Please the attached documents and related textbooks for the question details
APA FormatNo Plagiarism
Assignment 1
Textbook: Information Systems for Business and Beyond
Please answer the following
From Chapter 3 – Answer Study questions 1-8 and Exercise 2
From Chapter 2 – Answer Study questions 1-13 and Exercise 5
All the above questions should be submitted in one Word document
Please understand that Plagiarism will not be tolerated and will result in a zero grade.
Submission Requirements
Font: Times New Roman, size 12, double-space
Citation Style: APA
Length: At least six Pages
References: Please use citations and references where appropriate
No Plagiarism
Assignment 2
Textbook: Information Technology and Organizational Learning
Please answer the Following
From Chapter 3 – Complete the two essay assignments noted below:
1. Review the strategic integration section. Note what strategic integration is and how it ties to the implementation of technology within an organization.
2. Review the information technology roles and responsibilities section. Note how IT is divided based on operations and why this is important to understand within an organization.
Submission Requirements
Font: Times New Roman, size 12, double-space
Length: At least two Pages
Citation Style: APA
References: Please use citations and references where appropriate
No Plagiarism
The above submission should adhere to APA formatting standards. Remember the page length does not include the APA cover page or any references. Please understand that Plagiarism will not be tolerated and will result in a zero grade.
Chapter 3: Software
Learning Objectives
Upon successful completion of this chapter, you will be
able to:
• define the term
software;
• identify and describe the two primary categories of
software;
• describe the role ERP software plays in an
organization;
• describe cloud computing and its advantages and
disadvantages for use in an organization; and
• define the term open-source and identify its
primary characteristics.
The second component of an information system is software, the
set of instructions that tells the hardware what to do. Software
is created by developers through the process of programming
(covered in more detail in Chapter 10). Without software, the
hardware would not be functional.
54 | Chapter 3: Software
Types of Software
Software can be broadly divided into two categories: operating
systems and application software. Operating systems manage the
hardware and create the interface between the hardware and the
user. Application software performs specific tasks such as word
processing, accounting, database management, video games, or
browsing the web.
Operating Systems
An operating system is first loaded into the computer by the
boot program, then it manages all of the programs in the computer,
including both programs native to the operating system such as
file and memory management and application software. Operating
systems provide you with these key functions:
1. managing the hardware resources of the computer;
2. providing the user-interface components;
Chapter 3: Software | 55
Linux Ubuntu desktop
3. providing a platform for software developers to write
applications.
All computing devices require an operating system. The most
popular operating systems for personal computers are: Microsoft
Windows, Apple’s Mac OS, and various versions of Linux.
Smartphones and tablets run operating systems as well, such as
iOS (Apple), Android (Google), Windows Mobile (Microsoft), and
Blackberry.
Microsoft provided the first operating system for the IBM-PC,
released in 1981. Their initial venture into a Graphical User Interface
(GUI) operating system, known as Windows, occurred in 1985.
Today’s Windows 10 supports the 64-bit Intel CPU. Recall that
“64-bit” indicates the size of data that can be moved within the
computer.
Apple introduced the Macintosh computer 1984 with the first
commercially successful GUI. Apple’s operating system for the
Macintosh is known as “Mac OS ” and also uses an Intel CPU
supporting 64-bit processing. Mac OS versions have been named
after mountains such as El Capitan, Sierra, and High Sierra.
Multitasking, virtual memory, and voice input have become
standard features of both operating
systems.
The Linux operating system
is open source, meaning
individual developers are
allowed to make modifications
to the programming code.
Linux is a version of the Unix
operating. Unix runs on large
and expensive minicomputers.
Linux developer Linus Torvalds,
a professor in Finland and the creator of Linux, wanted to find a way
to make Unix run on less expensive personal computers. Linux has
many variations and now powers a large percentage of web servers
in the world.
56 |
Sidebar: Why Is Microsoft Software So
Dominant in the Business World?
If you’ve worked in business, you may have noticed that almost
all computers in business run a version of Microsoft Windows.
However, in classrooms from elementary to college, there is almost
a balance between Macs and PCs. Why has this not extended into
the business world?
As discussed in Chapter 1, many businesses used IBM mainframe
computers back in the 1960s and 1970s. When businesses migrated
to the microcomputer (personal computer) market, they elected to
stay with IBM and chose the PC. Companies took the safe route,
invested in the Microsoft operating system and in Microsoft
software/applications.
Microsoft soon found itself with the dominant personal computer
operating system for businesses. As the networked PC began to
replace the mainframe computer, Microsoft developed a network
operating system along with a complete suite of programs focused
on business users. Today Microsoft Office in its various forms
controls 85% of the market.
1
Application Software
The second major category of software is application
software.
1. [1]
Chapter 3: Software | 57
Image of Microsoft Excel
Application software is utilized directly today to accomplish
a
specific goal such as word processing, calculations on a
spreadsheet, or surfing the Internet using your favorite browser.
The “Killer” App
When a new type of digital
device is invented, there are
generally a small group of
technology enthusiasts who
will purchase it just for the joy
of figuring out how it works. A
“killer” application is one that
becomes so essential that large
numbers of people will buy a
device just to run that application. For the personal computer, the
killer application was the
spreadsheet.
