Lecture 2

Organisational Information Systems

(Unit 2)

Organisation A

Different ways in which information can create value for organisations:

Reduce cost

Create new reality

Manage risks

Add value Customers and markets

Transactions and processes

Market, financial, legal, operational

New products, new services, new business ideas

(Chaffey and Wood, 2005)

Organisation C

Organisation B

Information Systems

Operations Support Systems

Management Support Systems

Transaction Processing

Systems

Process Control

Systems

Enterprise Collaboration

Systems

Management Information

Systems

Decision Support Systems

Executive Information

Systems

Operations and management classification of information systems (James A O’Brien (2004), ‘Management Information Systems, Managing information technology in the business enterprise’, 6th Edition, McGraw-Hill Irwin).

Support of business operations

Support of managerial

decision making

Processing business

transactions

Control of industrial

processes

Team and work group collaboration

Pre-specified reporting for managers

Interactive decision support

Information tailored for executives

Advances in IT and telecommunications

Globalisation Digital firms

Virtual enterprise

Globalisation

“..the increasing integration of economies around the world, particularly through trade and financial flows. .. the movement of people (labour) and knowledge (technology) across international borders.”

(The IMF Staff (2002) at www,imf.org/external/np/exr/ib/2000/041200.htm)

Virtual enterprise

A company that: joins with another company operationally, but not physically, to design and manufacture a product; distributed geographically and whose work is coordinated through electronic communications; share skills, costs, and access to one another’s markets

Digital firms

A firm in which nearly all organisation’s significant business relationships with customers, suppliers, and employees are digitally enabled and mediated. Core business processes are accomplished through digital networks

Digital Firms

• sense and respond to their environments more rapidly than traditional firms

• offer extraordinary opportunities for more flexible global organisation and management.

• time shifting and space shifting are the norms

Customers

Suppliers Business partners

Remote offices and work groups

Factories •Online marketing•Online sales•Built-to-order products•Customer service•Sales force automation

•Procurement •Supply chain management•Joint design

•outsourcing

•Communicate plans and policies•Group collaboration•Electronic communication•Scheduling

•Just-in-time production•Continuous inventory replenishment•Production planning

The Emerging Digital Firm

(Laudon & Laudon, 9th Edition, 2006:12)

Exercise

Laudon and Laudon, 10th Edition: Read the case study on Accenture in Chapter 1, page 9 and do the exercises at the end.

OR

Laudon and Laudon, 9th Edition: Read the case study on CEMEX in Chapter 1, page 14, and do the exercises at the end.

Characteristics of organisational problems and solutions

structured unstructuredSemi-

structured

Problem

Solution

Optimising Satisficing The rational model Bounded-rationality

Problem uniqueness

Impact on reaching corporate

goals

Decision making

authority

Number of people and functions

affected by decision

Need for

external dataPlanning

horizon

Strategic management

Tactical management

Operational management

Decision Dimensions in an OrganisationStair and Reynolds

High

Low

Decision Support Systems

• A set of interactive software programs that provide managers with data, tools, and models to make semistructured and unstructured decisions.

DSS support management decision making by integrating:

• Company performance data

• Business rules based on decision tables

• Analytical tools and models for forecasting and planning

Internal and External databases

Dialog Management

Model Management

Data Management

User

DSS

The structure of DSS

(Information Systems, Zwass, p57)

Knowledge Management

Decision Models

• Statistical Models

• Financial and Accounting Models

• Production Models

• Marketing Models

• Human Resource Models

Summary statistics, trend projections, hypothesis testing, etc.

Cash flow, internal rate of return, other investment analysis

Examples of Model driven DSS

• Voyage estimating system (Laudon & Laudon, Chapter 2, pages 54-57

• More examples in Laudon & Laudon, Chapter 12,

Cargo booking agent

Cargo reservation

system

Flight schedule

server

Passenger reservation

system

Passenger booking agent

CargoProf revenue

management system

request

Confirm/reject

Cargo size, rate data

Passenger forecast data

Cargo availability forecast

Availability/ minimum price

1

2

(Laudon & Laudon, 8th ed., page 351)

Data driven DSS

• Make use of OLAP and data mining to extract useful information.

• With OLAP uses need to have a good idea of what information they are looking for.

• OLAP allows data to be viewed from different perspectives, i.e. the same data is viewed in different ways using multiple dimensions.

