The Role of Information Systems in

Organisations

Session 02

1.1 © 2007 by Prentice Hall

 Management Information Systems

LEARNING OBJECTIVES

• Explain why information systems are so essential

in Organisations today.

• Define an information system from both a

technical and a business perspective.

• Identify and describe the three dimensions of

information systems.

1.2 © 2007 by Prentice Hall

 LEARNING OBJECTIVES (Continued)

• Assess the complementary assets required for

information technology to provide value to a
business.

• Identify and describe contemporary approaches

to the study of information systems and
distinguish between computer literacy and
information systems literacy.

1.3 © 2007 by Prentice Hall

 Management Information Systems
Smart Systems and Smart Ways of Working Help Toyota Become Number One

• Problem: Tough competition and demanding customers.

• Solutions: Redesigned order and production processes
reduce costs, increase revenue, and improve customer
service.
• Oracle E-Business Suite makes it possible to build cars
to order and forecast demand and production
requirements more accurately.
• Demonstrates IT’s role in analyzing market trends and
monitoring quality, efficiency, and costs.
• Illustrates the emerging digital firm landscape where
businesses can use tools to analyze critical data.

1.4 © 2007 by Prentice Hall

 The Role of Information Systems in Business Today

• How information systems are transforming

business
• Increased technology investments
• Increased responsiveness to customer demands: A
“Fed-Ex” economy
• Shifts in media and advertising (e.g. blogs, google ads)
• New federal security and accounting laws
• Globalization opportunities
• Internet has drastically reduced costs of operating on
global scale
1.5 © 2007 by Prentice Hall
 Information Technology Capital Investment

Figure 2-1
1.6 © 2007 by Prentice Hall
 • In the emerging, fully digital firm
– Significant business relationships are digitally enabled
and mediated
– Core business processes are accomplished through
digital networks
– Key corporate assets are managed digitally

• Digital firms offer greater flexibility in

organization and management
– Time shifting, space shifting

1.7 © 2007 by Prentice Hall

 • Growing interdependence between ability to use information
technology and ability to implement corporate strategies and
achieve corporate goals

• Business firms invest heavily in information systems to

achieve six strategic business objectives:

– Operational excellence
– New products, services, and business models
– Customer and supplier intimacy
– Improved decision making
– Competitive advantage
– Survival

1.8 © 2007 by Prentice Hall

 • Operational excellence:

– Improvement of efficiency to attain higher

profitability

– Information systems, technology an important tool in

achieving greater efficiency and productivity

– E.g. Wal-Mart’s RetailLink system links suppliers to

stores for superior replenishment system

1.9 © 2007 by Prentice Hall

 • New products, services, and business
models:
– Business model: describes how company
produces, delivers, and sells product or
service to create wealth
– Information systems and technology a major
enabling tool for new products, services,
business models
• E.g. Apple’s iPod, iTunes and Netflix’s Internet-
based DVD rentals

1.10 © 2007 by Prentice Hall

 • Customer and supplier intimacy:
– Serving customers well leads to customers
returning, which raises revenues and profits
• E.g. High-end hotels that use computers to track
customer preferences and use to monitor and
customize environment
– Intimacy with suppliers allows them to provide
vital inputs, which lowers costs
• E.g. J.C.Penney’s information system which links
sales records to contract manufacturer

1.12 © 2007 by Prentice Hall

 • Improved decision-making
– Without accurate information:
• Managers must use forecasts, best guesses, luck
• Leads to:
– Overproduction, underproduction of goods and services
– Misallocation of resources
– Poor response times
• Poor outcomes raise costs, lose customers
– E.g. Verizon’s Web-based digital dashboard to
provide managers with real-time data on customer
complaints, network performance, line outages, etc.

1.12 © 2007 by Prentice Hall

 • Operational excellence:
– Improvement of efficiency to attain higher profitability

• New products, services, and business models:

– Enabled by technology

• Customer and supplier intimacy:

– Serving customers raises revenues and profits
1.13 © 2007 by Prentice Hall

– Better communication with suppliers lowers costs

 • Competitive advantage
– Delivering better performance
– Charging less for superior products
– Responding to customers and suppliers in real time
– Often achieved when firm achieves one of first four
advantages
– E.g. Dell: Consistent profitability over 25 years; Dell
remains one of the most efficient producer of PCs in
world.
– But Dell has lost some of its advantages to fast
followers-- HP

1.14 © 2007 by Prentice Hall

 • Survival
– Information technologies as necessity of
business

– May be:
• Industry-level changes, e.g. Citibank’s introduction
of ATMs

• Governmental regulations requiring record-keeping

– E.g. Toxic Substances Control Act, Sarbannes-OxleyAct

1.15 © 2007 by Prentice Hall

 The Interdependence Between Organizations and
Information Technology

There is a growing interdependence between a firm’s information systems and its business capabilities.
Changes in strategy, rules, and business processes increasingly require changes in hardware, software,
databases, and telecommunications. Often, what the organization would like to do depends on what its
systems will permit it to do.
Figure 2-2
 • Information system:
– Set of interrelated components

– Collect, process, store, and distribute information

– Support decision making, coordination, and

control

• Information vs. data

– Data are streams of raw facts

– Information is data shaped into meaningful form

1.17 © 2007 by Prentice Hall
 Data and Information

Raw data from a supermarket checkout counter can be processed and

organized to produce meaningful information, such as the total unit sales of
dish detergent or the total sales revenue from dish detergent for a specific
store or sales territory.
Figure 2-3
 • Information system: Three activities
produce information organizations need
– Input: Captures raw data from organization
or external environment
– Processing: Converts raw data into
meaningful form
– Output: Transfers processed information
to people or activities that use it

1.19 © 2007 by Prentice Hall

 • Feedback:
– Output returned to appropriate members of
organization to help evaluate or correct input
stage

• Computer/Computer program vs.

information system

– Computers and software are technical foundation

and tools, similar to the material and tools used to
build a house
1.20 © 2007 by Prentice Hall
 Functions of an Information System

An information system contains information about an organization and its surrounding environment. Three basic
activities—input, processing, and output—produce the information organizations need. Feedback is output returned
to appropriate people or activities in the organization to evaluate and refine the input. Environmental actors, such
as customers, suppliers, competitors, stockholders, and regulatory agencies, interact with the organization and its
information systems. Figure 2-4
© 2007 by Prentice Hall
 Information Systems Are More Than Computers

Using information systems effectively requires an understanding of the organization,

management, and information technology shaping the systems. An information system
creates value for the firm as an organizational and management solution to challenges
posed by the environment
.

Figure 2-5
• Organizational dimension of
information systems
– Hierarchy of authority, responsibility
• Senior management
• Middle management
• Operational management
• Knowledge workers
• Data workers
• Production or service workers
 Levels in a Firm

rganizations are hierarchies consisting of three principal levels: senior

management, middle management, and operational management. Information
systems serve each of these levels. Scientists and knowledge workers often
work with middle management.
Figure 2-6
 • Organizational dimension of information
systems (cont.)
– Separation of business functions
• Sales and marketing
• Human resources
• Finance and accounting
• Production and manufacturing)
– Unique business processes
– Unique business culture
– Organizational politics

1.25 © 2007 by Prentice Hall

• Management dimension of
information system
– Managers set organizational strategy for
responding to business challenges
– In addition, managers must act creatively:
• Creation of new products and services
• Occasionally re-creating the organization
• Technology dimension of information
systems
– Computer hardware and software
– Data management technology
– Networking and telecommunications
technology
• Networks, the Internet, intranets and extranets,
World Wide Web
– IT infrastructure: provides platform that
system is built on
 UPS Competes Globally with Information Technology

• Read the Interactive Session: Technology, and then

discuss the following questions:

• What are the inputs, processing, and outputs of

UPS’s package tracking system?

• What technologies are used by UPS? How are these

technologies related to UPS’s business strategy?

• What problems do UPS’s information systems solve?

What would happen if these systems were not available?
1.29 © 2007 by Prentice Hall
 • Dimensions of UPS tracking system
– Organizational:
• Procedures for tracking packages and managing
inventory and provide information

– Management:
• Monitor service levels and costs

– Technology:

• Handheld computers, bar-code scanners, networks,

desktop computers, etc.
1.29 © 2007 by Prentice Hall
• Business perspective on information
systems:
– Information system is instrument for
creating value
– Investments in information technology will
result in superior returns:
• Productivity increases
• Revenue increases
• Superior long-term strategic positioning
• Business information value chain
– Raw data acquired and transformed through stages
that add value to that information

– Value of information system determined in part by extent to

which it leads to better decisions, greater efficiency, and
higher profits

• Business perspective: Calls attention to

organizational and managerial nature of
information systems
 Perspectives on Information Systems

The Business Information Value Chain

From a business perspective, information systems are part of a series of value-adding

activities for acquiring, transforming, and distributing information that managers can use to
improve decision making, enhance organizational performance, and, ultimately, increase firm
profitability.
Figure 2-7
 Variation in Returns on
Information Technology Investment

Although, on average, investments in information technology produce returns

far above those returned by other investments, there is considerable variation
across firms.
Figure 2-8
• Investing in information technology does not
guarantee good returns

• Considerable variation in the returns firms

receive from systems investments

• Factors:
– Adopting the right business model
– Investing in complementary assets (organizational
and management capital)
• Complementary assets:
– Assets required to derive value from a
primary investment
– Firms supporting technology investments
with investment in complementary assets
receive superior returns
– E.g.: invest in technology and the people to
make it work properly
 Complementary assets include:
– Organizational investments, e.g.
• Appropriate business model

• Efficient business processes

– Managerial investments, e.g.

• Incentives for management innovation

• Teamwork and collaborative work environments

– Social investments, e.g.

• The Internet and telecommunications infrastructure

• Technology standards
1.36 © 2007 by Prentice Hall
Contemporary Approaches to Information Systems

The study of information systems deals with issues and insights contributed
from technical and behavioral disciplines.

Figure 2-9
 • Technical approach
• Emphasizes mathematically based models
• Computer science, management science,
operations research
• Behavioral approach
• Behavioral issues (strategic business
integration, implementation, etc.)
• Psychology, economics, sociology

1.38 © 2007 by Prentice Hall

• Management Information Science
• Combines computer science, management science,
operations research and practical orientation with
behavioral issues

• Four main actors

• Suppliers of hardware and software
• Business firms
• Managers and employees
• Firm’s environment (legal, social, cultural context)
Sociotechnical view
• Optimal organizational performance
achieved by jointly optimizing both
social and technical systems used in
production

• Helps avoid purely technological

approach
 Perspectives on Information Systems

A Sociotechnical Perspective on Information Systems

In a sociotechnical perspective, the performance of a system is optimized when

both the technology and the organization mutually adjust to one another until a
satisfactory fit is obtained.
Figure 2-10
 Session 03

Information Systems,
Organizations, and
Strategy
 LEARNING OBJECTIVES

• Identify and describe important features of

organizations that managers need to know about in
order to build and use information systems
successfully.
• Evaluate the impact of information systems on
organizations.
• Demonstrate how Porter’s competitive forces model
and the value chain model help businesses use
information systems for competitive advantage.
 LEARNING OBJECTIVES
(Continued)

• Demonstrate how information systems help

businesses use synergies, core competencies, and
network-based strategies to achieve competitive
advantage.

• Assess the challenges posed by strategic information

systems and management solutions.
 Will the New US Airways Be Able to Fly?
• Problem: Intense competition and environmental changes.
• Solutions: Revising business processes and integrating them
with information systems and culture could increase sales and
reduce costs.
• Selecting appropriate systems and technology eliminates
redundant systems.
• Demonstrates IT’s role in supporting improved business
processes.
• Illustrates the benefits of integrating information systems in
the face of interdependence of environment, culture, process,
strategy, and systems.
 Organizations and Information Systems

• Information technology and organizations

influence one another

• Complex relationship influenced by organization’s

structure, business processes, politics, culture,
environment, and management decisions
 Organizations and Information Systems
The Two-Way Relationship Between Organizations
and Information Technology

This complex two-way relationship is

mediated by many factors, not the least
of which are the decisions made—or
not made—by managers. Other factors
Figure 3-1 mediating the relationship include the
organizational culture, structure,
politics, business processes, and
environment.
 Organizations and Information Systems

• What is an organization?
• Technical definition:
• Stable, formal social structure that takes resources
from environment and processes to produce outputs.
• A formal legal entity with internal rules and
procedures, as well as a social structure
• Behavioral definition:
• A collection of rights, privileges, obligations, and
responsibilities that is delicately balanced over a
period of time through conflict and conflict resolution
 Organizations and Information Systems

The Technical Microeconomic

Definition of the Organization

Figure 3-2

In the microeconomic definition of organizations, capital and labor (the primary production factors provided by the environment) are
transformed by the firm through the production process into products and services (outputs to the environment). The products and services
are consumed by the environment, which supplies additional capital and labor as inputs in the feedback loop.
 Organizations and Information Systems
The Behavioral View of Organizations

Figure 3-3
The behavioral view of organizations emphasizes group
relationships, values, and structures.
 Organizations and Information Systems

• Features of organizations
• All modern organizations share some
characteristics, such as:
• Use of hierarchical structure
• Accountability, authority in system of impartial
decision-making
• Adherence to principle of efficiency
• Other features include: Routines and business
processes and organizational politics, culture,
environments and structures
 Organizations and Information Systems

• Routines and business processes

• Routines (standard operating procedures)
• Precise rules, procedures, and practices
developed to cope with virtually all expected
situations
• Business processes: Collections of routines
• Business firm: Collection of business
processes
 Organizations and Information Systems
Routines, Business Processes, and Firms

All organizations are composed of

individual routines and behaviors, a
collection of which make up a
business process. A collection of
business processes make up the
business firm. New information
system applications require that
individual routines and business
processes change to achieve high
levels of organizational performance.

Figure 3-4
 Organizations and Information Systems

• Organizational politics
• Divergent viewpoints lead to political
struggle, competition, and conflict
• Political resistance greatly hampers
organizational change
 Organizations and Information Systems

• Organizational culture:
• Encompasses set of assumptions that define
goal and product
• What products the organization should produce
• How and where it should be produced
• For whom the products should be produced
• May be powerful unifying force as well as
restraint on change
 Organizations and Information Systems

• Organizational environments:
• Organizations and environments have a reciprocal
relationship
• Organizations are open to, and dependent on, the
social and physical environment
• Organizations can influence their environments
• Environments generally change faster than
organizations
• Information systems can be instrument of
environmental scanning, act as a lens
 Organizations and Information Systems
Environments and Organizations
Have a Reciprocal Relationship

Environments shape what

organizations can do, but
organizations can
influence their
environments
and decide to change
environments altogether.
Information technology
plays a critical role in
helping
organizations perceive
environmental change
and in helping
organizations act on their
environment.

