable of • enforcing rules and work procedures; • detecting errors, such as missing data, invalid data, and inconsistent data; and • automating certain decision-making functions. (Source: Alter, 1999)

3. TPS (Contd.) • Batch Processing: Information on individual transactions is collected and stored. Based on a schedule or number accumulated the transactions are processed later to update the database. • Examples are processing of checks and other paper forms, generation of paychecks, and weekend deposits into ATMs. • Problems - error correction & data currency. (Source: Alter, 1999)

4. TPS (Contd.) • Real-time Processing: Each transaction is processed immediately. An advantage is immediate error correction. • Examples are airline reservation systems and bursar/bank systems. • Characterized by quick response and high availability. (Source: Alter, 1999)

5. ERP System - a TPS? • An ERP system encompasses transaction processing done in various functional areas of an enterprise. • Actually an ERP system is a hybrid system that has characteristics of many of the individual information system types including the TPS. (Source: Alter, 1999)

6. Management Information System (MIS) • MISs generate summary information for monitoring performance, maintaining coordination, and providing background about the organization’s operation. • Users are both managers and the employees who receive feedback about performance indicators. • MISs extract and summarize data from TPSs. (Source: Alter, 1999)

7. MIS (Contd.) • Typically provide pre-specified reports on a scheduled basis. • MIS provides information; people decide how to improve performance. • Executive Information Systems (EISs) take MISs to the next level. (Source: Alter, 1999)

8. Executive Information System (EIS) • EISs offer a highly interactive system that provides managers and executives flexible access to information for monitoring operating results and general business conditions. • Executives can “drill down” to understand specific items of concern in more detail. • Data is replenished periodically from internal and external sources. (Source: Alter, 1999)

9. EIS (Contd.) • Typical characteristics of EISs are • user-friendly interfaces; • variety of formats (tables, graphs, etc.); • triggers for exceptional conditions; • multiple levels of detail;and • customizable reports. • EISs help executives find the information they need whenever they need it and in whatever form is most useful. (Source: Alter, 1999)

10. Decision Support System (DSS) • A DSS is an interactive IS that provides information, models, and data manipulation tools to help make decisions in semi-structured and unstructured situations. • In contrast to MIS, a DSS supports managers and professionals doing largely analytical work in less structured situations. (Source: Alter, 1999)

11. DSS (Contd.) • The traditional DSS approach includes interactive problem solving; direct use of models; user-controllable methods for displaying and analyzing data; and formulating and evaluating alternatives. • Examples range from spreadsheets to customized simulation or optimization models focusing on specific situations. (Source: Alter, 1999)

12. DSS (Contd.) • DSSs support repetitive decision making by structuring the decision to some extent and defining procedures and formats. • An example of the repetitive case is the use of a DSS by insurance agents to help customers choose the “right” insurance policy - options, cost and benefits. (Source: Alter, 1999)

13. DSS (Contd.) • DSSs support non-repetitive decision making by providing data, models, analytical tools, and interface methods. • An example is a system that helps marketing managers evaluate alternative marketing plans and track results. Data includes internal sales results and external market research databases. (Source: Alter, 1999)

14. New Approaches to DSS • Online Analytical Processing (OLAP) and data mining. • OLAP is the use of online data analysis tools to explore large transaction databases. • Data mining is the use of data analysis tools to find patterns in large transaction databases. (Source: Alter, 1999)

15. Data Mining (Contd.) • Examples are customer buying patterns in grocery stores and statistical profiles of customers who are likely to switch long-distance carriers. • One of the difficulties in data mining is the problem of differentiating between meaningful and spurious patterns. (Source: Alter, 1999)

16. Execution Systems • These systems directly support people doing the value-added work in an organization. • Examples are systems that help plastic surgeons design operations and show likely results to their patients. • Expert or knowledge-based systems are one type of execution systems. (Source: Alter, 1999)

17. Expert Systems • Expert systems support the intellectual work of professionals engaged in design, diagnosis, or evaluation of complex situations requiring expert knowledge in a well-defined area. • Common applications are medical diagnosis, troubleshooting, chemical analysis, data interpretation, etc. (Source: Alter, 1999)

18. Office Automation Systems • An OAS facilitates everyday information processing tasks in offices and business organizations. They include a wide array of productivity tools. • Spreadsheets • Word processors, desktop publishing tools • Presentation packages • Personal database systems (Source: Alter, 1999)

19. Communication Systems • The broad categories of communication systems are • Teleconferencing • Messaging systems - e-mail, v-mail, and fax • Groupware (e.g. Lotus Notes) • Intranets and extranets • Knowledge management systems (Source: Alter, 1999)