The first spreadsheet was created by an MBA student at Harvard
University who tired of making repeated calculations to determine
the optimal result on a problem and decided to create a tool that
allowed the user to easily change values and recalculate formulas.
The result was the spreadsheet. Today’s dominant spreadsheet is
Microsoft Excel which still retains the basic functionality of the first
spreadsheet.
Productivity Software
Along with the spreadsheet, several other software applications
have become standard tools for the workplace. Known as
productivity software, these programs allow office employees to
complete their daily work efficiently. Many times these applications
58 | Information Systems for Business and Beyond (2019)
come packaged together, such as in Microsoft’s Office suite. Here is
a list of some of these applications and their basic functions:
• Word processing Users can create and edit documents using
this class of software. Functions include the ability to type and
edit text, format fonts and paragraphs, as well as add, move,
and delete text throughout the document. Tables and images
can be inserted. Documents can be saved in a variety of
electronic file formats with Microsoft Word’s DOCX being the
most popular. Documents can also be converted to other
formats such as Adobe’s PDF (Portable Document Format) or a
.TXT file.
• Spreadsheet This class of software provides a way to do
numeric calculations and analysis, displaying the result in
charts and graphs. The working area is divided into rows and
columns, where users can enter numbers, text, or formulas. It
is the formulas that make a spreadsheet powerful, allowing the
user to develop complex calculations that can change based on
the numbers entered. The most popular spreadsheet package
is Microsoft Excel, which saves its files in the XLSX
format.
• Presentation Users can create slideshow presentations using
this class of software. The slides can be projected, printed, or
distributed to interested parties. Text, images, audio, and
visual can all be added to the slides. Microsoft’s PowerPoint is
the most popular software right now, saving its files in PPTX
format.
• Some office suites include other types of software. For
example, Microsoft Office includes Outlook, its e-mail
package, and OneNote, an information-gathering collaboration
tool. The professional version of Office also includes Microsoft
Access, a database package. (Databases are covered more in
Chapter 4.)
Microsoft popularized the idea of the office-software productivity
Chapter 3: Software | 59
bundle with their release of the Microsoft Office Suite. This package
continues to dominate the market and most businesses expect
employees to know how to use this software. However, many
competitors to Microsoft Office do exist and are compatible with
the file formats used by Microsoft (see table below). Microsoft also
offers a cloud-based version of their office suite named Microsoft
Office 365. Similar to Google Drive, this suite allows users to edit
and share documents online utilizing cloud-computing technology.
Utility Software and Programming Software
Utility software includes programs that allow you to fix or modify
your computer in some way. Examples include anti-malware
software and programs that totally remove software you no longer
want installed. These types of software packages were created to
fill shortcomings in operating systems. Many times a subsequent
release of an operating system will include these utility functions as
part of the operating system itself.
Programming software’s purpose is to produce software. Most of
60 | Information Systems for Business and Beyond (2019)
https://commons.wikimedia.org/wiki/User:Wgsimon
Screen shot of Tableau (click to
enlarge)
these programs provide developers with an environment in which
they can write the code, test it, and convert/compile it into the
format that can then be run on a computer. This software is typically
identified as the Integrated Development Environment (IDE) and is
provided free from the corporation that developed the
programming language that will be used to write the code.
Sidebar: “PowerPointed” to Death
As presentation software has
gained acceptance as the
primary method to formally
present information to a group
or class, the art of giving an
engaging presentation is
becoming rare. Many
presenters now just read the
bullet points in the
presentation and immediately bore those in attendance, who can
already read it for themselves. The real problem is not with
PowerPoint as much as it is with the person creating and presenting.
Author and chief evangelist Guy Kawasaki has developed the 10/20/
30 rule for Powerpoint users. Just remember: 10 slides, 20 minutes,
30 point font.”
2
If you are determined to improve your PowerPoint
skills, read Presentation Zen by Garr Reynolds.
New digital presentation technologies are being developed that
go beyond Powerpoint. For example, Prezi uses a single canvas for
the presentation, allowing presenters to place text, images, and
2. [2]
Chapter 3: Software | 61
https://opentextbook.site/informationsystems2019/wp-content/uploads/sites/3/2018/07/TABLUE
https://opentextbook.site/informationsystems2019/wp-content/uploads/sites/3/2018/07/TABLUE
other media on the canvas, and then navigate between these objects
as they present. Tools such as Tableau allow users to analyze data in
depth and create engaging interactive visualizations.
Sidebar: I Own This Software, Right?
Well…
When you purchase software and install it on your computer, are
you the owner of that software? Technically, you are not! When you
install software, you are actually just being given a license to use it.
When you first install a package, you are asked to agree to the terms
of service or the license agreement. In that agreement, you will find
that your rights to use the software are limited. For example, in
the terms of the Microsoft Office software license, you will find
the following statement: “This software is licensed, not sold. This
agreement only gives you some rights to use the features included
in the software edition you licensed.”
For the most part, these restrictions are what you would expect.
You cannot make illegal copies of the software and you may not use
it to do anything illegal. However, there are other, more unexpected
terms in these software agreements. For example, many software
agreements ask you to agree to a limit on liability. Again, from
Microsoft: “Limitation on and exclusion of damages. You can
recover from Microsoft and its suppliers only direct damages up to
the amount you paid for the software. You cannot recover any other
damages, including consequential, lost profits, special, indirect or
incidental damages.” This means if a problem with the software
causes harm to your business, you cannot hold Microsoft or the
supplier responsible for damages.