Figure 3-5
 Organizations and Information Systems

• Organizational structure
• Five basic kinds of structure
• Entrepreneurial: Small start-up business
• Machine bureaucracy: Midsize manufacturing firm
• Divisionalized bureaucracy: Fortune 500 firms
• Professional bureaucracy: Law firms, school
systems, hospitals
• Adhocracy: Consulting firms
 Organizations and Information Systems

• Other Organizational Features

• Goals
• Constituencies
• Leadership styles
• Tasks
• Surrounding environments
How Information Systems Impact Organizations
and Business Firms
• Economic impacts
• IT changes relative costs of capital and the costs of
information
• Information systems technology is a factor of
production, like capital and labor
• IT affects the cost and quality of information and
changes economics of information
• Information technology helps firms contract in size
because it can reduce transaction costs (the cost of
participating in markets). Outsourcing expands
 How Information Systems Impact
Organizations and Business Firms
• Transaction cost theory
• Firms seek to economize on cost of
participating in market (transaction costs)
• IT lowers market transaction costs for firm,
making it worthwhile for firms to transact with
other firms rather than grow the number of
employees
How Information Systems Impact Organizations
and Business Firms
The Transaction Cost Theory of the Impact of
Information Technology on the Organization

Firms traditionally grew in size

to reduce transaction costs. IT
potentially reduces the costs for
a given size, shifting the
transaction cost curve inward,
opening up the possibility of
revenue growth without
increasing size, or even revenue
growth accompanied by
shrinking size.

Figure 3-6
 How Information Systems Impact
Organizations and Business Firms
• Agency theory:
• Firm is nexus of contracts among self-
interested parties requiring supervision
• Firms experience agency costs (the cost of
managing and supervising) which rise as firm
grows
• IT can reduce agency costs, making it possible
for firms to grow without adding to the costs of
supervising, and without adding employees
 How Information Systems Impact Organizations
and Business Firms
The Agency Cost Theory of the Impact of
Information Technology on the Organization

As firms grow in size and

complexity, traditionally they
experience rising agency costs.
IT shifts the agency cost curve
down and to the right, enabling
Figure 3-7
firms to increase size while
lowering agency costs.
 How Information Systems Impact Organizations and
Business Firms

• Organizational and behavioral impacts

• IT flattens organizations
• Decision-making pushed to lower levels
• Fewer managers needed (IT enables faster decision-
making and increases span of control)
• Postindustrial organizations
• Organizations flatten because in postindustrial
societies, authority increasingly relies on knowledge
and competence rather than formal positions
 How Information Systems Impact Organizations and
Business Firms
Flattening Organizations

Information systems can

reduce the number of levels in
an organization by providing
managers with information to
supervise larger numbers of
workers and by giving lower-
level employees more decision-
making authority.
Figure 3-8
How Information Systems Impact Organizations
and Business Firms
• Organizational resistance to change
• Information systems become bound up in
organizational politics because they influence access to
a key resource -- information
• Information systems potentially change an
organization’s structure, culture, politics, and work
• Most common reason for failure of large projects is due
to organizational & political resistance to change
 How Information Systems Impact Organizations and
Business Firms
Organizational Resistance and the Mutually Adjusting
Relationship Between Technology and the Organization

Implementing information
systems has consequences for
task arrangements, structures,
and people. According to this
model, to implement change,
all four components must be
changed simultaneously.
Figure 3-9
 How Information Systems Impact Organizations
and Business Firms
• The Internet and organizations
• The Internet increases the accessibility, storage, and
distribution of information and knowledge for
organizations
• The Internet can greatly lower transaction and agency
costs
• E.g. Large firm delivers internal manuals to
employees via intranet, saving millions of dollars in
distribution costs
 How Information Systems Impact Organizations
and Business Firms
• Central organizational factors to consider when
planning a new system:
• Environment
• Structure
• Hierarchy, specialization, routines, business processes
• Culture and politics
• Type of organization and style of leadership
• Main interest groups affected by system; attitudes of
end users
• Tasks, decisions, and business processes the system
will assist
 Using Information Systems to Achieve
Competitive Advantage
• Why do some firms become leaders within
their industry?
• Michael Porter’s competitive forces model
• Provides general view of firm, its competitors, and
environment
• Five competitive forces shape fate of firm
• Traditional competitors
• New market entrants
• Substitute products and services
• Customers
• Suppliers
Using Information Systems to Achieve
Competitive Advantage
Porter’s Competitive Forces Model

In Porter’s competitive forces model, the strategic position of the firm and its strategies are determined not only by
competition with its traditional direct competitors but also by four forces in the industry’s environment: new market
entrants, substitute products, customers, and suppliers.

Figure 3-10
 Using Information Systems to Achieve
Competitive Advantage
• Traditional competitors
• All firms share market space with competitors who
are continuously devising new products, services,
efficiencies, switching costs
• New market entrants
• Some industries have high barriers to entry, e.g.
computer chip business
• New companies have new equipment, younger
workers, but little brand recognition
 Using Information Systems to Achieve
Competitive Advantage
• Substitute products and services
• Substitutes customers might use if your prices
become too high, e.g. iTunes substitutes for CDs
• Customers
• Can customers easily switch to competitor’s
products? Can they force businesses to compete on
price alone in transparent marketplace?
• Suppliers
• Market power of suppliers when firm cannot raise
prices as fast as suppliers
 Using Information Systems to Achieve
Competitive Advantage
• Four generic strategies for dealing with
competitive forces, enabled by using IT
• Low-cost leadership
• Product differentiation
• Focus on market niche
• Strengthen customer and supplier intimacy
 Using Information Systems to Achieve
Competitive Advantage

• Low-cost leadership
• produce products and services at a lower price than
competitors while enhancing quality and level of
service.
• E.g. Wal-Mart, Dell
• Product differentiation
• Enable new products or services, greatly change
customer convenience and experience
• E.g. Google, Land’s End, Apple iPhone
 Using Information Systems to Achieve
Competitive Advantage
• Focus on market niche
• Use information systems to enable a focused
strategy on a single market niche; specialize.
• E.g. Hilton Hotels
• Strengthen customer and supplier intimacy’
• Use information systems to develop strong ties and
loyalty with customers and suppliers; increase
switching costs
• E.g. Chrysler, Amazon
 Using Information Systems to Achieve
Competitive Advantage

• The Internet’s impact on competitive

advantage
• Transformation, destruction, threat to some industries
• E.g. travel agency, printed encyclopedia, newspaper
• Competitive forces still at work, but rivalry more intense
• Universal standards allow new rivals, entrants to market
• New opportunities for building brands and loyal customer
bases
 Using Information Systems to Achieve
Competitive Advantage
• Business value chain model
• Views firm as series of activities that add value to
products or services
• Highlights activities where competitive strategies can
best be applied
• Primary activities vs. secondary activities
• At each stage, determine how information systems
can improve operational efficiency and improve
customer and supplier intimacy
• Utilize benchmarking, industry best practices
 Using Information Systems to Achieve
Competitive Advantage
The Value Chain Model

This figure provides examples of

systems for both primary and
support activities of a firm and of
its value partners that can add a
margin of value to a firm’s
products or services. Figure 3-11
 Using Information Systems to Achieve
Competitive Advantage

• Value web:
• Collection of independent firms using highly synchronized IT to
coordinate value chains to produce product or service
collectively

• More customer driven, less linear operation than traditional

value chain
 Using Information Systems to Achieve
Competitive Advantage
The Value Web

Figure 3-12
The value web is a networked system that can synchronize the value chains of business
partners within an industry to respond rapidly to changes in supply and demand.
 Using Information Systems to Achieve
Competitive Advantage
• Information systems can improve overall
performance of business units by
promoting synergies and core
competencies
• Synergies
• When output of some units used as inputs to
others, or organizations pool markets and
expertise
• E.g. merger of Bank One and JPMorgan Chase
• Purchase of YouTube by Google
 Using Information Systems to Achieve
Competitive Advantage

• Core competencies
• Activity for which firm is world-class leader
• Relies on knowledge, experience, and sharing this
across business units
• E.g. Procter & Gamble’s intranet and directory of
subject matter experts
 Using Information Systems to Achieve
Competitive Advantage

• Network-based strategies
• Take advantage of firm’s abilities to network
with each other
• Include use of:
• Network economics
• Virtual company model
 Using Information Systems to Achieve
Competitive Advantage
• Network economics
• Traditional economics: Law of diminishing returns
• The more any given resource is applied to production, the
lower the marginal gain in output, until a point is reached
where the additional inputs produce no additional outputs
• Network economics:
• Marginal cost of adding new participant almost zero, with
much greater marginal gain
• Value of community grows with size
• Value of software grows as installed customer base grows
 Using Information Systems to Achieve
Competitive Advantage

• Virtual company strategy

• Virtual company uses networks to ally with other
companies to create and distribute products without
being limited by traditional organizational boundaries
or physical locations
• E.g. Li Fung manages production, shipment of
garments for major fashion companies, outsourcing
all work to over 7,500 suppliers
 Using Systems for Competitive
Advantage: Management Issues
• Sustaining competitive advantage
• Because competitors can retaliate and copy strategic systems,
competitive advantage is not always sustainable; systems may
become tools for survival
• Performing strategic systems analysis
• What is structure of industry?
• What are value chains for this firm?
• Managing strategic transitions
• Adopting strategic systems requires changes in business goals,
relationships with customers and suppliers, and business
processes
Session 04

Decision Making and Business

Intelligence I
Discuss how concepts of business
intelligence, data warehousing, data
mining and big data been applied in
organisations with examples in Sri
Lankan context.
What Is Business
Intelligence?
· Originally a term coined by the Gartner
Group in 1993, Business Intelligence (BI) is
a broad range of software and solutions
aimed at collection, consolidation, analysis
and providing access to information that
allows users across the business to make
better decisions.
· The technology includes software for
database query and analysis,
multidimensional databases or OLAP tools,
data warehousing and data mining, and
web enabled reporting capabilities.
· Applied across disciplines but especially
in Customer Relationship Management
(CRM), Supply Chain Management (SCM)
Enterprise Resource Planning
Provide better, faster and more accessible
reports
 Data warehouse
A data warehouse is a physically separate
database from a company’s operational
environments. Its purpose is to provide decision
support from its data repository that makes
operational data accessible in a form that is readily
acceptable for decision support and other user’s
applications. Data warehousing is the process of
taking internal data, cleansing it, and storing it in a
data warehouse where it can be accessed by various
decision makers in the decision-making process.
External information is also brought into the data
warehouse.
5-4
 Data Warehouse
Subject oriented
Scrubbed so that data from heterogeneous sources are
standardized
Nonvolatile
 Read only
Summarized
Not normalized; may be redundant
Data from both internal and external sources is present
Metadata included
 Data about data
 Business metadata
 Semantic metadata

5-5
 Architecture
May have one or more tiers
 Determined by warehouse, data acquisition
(back end), and client (front end)
 One tier, where all run on same platform, is rare
 Two tier usually combines DSS engine (client)
with warehouse
 More economical
 Three tier separates these functional parts

5-6
Data Warehouse Design
Dimensional modeling
 Retrieval based
 Implemented by star schema
 Central fact table
 Dimension tables

5-9
 star schema
A Star Schema is a technique used to define the
structure of a data warehouse. It consists of two
components, dimension tables (which define the
criteria by which data will be retrieved ;e.g., location,
product, time and fact tables (the data that is of
interest to the organization). Facts can be highly
summarized or detail data

5-10
 The data contained in a data warehouse has been
cleansed and thus has little redundancy and a higher
level of integrity. This gives a higher level of
confidence in the decisions made based on the data
contained in the warehouse. Benefits include a
common storage format, quick access to data for
strategic use, and accurate data.

5-12
Data Mining
 Data mining
Process of semi-automatically analyzing
large databases to find patterns that are:
 valid: hold on new data with some certainity
 novel: non-obvious to the system

 useful: should be possible to act on the item

 understandable: humans should be able to

interpret the pattern
Also known as Knowledge Discovery in
Databases (KDD)
 Applications
Banking: loan/credit card approval
 predict good customers based on old customers
Customer relationship management:
 identify those who are likely to leave for a competitor.
Targeted marketing:
 identify likely responders to promotions
Fraud detection: telecommunications, financial
transactions
 from an online stream of event identify fraudulent events
Manufacturing and production:
 automatically adjust knobs when process parameter changes
Applications (continued)
Medicine: disease outcome, effectiveness of
treatments
 analyze patient disease history: find relationship
between diseases
Molecular/Pharmaceutical: identify new drugs
Scientific data analysis:
 identify new galaxies by searching for sub clusters
Web site/store design and promotion:
 find affinity of visitor to pages and modify layout
 The KDD process
Problem fomulation
Data collection
 subset data: sampling might hurt if highly skewed data
 feature selection: principal component analysis, heuristic
search
Pre-processing: cleaning
 name/address cleaning, different meanings (annual, yearly),
duplicate removal, supplying missing values
Transformation:
 map complex objects e.g. time series data to features e.g.
frequency
Choosing mining task and mining method:
Result evaluation and Visualization:
Relationship with other fields
Overlaps with machine learning, statistics,
artificial intelligence, databases, visualization
but more stress on
 scalability of number of features and instances

 stress on algorithms and architectures whereas

foundations of methods and formulations provided
by statistics and machine learning.

 automation for handling large, heterogeneous data

Data Mining in Practice
 Application Areas
Industry Application
Finance Credit Card Analysis
Insurance Claims, Fraud Analysis
Telecommunication Call record analysis
Transport Logistics management
Consumer goods promotion analysis
Data Service providers Value added data
Utilities Power usage analysis
 Why Now?
Data is being produced
Data is being warehoused
The computing power is available
The computing power is affordable
The competitive pressures are strong
Commercial products are available
 Data Mining works with
Warehouse Data
Data Warehousing provides the
Enterprise with a memory

Data Mining provides the

Enterprise with intelligence
 Usage scenarios
Data warehouse mining:
 assimilate data from operational sources
 mine static data
Mining log data
Continuous mining: example in process
control
Stages in mining:
 data selection  pre-processing: cleaning
 transformation  mining  result
evaluation  visualization
 Mining market
Around 20 to 30 mining tool vendors
Major tool players:
 Clementine,
 IBM’s Intelligent Miner,
 SGI’s MineSet,
 SAS’s Enterprise Miner.
All pretty much the same set of tools
Many embedded products:
 fraud detection:
 electronic commerce applications,
 health care,
 customer relationship management: Epiphany
Vertical integration: Mining on
the web
Web log analysis for site design:
 what are popular pages,

 what links are hard to find.

Electronic stores sales enhancements:

 recommendations, advertisement:

 Collaborative filtering: Net perception, Wisewire

 Inventory control: what was a shopper

looking for and could not find..
OLAP Mining integration
OLAP (On Line Analytical Processing)
 Fast interactive exploration of multidim.
aggregates.
 Heavy reliance on manual operations for
analysis:
 Tedious and error-prone on large
multidimensional data
Ideal platform for vertical integration of mining
but needs to be interactive instead of batch.
 State of art in mining OLAP
integration
Decision trees [Information discovery, Cognos]
 find factors influencing high profits
Clustering [Pilot software]
 segment customers to define hierarchy on that
dimension
Time series analysis: [Seagate’s Holos]
 Query for various shapes along time: eg. spikes, outliers
Multi-level Associations [Han et al.]
 find association between members of dimensions
Sarawagi [VLDB2000]
 Data Mining in Use
The US Government uses Data Mining to track
fraud

A Supermarket becomes an information broker

Basketball teams use it to track game strategy

Target Marketing

Holding on to Good Customers

Weeding out Bad Customers

 Data Science,
Engineering, and Data-
Driven Decision Making
In the 1990s, automated decision-making changed the banking and
customer credit industries dramatically. In the 1990s, banks and
telecommunications companies also implemented massive-scale
systems for managing data-driven fraud control decisions.

