1. 1 Pertemuan 14 Enhancing management decision making: EIS dan Sispak Matakuliah: M0084/Sistem Informasi dalam Manajemen Tahun: 2005 Versi: 1/1

2. 2 Learning Outcomes Pada akhir pertemuan ini, diharapkan mahasiswa akan mampu : Mahasiswa dapat Menghubungkan kebutuhan perusahaan dalam pengambilan keputusan dengan Sistem Pakar dan EIS (C4)

3. 3 Outline Materi Peran Eksekutif Perbaikan dari EIS EIS berbasis komputer Implementasi keputusan EIS Critical Success Factor Future Trends Kecerdasan Buatan Model Sistem Pakar

4. 1.4 © 2003 by Prentice Hall Executive Support Systems (ESS): Information system at strategic level of an organizationInformation system at strategic level of an organization Addresses unstructured decision-making through advanced graphics and communicationsAddresses unstructured decision-making through advanced graphics and communications EXECUTIVE SUPPORT IN THE ENTERPRISE Essentials of Management Information Systems Chapter 11 Enhancing Management Decision-Making for the Digital Firm

5. 1.5 © 2003 by Prentice Hall Brings together data from the entire organizationBrings together data from the entire organization Allows managers to select, access, and tailor dataAllows managers to select, access, and tailor data Enables executive and any subordinates to look at the same data in the same wayEnables executive and any subordinates to look at the same data in the same way The Role of Executive Support Systems in the Organization Essentials of Management Information Systems Chapter 11 Enhancing Management Decision-Making for the Digital Firm EXECUTIVE SUPPORT IN THE ENTERPRISE

6. 1.6 © 2003 by Prentice Hall Developing ESS: Ease of useEase of use Facility for environmental scanningFacility for environmental scanning External and internal sources of information to be used for environmental scanningExternal and internal sources of information to be used for environmental scanning The Role of Executive Support Systems in the Organization Essentials of Management Information Systems Chapter 11 Enhancing Management Decision-Making for the Digital Firm EXECUTIVE SUPPORT IN THE ENTERPRISE

7. 1.7 © 2003 by Prentice Hall Analyzes, compares, and highlights trendsAnalyzes, compares, and highlights trends Provides greater clarity and insight into dataProvides greater clarity and insight into data Speeds up decision-makingSpeeds up decision-making Benefits of Executive Support Systems Essentials of Management Information Systems Chapter 11 Enhancing Management Decision-Making for the Digital Firm EXECUTIVE SUPPORT IN THE ENTERPRISE

8. 1.8 © 2003 by Prentice Hall Improves management performanceImproves management performance Increases management’s span of controlIncreases management’s span of control Better monitoring of activitiesBetter monitoring of activities Benefits of Executive Support Systems Essentials of Management Information Systems Chapter 11 Enhancing Management Decision-Making for the Digital Firm EXECUTIVE SUPPORT IN THE ENTERPRISE

9. 1.9 © 2003 by Prentice Hall ESS for business intelligence: Identifies changing market conditionsIdentifies changing market conditions Formulates responsesFormulates responses Tracks implementation effortsTracks implementation efforts Learns from feedbackLearns from feedback Executive Support Systems and the Digital Firm Essentials of Management Information Systems Chapter 11 Enhancing Management Decision-Making for the Digital Firm EXECUTIVE SUPPORT IN THE ENTERPRISE

10. 1.10 © 2003 by Prentice Hall Monitoring corporate performance: balanced scorecard systems Model for analyzing firm performanceModel for analyzing firm performance Supplements traditional financial measures with measurements from additional business perspectivesSupplements traditional financial measures with measurements from additional business perspectives Executive Support Systems and the Digital Firm Essentials of Management Information Systems Chapter 11 Enhancing Management Decision-Making for the Digital Firm EXECUTIVE SUPPORT IN THE ENTERPRISE

11. EIS Features n A central purpose n A common core of data n Two principal methods of use –Retrieve reports –Conduct analyses n A support organization –EIS coach –EIS chauffeur From Rockart and Treacy 16-11

12. Personal computer Make corporate information available Information requests Executive database Corporate database Electronic mailboxes Software library Current news, explanations External data and information Information displays Executive workstation Corporate mainframe To other executive workstation To other executive workstation An EIS Model 16-12