62 | Information Systems for Business and Beyond (2019)
Applications for the Enterprise
As the personal computer proliferated inside organizations, control
over the information generated by the organization began
splintering. For instance, the customer service department creates
a customer database to keep track of calls and problem reports,
and the sales department also creates a database to keep track of
customer information. Which one should be used as the master
list of customers? Or perhaps someone in sales might create a
spreadsheet to calculate sales revenue, while someone in finance
creates a different revenue document that meets the needs of their
department, but calculates revenue differently. The two
spreadsheets will report different revenue totals. Which one is
correct? And who is managing all of this information?
Enterprise Resource Planning
In the 1990s
the need to bring an organization’s information back under
centralized control became more apparent. The Enterprise
Resource Planning (ERP) system (sometimes just called enterprise
software) was developed to bring together an entire organization
within one program. ERP software utilizes a central database that
is implemented throughout the entire organization. Here are some
key points about ERP.
• A software application. ERP is an application that is used by
Chapter 3: Software | 63
many of an organization’s employees.
• Utilizes a central database. All users of the ERP edit and save
their information from the same data source. For example, this
means there is only one customer table in the database, there
is only one sales (revenue) table in the database, etc.
• Implemented organization-wide. ERP systems include
functionality that covers all of the essential components of a
business. An organization can purchase modules for its ERP
system that match specific needs such as order entry,
manufacturing, or planning.
ERP systems were originally marketed to large corporations.
However, as more and more large companies began installing them,
ERP vendors began targeting mid-sized and even smaller
businesses. Some of the more well-known ERP systems include
those from SAP, Oracle, and Microsoft.
In order to effectively implement an ERP system in an
organization, the organization must be ready to make a full
commitment. All aspects of the organization are affected as old
systems are replaced by the ERP system. In general, implementing
an ERP system can take two to three years and cost several million
dollars.
So why implement an ERP system? If done properly, an ERP
system can bring an organization a good return on their investment.
By consolidating information systems across the enterprise and
using the software to enforce best practices, most organizations
see an overall improvement after implementing an ERP. Business
processes as a form of competitive advantage will be covered in
Chapter 9.
64 | Information Systems for Business and Beyond (2019)
Customer Relationship Management
A Customer Relationship Management (CRM) system manages an
organization’s customers. In today’s environment, it is important to
develop relationships with your customers, and the use of a well-
designed CRM can allow a business to personalize its relationship
with each of its customers. Some ERP software systems include
CRM modules. An example of a well-known CRM package is
Salesforce.
Supply Chain Management
Supply Chain
Many organizations must deal with the complex task of managing
their supply chains. At its simplest, a supply chain is the linkage
between an organization’s suppliers, its manufacturing facilities,
and the distributors of its products. Each link in the chain has a
multiplying effect on the complexity of the process. For example,
if there are two suppliers, one manufacturing facility, and two
distributors, then the number of links to manage = 4 ( 2 x 1 x
2 ). However, if two more suppliers are added, plus another
manufacturing facility, and two more distributors, then the number
of links to manage = 32 ( 4 x 2 x 4 ). Also, notice in the above
illustration that all arrows have two heads, indicating that
information flows in both directions. Suppliers are part of a
business’s supply chain. They provide information such as price,
size, quantity, etc. to the business. In turn, the business provides
information such as quantity on hand at every store to the supplier.
The key to successful supply chain management is the information
system.
Chapter 3: Software | 65
https://commons.wikimedia.org/wiki/Category:Supply_chain#/media/File:A_company%27s_supply_chain_(en)
A Supply Chain Management (SCM) system handles the
interconnection between these links as well as the inventory of
the products in their various stages of development. As discussed
previously much of Walmart’s success has come from its ability
to identify and control the supply chain for its products. Walmart
invested heavily in their information system so they could
communicate with their suppliers and manage the thousands of
products they sell.
Walmart realized in the 1980s that the key to their success was
information systems. Specifically, they needed to manage their
complex supply chain with its thousands of suppliers, thousands
of retail outlets, and millions of customers. Their success came
from being able to integrate information systems to every entity
(suppliers, warehouses, retail stores) through the sharing of sales
and inventory data. Take a moment to study the diagram
above…look for the double-headed arrow. Notice that data flows
down the supply chain from suppliers to retail stores. But it also
flows up the supply chain, back to the suppliers so they can be up to
date regarding production and shipping.
Mobile Applications
Just as with the personal computer, mobile devices such as
66 | Information Systems for Business and Beyond (2019)
smartphones and electronic tablets also have operating systems and
application software. These mobile devices are in many ways just
smaller versions of personal computers. A mobile app is a software
application designed to run specifically on a mobile device.
As shown in Chapter 2, smartphones are becoming a dominant
form of computing, with more smartphones being sold than
personal computers. A greater discussion of PC and smartphone
sales appears in Chapter 13, along with statistics regarding the
decline in tablet sales. Businesses have adjusted to this trend by
increasing their investment in the development of apps for mobile
devices. The number of mobile apps in the Apple App Store has
increased from zero in 2008 to over 2 million in 2017.
