Accounting Information Systems: Essential Concepts and Applications Fourth Edition by Wilkinson, Cerullo, Raval, and Wong-On-Wing Module 2: Decision Support and Expert Systems Slides Authored by Somnath Bhattacharya, Ph.D. Florida Atlantic University Decision Support Systems: Advantages Improved effectiveness in making strategic and tactical decisions Greater timeliness in collecting and processing the needed data that bear on unstructured and semi-structured decisions Broader understanding by the decision makers of the array of factors involved in problems requiring complex decisions and their relationships to each other Key Components of a Decision Support System DSS data base DSS model base DSS user interface Terminal or microcomputer User Figure M2-1 A Comprehensive Data Base that Spans a Firm’s Decision Needs Environmental Data Internal Planning Data Other Model Data Summaries }* Chart of Accounts C u s to m e r D a ta In v e n to ry D a ta S u p p lie r D a ta E m p lo y e e D a ta P ro p e rty (p la n t a s s e ts ) D a ta ** S a le s O rd e r P ro d u c tio n & S h ip p in g R e c o rd s P u rc h a s e O rd e rs T im e R e c o rd s D is b u rs e m e n t R e c o rd s * = Planning data base ** = Operational data base Figure M2-2 DSS Model Base Decision Models Decision models Optimization models Firm-wide Planning Models Corporate models Financial planning models Modeling Languages Model Base Management Systems A Variety of Models Used by Decision Support Systems Model Description 1) Regression 2) Exponential smoothing 3) PERT 4) Linear programming 5) Line-of-balance 6) Economic order quantity 7) Supplier evaluation 8) Transportation 9) Discounted cash-flow 10) Production cost-variance 11) Cash-flow 12) Budget 13) Manpower planning Figure M2-3 Typical Function Aided 1) Sales forecasting 2) Sales forecasting 3) Engineering design 4) Production scheduling 5) Production routing 6) Inventory control 7) Purchasing 8) Physical distribution 9) Investment planning 10) Cost analysis 11) Financing 12) Accounting control 13) Personnel planning Model Manipulation Techniques Used with Financial Models Time-Based Simulation “What-If” Analysis Sensitivity Analysis Goal-seeking Analysis Figure M2-4 More on Model-Base Management Systems This is a modeling counterpart to a DBMS Its functions usually consist of providing Links between models in a DSS A model definition language Mechanisms for modifying decision models A user-friendly means of executing and manipulating models User Interfaces Query Languages Command language approach Menu approach GUI Group Decision Support Systems GDSSs allow for the rapid dissemination of information and support collaboration among group members Electronic mail software Lotus Notes Expert Systems An Expert System is a computerized software model that simulates the thinking process of one or more human experts in solving a complex problem or in making a decision. Components of an Expert System Knowledge Base Task-specific Data Base Inference Engine Forward chaining Backward chaining Development Engine Components of an Expert System Knowledge Base Inference Engine User Interface Task Specific Data Base Users Figure M2-6 Decision Situations and DSSs Expert Systems Neural Network Technology Complex Simple Conventional Software Structured Semi-structured Figure M2-7 Statistics Unstructured Decision Situation Completely Random Factors to Consider when Selecting Accounting ES Applications - I Problems or decisions requiring judgment are moderately complex to very complex and welldefined Operational and tactical problems are highly structured to somewhat semi-structured, recurring, and repetitive Expertise is difficult to acquire. Human experts are expensive and in short supply. Non-human expertise is available in the form of authoritative pronouncements, such as APBs, FASBs, and IRS tax regulations The accounting problem can be solved in a relatively short period of time The accounting problem is rule-intensive and can be solved with “if-then” rules Figure M2-8 Factors to Consider when Selecting Accounting ES Applications - II Common sense or intuition is not required to solve the problems The accounting problem cannot be solved efficiently with traditional or conventional computer software programs, such as COBOL or FORTRAN The body of knowledge is being continually updated The problem’s conversion to a computer-based expert system must result in a high payoff The expert system must produce clearly identified solutions with which most experts must agree among themselves Figure M2-8 Continued Areas of Accounting Expert Systems: Auditing (Internal & External) Deciding whether to accept a prospective auditee Evaluating risks and the internal control structure in computer systems Reviewing prior years’ working papers Issuing audit reports and forming audit opinions Writing audit programs Assisting in making a going-concern judgment Scheduling audit personnel Analyzing the adequacy of the allowance for doubtful accounts Analyzing unusual transactions Figure M2-9 Areas of Accounting Expert Systems: Taxation Advising on potential acquisitions and mergers Claiming a dependent Auditing deferred tax accruals Determining corporate tax status Determining if a firm qualifies for Subchapter S tax status Offering personal and corporate tax planning advice Figure M2-9 Continued Areas of Accounting Expert Systems: Cost/Managerial Analyzing significant variances and explaining the variation Assisting in monthly closings Allocating revenue and expenses Analyzing performance of projects Reviewing trial balances Figure M2-9 Continued Areas of Accounting Expert Systems: Financial Accounting Accounting for non-monetary transactions (APB No. 29) Accounting for contingencies (FAS No. 5) Purchasing vs. pooling (APB No. 16) Accounting for futures contracts (FAS No. 80) Developing expert systems for other professional pronouncements Classifying financial transactions correctly Evaluating credit worthiness Figure M2-9 Continued Examples of ES in Accounting: Auditing Figure M2-10 Nam e P u rp o se D e v e lo p e r L o a n P ro b e T o a ssist b a n k s in KPM G Peat a sse ssin g co m m e rcia l M a rw ick lo a n p o rtfo lio s A u d ito r T o a ssist in e v a lu a tin g D u n g a n th e a d e q u a cy o f th e (U n iv e rsity o f a llo w a n ce fo r b a d S o u th F lo rid a ) d e b ts E D P -X P E R T T o a id a u d it sp e cia lists in e v a lu a tin g th e re lia b ility o f co n tro ls in co m p u te r sy ste m s H a n se n a n d M e ssie r (U n iv e rsity o f F lo rid a ) G C -X T o a id in m a k in g g o in g -co n ce rn ju d g m e n ts B ig g s a n d S e lfrid g e (U n iv e rsity o f C o n n e c ticu t) A u d it P la n n e r T o a id in m a k in g S te in b a rt m a te ria lity ju d g m e n ts (A rizo n a S ta te Examples of ES in Accounting: Tax Nam e P u rp o se D e v e lo p e r T A X A D V IS O R T o a id ta x s p e c ia lis ts in r e n d e r in g e s ta te p la n n in g a d v ic e M ic h a e ls o n ( U n iv e r s ity o f N o r th T e x a s ) E xp e rT A X T o a id in ta x p la n n in g a n d c o r p o r a te ta x a c c r u a ls C o o p e rs a n d L y b ra n d T a x p a y e r S e r v ic e A s s is ta n t T o a id IR S a g e n ts in a n s w e r in g ta x p a y e r q u e s tio n s o n c o m p le x ta x is s u e s IR S Figure M2-10 Continued Emerging Developments Intelligent Agent Software Integrating DSSs with other support systems Fuzzy Logic Developments in Multimedia and Hypertext Accounting Information Systems: Essential Concepts and Applications Fourth Edition by Wilkinson, Cerullo, Raval, and Wong-On-Wing Copyright © 2000 John Wiley & Sons, Inc. 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