13. Make corporate information available Information requests Executive database Corporate database Electronic mailboxes Software library Current news, explanations External data and information Information displays Executive workstation Corporate mainframe To other executive workstation To other executive workstation An EIS Model 16-13

14. Dialogue Between Executive and EIS n Typically by a series of menus, keyboarding is minimized n Drill down to specific information needed from the overview level 16-14

15. MEDIAL INTERNATIONAL GROUP MIG Product Profitability Analysis Magazines in Europe have been performing poorly. While sales are up, production costs have soared. This is due to the labor disputes in the pulp and paper industry. Starting next month, costs should be back in line with earlier projections. Actual Planned Variance %Variance Newspapers 1,421,709 1,559,184 (137,475) (8.82) Magazines 490,855 518,687 (27,832) (5.37) Periodicals 1,912,564 2,077,872 (165,308) (7.96) Actual Planned Variance %Variance Newspapers 1,421,709 1,559,184 (137,475) (8.82) Magazines 490,855 518,687 (27,832) (5.37) Periodicals 1,912,564 2,077,872 (165,308) (7.96) x100x100 An Information Display That Includes a Computer- Generated Narrative Explanation 16-15

16. Incorporation of Management Concepts n Critical success factors n Management by exception n Mental model –Information compression 16-16

17. SALES - $ IN MILLIONS AS OF NOVEMBER 1994 SOURCE GLORIA YANDERS BILL BLASS SALES CURRENTHISTORY YEAR TO DATEOVER/ UNDER MB PROGRAM ACTUAL THIS MO LAST MO HERC $861.4 $30.7 $59.1 C-5B 621.9 0.3 4.5 OTHER 398.7 12.9 10.1 TOTAL $1,882.0 $43.9 $44.4 YEAR-END FORECAST CURRENT FORECAST Y-L O/U MB YR CURRENT O/ U PRIOR $949.8 $28.6 95 $2102.6 $ 8.0 699.0 1.2 96 2400.0 105.0 458.8 13.6 97 3130.0 98.0 $2107.6 $43.4 98 3390.0 58.0 99 2110.0 281.0 COMMENTS FAVORABLE VARIANCE PRIMARILY DUE TO TWO ADDITIONAL HERCULES SALES FORECAST BUDGET ACTUAL 16-17

18. EIS Implementation Decisions Three Key Questions: 1. Do we need an EIS? 2. Is there application-development software available? 3. Should we purchase prewritten EIS software? software? 16-18

19. EIS Critical Success Factors Rockart and DeLong 1. Committed/informed executive sponsor 2. Operating sponsor 3. Appropriate information services staff 4. Appropriate information technology (IT) 5. Data management 6. Link to business objectives 7. Manage organizational resistance 8. Manage the spread and evolution 16-19

20. Prerequisite Activities for the EIS Purchasing and Performance Systems Information technology standards Information needs Analysis of Organization Information Systems Plan Corporate data model EIS 16-20

21. Future EIS Trends n Use will become commonplace n Decreasing software prices n Will influence MIS/DSS n The computer will always play a support role 16-21

22. 1.22 © 2003 by Prentice Hall Knowledge BaseKnowledge Base Rule-based Expert SystemRule-based Expert System Rule BaseRule Base Knowledge FramesKnowledge Frames Capturing Knowledge: Expert Systems Essentials of Management Information Systems Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE

23. 1.23 © 2003 by Prentice Hall Rules in an AI Program Essentials of Management Information Systems Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE Figure 10-9

24. 1.24 © 2003 by Prentice Hall AI shellAI shell Inference EngineInference Engine Forward ChainingForward Chaining Backward ChainingBackward Chaining Capturing Knowledge: Expert Systems Essentials of Management Information Systems Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE

25. 1.25 © 2003 by Prentice Hall Frames to Model Knowledge Essentials of Management Information Systems Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE Figure 10-10

26. 1.26 © 2003 by Prentice Hall Inference Engines in Expert Systems Essentials of Management Information Systems Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE Figure 10-11

27. 1.27 © 2003 by Prentice Hall Knowledge engineer Specialist eliciting information and expertise from other professionalsSpecialist eliciting information and expertise from other professionals Translates information into set of rules, or frames, for an expert systemTranslates information into set of rules, or frames, for an expert system BlueCross BlueShield of North CarolinaBlueCross BlueShield of North Carolina Countrywide Funding Corp.Countrywide Funding Corp. Essentials of Management Information Systems Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE Building an Expert System

28. 28 End of Session 14