3
Building a mobile app will will be covered in Chapter 10.
Cloud Computing
Historically, for software to run on a computer an individual copy
of the software had to be installed on the computer. The concept of
“cloud” computing changes this.
Cloud Computing
The “cloud” refers to applications, services, and data storage
located on the Internet. Cloud service providers rely on giant server
farms and massive storage devices that are connected via the
Internet. Cloud computing allows users to access software and data
storage services on the Internet.
You probably already use cloud computing in some form. For
example, if you access your e-mail via your web browser, you are
3. [3]
Chapter 3: Software | 67
using a form of cloud computing if you are using Google Drive’s
applications. While these are free versions of cloud computing,
there is big business in providing applications and data storage over
the web. Cloud computing is not limited to web applications. It can
also be used for services such as audio or video streaming.
Advantages of Cloud Computing
• No software to install or upgrades to maintain.
• Available from any computer that has access to the Internet.
• Can scale to a large number of users easily.
• New applications can be up and running very quickly.
• Services can be leased for a limited time on an as-needed
basis.
• Your information is not lost if your hard disk crashes or your
laptop is lost or stolen.
• You are not limited by the available memory or disk space on
your computer.
Disadvantages of Cloud Computing
• Your information is stored on someone else’s computer.
• You must have Internet access to use it.
• You are relying on a third-party to provide these services.
Cloud computing has the ability to really impact how
organizations manage technology. For example, why is an IT
department needed to purchase, configure, and manage personal
computers and software when all that is really needed is an Internet
connection?
68 | Information Systems for Business and Beyond (2019)
Using a Private Cloud
Many organizations are understandably nervous about giving up
control of their data and some of their applications by using cloud
computing. But they also see the value in reducing the need for
installing software and adding disk storage to local computers. A
solution to this problem lies in the concept of a private cloud. While
there are various models of a private cloud, the basic idea is for
the cloud service provider to section off web server space for a
specific organization. The organization has full control over that
server space while still gaining some of the benefits of cloud
computing.
Virtualization
Virtualization is the process of using software to simulate a
computer or some other device. For example, using virtualization
a single physical computer can perform the functions of several
virtual computers, usually referred to as Virtual Machines (VMs).
Organizations implement virtual machines in an effort to reduce
the number of physical servers needed to provide the necessary
services to users. This reduction in the number of physical servers
also reduces the demand for electricity to run and cool the physical
servers. For more detail on how virtualization works, see this
informational page from VMWare.
Chapter 3: Software | 69
http://www.vmware.com/virtualization/virtualization-basics/how-virtualization-works.html
http://www.vmware.com/virtualization/virtualization-basics/how-virtualization-works.html
Example program “Hello World”
written in Java
Software Creation
Modern software applications
are written using a
programming language such as
Java, Visual C, C++, Python, etc.
A programming language
consists of a set of commands
and syntax that can be
organized logically to execute
specific functions. Using this language a programmer writes a
program (known as source code) that can then be compiled into
machine-readable form, the ones and zeroes necessary to be
executed by the CPU. Languages such as HTML and Javascript are
used to develop web pages.
Open-Source Software
When the personal computer was first released, computer
enthusiasts banded together to build applications and solve
problems. These computer enthusiasts were motivated to share any
programs they built and solutions to problems they found. This
collaboration enabled them to more quickly innovate and fix
problems.
As software began to become a business, however, this idea of
sharing everything fell out of favor with many developers. When a
program takes hundreds of hours to develop, it is understandable
that the programmers do not want to just give it away. This led to a
new business model of restrictive software licensing which required
payment for software, a model that is still dominant today. This
model is sometimes referred to as closed source, as the source code
is not made available to others.
70 | Information Systems for Business and Beyond (2019)
There are many, however, who feel that software should not be
restricted. Just as with those early hobbyists in the 1970s, they feel
that innovation and progress can be made much more rapidly if
they share what has been learned. In the 1990s, with Internet access
connecting more people together, the open-source movement
gained steam.
Open Office Suite
Open-source software makes the source code available for
anyone to copy and use. For most people having access to the
source code of a program does little good since it is challenging to
modify existing programming code. However, open-source software
is also available in a compiled format that can be downloaded and
installed. The open-source movement has led to the development
of some of the most used software in the world such as the Firefox
browser, the Linux operating system, and the Apache web server.
Many businesses are wary of open-source software precisely
because the code is available for anyone to see. They feel that this
increases the risk of an attack. Others counter that this openness
actually decreases the risk because the code is exposed to
thousands of programmers who can incorporate code changes to
quickly patch vulnerabilities.
There are thousands of open-source applications available for
download. For example, you can get the productivity suite from
Chapter 3: Software | 71
Open Office. One good place to search for open-source software is
sourceforge.net, where thousands of programs are available for free
download.
Summary
Software gives the instructions that tell the hardware what to do.
There are two basic categories of software: operating systems and
applications. Operating systems interface with the computer
hardware and make system resources available. Application
software allows users to accomplish specific tasks such as word
processing, presentations, or databases. This group is also referred
to as productivity software. An ERP system stores all data in a
centralized database that is made accessible to all programs and
departments across the organization. Cloud computing provides
access to software and databases from the Internet via a web
browser. Developers use various programming languages to develop
software.
