1 / 7

ACCT 3340 – Spring 2007 CH 5 - ADVANCED INFORMATION SYSTEMS

ACCT 3340 – Spring 2007 CH 5 - ADVANCED INFORMATION SYSTEMS. Key Concepts: Hierarchy of organizational decisions -see fig p. 2 TPS – highly structured decisions, lower level (Level 1) DSS – semi-structured decisions, mid level management (Level 2)

ava-norman
Download Presentation

ACCT 3340 – Spring 2007 CH 5 - ADVANCED INFORMATION SYSTEMS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ACCT 3340 – Spring 2007CH 5 - ADVANCED INFORMATION SYSTEMS Key Concepts: Hierarchy of organizational decisions -see fig p. 2 TPS – highly structured decisions, lower level (Level 1) DSS – semi-structured decisions, mid level management (Level 2) Expert systems – unstructured decisions, non-programmable, complex problems, top level management (Level 3) Ruled-based ES (see fig p.16) vs Case-based ES (in appendix)

  2. Hierarchy of organizational decisions • Be familiar with the Decision triangle p. 2 • Be sure you know the characteristics of TPS, DSS, and ES and the comparison of TPS, DSS, and ES on p. 14 chart.

  3. TPS Transaction processing systems • Involves routine, recurring decisions • Uses routine transaction data either from outside exchanges or internal • Standard reports only • Range from legacy COBOL to ERP systems • See transaction processing cycles in appendix to Ch. 1

  4. DSS Decision support systems • Semi structured decisions, mid level management, • Fuzzy decision rules, requires human judgment, uncertainty, often difficult to articulate a decision approach • Uses data from internal and external sources (Lexis/Nexis, etc)., often use statistical models, EOQ. Often based on spreadsheet or database models • Variety of flexible reports, what-if questions, goal seeking, optimization supported, can be designed to force managers to consider relevant info • Exec Info Sys - Often very user friendly GUI interfaces, min computer skills • Applications might include cash forecasting, portfolio management, budget setting, inventory management, sales and marketing analysis, danger of faulty models and over reliance. • Know components of DSS (fig p. 7) and adv/disadv of DSS (fig p. 9)

  5. Data warehouses, data marts, and data mining • Be sure you know what is meant by data warehouses, data marts, and data mining. • Data warehouses are archival data used for many strategic purposes. • Data marts are designed to meet a particular user need (more specialized and targeted tactical purpose)

  6. Expert systems (ES) • ES is a subfield of artificial intelligence (AI) • Seeks to capture expert knowledge, i.e., to imitate the reasoning ability of human expert • Consultative role, not meant to replace the expert • Consultation and justification features • Hueristic reasoning feature (very fuzzy input and rules) • Incomplete info is OK, can give certainty factor • Know benefits and problems with ES -see fig p. 21 • Accounting and auditing applications – see fig p. 22 • Development issues – knowledge acquisition, verbal protocol analysis, validation methods

  7. Rule-based vs Case-based ES • Know components of rule-based ES (fig p. 16) and sample rules for credit granting (fig p. 17) • Know cased based reasoning process in appendix (p. 28) and diagram (p. 29)

More Related