As retail system were increasingly computerized, merchandising

decisions were automated. Famous example include Harrah’s
casinos’ reward programs and the automated recommendations of
Amazon and Netflix. Currently we are seeing a revolution in
advertising, due in large part to a huge increase in the amount of
time consumers are spending online, and the ability online to make
(literally) split-second advertising decision.
29
Data Processing and “Big Data”
It is important to digress here to address another point.
There is a lot to data processing that is not data science—
despite the impression one might get from the media. Data
engineering and processing are critical to support data
science, but they are more general.
For example, these days many data processing skills,
systems, and technologies often are mistakenly cast as data
science. To understand data science and data-driven
businesses it is important to understand the differences.
Data science needs access to data and it often benefits from
sophisticated data engineering that data processing
technologies may facilitate, but these technologies are not
data science technologies per se. 30
 Data Processing and
“Big Data”
Data processing technologies are very important for many data-oriented
business tasks that do not involve extracting knowledge or data-driven
decision-making, such as efficient transaction processing, modern web
system processing, and online advertising campaign management.

“Big data” technologies (such as Hadoop, HBase, and MongoDB) have

received considerable media attention. Big data essentially means datasets
that are too large for traditional data processing systems, and therefore
require new processing technologies.

As with the traditional technologies, big data technologies are used for
many tasks, including data engineering. Occasionally, big data technologies
are actually used for implementing data mining techniques. 31
 Data Processing and
“Big Data”
However, much more often the well-known big data technologies are
used for data processing in support of the data mining techniques and
other data science activities.

A study, conducted by economist Prasanna Tambe of NYU’s Stern

School, examined the extent to which big data technologies seem to
help firms (Tambe, 2012). He finds that, after controlling for various
possible confounding factors, using big data technologies is associated
with significant additional productivity growth.
32
 Data Processing and
“Big Data”
Specifically, one standard deviation higher utilization of big data

technologies is associated with 1%–3% higher productivity than

the average firm; one standard deviation lower in terms of big data

utilization is associated with 1%–3% lower productivity. This leads

to potentially very large productivity differences between the firms

at the extremes.
33
From Big Data 1.0 to Big Data 2.0
One way to think about the state of big data technologies is to
draw an analogy with the business adoption of Internet
technologies.

In Web 1.0, businesses busied themselves with getting the basic

internet technologies in place, so that they could establish a web
presence, build electronic commerce capability, and improve the
efficiency of their operations.

Once firms had incorporated Web 1.0 technologies thoroughly

(and in the process had driven down prices of the underlying
technology) they started to look further. They began to ask what
the Web could do for them, and how it could improve things they’d
always done—and we entered the era of Web 2.0, where new
systems and companies began taking advantage of the
interactive nature of the Web. 34
 From Big Data 1.0 to
Big Data 2.0
We should expect a Big Data 2.0 phase to follow Big Data 1.0.

Once firms have become capable of processing massive data in a

flexible fashion, they should begin asking: “What can I now do that I

couldn’t do before, or do better than I could do before?” This is likely

to be the golden era of data science.

35
 Data and Data Science
Capability as a Strategic Asset
The prior sections suggest one of the fundamental principles of
data science: data, and the capability to extract useful
knowledge from data, should be regarded as key strategic
assets.
Too many businesses regard data analytics as pertaining mainly
to realizing value from some existing data, and often without
careful regard to whether the business has the appropriate
analytical talent.
The best data science team can yield little value without the
appropriate data; the right data often cannot substantially
improve decisions without suitable data science talent. As with
all assets, it is often necessary to make investments.
36
Session 05: Foundations of
Business Intelligence:
Databases and Information
Management
 Management Information Systems
Databases and Information Management

LEARNING OBJECTIVES

• Describe basic file organization concepts and the

problems of managing data resources in a traditional
file environment.

• Describe the principles of a database management

system and the features of a relational database.

• Apply important database design principles.

 Management Information Systems
Databases and Information Management

LEARNING OBJECTIVES (cont’d)

• Evaluate tools and technologies for providing

information from databases to improve business
performance and decision making.

• Assess the role of information policy, data

administration, and data quality assurance in the
management of organizational data resources.
 Management Information Systems
Business Intelligence: Databases and Information Management

• Problem: Gaining knowledge of customers and making

effective use of fragmented customer data.
• Solutions: Use relational database technology to
increase revenue and productivity.
• Data access rules and a comprehensive customer
database consolidate customer data.
• Demonstrates IT’s role in creating customer intimacy and
stabilizing infrastructure.
• Illustrates digital technology’s role in standardizing how
data from disparate sources are stored, organized, and
managed.
 Management Information Systems
Business Intelligence: Databases and Information Management
Organizing Data in a Traditional File Environment

• File organization concepts

• Computer system uses hierarchies
• Field: Group of characters
• Record: Group of related fields
• File: Group of records of same type
• Database: Group of related files
• Record: Describes an entity
• Entity: Person, place, thing on which we store
information
• Attribute: Each characteristic, or quality, describing entity
• E.g. Attributes Date or Grade belong to entity COURSE
 Management Information Systems
Databases and Information Management
Organizing Data in a Traditional File Environment

The Data Hierarchy

A computer system
organizes data in a
hierarchy that starts with the
bit, which represents either
a 0 or a 1. Bits can be
grouped to form a byte to
represent one character,
number, or symbol. Bytes
can be grouped to form a
field, and related fields can
be grouped to form a record.
Related records can be
collected to form a file, and
related files can be
organized into a database.
Figure 5-1
 Management Information Systems
Databases and Information Management
Organizing Data in a Traditional File Environment

• Problems with the traditional file processing (files

maintained separately by different departments)
• Data redundancy and inconsistency
• Data redundancy: Presence of duplicate data in multiple files
• Data inconsistency: Same attribute has different values
• Program-data dependence:
• When changes in program requires changes to data accessed by
program
• Lack of flexibility
• Poor security
• Lack of data sharing and availability
 Management Information Systems
Databases and Information Management
Organizing Data in a Traditional File Environment
Traditional File Processing

The use of a traditional approach to file processing encourages each functional area in a corporation to
develop specialized applications and files. Each application requires a unique data file that is likely to be a
subset of the master file. These subsets of the master file lead to data redundancy and inconsistency,
processing inflexibility, and wasted storage resources.

Figure 5-2
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

• Database:
• Collection of data organized to serve many applications by
centralizing data and controlling redundant data
• Database management system:
• Interfaces between application programs and physical data files
• Separates logical and physical views of data
• Solves problems of traditional file environment
• Controls redundancy
• Eliminated inconsistency
• Uncouples programs and data
• Enables central management and security
 The Database Approach to Data Management

Human Resources Database with Multiple Views

A single human resources database provides many different views of data, depending on the information
requirements of the user. Illustrated here are two possible views, one of interest to a benefits specialist and
one of interest to a member of the company’s payroll department.

Figure 5-3
 The Database Approach to Data Management

• Relational DBMS
• Represent data as two-dimensional tables called relations or files
• Each table contains data on entity and attributes
• Table: Grid of columns and rows
• Rows (tuples): Records for different entities
• Fields (columns): Represents attribute for entity
• Key field: Field used to uniquely identify each record
• Primary key: Field in table used for key fields
• Foreign key: Primary key used in second table as look-up field to
identify records from original table
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

Relational Database Tables

A relational database organizes data in the form of two-dimensional tables. Illustrated here are tables for
the entities SUPPLIER and PART showing how they represent each entity and its attributes.
Supplier_Number is a primary key for the SUPPLIER table and a foreign key for the PART table.

Figure 5-4
Management Information Systems
Databases and Information Management
The Database Approach to Data Management
Relational Database Tables (cont.)

Figure 5-4B
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

• Operations of a Relational DBMS: Three basic

operations used to develop useful sets of data
• SELECT: Creates subset of data of all records that
meet stated criteria
• JOIN: Combines relational tables to provide user with
more information than available in individual tables
• PROJECT: Creates subset of columns in table,
creating tables with only the information specified
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

The Three Basic Operations of a Relational DBMS

The select, project, and join operations enable data from two different tables to be combined and only
selected attributes to be displayed.
Figure 7-5
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

• Hierarchical and Network DBMS: Older

systems
• Hierarchical DBMS: Models one-to-many
relationships
• Network DBMS: Models many-to-many
relationships
• Both less flexible than relational DBMS and do not
support ad hoc, natural language
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

• Object-Oriented DBMS (OODBMS)

• Stores data and procedures as objects
• Capable of managing graphics, multimedia, Java applets
• Relatively slow compared with relational DBMS for processing large numbers of transactions
• Hybrid object-relational DBMS: Provide capabilities of both OODBMS and relational DBMS
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

• Capabilities of Database Management Systems

• Data definition capability: Specifies structure of database
content, used to create tables and define characteristics of fields
• Data dictionary: Automated or manual file storing definitions of
data elements and their characteristics
• Data manipulation language: Used to add, change, delete,
retrieve data from database
• Structured Query Language (SQL)
• Microsoft Access user tools for generation SQL
• Also: Many DBMS have report generation capabilities for
creating polished reports (Crystal Reports)
 The Database Approach to Data Management

Sample Data Dictionary Report

Figure 5-6
The sample data dictionary
report for a human
resources database
provides helpful
information, such as the size
of the data element, which
programs and reports use it,
and which group in the
organization
is the owner responsible for
maintaining it.
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

Example of an SQL Query

Illustrated here are the SQL statements for a query to select suppliers for parts 137 or 150. They produce a
list with the same results as Figure 6-5.

Figure 5-7
 The Database Approach to Data Management

An Access Query

Illustrated here is how the query in Figure 6-7 would be constructed using query-building tools in the
Access Query Design View. It shows the tables, fields, and selection criteria used for the query.

Figure 5-8
 Management Information Systems
Databases and Information Management
The Database Approach to Data Management

• Designing Databases
• Conceptual (logical) design: abstract model from business
perspective
• Physical design: How database is arranged on direct-access
storage devices
• Design process identifies:
• Relationships among data elements, redundant database
elements
• Most efficient way to group data elements to meet business
requirements, needs of application programs
• Normalization
• Streamlining complex groupings of data to minimize redundant
data elements and awkward many-to-many relationships
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

An Unnormalized Relation for Order

An unnormalized relation contains repeating groups. For example, there can be many parts and suppliers
for each order. There is only a one-to-one correspondence between Order_Number and Order_Date.

Figure 5-9
 Management Information Systems
Databases and Information Management
The Database Approach to Data Management

Normalized Tables Created from Order

After normalization, the original relation ORDER has been broken down into four smaller relations. The
relation ORDER is left with only two attributes and the relation LINE_ITEM has a combined, or
concatenated, key consisting of Order_Number and Part_Number.

Figure 7-10
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

• Entity-relationship diagram
• Used by database designers to document the data model
• Illustrates relationships between entities
• Distributing databases: Storing database in more than
one place
• Reduced vulnerability, increased responsiveness
• May depart from standard definitions, pose security problems
• Partitioned: Separate locations store different parts of database
• Replicated: Central database duplicated in entirety at different
locations
 Management Information Systems
Databases and Information Management

The Database Approach to Data Management

An Entity-Relationship Diagram

This diagram shows the relationships between the entities ORDER, LINE_ITEM, PART, and SUPPLIER that
might be used to model the database in Figure 6-10.

Figure 5-11
 Management Information Systems
Databases and Information Management
The Database Approach to Data Management
Distributed Databases

There are alternative ways of distributing a database. The central database can be partitioned (a) so that each remote
processor has the necessary data to serve its own local needs. The central database also can be replicated (b) at all remote
locations.
Figure 5-12
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

• For very large databases and systems, special

capabilities and tools are required for analyzing
large quantities of data and for accessing data
from multiple systems
• Data warehousing
• Data mining
• Tools for accessing internal databases through the Web
 Management Information Systems
Databases and Information Management
Using Databases to Improve Business Performance and Decision Making

• Database warehouses
• Data warehouse:
• Stores current and historical data from many core operational
transaction systems
• Consolidates and standardizes information for use across enterprise,
but data cannot be altered
• Data warehouse system will provide query, analysis, and reporting
tools

• Data marts:
• Subset of data warehouse with summarized or highly focused portion
of firm’s data for use by specific population of users
• Typically focuses on single subject or line of business
 Management Information Systems
Databases and Information Management
Using Databases to Improve Business Performance and Decision Making

Components of a Data Warehouse

The data warehouse extracts current and historical data from multiple operational systems inside the organization. These data are combined
with data from external sources and reorganized into a central database designed for management reporting and analysis. The information
directory provides users with information about the data available in the warehouse.

Figure 5-13
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

• Business Intelligence:
• Tools for consolidating, analyzing, and providing access
to vast amounts of data to help users make better
business decisions
• E.g. Harrah’s Entertainment analyzes customers to
develop gambling profiles and identify most profitable
customers
• Principle tools include:
• Software for database query and reporting
• Online analytical processing (OLAP)
• Data mining
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

Business Intelligence

A series of analytical tools

works with data stored in
databases to find patterns
and insights for helping
managers and employees
make better decisions to
improve organizational
performance.

Figure 5-14
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

• Online analytical processing (OLAP)

• Supports multidimensional data analysis
• Enables viewing data using multiple dimensions
• Each aspect of information (product, pricing, cost,
region, time period) is different dimension
• E.g. how many washers sold in East in June
• OLAP enables rapid, online answers to ad hoc queries
 Management Information Systems
Databases and Information Management
Using Databases to Improve Business Performance and Decision Making

Multidimensional Data Model

The view that is showing is

product versus region. If
you rotate the cube 90
degrees, the face that will
show is product versus
actual and projected sales. If
you rotate the cube 90
degrees again, you will see
region versus actual and
projected sales. Other views
are possible.

Figure 5-15
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

• Data mining:
• More discovery driven than OLAP
• Finds hidden patterns, relationships in large databases
• Infers rules to predict future behavior
• The patterns and rules are used to guide decision making
and forecast the effect of those decisions
• Popularly used to provide detailed analyses of patterns in
customer data for one-to-one marketing campaigns or to
identify profitable customers.
• Less well known: used to trace calls from specific
neighborhoods that use stolen cell phones and phone
accounts
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

• Types of information obtainable from data mining

• Associations: Occurrences linked to single event
• Sequences: Events linked over time
• Classification: Recognizes patterns that describe group to
which item belongs
• Clustering: Similar to classification when no groups have
been defined; finds groupings within data
• Forecasting: Uses series of existing values to forecast what
other values will be
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

• Predictive analysis
• Uses data mining techniques, historical data, and
assumptions about future conditions to predict outcomes of
events
• E.g. Probability a customer will respond to an offer or
purchase a specific product.
• Data mining seen as challenge to individual
privacy
• Used to combine information from many diverse sources to
create detailed “data image” about each of us—income,
driving habits, hobbies, families, and political interests
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

• Databases and the Web

• Many companies use Web to make some internal
databases available to customers or partners
• Typical configuration includes:
• Web server
• Application server/middleware/CGI scripts
• Database server (hosting DBM)
• Advantages of using Web for database access:
• Ease of use of browser software
• Web interface requires few or no changes to database
• Inexpensive to add Web interface to system
 Management Information Systems
Databases and Information Management

Using Databases to Improve Business Performance and Decision Making

Linking Internal Databases to the Web

Users access an organization’s internal database through the Web using their desktop PCs and Web
browser software.