Study Questions
1. Develop your own definition of software being certain to
explain the key terms.
2. What are the primary functions of an operating system?
3. Which of the following are operating systems and which are
applications: Microsoft Excel, Google Chrome, iTunes,
Windows, Android, Angry Birds.
4. What is your favorite software application? What tasks does it
help you accomplish?
72 | Information Systems for Business and Beyond (2019)
http://sourceforge.net/
5. How would you categorize the software that runs on mobile
devices? Break down these apps into at least three basic
categories and give an example of each.
6. What does an ERP system do?
7. What is open-source software? How does it differ from closed-
source software? Give an example of each.
8. What does a software license grant to the purchaser of the
software?
Exercises
1. Find a case study online about the implementation of an ERP
system. Was it successful? How long did it take? Does the case
study tell you how much money the organization spent?
2. If you were running a small business with limited funds for
information technology, would you consider using cloud
computing? Find some web-based resources that support your
decision.
3. Go to sourceforge.net and review their most downloaded
software applications. Report on the variety of applications you
find. Then pick one that interests you and report back on what
it does, the kind of technical support offered, and the user
reviews.
4. Review this article on the security risks of open-source
software. Write a short analysis giving your opinion on the
different risks discussed.
5. List three examples of programming languages? What features
in each language makes it useful to developers?
Chapter 3: Software | 73
http://sourceforge.net/
http://www.zdnet.com/six-open-source-security-myths-debunked-and-eight-real-challenges-to-consider-7000014225
Lab
1. Download Apache Open Office and create a document. Note: If
your computer does not have Java Runtime Environment (JRE)
32-bit (x86) installed, you will need to download it first from
this site.Open Office runs only in 32-bit (x86) mode. Here is a
link to the Getting Started documentation for Open Office.
How does it compare to Microsoft Office? Does the fact that
you got it for free make it feel less valuable?
1. Statista. (2017). Microsoft – Statistics & Facts. Retrieved from
https://www.statista.com/topics/823/microsoft/
2. Kawasaki, G. (n.d.). The 10/20/30 Rules for PowerPoint.
Retrieved from https://guykawasaki.com/the_102030_rule/.↵
3. Statista. (2018). Number of apps in Apple App Store July 2008 to
January 2017. Retrieved from https:https://www.statista.com/
statistics/263795/number-of-available-apps-in-the-apple-
app-store/.↵
74 | Information Systems for Business and Beyond (2019)
http://www.openoffice.org/download
http://www.oracle.com/technetwork/java/javase/downloads/jre8-downloads-2133155.html
http://wiki.openoffice.org/w/images/3/3c/0108GS33-GettingStartedWithBase
Chapter 4: Data and
Databases
Learning Objectives
Upon successful completion of this chapter, you
will be able to:
• Describe the differences between data,
information, and knowledge;
• Describe why database technology must be
used for data resource management;
• Define the term database and identify the
steps to creating one;
• Describe the role of a database
management system;
• Describe the characteristics of a data
warehouse; and
• Define data mining and describe its role in
an organization.
Chapter 4: Data and Databases | 75
Introduction
You have already been introduced to the first two components of
information systems: hardware and software. However, those two
components by themselves do not make a computer useful. Imagine
if you turned on a computer, started the word processor, but could
not save a document. Imagine if you opened a music player but
there was no music to play. Imagine opening a web browser but
there were no web pages. Without data, hardware and software
are not very useful! Data is the third component of an information
system.
Data, Information, and Knowledge
There have been many definitions and theories about data,
information, and knowledge. The three terms are often used
interchangeably, although they are distinct in nature. We define
and illustrate the three terms from the perspective of information
systems.
76 | Information Systems for Business and Beyond (2019)
Data are the raw facts, and may
be devoid of context or intent. For example, a sales order of
computers is a piece of data. Data can be quantitative or qualitative.
Quantitative data is numeric, the result of a measurement, count,
or some other mathematical calculation. Qualitative data is
descriptive. “Ruby Red,” the color of a 2013 Ford Focus, is an example
of qualitative data. A number can be qualitative too: if I tell you my
favorite number is 5, that is qualitative data because it is descriptive,
not the result of a measurement or mathematical calculation.
Information is processed data that possess context, relevance, and
purpose. For example, monthly sales calculated from the collected
daily sales data for the past year are information. Information
typically involves the manipulation of raw data to obtain an
indication of magnitude, trends, in patterns in the data for a
purpose.
Knowledge in a certain area is human beliefs or perceptions about
relationships among facts or concepts relevant to that area. For
example, the conceived relationship between the quality of goods
Chapter 4: Data and Databases | 77
and the sales is knowledge. Knowledge can be viewed as
information that facilitates action.
Once we have put our data into context, aggregated and analyzed
it, we can use it to make decisions for our organization. We can
say that this consumption of information produces knowledge. This
knowledge can be used to make decisions, set policies, and even
spark innovation.
Explicit knowledge typically refers to knowledge that can be
expressed into words or numbers. In contrast, tacit knowledge
includes insights and intuitions, and is difficult to transfer to
another person by means of simple communications.
Evidently, when information or explicit knowledge is captured
and stored in computer, it would become data if the context or
intent is devoid.
