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Pertemuan 14 Enhancing management decision making: EIS dan Sispak. Matakuliah : TI307 / Sistem Informasi Tahun : 20 12 Versi : 1. Learning Outcomes. Pada akhir pertemuan ini, diharapkan mahasiswa akan mampu :

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Pertemuan 14 Enhancing management decision making: EIS dan Sispak


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pertemuan 14 enhancing management decision making eis dan sispak

Pertemuan 14Enhancing management decision making: EIS dan Sispak

Matakuliah : TI307/SistemInformasi

Tahun : 2012

Versi : 1

learning outcomes
Learning Outcomes

Pada akhir pertemuan ini, diharapkan mahasiswa

akan mampu :

  • Mahasiswa dapat Menghubungkan kebutuhan perusahaan dalam pengambilan keputusan dengan Sistem Pakar dan EIS (C4)
outline materi
Outline Materi
  • Peran Eksekutif
  • Perbaikan dari EIS
  • EIS berbasis komputer
  • Implementasi keputusan EIS
  • Critical Success Factor
  • Future Trends
  • Kecerdasan Buatan
  • Model Sistem Pakar
slide4

Essentials of Management Information Systems

Chapter 11 Enhancing Management Decision-Making for the Digital Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE

  • Executive Support Systems (ESS):
  • Information system at strategic level of an organization
  • Addresses unstructured decision-making through advanced graphics and communications
slide5

Essentials of Management Information Systems

Chapter 11 Enhancing Management Decision-Making for the Digital Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE

The Role of Executive Support Systems in the Organization

  • Brings together data from the entire organization
  • Allows managers to select, access, and tailor data
  • Enables executive and any subordinates to look at the same data in the same way
slide6

Essentials of Management Information Systems

Chapter 11 Enhancing Management Decision-Making for the Digital Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE

The Role of Executive Support Systems in the Organization

  • Developing ESS:
  • Ease of use
  • Facility for environmental scanning
  • External and internal sources of information to be used for environmental scanning
slide7

Essentials of Management Information Systems

Chapter 11 Enhancing Management Decision-Making for the Digital Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE

Benefits of Executive Support Systems

  • Analyzes, compares, and highlights trends
  • Provides greater clarity and insight into data
  • Speeds up decision-making
slide8

Essentials of Management Information Systems

Chapter 11 Enhancing Management Decision-Making for the Digital Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE

Benefits of Executive Support Systems

  • Improves management performance
  • Increases management’s span of control
  • Better monitoring of activities
slide9

Essentials of Management Information Systems

Chapter 11 Enhancing Management Decision-Making for the Digital Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE

Executive Support Systems and the Digital Firm

  • ESS for business intelligence:
  • Identifies changing market conditions
  • Formulates responses
  • Tracks implementation efforts
  • Learns from feedback
slide10

Essentials of Management Information Systems

Chapter 11 Enhancing Management Decision-Making for the Digital Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE

Executive Support Systems and the Digital Firm

  • Monitoring corporate performance:
  • balanced scorecard systems
  • Model for analyzing firm performance
  • Supplements traditional financial measures with measurements from additional business perspectives
eis features
EIS Features
  • A central purpose
  • A common core of data
  • Two principal methods of use
    • Retrieve reports
    • Conduct analyses
  • A support organization
    • EIS coach
    • EIS chauffeur

From Rockart and Treacy

16-11

slide12

An EIS Model

Information

requests

Personal

computer

Executive

database

Information

displays

Executive workstation

To other

executive

workstation

To other

executive

workstation

Corporate

database

Make

corporate

information

available

Electronic

mailboxes

Current news,

explanations

Software

library

Corporate mainframe

External

data and

information

16-12

slide13

An EIS Model

Information

requests

Executive workstation

Executive

database

Information

displays

To other

executive

workstation

To other

executive

workstation

Corporate

database

Make

corporate

information

available

Current news,

explanations

Electronic

mailboxes

Corporate mainframe

Software

library

External

data and

information

16-13

dialogue between executive and eis
Dialogue Between Executive and EIS
  • Typically by a series of menus, keyboarding is minimized
  • Drill down to specific information needed from the overview level

16-14

slide15

An Information Display That Includes a Computer-Generated Narrative Explanation

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.

x

1

0

0

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)

16-15

incorporation of management concepts
Incorporation ofManagement Concepts
  • Critical success factors
  • Management by exception
  • Mental model
    • Information compression

16-16

slide17

SALES

SOURCE

GLORIA YANDERS

BILL BLASS

SALES -$ IN MILLIONS

AS OF NOVEMBER 1994

HISTORY

BUDGET

CURRENT

ACTUAL

FORECAST

YEAR-END FORECAST CURRENT FORECAST

YEAR TO DATE

OVER/ UNDER MB

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

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

COMMENTSFAVORABLE VARIANCE PRIMARILY DUE TO TWO ADDITIONAL HERCULES

SALES

16-17

eis implementation decisions three key questions
EIS Implementation DecisionsThree Key Questions:

1. Do we need an EIS?

2. Is there application-development software available?

3. Should we purchase prewritten EIS

software?

16-18

eis critical success factors rockart and delong
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

slide20

Prerequisite Activities for the EIS

Information

needs

Information

technology standards

Analysis of

Organization

Corporate

data model

Information

Systems Plan

Purchasing and

Performance

Systems

EIS

16-20

future eis trends
Future EIS Trends
  • Use will become commonplace
  • Decreasing software prices
  • Will influence MIS/DSS
  • The computer will always play a support role

16-21

slide22

Essentials of Management Information Systems

Chapter 10 Managing Knowledge for the Digital Firm

ARTIFICIAL INTELLIGENCE

Capturing Knowledge: Expert Systems

  • Knowledge Base
  • Rule-based Expert System
  • Rule Base
  • Knowledge Frames
slide23

Essentials of Management Information Systems

Chapter 10 Managing Knowledge for the Digital Firm

Figure 10-9

ARTIFICIAL INTELLIGENCE

Rules in an AI Program

slide24

Essentials of Management Information Systems

Chapter 10 Managing Knowledge for the Digital Firm

ARTIFICIAL INTELLIGENCE

Capturing Knowledge: Expert Systems

  • AI shell
  • Inference Engine
  • Forward Chaining
  • Backward Chaining
slide25

Essentials of Management Information Systems

Chapter 10 Managing Knowledge for the Digital Firm

Figure 10-10

ARTIFICIAL INTELLIGENCE

Frames to Model Knowledge

slide26

Essentials of Management Information Systems

Chapter 10 Managing Knowledge for the Digital Firm

Figure 10-11

ARTIFICIAL INTELLIGENCE

Inference Engines in Expert Systems

slide27

Essentials of Management Information Systems

Chapter 10 Managing Knowledge for the Digital Firm

ARTIFICIAL INTELLIGENCE

Building an Expert System

Knowledge engineer

  • Specialist eliciting information and expertise from other professionals
  • Translates information into set of rules, or frames, for an expert system
  • BlueCross BlueShield of North Carolina
  • Countrywide Funding Corp.