Figure 5-16
 Management Information Systems
Databases and Information Management
Using Databases to Improve Business Performance and Decision Making

The Internet Movie

Database Web site is
linked to a massive
database that
includes summaries,
cast information, and
actor biographies for
almost every film
ever released.
 Management Information Systems
Databases and Information Management

Managing Data Resources

• Managing data resources:

• Establishing an information policy
• Information policy: Specifies firm’s rules, procedures, roles for
sharing, standardizing data
• Data administration: Responsible for specific policies and
procedures; data governance
• Database administration: Database design and management
group responsible for defining, organizing, implementing,
maintaining database

• Ensuring data quality

 Management Information Systems
Databases and Information Management

Managing Data Resources

• Ensuring data quality

• More than 25% critical data in Fortune 1000 company
databases is inaccurate or incomplete

• Before new database in place, need to identify and

correct faulty data and establish better routines for
editing data once database in operation

• Most data quality problems stem from faulty input0

 Management Information Systems
Databases and Information Management
Managing Data Resources

• Data quality audit:

• Structured survey of the accuracy and level of
completeness of the data in an information system

• Data cleansing:
• Detecting, and correcting data that are incorrect,
incomplete, improperly formatted, or redundant.
• Enforces consistency among different sets of data from
separate information systems
 Session 06
E-Commerce: Digital
Markets, Digital Goods
 LEARNING OBJECTIVES

• Identify the unique features of e-commerce, digital

markets, and digital goods.
• Describe how Internet technology has changed
business models.
• Identify the various types of e-commerce and explain
how e-commerce has changed consumer retailing and
business-to-business transactions.
• Evaluate the role of m-commerce in business, and
describe the most important m-commerce applications.
• Identify the principal payment systems for electronic
commerce.
 Nexus Games: E-Commerce Goes Social

• Problem: Building a business model that serves the

emerging market for social networking sites.
• Solutions: Sell games that are social experiences. Online
users can access full games for free but must pay for any
“virtual items” to enhance game play
– Prepaid cards used to purchase Nexon game items are second best-
selling entertainment gift card at Target

• Nexon games all feature Forums where users can

socialize, share tips
• Demonstrates digital technology’s role in generating new
business models
 Electronic Commerce and the Internet

• E-commerce
• Use of the Internet and Web to transact business
• Digitally enabled transactions
• History of e-commerce
• Began in 1995 and grew exponentially; still growing at an
annual rate of 16 percent
• Rapid growth led to market bubble
• While many companies failed, many survived with soaring
revenues
• E-commerce today the fastest growing form of retail trade in
U.S., Europe, Asia
 Electronic Commerce and the Internet

The Growth of E-Commerce

Retail e-commerce revenues have grown

exponentially since 1995 and have only recently
“slowed” to a very rapid 16 percent annual
increase, which is projected to remain the same
Figure 9-1
until 2022.
 Electronic Commerce and the Internet

• Eight unique features of e-commerce technology

1. Ubiquity
• Internet/Web technology available everywhere: work, home,
etc., and anytime
2. Global reach
• The technology reaches across national boundaries, around
Earth
3. Universal standards
• One set of technology standards: Internet standards
4. Richness
• Supports video, audio, and text messages
 Electronic Commerce and the Internet

• Eight unique features (cont.)

5. Interactivity
• The technology works through interaction with the user
6. Information density
• Vast increases in information density—the total amount and
quality of information available to all market participants
7. Personalization/Customization:
• Technology permits modification of messages, goods
8. Social technology
• The technology promotes user content generation and social
networking
 Electronic Commerce and the Internet

• Key concepts in e-commerce

• Digital markets reduce
• Information asymmetry
• Search costs
• Transaction costs
• Menu costs
• Digital markets enable
• Price discrimination
• Dynamic pricing
• Disintermediation
 Electronic Commerce and the Internet

The Benefits of Disintermediation to the Consumer

The typical distribution channel has several intermediary layers, each of which adds to the final
cost of a product, such as a sweater. Removing layers lowers the final cost to the consumer.

Figure 9-2
 Electronic Commerce and the Internet

• Key concepts in e-commerce (cont.)

• Digital goods
• Goods that can be delivered over a digital network
• E.g., Music tracks, video, software, newspapers, books
• Cost of producing first unit almost entire cost of product:
marginal cost of producing 2nd unit is about zero
• Costs of delivery over the Internet very low
• Marketing costs remain the same; pricing highly variable
• Industries with digital goods are undergoing revolutionary
changes (publishers, record labels, etc.)
 Electronic Commerce and the Internet

• Internet business models

• Pure-play models
• Clicks-and-mortar models
• Social Network
• Online meeting place
• Social shopping sites
• Can provide ways for corporate clients to target customers through
banner ads and pop-up ads

• Online marketplace:
• Provides a digital environment where buyers and sellers can
meet, search for products, display products, and establish prices
for those products
 Electronic Commerce and the Internet

• Content provider
• Providing digital content, such as digital news, music, photos,
or video, over the Web
• Online syndicators: Aggregate content from multiple sources,
package for distribution, and resell to third-party Web sites
• Service provider
• Provides Web 2.0 applications such as photo sharing and
interactive maps, and services such as data storage
• Portal
• “Supersite” that provides comprehensive entry point for huge
array of resources and services on the Internet
 Electronic Commerce and the Internet

• Virtual storefront:
• Sells physical products directly to consumers or to
individual businesses
• Information broker:
• Provides product, pricing, and availability information to
individuals and businesses
• Transaction broker:
• Saves users money and time by processing online sales
transactions and generating a fee for each transaction
 Electronic Commerce

Types of Electronic Commerce

• Business-to-consumer (B2C)
• Business-to-business (B2B)
• Consumer-to-consumer (C2C)
• Mobile commerce (m-commerce)
 Electronic Commerce

• Interactive marketing and personalization

• Web sites are bountiful source of details about customer
behavior, preferences, buying patterns used to tailor
promotions, products, services, and pricing

• Clickstream tracking tools: Collect data on customer

activities at Web sites

• Used to create personalized Web pages

• Collaborative filtering: Compares customer data to other

customers to make product recommendations
 Electronic Commerce

Web Site Visitor Tracking

Figure 9-3
E-commerce Web sites
have tools to track a
shopper’s every step
through an online store.
Close examination of
customer behavior at a
Web site selling women’s
clothing shows what the
store might learn at each
step and what actions it
could take to increase
sales.
 Electronic Commerce

Web Site Personalization

Firms can create unique personalized Web

pages that display content or ads for products
or services of special interest to individual
users, improving the customer experience and
Figure 9-4
creating additional value.
 Electronic Commerce

• Blogs
• Personal web pages that contain series of chronological
entries by author and links to related Web pages
• Has increasing influence in politics, news
• Corporate blogs: New channels for reaching customers,
introducing new products and services
• Blog analysis by marketers
• Customer self-service
• Web sites and e-mail to answer customer questions or to
provide customers with product information
• Reduces need for human customer-support expert
 Electronic Commerce

• B2B e-commerce: New efficiencies and

relationships
• Electronic data interchange (EDI)
• Computer-to-computer exchange of standard transactions
such as invoices, purchase orders
• Major industries have EDI standards that define structure
and information fields of electronic documents for that
industry
• More companies increasingly moving away from private
networks to Internet for linking to other firms
• E.g., Procurement: Businesses can now use Internet to locate
most low-cost supplier, search online catalogs of supplier
products, negotiate with suppliers, place orders, etc.
 Electronic Commerce

Electronic Data Interchange (EDI)

Companies use EDI to automate transactions for B2B e-commerce and continuous inventory replenishment.
Suppliers can automatically send data about shipments to purchasing firms. The purchasing firms can use
EDI to provide production and inventory requirements and payment data to suppliers.

Figure 9-5
 Electronic Commerce

• Private industrial networks (private exchanges)

• Large firm using extranet to link to its suppliers, distributors
and other key business partners
• Owned by buyer
• Permits sharing of:
• Product design and development
• Marketing
• Production scheduling and inventory management
• Unstructured communication (graphics and e-mail)
 Electronic Commerce

A Private Industrial Network

Figure 9-6
A private industrial
network, also known
as a private exchange,
links a firm to its
suppliers, distributors,
and other key
business partners for
efficient supply chain
management and other
collaborative
commerce activities.
 Electronic Commerce

• Net marketplaces (e-hubs)

• Single market for many buyers and sellers
• Industry-owned or owned by independent intermediary
• Generate revenue from transaction fees, other services
• Use prices established through negotiation, auction, RFQs, or
fixed prices
• May focus on direct or indirect goods
• May support long-term contract purchasing or short-term spot
purchasing
• May serve vertical or horizontal marketplaces
 Electronic Commerce

A Net Marketplace

Figure 9-7
Net marketplaces
are online
marketplaces
where multiple
buyers can
purchase from
multiple sellers.
 Electronic Commerce

• Exchanges
• Independently owned third-party Net marketplaces
• Connect thousands of suppliers and buyers for spot
purchasing
• Typically provide vertical markets for direct goods for single
industry (food, electronics)
• Proliferated during early years of e-commerce; many have
failed
• Competitive bidding drove prices down and did not offer long-
term relationships with buyers or services to make lowering
prices worthwhile
 M-Commerce

• M-commerce services and applications

• Although m-commerce represents small fraction of total
e-commerce transactions, revenue has been steadily
growing
• Location-based services
• Banking and financial services
• Wireless Advertising
• Games and entertainment
 M-Commerce

Global M-commerce Revenue 2000-2012

Figure 9-8
M-commerce sales represent a small fraction of total e-commerce sales, but that percentage is steadily growing.
 M-Commerce

• Limitations in mobile’s access of Web information

• Data limitations
• Small display screens
• Wireless portals (mobile portals)
• Feature content and services optimized for mobile
devices to steer users to information they are most
likely to need
 Electronic Commerce Payment Systems

• Types of electronic payment systems

• Digital wallet
• Stores credit card and owner identification information and
enters the shopper’s name, credit card number, and
shipping information automatically when invoked to
complete a purchase
• Accumulated balance digital payment systems
• Used for micropayments ($10 or less)
• Accumulating debit balance that is paid periodically on credit
card or telephone bills
 Electronic Commerce Payment Systems

• Stored value payment systems

• Enable online payments based on value stored in online
digital account
• May be merchant platforms or peer-to-peer (PayPal)
• Digital checking
• Extend functionality of existing checking accounts to be used
for online payments
• Electronic billing presentment and payment
systems
• Paying monthly bills through electronic fund transfers or credit
cards
 Electronic Commerce Payment Systems

• Digital payments systems for m-commerce

• Three types of mobile payment systems in use
in Japan
• Stored value system charged by credit cards or bank
accounts
• Mobile debit cards
• Mobile credit cards
• In the U.S., the cell phone has not yet evolved
into a mobile payment system
 Session 07
Securing Information
Systems
 LEARNING OBJECTIVES

• Analyze why information systems need special protection

from destruction, error, and abuse.

• Assess the business value of security and control.

• Design an organizational framework for security and

control.

• Evaluate the most important tools and technologies for

safeguarding information resources.
 Phishing: A Costly New Sport for Internet Users

• Problem: Large number of vulnerable users of online

financial services, ease of creating bogus Web sites.
• Solutions: Deploy anti-phishing software and services and
a multilevel authentication system to identify threats and
reduce phishing attempts.
• Deploying new tools, technologies, and security
procedures, along with educating consumers, increases
reliability and customer confidence.
• Demonstrates IT’s role in combating cyber crime.
• Illustrates digital technology as part of a multilevel
solution as well as its limitations in overcoming
discouraged consumers.
 Systems Vulnerability and Abuse

• Security
• Policies, procedures, and technical measures used to prevent
unauthorized access, alteration, theft, or physical damage to
information systems

• Controls
• Methods, policies, and organizational procedures that ensure:
• Safety of organization’s assets
• Accuracy and reliability of accounting records
• Operational adherence to management standards
 Systems Vulnerability and Abuse

• Why systems are vulnerable

• Electronic data vulnerable to more types of threats
than manual data
• Networks
• Potential for unauthorized access, abuse, or fraud is not
limited to single location but can occur at any access point
in network
• Vulnerabilities exist at each layer and between layers
• E.g. user error, viruses, hackers, radiation, hardware or
software failure, theft
 Systems Vulnerability and Abuse

Contemporary Security Challenges and Vulnerabilities

The architecture of a Web-based application typically includes a Web client, a server, and corporate information
systems linked to databases. Each of these components presents security challenges and vulnerabilities. Floods,
fires, power failures, and other electrical problems can cause disruptions at any point in the network.

Figure 7-1
 Systems Vulnerability and Abuse

• Internet vulnerabilities
• Public network, so open to anyone
• Size of Internet means abuses may have
widespread impact
• Fixed IP addresses are fixed target for hackers
• VoIP phone service vulnerable to interception
• E-mail, instant messaging vulnerable to malicious
software, interception
 Systems Vulnerability and Abuse

• Wireless security challenges

• Many home networks and public hotspots open to anyone,

so not secure, communication unencrypted

• LANs using 802.11 standard can be easily penetrated

• Service set identifiers (SSIDs) identify access points in

Wi-Fi network and are broadcast multiple times

• WEP (Wired Equivalent Privacy): Initial Wi-Fi security

standard not very effective as access point and all users
share same password
 Systems Vulnerability and Abuse

Wi-Fi Security Challenges

Many Wi-Fi networks can

be penetrated easily by
intruders using sniffer
programs to obtain an
address to access the
resources of a network
without authorization.
Figure 7-2
 Systems Vulnerability and Abuse

• Malicious software (malware)

• Computer virus
• Rogue software program that attaches to other
programs or data files
• Payload may be relatively benign or highly destructive
• Worm:
• Independent program that copies itself over network

• Viruses and worms spread via:

• Downloaded software files
• E-mail attachments
• Infected e-mail messages or instant messages
• Infected disks or machines
 Systems Vulnerability and Abuse

• Trojan horse
• Software program that appears to be benign but then does
something other than expected
• Does not replicate but often is way for viruses or malicious
code to enter computer system
• Spyware
• Small programs installed surreptitiously on computers to
monitor user Web surfing activity and serve advertising
• Key loggers
• Record and transmit every keystroke on computer
• Steal serial numbers, passwords
 Systems Vulnerability and Abuse

• Hacker
• Individual who intends to gain unauthorized access to
computer system
• Cybervandalism
• Intentional disruption, defacement, or destruction of Web
site or corporate information system
• Spoofing
• Misrepresentation, e.g. by using fake e-mail addresses or
redirecting to fake Web site
• Sniffer:
• Eavesdropping program that monitors information traveling
over network
 Systems Vulnerability and Abuse

• Denial-of-service (DoS) attack:

• Flooding network or Web server with thousands of false
requests so as to crash or slow network

• Distributed denial-of-service (DDoS) attack

• Uses hundreds or thousands of computers to inundate and
overwhelm network from many launch points
• Botnet
• Collection of “zombie” PCs infected with malicious
software without their owners’ knowledge and used to
launch DDoS or perpetrate other crimes
 Systems Vulnerability and Abuse

Worldwide Damage from Digital Attacks

This chart shows estimates of the average annual worldwide damage from hacking, malware, and spam since 1999.
These data are based on figures from mi2G and the authors.