The final step up the information ladder is the step from
knowledge (knowing a lot about a topic) to wisdom. We can say
that someone has wisdom when they can combine their knowledge
and experience to produce a deeper understanding of a topic. It
often takes many years to develop wisdom on a particular topic, and
requires patience.
Big Data
Almost all software programs require data to do anything useful.
For example, if you are editing a document in a word processor
such as Microsoft Word, the document you are working on is the
data. The word-processing software can manipulate the data: create
a new document, duplicate a document, or modify a document.
Some other examples of data are: an MP3 music file, a video file, a
spreadsheet, a web page, a social media post, and an e-book.
Recently, big data has been capturing the attention of all types of
organizations. The term refers to such massively large data sets that
conventional data processing technologies do not have sufficient
78 | Information Systems for Business and Beyond (2019)
power to analyze them. For example, Walmart must process millions
customer transactions every hour across the world. Storing and
analyzing that much data is beyond the power of traditional data
management tools. Understanding and developing the best tools
and techniques to manage and analyze these large data sets are a
problem that governments and businesses alike are trying to solve.
Databases
The goal of many information systems is to transform data into
information in order to generate knowledge that can be used for
decision making. In order to do this, the system must be able to take
data, allow the user to put the data into context, and provide tools
for aggregation and analysis. A database is designed for just such a
purpose.
Why Databases?
Data is a valuable resource in the organization. However, many
people do not know much about database technology, but use non-
database tools, such as Excel spreadsheet or Word document, to
store and manipulate business data, or use poorly designed
databases for business processes. As a result, the data are
redundant, inconsistent, inaccurate, and corrupted. For a small
data set, the use of non-database tools such as spreadsheet may
not cause serious problem. However, for a large organization,
corrupted data could lead to serious errors and destructive
consequences. The common defects in data resources management
are explained as follows.
(1) No control of redundant data
People often keep redundant data for convenience. Redundant
Chapter 4: Data and Databases | 79
data could make the data set inconsistent. We use an illustrative
example to explain why redundant data are harmful. Suppose the
registrar’s office has two separate files that store student data: one
is the registered student roster which records all students who have
registered and paid the tuition, and the other is student grade roster
which records all students who have received grades.
As you can see from the two spreadsheets, this data management
system has problems. The fact that “Student 4567 is Mary Brown,
and her major is Finance” is stored more than once. Such
occurrences are called data redundancy. Redundant data often
make data access convenient, but can be harmful. For example, if
Mary Brown changes her name or her major, then all her names and
major stored in the system must be changed altogether. For small
data systems, such a problem looks trivial. However, when the data
system is huge, making changes to all redundant data is difficult if
not impossible. As a result of data redundancy, the entire data set
can be corrupted.
(2) Violation of data integrity
Data integrity means consistency among the stored data. We
use the above illustrative example to explain the concept of data
integrity and how data integrity can be violated if the data system is
flawed. You can find that Alex Wilson received a grade in MKT211;
however, you can’t find Alex Wilson in the student roster. That is,
the two rosters are not consistent. Suppose we have a data integrity
control to enforce the rules, say, “no student can receive a grade
unless she/he has registered and paid tuition”, then such a violation
of data integrity can never happen.
(3) Relying on human memory to store and to search needed data
The third common mistake in data resource management is the
80 | Information Systems for Business and Beyond (2019)
over use of human memory for data search. A human can remember
what data are stored and where the data are stored, but can also
make mistakes. If a piece of data is stored in an un-remembered
place, it has actually been lost. As a result of relying on human
memory to store and to search needed data, the entire data set
eventually becomes disorganized.
To avoid the above common flaws in data resource management,
database technology must be applied. A database is an organized
collection of related data. It is an organized collection, because in
a database, all data is described and associated with other data.
For the purposes of this text, we will only consider computerized
databases.
Though not good for replacing databases, spreadsheets can be
ideal tools for analyzing the data stored in a database. A spreadsheet
package can be connected to a specific table or query in a database
and used to create charts or perform analysis on that data.
Data Models and Relational Databases
Databases can be organized in many different ways by using
different models. The data model of a database is the logical
structure of data items and their relationships. There have been
several data models. Since the 1980s, the relational data model
has been popularized. Currently, relational database systems are
commonly used in business organizations with few exceptions. A
relational data model is easy to understand and use.
In a relational database, data is organized into tables (or relations).
Each table has a set of fields which define the structure of the data
stored in the table. A record is one instance of a set of fields in a
table. To visualize this, think of the records as the rows (or tuple) of
the table and the fields as the columns of the table.
In the example below, we have a table of student data, with each
row representing a student record , and each column representing
Chapter 4: Data and Databases | 81
one filed of the student record. A special filed or a combination
of fields that determines the unique record is called primary key
(or key). A key is usually the unique identification number of the
records.
Rows and columns in a table
Designing a Database
Suppose a university wants to create a School Database to track
data. After interviewing several people, the design team learns that
the goal of implementing the system is to give better insight into
students’ performance and academic resources. From this, the
team decides that the system must keep track of the students, their
grades, courses, and classrooms. Using this information, the design
team determines that the following tables need to be created:
• STUDENT: student name, major, and e-mail.
• COURSE: course title, enrollment capacity.
• GRADE: this table will correlate STUDENT with COURSE,
allowing us to have any given student to enroll multiple
courses and to receive a grade for each course.
