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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