Figure 7-3
 Systems Vulnerability and Abuse

• Computer crime
• Computer as target of crime
• Accessing computer without authority
• Breaching confidentiality of protected computerized data
• Computer as instrument of crime
• Theft of trade secrets and unauthorized copying of software or
copyrighted intellectual property
• Using e-mail for threats or harassment
• Most economically damaging computer crimes
• DoS attacks and viruses
• Theft of service and disruption of computer systems
 Systems Vulnerability and Abuse

• Identity theft
• Using key pieces of personal information (social security
numbers, driver’s license numbers, or credit card numbers) to
impersonate someone else
• Phishing
• Setting up fake Web sites or sending e-mail messages that look
like those of legitimate businesses to ask users for confidential
personal data
• Evil twins
• Bogus wireless networks used to offer Internet connections,
then to capture passwords or credit card numbers
 Systems Vulnerability and Abuse

• Pharming
• Redirecting users to bogus Web page, even when individual
types correct address into browser
• Computer Fraud and Abuse Act (1986)
• Makes it illegal to access computer system without authorization
• Click fraud
• Fraudulently clicking on online ad without intention of learning
more about advertiser or making purchase
• Cyberterrorism and cyberwarfare:
• At least twenty countries are believed to be developing offensive
and defensive cyberwarfare capabilities
 Systems Vulnerability and Abuse

• Internal threats: Employees

• Company insiders pose serious security problems
• Access to inside information– like security codes and passwords
• May leave little trace
• User lack of knowledge: Single greatest cause of network
security breaches
• Compromised passwords
• Social engineering
• Errors introduced into software by:
• Faulty data entry, misuse of system
• Mistakes in programming, system design
 Systems Vulnerability and Abuse

• Software vulnerability
• Software errors are constant threat to information systems
• Cost U.S. economy $59.6 billion each year
• Can enable malware to slip past antivirus defenses
• Patches
• Created by software vendors to update and fix
vulnerabilities
• However, maintaining patches on all firm’s devices is time
consuming and evolves more slowly than malware
 Business Value of Security and Control

• Business value of security and control

• Protection of confidential corporate and personal information
• Value of information assets
• Security breach of large firm results in average loss of 2.1 %
of market value
• Legal liability
• Electronic Records Management (ERM)
• Policies, procedures, and tools for managing retention,
destruction, and storage of electronic records
 Business Value of Security and Control

• Legal and regulatory requirements for ERM

• HIPAA
• Outlines medical security and privacy rules
• Gramm-Leach-Bliley Act
• Requires financial institutions to ensure security and
confidentiality of customer data
• Sarbanes-Oxley Act
• Imposes responsibility on companies and their
management to safeguard accuracy and integrity of
financial information used internally and released externally
 Business Value of Security and Control

• Electronic evidence and computer

forensics
• Legal cases today increasingly rely on evidence
represented as digital data
• E-mail most common electronic evidence
• Courts impose severe financial, even criminal
penalties for improper destruction of electronic
documents, failure to produce records, and failure
to store records properly
 Business Value of Security and Control

• Computer forensics
• Scientific collection, examination,
authentication, preservation, and analysis of
data on computer storage media so that it can
be used as evidence in a court
• Awareness of computer forensics should be
incorporated into firm’s contingency planning
process
 Establishing a Framework for Security and Control

• ISO 17799
• International standards for security and control specifies best
practices in information systems security and control
• Risk Assessment
• Determines level of risk to firm if specific activity or process is not
properly controlled
• Value of information assets
• Points of vulnerability
• Likely frequency of problem
• Potential for damage
• Once risks are assessed, system builders concentrate on control
points with greatest vulnerability and potential for loss
 Establishing a Framework for Security and Control

Online Order Processing Risk Assessment

EXPOSURE PROBABILITY OF LOSS RANGE / EXPECTED

OCCURRENCE (AVERAGE) ANNUAL LOSS

Power failure 30 % $5,000 - $200,000 $30,750

($102.500)

Embezzlement 5% $1,000 - $50,000 $1,275

($25,500)

User error 98 % $200 - $40,000 $19,698

($20,100)

Table 7-3
 Technologies and Tools for Security

• Security policy
• Statements ranking information risks, identifying acceptable
security goals, and identifying mechanisms for achieving
these goals
• Chief Security Officer (CSO)
• Heads security group in larger firms
• Responsible for enforcing security policy
• Security group
• Educates and trains users
• Keeps management aware of security threats and
breakdowns
• Maintains tools chosen to implement security
 Technologies and Tools for Security

• Acceptable Use Policy (AUP)

• Defines acceptable uses of firm’s information resources and
computing equipment
• A good AUP defines acceptable actions for every user and
specifies consequences for noncompliance
• Authorization policies
• Determine level of access to information assets for different
levels of users
• Authorization management systems
• Allow each user access only to those portions of system that
person is permitted to enter, based on information
established by set of access rules
 Establishing a Framework for Security and Control

Security Profiles for a Personnel System

Figure 7-4
These two examples represent
two security profiles or data
security patterns that might be
found in a personnel system.
Depending on the security
profile, a user would have
certain restrictions on access
to various systems, locations,
or data in an organization.
 Technologies and Tools for Security

• Ensuring business continuity

• Fault-tolerant computer systems
• Ensure 100% availability
• Utilize redundant hardware, software, power supply components
• Critical for online transaction processing
• High availability computing
• Tries to minimize downtime
• Helps firms recover quickly from system crash
• Utilizes backup servers, distributed processing, high capacity
storage, disaster recovery and business continuity plans
• Recovery-oriented computing: Designing systems,
capabilities, tools that aid in quick recovery, correcting mistakes
 Technologies and Tools for Security

• Disaster recovery planning

• Restoring computing and communication services after
earthquake, flood, etc.
• Can be outsourced to disaster recovery firms
• Business continuity planning
• Restoring business operations after disaster
• Identifies critical business processes and determines how to
handle them if systems go down
• Business impact analysis
• Use to identify most critical systems and impact system outage has
on business
 Technologies and Tools for Security

• Auditing
• MIS audit: Examines firm’s overall security environment as
well as controls governing individual information systems
• Security audit: Reviews technologies, procedures,
documentation, training, and personnel
• Audits:
• List and rank all control weaknesses
• Estimate probability of occurrence
• Assess financial and organizational impact of each threat
 Establishing a Framework for Security and Control
Sample Auditor’s List of Control Weaknesses

Figure 7-5
This chart is a sample page
from a list of control
weaknesses that an auditor
might find in a loan system in a
local commercial bank. This
form helps auditors record and
evaluate control weaknesses
and shows the results of
discussing those weaknesses
with management, as well as
any corrective actions taken by
management.
 Technologies and Tools for Security

• Access control
• Policies and procedures used to prevent improper access to
systems by unauthorized insiders and outsiders
• Users must be authorized and authenticated
• Authentication:
• Typically established by password systems
• New authentication technologies:
• Tokens
• Smart cards
• Biometric authentication
 Technologies and Tools for Security

• Firewalls:
• Hardware and software controlling flow of incoming
and outgoing network traffic
• Prevents unauthorized access
• Screening technologies
• Packet filtering
• Stateful inspection
• Network address translation (NAT)
• Application proxy filtering
 Technologies and Tools for Security

A Corporate Firewall

The firewall is placed between the firm’s private network and the public Internet or another distrusted
network to protect against unauthorized traffic.

Figure 7-6
 Technologies and Tools for Security

• Intrusion detection systems:

• Full-time, real-time monitoring tools

• Placed at most vulnerable points of corporate networks

to detect and deter intruders

• Scanning software looks for patterns such as bad

passwords, removal of important files, and notifies
administrators
 Technologies and Tools for Security

• Antivirus software, antispyware software

• Antivirus software:
• Checks computer systems and drives for presence of
computer viruses
• To remain effective, antivirus software must be continually
updated
• Antispyware software tools:
• Many leading antivirus software vendors include
protection against spyware
• Standalone tools available (Ad-ware, Spybot)
 Technologies and Tools for Security

• Securing wireless networks

• WEP: Provides some measure of security if activated
• VPN technology: Can be used by corporations to help
security
• 802.11i specification: Tightens security for wireless LANs
• Longer encryption keys that are not static
• Central authentication server
• Mutual authentication

• Wireless security should be accompanied by appropriate

policies and procedures for using wireless devices
 Technologies and Tools for Security

• Encryption:
• Transforming message into cipher text, using encryption key
• Receiver must decrypt encoded message

• Two main methods for encrypting network traffic

• Secure Sockets Layer (SSL) /Transport Layer Security
(TLS)
• Establishes secure connection between two computers
• Secure HTTP (S-HTTP)
• Encrypts individual messages
 Technologies and Tools for Security

• Two methods of encryption:

• Symmetric key encryption
• Shared, single encryption key sent to receiver
• Public key encryption
• Two keys, one shared/public and one private
• Messages encrypted with recipient’s public key
but can only be decoded with recipient’s private
key
 Technologies and Tools for Security

Public Key Encryption

A public key encryption system can be viewed as a series of public and private keys that lock data when they are transmitted and
unlock the data when they are received. The sender locates the recipient’s public key in a directory and uses it to encrypt a message.
The message is sent in encrypted form over the Internet or a private network. When the encrypted message arrives, the recipient uses
his or her private key to decrypt the data and read the message.

Figure 7-7
 Technologies and Tools for Security

• Digital signature
• Encrypted message that only sender with private key can create
• Used to verify origin and contents of message
• Digital certificates
• Data files used to establish identity of users and electronic assets
for protection of online transactions
• Uses trusted third party, certificate authority (CA), to validate user’s
identity
• Public Key Infrastructure (PKI)
• Use of public key cryptography working with certificate authority
 Technologies and Tools for Security

Digital Certificates

Figure 7-8
Digital certificates help
establish the identity of
people or electronic
assets. They protect
online transactions by
providing secure,
encrypted, online
communication.
Describe Technologies and Tools for Security being used by
organisations
Building Systems
 LEARNING OBJECTIVES

• Demonstrate how building new systems produces

organizational change.

• Identify and describe the core activities in the

systems development process.

• Evaluate alternative methods for building information

systems.

• Compare alternative methodologies for modeling

systems.

• Identify and describe new approaches for system-

building in the digital firm era.
 A New Ordering System for Girl Scout Cookies

• Problem: Inefficient manual procedures, high error

rate.
• Solutions: Eliminate manual procedures, design new
ordering process, and implement database building
software to batch and track orders automatically and
schedule order pickups.
• QuickBase for Corporate Workgroups software
service increased efficiency and reduced errors.
• Demonstrates IT’s role in updating traditional
business processes.
• Illustrates digital technology as the focus of
designing and building new information systems.
 Systems as Planned Organizational Change

• Four kinds of structural organizational change

enabled by IT
1. Automation
• Increase efficiency, replace manual tasks
2. Rationalization
• Streamline standard operating procedures
3. Business process reengineering
• Analyze, simplify, and redesign business processes
4. Paradigm shifts
• Rethink nature of business, define new business model, change
nature of organization
 Systems as Planned Organizational Change

Organizational Change Carries Risks and Rewards

The most common forms of organizational change are automation and rationalization. These
relatively slow-moving and slow-changing strategies present modest returns but little risk. Faster
and more comprehensive change—such as reengineering and paradigm shifts—carries high
rewards but offers substantial chances of failure.

Figure 8-1
 Systems as Planned Organizational Change

• Business process reengineering (BPR)

• Large payoffs can result from redesigning business
processes
• E.g. Home mortgage industry used IT to redesign mortgage
application process costing $3000 and taking 6-8 weeks to
1-week process costing $1000
• Replaced sequential tasks with “work cell” or team approach

• Work flow management: Process of streamlining

business procedures so documents can be moved easily
and efficiently
 Systems as Planned Organizational Change

Redesigning Mortgage Processing in the United States

Figure 8-2A
By redesigning their mortgage processing
systems and the mortgage application
process, mortgage banks have been able
to reduce the costs of processing the
average mortgage from $3,000 to $1,000
and reduce the time of approval from six
weeks to one week or less. Some banks
are even preapproving mortgages and
locking interest rates on the same day the
customer applies.
 Systems as Planned Organizational Change

Redesigning Mortgage Processing in the United States

Figure 8-2B
 Systems as Planned Organizational Change

Business Process Redesign at the Small Business

Administration
• Read the Interactive Session: Organizations, and then
discuss the following questions:
• What was wrong with the existing computer system (ALCS)
and why did SBA decide to replace it?
• What was the purpose of re-organizing the ODA and
centralizing IT in a single office, and centralizing other
functions like the call center in a single office?
• In what other ways could the agency use information systems
to improve the process of loan application, approval, and
maintenance?
 Systems as Planned Organizational Change

• Steps in effective reengineering

• Determine which business processes should be improved
• Strategic analysis
• Pain points

• Identify and describe existing process

• Identify inputs and outputs, flow of products, network of
activities and buffers, resources, information structure and flow,
process owners, process actors and decision makers
• Understand how much process costs and how long to perform
• Process cost, process time, process quality, process flexibility
 Systems as Planned Organizational Change

• Steps in effective reengineering (cont.)

• Determine which methods can improve process
• Replace sequential steps with parallel
• Enrich jobs by enhancing decision making and concentrating
information
• Enable information sharing throughout to all participants
• Eliminate buffers (decision delays and inventories)
• Transform batch processing and decision making into continuous
flow processes
• Automate decision tasks wherever possible
 Systems as Planned Organizational Change

• Business process management

• Includes:
• Work flow management
• Business process modeling notation
• Quality measurement and management
• Change management
• Tools for standardizing business processes so they can be
continually manipulated
• Process monitoring and analytics
• To verify process performance has improved and measure
impact of process changes on key business performance
indicators
 Systems as Planned Organizational Change

• Business process management (BPM)

• Helps firms manage process changes through use
of process-mapping tools to:
• Identify and document existing processes
• Create models of improved processes that can
be translated into software systems
 Systems as Planned Organizational Change

• Quality management:
• Fine-tuning business processes to improve quality in their products,
services, and operations
• The earlier in the business cycle a problem is eliminated, the less it
costs the company
• Quality improvements raise level of product and service quality as well
as lower costs
• Total Quality Management (TQM):
• Achievement of quality control is end in itself
• Everyone is expected to contribute to improvement of quality
• Six sigma:
• Specific measure of quality
• 3.4 defects per million opportunities
 Systems as Planned Organizational Change

• Information systems support quality

improvements by helping firms:
• Simplify products or processes
• Make improvements based on customer demands
• Reduce cycle time
• Improve quality and precision of design and production
• Meet benchmarking standards
• Benchmarking: Setting strict standards for products, services,
and other activities, and then measuring performance against
those standards
 Overview of Systems Development

• Systems development: Activities that go into

producing an information system solution to an
organizational problem or opportunity
• Systems analysis
• Systems design
• Programming
• Testing
• Conversion
• Production and maintenance
 Overview of Systems Development

The Systems Development Process

Building a system can be broken down into six core activities.