• CLASSROOM: classroom location, classroom type, and
classroom capacity
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Now that the design team has determined which tables to create,
they need to define the specific data items that each table will hold.
This requires identifying the fields that will be in each table. For
example, course title would be one of the fields in the COURSE
table. Finally, since this will be a relational database, every table
should have a field in common with at least one other table (in other
words, they should have relationships with each other).
A primary key must be selected for each table in a relational
database. This key is a unique identifier for each record in the table.
For example, in the STUDENT table, it might be possible to use the
student name as a way to identify a student. However, it is more
than likely that some students share the same name. A student’s
e-mail address might be a good choice for a primary key, since e-
mail addresses are unique. However, a primary key cannot change,
so this would mean that if students changed their e-mail address we
would have to remove them from the database and then re-insert
them – not an attractive proposition. Our solution is to use student
ID as the primary key of the STUDENT table. We will also do this
for the COURSE table and the CLASSROOM table. This solution is
quite common and is the reason you have so many IDs! The primary
key of table can be just one field, but can also be a combination of
two or more fields. For example, the combination of StudentID and
CourseID the GRADE table can be the primary key of the GRADE
table, which means that a grade is received by a particular student
for a specific course.
The next step of design of database is to identify and make the
relationships between the tables so that you can pull the data
together in meaningful ways. A relationship between two tables is
implemented by using a foreign key. A foreign key is a field in one
table that connects to the primary key data in the original table. For
example, ClassroomID in the COURSE table is the foreign key that
connects to the primary key ClassroomID in the CLASSROOM table.
With this design, not only do we have a way to organize all of the
data we need and have successfully related all the table together to
Chapter 4: Data and Databases | 83
Tables of the
student
database
meet the requirements, but have also prevented invalid data from
being entered into the database. You can see the final database
design in the figure below:
Normalization
When designing a database, one important concept to understand
is normalization. In simple terms, to normalize a database means to
design it in a way that: 1) reduces data redundancy; and 2) ensure
data integrity.
In the School Database design, the design team worked to achieve
these objectives. For example, to track grades, a simple (and wrong)
solution might have been to create a Student field in the COURSE
table and then just list the names of all of the students there.
However, this design would mean that if a student takes two or
more courses, then his or her data would have to be entered twice
or more times. This means the data are redundant. Instead, the
designers solved this problem by introducing the GRADE table.
In this design, when a student registers into the school system
before taking a course, we first must add the student to the
STUDENT table, where their ID, name, major, and e-mail address
are entered. Now we will add a new entry to denote that the
student takes a specific course. This is accomplished by adding a
record with the StudentD and the CourseID in the GRADE table.
If this student takes a second course, we do not have to duplicate
the entry of the student’s name, major, and e-mail; instead, we
84 | Information Systems for Business and Beyond (2019)
only need to make another entry in the GRADE table of the second
course’s ID and the student’s ID.
The design of the School database also makes it simple to change
the design without major modifications to the existing structure.
For example, if the design team were asked to add functionality
to the system to track instructors who teach the courses, we could
easily accomplish this by adding a PROFESSOR table (similar to the
STUDENT table) and then adding a new field to the COURSE table
to hold the professors’ ID.
Data Types
When defining the fields in a database table, we must give each field
a data type. For example, the field StudentName is text string, while
EnrollmentCapacity is number. Most modern databases allow for
several different data types to be stored. Some of the more common
data types are listed here:
• Text: for storing non-numeric data that is brief, generally
under 256 characters. The database designer can identify the
maximum length of the text.
• Number: for storing numbers. There are usually a few different
number types that can be selected, depending on how large
the largest number will be.
• Boolean: a data type with only two possible values, such as 0 or
1, “true” or “false”, “yes” or “no”.
• Date/Time: a special form of the number data type that can be
interpreted as a number or a time.
• Currency: a special form of the number data type that formats
all values with a currency indicator and two decimal places.
• Paragraph Text: this data type allows for text longer than 256
characters.
• Object: this data type allows for the storage of data that cannot
Chapter 4: Data and Databases | 85
Open Office Database Management
System
be entered via keyboard, such as an image or a music file.
There are two important reasons that we must properly define
the data type of a field. First, a data type tells the database what
functions can be performed with the data. For example, if we wish
to perform mathematical functions with one of the fields, we must
be sure to tell the database that the field is a number data type. For
example, we can subtract the course capacity from the classroom
capacity to find out the number of extra seats available.
The second important reason to define data type is so that the
proper amount of storage space is allocated for our data. For
example, if the StudentName field is defined as a Text(50) data type,
this means 50 characters are allocated for each name we want to
store. If a student’s name is longer than 50 characters, the database
will truncate it.
Database Management Systems
To the computer, a database
looks like one or more files. In
order for the data in the
database to be stored, read,
changed, added, or removed, a
software program must access
it. Many software applications
have this ability: iTunes can
read its database to give you a listing of its songs (and play the
songs); your mobile-phone software can interact with your list of
contacts. But what about applications to create or manage a
database? What software can you use to create a database, change
a database’s structure, or simply do analysis? That is the purpose of
a category of software applications called database management
systems (DBMS).
86 | Information Systems for Business and Beyond (2019)
DBMS packages generally provide an interface to view and change
the design of the database, create queries, and develop reports.