Data driven DSS

• Data mining is more discovery driven.

• Finds hidden patterns and relationships.

• Data mining can yield associations, sequences, classifications, clusters, and forecasts.

Types of Analytical Modelling

• What-if Analysis– Change selected variables and observe its effect on

other variables• Sensitivity Analysis

– Observe how repeated changes to one variable affect other variables

• Goal-seeking Analysis (how-can)– Make repeated changes to selected variables until a

chosen variable reach a target value• Optimisation Analysis

– Finding an optimum value for selected variables, under a set of given constraints

Group Decision Support Systems (GDSS)

• Computer-based systems that enhance group decision making and improve the flow of information among group members.

GDSS Alternatives

[Figure 10.14]

Stair & Raynolds

Decision Room

– Decision makers are located in the same building or geographic area.

– Decision makers are occasional users of the GDSS approach.

Decision room alternative

Stair & Raynolds

Local Decision network

Schultheis & Sumner

Teleconferencing alternative

GDSS Alternatives

-Location of group members is distant.

-Decision frequency is low.

-Group meetings at different locations are tied together

Teleconferencing

video cameras

chairs

table

terminals

public screen

Robert Schulthesis and Mary SumnerSchultheis & Sumner

Wide area decision network

– Location of group members is geographically remote.

– Decision frequency is high.

– Virtual workgroups• Groups of workers located

around the world working on common problems via a GDSS

Wide area decision network

Stair & Raynolds

The Executive Support System

The Executive Support System (ESS)

• An IS that is focused on meeting the strategic needs of the organisation

• Designed explicitly for the purposes of senior management

• Used by senior management without technical intermediaries Easy to use, easy to learn

• Use state-of-the-art integrated graphics, text, and communication technology

Web browsing, e-mail, groupware tools, DSS and Expert System capabilities

• Also known as an Executive Information System (EIS)

The Executive Support System (ESS)

• Require a greater proportion of information from outside the business

Competitors, government, trade associations, consultants, etc.

• Are linked with value added business processes

ESS Support:• defining an overall vision

• strategic planning

• strategic organising and staffing

• strategic control

• crisis management

Expert Systems

Knowledge Based Information System (KBIS)

Expert System (ES):–A KBIS that uses its knowledge about a specific area to act as an expert consultant to the end user

USER

IF… and IF … and IF … and IF … THEN

QUERY

EXPERT ADVICE

Inference Engine

INPUT

OUTPUT

User Interface Programs

User Interface Programs

Expert System Software

Fact… Fact… Realtionship … Fact … Realtionship … Realtionship …

Knowledge Base

Expert System

Knowledge Acquisition programme

Knowledge Engineering

THE EXPERT and/or THE KNOWLEDGE ENGINEER

Expert System Development

Components of an Expert System, and the components involved in building the knowledge base.

(Adapted from O’Brien (2004:293) and Oz(2006:333))

Whale Watcher

http://www.aiinc.ca/demos/whale.html

Expert Systems Applications in Business

Chapter 11, Minicase 2, Page 501-502 of Turban etal.

Pages 438-439, Laudon and Laudon

http://www.exsys.com/exsys.html - Case Studies

Expert Systems Applications in Business

CLUES (Countrywide’s Loan Underwriting Expert Systems)

Intelligent help desk - IBM, Microsoft, Compaq

CADS (Consumer Appliance Diagnostic System) - Whirlpool

Web-based Expert Systems

Disseminating knowledge and expertise

Transferring ESs over the Net to human users and other computerised systems

Also supports the spread of multimedia-based ES (intellimedia systems)

Executive support systems

(ESS)

Decision support systems

(DSS)

Management Information

systems (MIS)

Transaction processing

systems (TPS)

Knowledge systems (ES and office systems)

Laudon & Laudon, p47

Artificial Intelligence

Cognitive Science Applications

Robotics Applications

Natural Interface Applications

Expert systems Learning systems Fuzzy Logic Genetic Algorithms Neural Networks Intelligent Agents

Visual perception Tactility Dexterity Locomotion Navigation

Natural languages Speech recognition Multisensory interfaces Virtual reality

The major application areas of AI (O’Brien, 2002:223)

Intelligent Support Systems

• Systems that augment a manager’s intelligence and expertise – Expert Systems (ES)

– Artificial intelligence• Natural Language processing• Neural networks• Fuzzy Logic• Intelligent agents