Figure 8-3
 Overview of Systems Development

• Systems analysis
• Analysis of problem
• Defining the problem and identifying causes
• Specifying solutions
• Written systems proposal report describes costs and benefits of
each alternative solution
• Identifying information requirements to be met
• Who needs what information where, when, and how
• Includes feasibility study
• Is solution a good investment?
• Is required technology, skill available?
 Overview of Systems Development

• Systems design
• Describe system specifications that will deliver functions
identified during systems analysis
• Should address all managerial, organizational, and
technological components of system solution
• Role of end users
• User information requirements drive system-building
• Users must have sufficient control over design process to
ensure that system reflects their business priorities and
information needs
• Insufficient user involvement in design effort is major cause of
system failure
 Overview of Systems Development

Design Specifications
OUTPUT PROCESSING DOCUMENTATION
Medium Computations Operations documentation
Content Program modules Systems documents
Timing Required reports User documentation
Timing of outputs
INPUT CONVERSION
Origins MANUAL PROCEDURES Transfer files
Flow What activities Initiate new procedures
Data entry Who performs them Select testing method
When Cut over to new system
USER INTERFACE
How
Simplicity TRAINING
Where
Efficiency Select training techniques
Logic CONTROLS Develop training modules
Feedback Input controls (characters, limit, reasonableness) Identify training facilities
Errors Processing controls (consistency, record counts)
ORGANIZATIONAL CHANGES
Output controls (totals, samples of output)
DATABASE DESIGN Task redesign
Procedural controls (passwords, special forms)
Logical data model Job redesign
Volume and speed SECURITY Process design
requirements Access controls Organization structure design
File organization and Catastrophe plans Reporting relationships
design Audit trails
Record specifications
 Overview of Systems Development

• Programming:
• System specifications from design stage are translated into
software program code
• Software may be purchased, leased, or outsourced instead
• Testing
• To ensure system produces right results
• Test plan: All preparations for series of tests
• Unit testing: Tests each program in system separately
• System testing: Tests functioning of system as a whole
• Acceptance testing: Makes sure system is ready to be used in
production setting
 Overview of Systems Development

A Sample Test Plan to Test a Record Change

When developing a test plan, it is imperative to include the various conditions to be tested, the requirements for each
condition tested, and the expected results. Test plans require input from both end users and information systems specialists.

Figure 8-4
 Overview of Systems Development

• Conversion
• Process of changing from old system to new system
• Four main strategies
• Parallel strategy
• Direct cutover
• Pilot study
• Phased approach
• Requires end-user training
• Finalization of detailed documentation showing how system works
from technical and end-user standpoint
 Overview of Systems Development

• Production and maintenance

• System reviewed to determine if any revisions needed
• May prepare formal postimplementation audit document
• Maintenance
• Changes in hardware, software, documentation, or procedures
to a production system to correct errors, meet new
requirements, or improve processing efficiency
• 60 percent of maintenance work:
• User enhancements
• Improving documentation
• Recoding system components for greater processing efficiency
 Overview of Systems Development

Summary of Systems Development Activities

CORE ACTIVITY DESCRIPTION
Systems analysis Identify problem(s)
Specify solutions
Establish information requirements

Systems design Create design specifications

Programming Translate design specifications into

code

Testing Unit test

Systems test
Acceptance test

Conversion Plan conversion

Prepare documentation
Train users and technical staff

Production and Operate the system

maintenance Evaluate the system
Modify the system
 Overview of Systems Development

• Most prominent methodologies for modeling and

designing systems:
• Structured methodologies
• Object-oriented development

• Structured methodologies
• Structured: Techniques are step-by-step, progressive
• Process-oriented: Focusing on modeling processes or
actions that manipulate data
• Separate data from processes
 Overview of Systems Development

• Data flow diagram:

• Primary tool for representing system’s component processes and flow
of data between them
• Offers logical graphic model of information flow
• High-level and lower-level diagrams can be used to break processes
down into successive layers of detail

• Data dictionary: Defines contents of data flows and data stores

• Process specifications: Describe transformation occurring within
lowest level of data flow diagrams
• Structure chart: Top-down chart, showing each level of design,
relationship to other levels, and place in overall design structure
 Overview of Systems Development

Data Flow Diagram for Mail-In University Registration System

Figure 8-5
The system has three
processes: Verify
availability (1.0), Enroll
student (2.0), and
Confirm registration
(3.0). The name and
content of each of the
data flows appear
adjacent to each arrow.
There is one external
entity in this system: the
student. There are two
data stores: the student
master file and the
course file.
 Overview of Systems Development

High-Level Structure Chart for a Payroll System

This structure chart shows the highest or most abstract level of design for a payroll system, providing an overview of the entire system.

Figure 8-6
 Overview of Systems Development
• Object-oriented development
• Uses object as basic unit of systems analysis
and design
• Object:
• Combines data and the specific processes that
operate on those data
• Data encapsulated in object can be accessed and
modified only by operations, or methods,
associated with that object

• Object-oriented modeling based on concepts

of class and inheritance
• Objects belong to a certain class and have
features of that class
• May inherit structures and behaviors of a more
general, ancestor class
 Overview of Systems Development

Class and Inheritance

This figure illustrates how classes inherit the common features of their superclass.

Figure 8-7
 Overview of Systems Development

• Object-oriented development
• More iterative and incremental than traditional structured
development
• Systems analysis: Interactions between system and users
analyzed to identify objects
• Design phase: Describes how objects will behave and interact;
grouped into classes, subclasses and hierarchies
• Implementation: Some classes may be reused from existing
library of classes, others created or inherited

• Because objects reusable, object-oriented development can

potentially reduce time and cost of development
 Overview of Systems Development

• Computer-aided software engineering (CASE)

• Software tools to automate development and reduce
repetitive work, including
• Graphics facilities for producing charts and diagrams
• Screen and report generators, reporting facilities
• Analysis and checking tools
• Data dictionaries
• Code and documentation generators
• May be front-end or back-end tools
• Support iterative design by automating revisions and
changes and providing prototyping facilities
 Alternative Systems-Building Approaches

• Traditional systems lifecycle:

• Oldest method for building information systems
• Phased approach - divides development into formal stages
• Follows “waterfall” approach: Tasks in one stage finish
before another stage begins
• Maintains formal division of labor between end users and
information systems specialists
• Emphasizes formal specifications and paperwork
• Still used for building large complex systems
• Can be costly, time-consuming, and inflexible
 Alternative Systems-Building Approaches

• Prototyping
• Building experimental system rapidly and inexpensively for
end users to evaluate
• Prototype: Working but preliminary version of information
system
• Approved prototype serves as template for final system
• Steps in prototyping
1. Identify user requirements
2. Develop initial prototype
3. Use prototype
4. Revise and enhance prototype
 Alternative Systems-Building Approaches

Class and Inheritance

Figure 8-8
The process of developing a prototype
can be broken down into four steps.
Because a prototype can be developed
quickly and inexpensively, systems
builders can go through several
iterations, repeating steps 3 and 4, to
refine and enhance the prototype before
arriving at the final operational one.
 Alternative Systems-Building Approaches

• Advantages of prototyping
• Useful if some uncertainty in requirements or design
solutions
• Often used for end-user interface design
• More likely to fulfill end-user requirements
• Disadvantages
• May gloss over essential steps
• May not accommodate large quantities of data or large
number of users
• May not undergo full testing or documentation
 Alternative Systems-Building Approaches

• End-user development:
• Uses fourth-generation languages to allow end-users to
develop systems with little or no help from technical specialists
• Fourth generation languages:
• Less procedural than conventional programming languages
• 7 categories: PC software tools, query languages, report
generators, graphics languages, application generators, application
software packages, and very high-level programming languages
• Advantages:
• More rapid completion of projects, high-level of user satisfaction
• Disadvantages:
• Not designed for processing-intensive applications, inadequate
control, testing, documentation, or adherence to standards
 Alternative Systems-Building Approaches

• Application software packages

• Save time and money
• Many packages offer customization features:
• Allow software package to be modified to meet unique
requirements without destroying integrity of package software
• Evaluation criteria for systems analysis include:
• Functions provided by the package, flexibility, user friendliness,
hardware and software resources, database requirements,
installation and maintenance efforts, documentation, vendor
quality, and cost
• Request for Proposal (RFP)
• Detailed list of questions submitted to packaged-software vendors
 Alternative Systems-Building Approaches

• Outsourcing
• Several types
• Application service providers (ASPs)
• Subscribing companies use software and computer hardware provided
by ASP as technical platform for systems
• Domestic or foreign external vendors
• Hired to design, create software
• Allows organization flexibility in IT needs
• Allows vendors:
• Economies of scale
• Enhance core competencies
• Disadvantages
• Hidden costs, loss of control
 Application Development for the Digital Firm

How to Get Outsourcing Right: Avoid Getting It Wrong

• Read the Interactive Session: Management, and then

discuss the following questions:
• What is the basis for vendor firms claiming they can provide
IT services more economically than a firm’s own IT staff?
• Why is it difficult to write iron-clad legal contracts specifying
in detail strategic alliance outsourcing relationships?
• Why do joint ventures and co-sourcing outsourcing
relationships have a better chance of success?
 Application Development for the Digital Firm

• Rapid application development (RAD)

• Process of creating workable systems in a very
short period of time
• Utilizes techniques such as:
• Visual programming and other tools for building
graphical user interfaces
• Iterative prototyping of key system elements
• Automation of program code generation,
• Close teamwork among end users and
information systems specialists
 Application Development for the Digital Firm

• Joint application design (JAD)

• Used to accelerate generation of information
requirements and to develop initial systems design
• Brings end users and information systems
specialists together in interactive session to discuss
system’s design
• Can significantly speed up design phase and
involve users at intense level
 Agile frameworks

• Agile project management is an iterative approach to

delivering a project throughout its life cycle.

• Iterative or agile life cycles are composed of

several iterations or incremental steps towards the
completion of a project.

• Iterative approaches are frequently used in software

development projects to promote velocity and adaptability
since the benefit of iteration is that you can adjust as you go
along rather than following a linear path.
 Application Development for the Digital Firm

• Component-based development
• Groups of objects that provide software for common
functions such as online ordering capability and can be
combined to create large-scale business applications
• Web services
• Reusable software components that use open, Internet
standards (platform independent)
• Enable applications to communicate with no custom
programming required to share data and services
• Software components deliverable over Internet
• Can engage other Web services for more complex
transactions, such as checking credit, procurement, or ordering
products
 Agile frameworks

• scrum
– key concepts: roles, ceremonies, artefacts
– resources: scrum alliance, mountain goat, linkedin learning
• dsdm: dynamic systems development method
– key concepts: phases and stages, MoSCoW, modelling
– resources: ABC (agile business consortium)
• kanban
– key concepts: the visualization board, flow, sharing out of work
– resources: leankit, kanbantool, kanbanize, etc
• extreme programming (xp)
– key concepts: pair programming, ultra-frequent testing,
– resources: extremeProgramming.org, kent beck's books
 1-1

E-MARKETING
E-Marketing in Context
Lecture 1: Past, Present, and Future
 Core Books

Chaffey, D. and Ellis- Chaffey, D. and Smith, PR. Heinze A. Fletcher G.

Chadwick, F. (2019). (2017). E Marketing Rashod T. Cruz A.
Digital Marketing Excellence Planning & (2022) Digital & Social
strategy, optimising and Media Marketing A
Implementation & Integrating online results -Driven
Practice 7th edition. marketing 5th Edition. approach 2nd Edition
Pearson Education Routledge. Routledge Chapter ,
Learning outcomes
 Define digital marketing concept and explain how
digital technologies support marketing.
 Distinguish between e-commerce and e-business .
 Explain alternative digital business models and the
different forms of online presence.
 Describe the various digital and social media channels
supporting business objectives.
 Explain the benefits and key challenges of digital
communications.
 From PC Era to Web 4.0

A group of internet-based applications that build on the ideological and

technological foundations of Web 2.0, and that all the creation and exchange of
user generated content (Kaplan and Haenlein, 2010).

Source: Chaffey, D. and Ellis-Chadwick, F. (2016) Digital marketing: strategy, implementation and practice, 6th Edition, Pearson, Ch 1.
Migration from Web 1.0 – Web 4.0

 Web 1.0 contained static content provided by the creator the

site. It was dominated by businesses and was commercially and
technically-based.
 Web 2.0 moved to content that was socially based and
generated by the audience.
 Web 3.0 advanced to the integration of content and
communications with an emphasis on real-time communications.
Sites were driven by online metrics.
 Web 4.0 focuses on customer engagement and cloud
operating systems. Web participation is essential now.
The Evolution of the Web (v1.0, 2.0, 3.0. 4.0, etc.)
What is Digital Marketing?
First lets look at the definition of marketing:
 “Marketing is the management process responsible
for identifying, anticipating and satisfying customer
requirements profitably.” (CIM, 2018)

One could then argue that Digital Marketing is:

 “Achieving marketing objectives through applying
digital technologies.” (Chaffey, 2000)
 What is digital Marketing
Definition –
The application of the internet & related technologies in conjunction with traditional
communications to achieve marketing objectives

‘Achieving marketing objectives through applying digital technologies’ (Chaffery et al

2012)

Online company presence –

Managing online – websites, social media, online advertising, emailing, search engine
marketing, partner arrangements with other websites

Techniques used to acquire new customers, help develop customer relationships ( E-CRM)

Examines customer journeys – The sequence of online & off line touch points a customer
take through a buying process or customer experience supporting multichannel
marketing
How do digital technologies support marketing?

 Marketing is the management process responsible for

identifying, anticipating and satisfying consumer
needs and requirements profitably (CIM, 2001 to
date).

Question
 How do digital technologies support marketing?
How do digital technologies support marketing?

 Identifying – the Internet can be used for marketing research to

find out customers needs and wants.
 E.g. understanding consumer journey using artificial intelligence (AI), use of
online surveys and online feedback tools such as
http://bit.ly/smartfeedback

 Anticipating – the Internet provides an additional channel by

which customers can access information and make purchases
 evaluating this demand is key to governing resource allocation to e-
marketing. E.g. Amazons collaborative filtering , online partnerships,
making use of cookies.

 Satisfying – a key success factor in e-marketing is achieving

customer satisfaction through the electronic channel, which raises
issues such as: is the site easy to use, does it perform adequately,
what is the standard of associated customer service and how are
physical products dispatched? E.g.online customer experience (UX)
 A more in-depth definition
(Chaffey & Ellis-Chadwick, 2016,p.11)

• Customer-centric digital marketing involves:

Applying…
• Digital technologies which form online channels…
(Web, e-mail, databases, mobile, Internet Protocol television- iPTV)
to…
• Contribute to marketing activities aimed at achieving
profitable acquisition and retention of customers
(within a multi/omni-channel buying process
and customer life cycle)
through…
• Improving customer knowledge (of their profiles, behaviour, value and
loyalty drivers), then delivering integrated targeted communications and
online services that match their individual needs
Benefits of digital marketing – The 5Ss
Table 1.2 The 5Ss of Internet marketing

Basic framework for

setting and reviewing
different types of goals
for digital strategy
development based on
the 5Ss.

Source: Chaffey and Smith (2012)

Introducing the scope of digital marketing (Chaffey &
Ellis-Chadwick, 2016,p.11)

 ‘Achieving marketing objectives through applying digital

technologies and media’
 The application of the internet & related technologies in
conjunction with traditional communications to achieve
marketing objectives.
 How?
 Managing different forms of online company presence –
websites, social media, online advertising, emailing, search engine
marketing, partner arrangements with other websites
 Using digital marketing techniques to acquire new customers,
help develop customer relationships ( E-CRM, social CRM)
 The role of digital platforms in supporting:
 customer journeys (online & off line touch points)
 multi/omnichannel marketing by linking business operations to achieve
profitability.
 7Ds of Managing Digital Marketing

Source : Chaffey D. (2022) Digital Marketing definitions . What is Digital Marketing

https://www.davechaffey.com/digital-marketing-definitions/what-is-digital-
marketing/
 Digital marketing toolbox
15

Email

Social
media Websites
advertising

Digital
toolbox
Social Online PR
networks

Search
Blogs engine
marketing

Hanlon A. ( 2019) Digital Marketing: Strategic Planning Chapter 3

Applications of digital marketing

 An advertising medium
 A direct-response medium

 A platform for sales transactions

 A lead-generation method

 A distribution channel

 A customer service mechanism

 A relationship-building medium.
 Digital business models and the
different forms of online presence
 Omni-channel strategy

 Omnis: all or universal

 A single unified approach with multiple touchpoints requiring a
seamless consistent experience, with a very rich responsive
back-end system
 To achieve this you need to make the right technology choice,
e.g. an appropriate top-tier Enterprise Resource Planning (ERP)
 Defined as: a strategy that manages channels as intermingled
touch points to allow consumers to live a seamless experience
within a brand ecosystem (Rigby, 2011; Brynjolfsson et al.,
2013)
 Key characteristics: informational and transactional touch
points integrated within a unique channel in order to allow
a seamless consumer journey
Sources: Karine Picot-Coupey Elodie Huré Lauren Piveteau , (2016),"Channel design to enrich customers’ shopping
experiences", International Journal of Retail & Distribution Management, Vol. 44 Iss 3 p.342.
Karine Picot-Coupey Elodie Huré Lauren Piveteau , (2016),"Channel design to enrich customers’ shopping experiences",
International Journal of Retail & Distribution Management, Vol. 44 Iss 3 p.342.
Single Multichannel Omnichannel
Channel
 Omni-channel strategy (Cont.)

 Channel articulation: unique channel

 The historical channel becomes a touch point among
others, within a unique channel.
 The emphasis of omni-channel retailing is on the
interplay between channels and brands.
 Shifting to an omni-channel strategy commits a brand
to a process of optimising customer experience and
redesigning channels and touch points from this
perspective (adopts a customer-centric perspective
rather than organisation-centric perspective)
Sources: Karine Picot-Coupey Elodie Huré Lauren Piveteau , (2016),"Channel design to enrich customers’ shopping
experiences", International Journal of Retail & Distribution Management, Vol. 44 Iss 3 p.342.
Karine Picot-Coupey Elodie Huré Lauren Piveteau , (2016),"Channel design to enrich customers’ shopping experiences",
International Journal of Retail & Distribution Management, Vol. 44 Iss 3 p.342.
Multi-, cross- and omni-channel retailing logistics

 Multichannel VS Omnichannel Customer Experience | What's The Difference?

 https://www.youtube.com/watch?v=P6-auqgqY1A

 Cross-channel, multi-channel, omni-channel. The evolution of retail logistics

 https://www.youtube.com/watch?v=5VeIjVhXAWw

 Retail Hero: Macy's, Chief Omnichannel Officer

 https://www.youtube.com/watch?v=jYJ-0xJeesw
 Macy's Goes Omnichannel
 https://www.youtube.com/watch?v=vV4J-xjM4I8

 Understanding omnichannel in fashion retail

 https://www.youtube.com/watch?v=c8ik74Wq5Ys
Marketing communication &
web presence
 Key marketing communications concepts

Source: Chaffey, D. and Ellis-Chadwick, F. (2016) Digital marketing: strategy, implementation and practice, 6th Edition, Pearson, Ch 1.
 Digital Media Channels

Source https://www.smartinsights.com/digital-marketing-strategy/what-
is-digital-marketing/
 Forms of web presence
Media channels to consider in developing a strategy

Paid media –Bought media . Direct payment to the site owner

when they service an ad (pay per click, lead scale generated)

Earned media- Generated through editorial comments & sharing

social networks –blogs customer advocates

Owned media- Company's own website, blog ,email list mobile

app social presence e.g. Facebook, twitter
 The intersection of the three key online media types

Application Programme Interfaces (APIs)- a method for automated data exchange

through a feed in a defined format, enabling different systems or web services to
integrate data. E.g. Facebook API.
Widget- a badge or button incorporated into a site or social network space by its
owner, but with content typically served from another site. Content can be updated in
real time.
Source: Chaffey, D. and Ellis-Chadwick, F. (2016) Digital marketing: strategy, implementation and practice, 6th Edition, Pearson, Ch 1.
 Six categories of e-communications tools or media channels
Source: Chaffey and Smith (2012)

Source: Chaffey and Ellis-Chadwick (2016) Digital marketing: strategy, implementation and practice, 6th Edition, Pearson, Ch 1.
 Benefits of digital communications in terms
deploying campaigns

 Accountability
 use of measurement systems, e.g. Google Analytics, to enable advertisers to
test the value generated from its ads.
 Testing (Act & Covert)
 creative executions, messaging or offers. E.g. Google’s Website Optimser (free
tool) to test alternative landing pages. A/B testing and multivariate testing.
 Flexibility
 Changing copy or offers during the campaign

 Google AdWords dayparting- ads displayed at different types of the day.

 Micro-targeting
 Using Google AdWords delivering alternative messages to different audiences
according to what they are searching for.
 Cost-control- e.g. key search word bidding, CPM, CPC.
Key challenges of digital communications

 Complexity
 Setting up and managing campaigns requires specialist expertise
 Responding to competitors
 The need for more resources to monitor competitor activity, e.g. Using the
automated bid management tools
 Responding to changes in technology and marketing platforms
 Keeping staff managing campaigns up-to-date with new technologies
 Cost- sometimes costs can be high, exceeding Euro 10/click.
 Attention-
 banner blindness where web users ignore online ads
 difficulty in engaging social media audiences with advertising
The growing range of digital
marketing platforms
Desktop, laptop and notebook platforms

1. Desk top browser platform (see next slide)

2. Desk top apps. Apple App Store, Microsoft Gadget.
3. Email platform
4. Feed-based and Application Programming Interface (API) data
exchange platforms.
 E.g. Rich Site Summary and Really Simple Syndication (RSS) feeds,
Twitter & Facebook status updates can be considered a form of feed or
stream where ads can be inserted.
5. Video-marketing platforms
- streamed video delivered through the above, e.g. browsers and plug-ins
- TV channels delivered through streaming over the Internet (Internet
Protocol Television- IPTV)
 Desktop platforms
Global market share held by leading desktop internet browsers from January 2015 to December 2018
Global desktop market share held by internet browsers 2015-2018

Note: Worldwide; January 2015 to December 2018; desktop only

Further information regarding this statistic can be found on page 8.
Source(s): StatCounter; ID 544400
2

Source: https://www.statista.com/statistics/544400/market-share-of-internet-
browsers-desktop/ Accessed 05/02/2019.
 Desktop platforms
Global market share held by leading desktop internet browsers from January 2015 to December 2018
Global desktop market share held by internet browsers 2015-2018

Note: Worldwide; January 2015 to December 2018; desktop only

Further information regarding this statistic can be found on page 8.
Source(s): StatCounter; ID 544400
6

Source: https://www.statista.com/statistics/544400/market-share-of-internet-
browsers-desktop/ Accessed 05/02/2019.
 Mobile phone and tablet platforms

 New opportunities to engage customers through mobile

marketing and location-based marketing
1. Mobile operating system and browser- mobile apps closely
integrated with the operating system.
2. Mobile-based apps. Apple iOS, Google Android, RIM or
Windows.
Mobile Web vs Mobile Apps: Where Should You Invest Your Marketing?
https://moz.com/blog/mobile-web-mobile-apps-invest-marketing-whiteboard-
friday
https://www.youtube.com/watch?v=F6c6IzudmLY
How technology is changing media
 Individual Assignments
36

Assignment Guidelines - Assignment 01

• Select Union Assurance Plc as the case organisation and you are to evaluate the online participation in marketing
activities based on their web site.
•There is no upper word limit, though it is expected to have at least 3000 words
• Secondary sources must be cited within the text and a list of references must be included to attain a higher
mark
•Submission deadline is 18th Week of delivery
•Each piece of student’s work should include the following information on the cover:
•Registration number of the candidate
•Unit name
•URL of the website being evaluated
•Suggested chapter outline for the report : Introduction, Evaluating website according to the marketing mix,
proposed improvements in terms of IMC, conclusion s.
•A soft copy of the work must be submitted along with the bound hard copy.

Assignment 02
You are required to do a multimedia presentation on findings related to assignment 01 lasting 8-10 minutes (18/19th weeks)

Weight 15% towards final grade

 This Week Essential Reading

Chaffey, D. and Ellis-Chadwick, F. (2019). Digital Marketing strategy,

Implementation & Practice 7th edition. Pearson Education Chapter 1

Chaffey, D. and Smith, PR. (2017). E Marketing Excellence Planning &

optimising and Integrating online marketing 5th Edition. Routledge.
Chapter 1

Heinze A. Fletcher G. Rashod T. Cruz A. (2022) Digital & Social Media

Marketing A results -Driven approach 2nd Edition Routledge Chapter 1, 13
 Enhancing
Decision Making
Session 10
 LEARNING OBJECTIVES

• Describe different types of decisions and the

decision-making process.

• Assess how information systems support the

activities of managers and management decision
making.

• Demonstrate how decision-support systems (DSS)

differ from MIS and how they provide value to the
business.
 LEARNING OBJECTIVES (cont’d)

• Demonstrate how executive support systems (ESS)

help senior managers make better decisions.

• Evaluate the role of information systems in helping

people working in a group make decisions more
efficiently.
 Procter & Gamble Restructures Its Supply Chain

• Problem: Cost pressures, complex supply chain.

• Solutions: Deploy modeling and optimization
software to maximize return on investment and
predict the most successful supply chain.
• Modeling software fueled with data from Oracle data
warehouse improved efficiency and reduced costs.
• Demonstrates IT’s role in restructuring a supply
chain.
• Illustrates digital technology improving decision
making through information systems.
 Decision Making and Information Systems

• Business value of improved decision making

• Improving hundreds of thousands of “small” decisions adds up to
large annual value for the business
• Types of decisions:
• Unstructured: Decision maker must provide judgment,
evaluation, and insight to solve problem
• Structured: Repetitive and routine; involve definite procedure
for handling so they do not have to be treated each time as new
• Semistructured: Only part of problem has clear-cut answer
provided by accepted procedure
 Decision Making and Information Systems

• Senior managers:
• Make many unstructured decisions
• E.g. Should we enter a new market?
• Middle managers:
• Make more structured decisions but these may include
unstructured components
• E.g. Why is order fulfillment report showing decline in
Minneapolis?
• Operational managers, rank and file employees
• Make more structured decisions
• E.g. Does customer meet criteria for credit?
 Decision Making and Information Systems

Information Requirements of Key Decision-Making

Groups in a Firm

Senior managers, middle managers, operational managers, and employees have different types of
decisions and information requirements.

Figure 10-1
 Decision Making and Information Systems

• Four stages of decision making

1. Intelligence
• Discovering, identifying, and understanding the problems
occurring in the organization
2. Design
• Identifying and exploring solutions to the problem
3. Choice
• Choosing among solution alternatives
4. Implementation
• Making chosen alternative work and continuing to monitor how
well solution is working
 Decision Making and Information Systems

Stages in Decision Making

The decision-making process can be

Figure 10-2
broken down into four stages.
 Decision Making and Information Systems

• Information systems can only assist in some of the

roles played by managers
• Classical model of management
• Five functions of managers
• Planning, organizing, coordinating, deciding, and controlling
• More contemporary behavioral models
• Actual behavior of managers appears to be less systematic,
more informal, less reflective, more reactive, and less well
organized than in classical model
• Mintzberg’s behavioral model of managers defines 10
managerial roles falling into 3 categories
 Decision Making and Information Systems

• Managerial roles
• Interpersonal roles: Figurehead
Leader
Liaison
• Informational roles: Nerve center
Disseminator
Spokesperson
• Decisional roles: Entrepreneur
Disturbance handler
Resource allocator
Negotiator
 Decision Making and Information Systems

• Three main reasons why investments in information

technology do not always produce positive results
1. Information quality
• High-quality decisions require high-quality information
(Accuracy,Integrity,Consistancy,Completeness,Validity,Timeliness,Accessibility)
2. Management filters
• Managers have selective attention and have variety of biases
that reject information that does not conform to prior
conceptions
3. Organizational culture
• Strong forces within organizations resist making decisions
calling for major change
 Systems for Decision Support

• Four kinds of systems for decision support

• Management information systems (MIS)

• Decision support systems (DSS)

• Executive support systems (ESS)

• Group decision support systems (GDSS)

 Systems for Decision Support

• Management information systems (MIS)

• Help managers monitor and control business by providing
information on firm’s performance and address structured
problems
• Typically produce fixed, regularly scheduled reports based on
data from TPS
• E.g. exception reports: Highlighting exceptional conditions, such
as sales quotas below anticipated level
• E.g. California Pizza Kitchen MIS
• For each restaurant, compares amount of ingredients used per
ordered menu item to predefined portion measurements and
identifies restaurants with out-of-line portions
 Systems for Decision Support

• Decision-support systems (DSS)

• Support unstructured and semistructured decisions
• Model-driven DSS
• Earliest DSS were heavily model-driven
• E.g. voyage-estimating DSS
• Data-driven DSS
• Some contemporary DSS are data-driven
• Use OLAP and data mining to analyze large pools of data
• E.g. business intelligence applications
 Systems for Decision Support

• Components of DSS
• Database used for query and analysis
• Current or historical data from number of
applications or groups
• May be small database or large data warehouse
• User interface
• Often has Web interface

• Software system with models, data mining, and other

analytical tools
 Systems for Decision Support

Overview of a Decision-Support System

The main components of the DSS are the DSS database, the user interface, and the DSS software system. The DSS database may be a small
database residing on a PC or a large data warehouse.

Figure 10-3
 Systems for Decision Support

• Model:
• Abstract representation that illustrates components or
relationships of phenomenon; may be physical,
mathematical, or verbal model
• Statistical models
• Optimization models
• Forecasting models
• Sensitivity analysis models
 Systems for Decision Support

Renault Speeds Up Delivery with a New DSS

• Read the Interactive Session: Technology, and then

discuss the following questions:
• How did this DSS improve decision making at Renault?
Describe some of the decisions that were improved by using
this system.
• How much of an impact did this DSS have on business
performance? Explain your answer.
• What management, organization, and technology factors had
to be addressed in order to make this system successful?
 Systems for Decision Support

• Data visualization tools:

• Help users see patterns and relationships in large amounts of
data that would be difficult to discern if data were presented as
traditional lists of text
• Geographic information systems (GIS):
• Category of DSS that use data visualization technology to
analyze and display data in form of digitized maps
• Used for decisions that require knowledge about geographic
distribution of people or other resources, e.g.:
• Helping local governments calculate emergency response times to
natural disasters
• Help retail chains identify profitable new store locations
 Systems for Decision Support

California’s South Coast

Air Quality Management
District (AQMD) is
responsible for
monitoring and
controlling emissions in
all of Orange County
and the urban portions
of Los Angeles,
Riverside, and San
Bernardino counties.
Displayed is a map
produced with ESRI GIS
software tracking
particulate matter
emissions from building
construction activity in
a two-by-two kilometer
area.
 Systems for Decision Support

• Web-based customer decision-support systems

(CDSS):
• Support decision-making process of existing or potential
customer
• Use Web information resources and capabilities for interactivity
and personalization to help users select products and services
• E.g. search engines, intelligent agents, online catalogs, Web
directories, newsgroup discussions, other tools
• Automobile companies that use CDSS to allow Web site visitors
to configure desired car
• Financial services companies with Web-based asset-
management tools for customers
 Systems for Decision Support

Does CompStat Reduce Crime?

• Read the Interactive Session: Management, and then

discuss the following questions:
• What management, organization, and technology factors
make CompStat effective?
• Can police departments effectively combat crime without the
CompStat system? Explain your answer.
• Why do you think the police need a computer system to tell
them where to deploy resources?
 Executive Support Systems (ESS)

• Executive support systems (ESS)

• Integrate data from different functional systems for firmwide
view
• Incorporate external data, e.g. stock market news, competitor
information, industry trends, legislative action
• Include tools for modeling and analysis
• Primarily for status, comparison information about
performance
• Facilities for environmental scanning - detecting signals of
problems, threats, or strategic opportunities
• Able to drill down from summary information to lower levels of
detail
 Executive Support Systems (ESS)

• Business value of executive support systems

• Enables executive to review more data in less time with greater
clarity than paper-based systems
• Result: Needed actions identified and carried out earlier
• Improves management performance
• Increases upper management’s span of control
• Can enable decision making to be decentralized and take place at
lower operating levels
• Increases executives’ ability to monitor activities of lower units
reporting to them
 Group Decision-Support Systems (GDSS)

• What Is a GDSS?
• Interactive, computer-based system used to facilitate
solution of unstructured problems by set of decision
makers working together as group
• Designed to improve quality and effectiveness of
decision-making meetings
• Make meetings more productive by providing tools to
facilitate:
• Planning, generating, organizing, and evaluating ideas
• Establishing priorities
• Documenting meeting proceedings for others in firm
 Group Decision-Support Systems (GDSS)

• Components of GDSS
• Hardware
• Facility: Appropriate facility, furniture, layout
• Electronic hardware: Audiovisual, computer, networking equipment
• Software
• Electronic questionnaires, electronic brainstorming tools, idea
organizers, questionnaire tools
• Tools for voting or setting priorities, stakeholder identification and
analysis tools, policy formation tools,
• Group dictionaries
• People
• Participants and trained facilitator, support staff
 Group Decision-Support Systems (GDSS)

• Overview of GDSS meeting

• Each attendee has workstation, networked to facilitator’s
workstation and meeting’s file server
• Whiteboards on either side of projection screen
• Seating arrangements typically semicircular, tiered
• Facilitator controls use of tools during meeting
• All input saved to server, kept confidential
• After meeting, full record (raw material and final output)
assembled and distributed
 Group Decision-Support Systems (GDSS)

Group System Tools

Figure 10-9
The sequence of activities and
collaborative support tools used in an
electronic meeting system facilitate
communication among attendees and
generate a full record of the meeting.
Source: From Nunamaker et al.,
“Electronic Meeting Systems to Support
Group Work,” Communications of the
ACM, July 1991. Reprinted by
permission.
 Group Decision-Support Systems (GDSS)

• Business value of GDSS

• Supports greater numbers of attendees
• Without GDSS, decision-making meeting process breaks
down with more than 5 attendees
• More collaborative atmosphere
• Guarantees anonymity
• Can increase number of ideas generated and
quality of decisions made
 Group Decision-Support Systems (GDSS)

• Business value of GDSS (cont.)

• Most useful for idea generation, complex
problems, large groups
• Successful use of GDSS depends on many
factors
• Facilitator’s effectiveness, culture and
environment, planning, composition of group,
appropriateness of tools selected, etc.
 Session 11
Managing Knowledge and
Artificial Intelligence
Learning Objectives
1. What is the role of knowledge management systems in
business?
2. What types of systems are used for enterprise-wide
knowledge management, and how do they provide
value for businesses?
3. What are the major types of knowledge work systems,
and how do they provide value for firms?
4. What are the business benefits of using intelligent
techniques for knowledge management?
5. How will MIS help my career?
Machine Learning Helps Akershus
University Hospital Make Better
Treatment Decisions (1 of 2)
• Problem
– Unstructured data
– Very large volume of data
– Opportunities from new technology
• Solutions
– Manage safety, costs, and health outcomes of patients
– Collect procedures, and test data
– Train Watson Explorer
– CT Scan Analysis System
Machine Learning Helps Akershus
University Hospital Make Better
Treatment Decisions (2 of 2)
• Organize treatments and improve safety
• Demonstrates role of artificial intelligence in helping
organizations improve performance and remain competitive
• Illustrates the ability of machine learning systems to analyze
vast quantities of data and find patterns
What is the Role of Knowledge
Management Systems in Business?
• Knowledge management systems among fastest growing areas of
software investment
• Information economy
– 37 percent U.S. labor force: knowledge and information workers
– 55 percent U.S. GDPfrom knowledge and information sectors
• Substantial part of a firm’s stock market value is related to intangible
assets: knowledge, brands, reputations, and unique business
processes
• Well-executed knowledge-based projects can produce extraordinary
ROI
Important Dimensions of Knowledge
(1 of 2)

• Data, knowledge, and wisdom

• Tacit knowledge and explicit knowledge
• Important dimensions of knowledge
– Knowledge is a firm asset.
– Knowledge has different forms.
– Knowledge has a location.
– Knowledge is situational.
Important Dimensions of Knowledge
(2 of 2)

• Knowledge-based core competencies

– Key organizational assets
• Knowing how to do things effectively and efficiently in ways
others cannot duplicate is a prime source of profit and
competitive advantage
– Example: Having a unique build-to-order production system
• Organizational learning
– Process in which organizations gain experience through
collection of data, measurement, trial and error, and
feedback
The Knowledge Management Value
Chain (1 of 3)
• Knowledge management
– Set of business processes developed in an organization to
create, store, transfer, and apply knowledge
• Knowledge management value chain
– Each stage adds value to raw data and information as they
are transformed into usable knowledge
 Knowledge acquisition
 Knowledge storage
 Knowledge dissemination
 Knowledge application
The Knowledge Management Value
Chain (2 of 3)
• Knowledge acquisition
– Documenting tacit and explicit knowledge
 Storing documents, reports, presentations, best practices
 Unstructured documents (e.g., e-mails)
 Developing online expert networks
– Creating knowledge
– Tracking data from TPS and external sources
• Knowledge storage
– Databases
– Document management systems
– Role of management
The Knowledge Management Value
Chain (3 of 3)
• Knowledge dissemination
– Portals, wikis
– E-mail, instant messaging
– Search engines, collaboration tools
– A deluge of information?
 Training programs, informal networks, and shared
management experience help managers focus attention on
important information.
• Knowledge application
– New business practices
– New products and services
– New markets
Figure 11.1 The Knowledge
Management Value Chain
Building Organizational and Management
Capital: Collaboration, Communities of
Practice, and Office Environments
• Developing new organizational roles and responsibilities for the
acquisition of knowledge
• Chief knowledge officer executives
• Dedicated staff / knowledge managers
• Communities of practice (COPs)
– Informal social networks of professionals and employees
– Activities include education, online newsletters, sharing
knowledge
– Reduce learning curves of new employees
Types of Knowledge Management
Systems
• Enterprise-wide knowledge management systems
– General-purpose firm-wide efforts to collect, store,
distribute, and apply digital content and knowledge
• Knowledge work systems (KWS)
– Specialized systems built for engineers, scientists, other
knowledge workers charged with discovering and creating
new knowledge
• Intelligent techniques
– Diverse group of techniques such as data mining used for
various goals: discovering knowledge, distilling knowledge,
discovering optimal solutions
Figure 11.2 Major Types of
Knowledge Management Systems
What Types of Systems Are Used for
Enterprise-Wide Knowledge
Management?
• Three major types of knowledge in an enterprise
– Structured documents
 Reports, presentations
 Formal rules
– Semistructured documents
 E-mails, videos
– Unstructured, tacit knowledge
• 80% of an organization’s business content is
semistructured or unstructured
What Is Artificial Intelligence? (1 of 3)
• Grand vision
– Computer hardware and software systems that are as
“smart” as humans
– So far, this vision has eluded computer programmers
and scientists
• Realistic vision
– Systems that take data inputs, process them, and
produce outputs (like all software programs) and that
can perform many complex tasks that would be difficult
or impossible for humans to perform.
What Is Artificial Intelligence? (2 of 3)
• Examples:
– Recognize millions of faces in seconds
– Interpret millions of CT scans in minutes
– Analyze millions of financial records
– Detect patterns in very large Big Data databases
– Improve their performance over time (“learn”)
– Navigate a car in certain limited conditions
– Respond to questions from humans (natural language);
speech activated assistants like Siri, Alexa, and
Cortana
What Is Artificial Intelligence? (3 of 3)
• Major Types of AI
– Expert systems
– Machine learning
– Neural networks and deep learning networks
– Genetic algorithms
– Natural language Processing
– Computer vision
– Robotics
Capturing Knowledge: Expert
Systems
• Capture tacit knowledge in very specific and limited domain of human
expertise

• Capture knowledge as set of rules

• Typically perform limited tasks

– Diagnosing malfunctioning machine
– Determining whether to grant credit for loan

• Used for discrete, highly structured decision making

• Knowledge base: Set of hundreds or thousands of rules

• Inference engine: Strategy used to search knowledge base

– Forward chaining
– Backward chaining
Figure 11.3 Rules in an Expert
System
Machine Learning
• How computer programs improve performance without
explicit programming
– Recognizing patterns
– Experience
– Prior learnings (database)
– Supervised vs. unsupervised learning
• Contemporary examples
– Google searches
– Recommender systems on Amazon, Netflix
Neural Networks
• Find patterns and relationships in massive amounts of data
too complicated for humans to analyze
• “Learn” patterns by searching for relationships, building
models, and correcting over and over again
• Humans “train” network by feeding it data inputs for which
outputs are known, to help neural network learn solution by
example from human experts.
• Used in medicine, science, and business for problems in
pattern classification, prediction, financial analysis, and
control and optimization
Figure 11.4 How a Neural Network
Works
Figure 11.5 A Deep Learning Network
Genetic Algorithms
• Useful for finding optimal solution for specific problem by
examining very large number of possible solutions for that
problem
• Conceptually based on process of evolution
– Search among solution variables by changing and
reorganizing component parts using processes such as
inheritance, mutation, and selection
• Used in optimization problems (minimization of costs,
efficient scheduling, optimal jet engine design) in which
hundreds or thousands of variables exist
• Able to evaluate many solution alternatives quickly
Figure 11.6 The Components of a
Genetic Algorithm
Natural Language Processing
• Understand, and speak in natural language. Read natural language
and translate
• Typically today based on machine learning, aided by very large
databases of common phrases and sentences in a given language
• Example: Google Translate
• Spam filtering systems
• Customer call center interactions: What is the customer’s problem?
What solutions worked in the past?
• Digital assistances: Sire, Alexa, Cortana, GoogleAssistant
• Not useful for an ordinary common sense human conversation but can
be very useful in limited domains, e.g. interacting with your car’s
heating system.
Computer Vision Systems
• Digital image systems that create a digital map of an image (like
a face, or a street sign), and recognize this image in large data
bases of images in near real time
• Every image has a unique pattern of pixels
• Facebook’s DeepFace can identify friends in photos across their
system, and the entire web
• Autonomous vehicles can recognize signs, road markers,
people, animals, and other vehicles with good reliability
• Industrial machine (robot) vision
• Passport control at airports
• Identifying people in crowds
Robotics
• Design, construction, and operation of machines that can
substitute for humans in many factory, office, and home
applications (home vacuums).
• Generally programmed to perform specific and detailed actions
in limited domains, e.g. robots spray paint autos, and assemble
certain parts, welding, heavy assembly movement.
• Used in dangerous situations like bomb disposal
• Surgical robots are expanding their capabilities
Intelligent Agents
• Work without direct human intervention to carry out
repetitive, predictable tasks
– Deleting junk e-mail
– Finding cheapest airfare
• Use limited built-in or learned knowledge base
– Some are capable of self-adjustment, for example: Siri
• Chatbots
• Agent-based modeling applications:
– Model behavior of consumers, stock markets, and
supply chains; used to predict spread of epidemics
Figure 11.7 Intelligent Agents in
P&G’s Supply Chain Network
Enterprise Content Management
Systems
• Help capture, store, retrieve, distribute, preserve
documents and semistructured knowledge
• Bring in external sources
– News feeds, research
• Tools for communication and collaboration
– Blogs, wikis, and so on
• Key problem: developing taxonomy
• Digital asset management systems
Figure 11.8 An Enterprise Content
Management System
Locating and Sharing Expertise
• Provide online directory of corporate experts in well-
defined knowledge domains
• Search tools enable employees to find appropriate expert
in a company
• Social networking and social business tools for finding
knowledge outside the firm
– Saving
– Tagging
– Sharing web pages
Learning Management Systems
(LMS)
• Provide tools for management, delivery, tracking, and
assessment of employee learning and training
• Support multiple modes of learning
– CD-ROM, web-based classes, online forums, and so on
• Automates selection and administration of courses
• Assembles and delivers learning content
• Measures learning effectiveness
• Massively open online courses (MOOCs)
– Web course open to large numbers of participants
Knowledge Workers and Knowledge
Work
• Knowledge workers
– Researchers, designers, architects, scientists, engineers who
create knowledge for the organization
– Three key roles
 Keeping organization current in knowledge
 Serving as internal consultants regarding their areas of
expertise
 Acting as change agents, evaluating, initiating, and promoting
change projects
• Knowledge work systems
– Systems for knowledge workers to help create new knowledge
and integrate that knowledge into business
Requirements of Knowledge Work
Systems
• Sufficient computing power for graphics, complex
calculations
• Powerful graphics and analytical tools
• Communications and document management
• Access to external databases
• User-friendly interfaces
• Optimized for tasks to be performed (design engineering,
financial analysis)
Figure 11.9 Requirements of
Knowledge Work Systems
Examples of Knowledge Work
Systems
• CAD (computer-aided design)
– Creation of engineering or architectural designs
– 3D printing
• Virtual reality systems
– Simulate real-life environments
– 3D medical modeling for surgeons
– Augmented reality (AR) systems
– VRML
What Are the Benefits of Using
Intelligent Techniques for Knowledge
Management?
• Intelligent techniques: Used to capture individual and collective
knowledge and to extend knowledge base
– To capture tacit knowledge: Expert systems, case-based
reasoning, fuzzy logic
– Knowledge discovery: Neural networks and data mining
– Generating solutions to complex problems: Genetic
algorithms
– Automating tasks: Intelligent agents
• Artificial intelligence (AI) technology:
– Computer-based systems that emulate human behavior