Most of these packages are designed to work with a specific type
of database, but generally are compatible with a wide range of
databases.
A database that can only be used by a single user at a time is not
going to meet the needs of most organizations. As computers have
become networked and are now joined worldwide via the Internet,
a class of database has emerged that can be accessed by two, ten,
or even a million people. These databases are sometimes installed
on a single computer to be accessed by a group of people at a
single location. Other times, they are installed over several servers
worldwide, meant to be accessed by millions. In enterprises the
relational DBMS are built and supported by companies such as
Oracle, Microsoft SQL Server, and IBM Db2. The open-source
MySQL is also an enterprise database.
Microsoft Access and Open Office Base are examples of personal
database-management systems. These systems are primarily used
to develop and analyze single-user databases. These databases are
not meant to be shared across a network or the Internet, but are
instead installed on a particular device and work with a single user
at a time. Apache OpenOffice.org Base (see screen shot) can be
used to create, modify, and analyze databases in open-database
(ODB) format. Microsoft’s Access DBMS is used to work with
databases in its own Microsoft Access Database format. Both Access
and Base have the ability to read and write to other database
formats as well.
Structured Query Language
Once you have a database designed and loaded with data, how
will you do something useful with it? The primary way to work
Chapter 4: Data and Databases | 87
with a relational database is to use Structured Query Language,
SQL (pronounced “sequel,” or simply stated as S-Q-L). Almost all
applications that work with databases (such as database
management systems, discussed below) make use of SQL as a way to
analyze and manipulate relational data. As its name implies, SQL is a
language that can be used to work with a relational database. From
a
simple request for data to a complex update operation, SQL is a
mainstay of programmers and database administrators. To give you
a taste of what SQL might look like, here are a couple of examples
using our School database:
The following query will retrieve the major of student John
Smith from
the STUDENT table:
SELECT StudentMajor
FROM STUDENT
WHERE StudentName = ‘John Smith’;
The following query will list the total number of students in
the STUDENT table:
SELECT COUNT(*)
FROM STUDENT;
SQL can be embedded in many computer languages that are used
to develop platform-independent web-based applications. An in-
depth description of how SQL works is beyond the scope of this
introductory text, but these examples should give you an idea of
the power of using SQL to manipulate relational databases. Many
DBMS, such as Microsoft Access, allow you to use QBE (Query-by-
Example), a graphical query tool, to retrieve data though visualized
commands. QBE generates SQL for you, and is easy to use. In
comparison with SQL, QBE has limited functionalities and is unable
to work without the DBMS environment.
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Other Types of Databases
The relational database model is the most used database model
today. However, many other database models exist that provide
different strengths than the relational model. The hierarchical
database model, popular in the 1960s and 1970s, connected data
together in a hierarchy, allowing for a parent/child relationship
between data. The document-centric model allowed for a more
unstructured data storage by placing data into “documents” that
could then be manipulated.
Perhaps the most interesting new development is the concept
of NoSQL (from the phrase “not only SQL”). NoSQL arose from the
need to solve the problem of large-scale databases spread over
several servers or even across the world. For a relational database
to work properly, it is important that only one person be able to
manipulate a piece of data at a time, a concept known as record-
locking. But with today’s large-scale databases (think Google and
Amazon), this is just not possible. A NoSQL database can work with
data in a looser way, allowing for a more unstructured environment,
communicating changes to the data over time to all the servers that
are part of the database.
As stated earlier, the relational database model does not scale
well. The term scale here refers to a database getting larger
and larger, being distributed on a larger number of computers
connected via a network. Some companies are looking to provide
large-scale database solutions by moving away from the relational
model to other, more flexible models. For example, Google now
offers the App Engine Datastore, which is based on NoSQL.
Developers can use the App Engine Datastore to develop
applications that access data from anywhere in the world.
Amazon.com offers several database services for enterprise use,
including Amazon RDS, which is a relational database service, and
Amazon DynamoDB, a NoSQL enterprise solution.
Chapter 4: Data and Databases | 89
Sidebar: What Is Metadata?
The term metadata can be understood as “data about data.”
Examples of metadata of database are:
• number of records
• data type of field
• size of field
• description of field
• default value of field
• rules of use.
When a database is being designed, a “data dictionary” is created to
hold the metadata, defining the fields and structure of the database.
Finding Value in Data: Business Intelligence
With the rise of Big Data and a myriad of new tools and techniques
at their disposal, businesses are learning how to use information to
their advantage. The term business intelligence is used to describe
the process that organizations use to take data they are collecting
and analyze it in the hopes of obtaining a competitive advantage.
Besides using their own data, stored in data warehouses (see below),
firms often purchase information from data brokers to get a big-
picture understanding of their industries and the economy. The
results of these analyses can drive organizational strategies and
provide competitive advantage.
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Data Visualization
Data visualization is the graphical representation of information and
data. These graphical representations (such as charts, graphs, and
maps) can quickly summarize data in a way that is more intuitive
and can lead to new insights and understandings. Just as a picture
of a landscape can convey much more than a paragraph of text
attempting to describe it, graphical representation of data can
quickly make meaning of large amounts of data. Many times,
visualizing data is the first step towards a deeper analysis and
understanding of the data collected by an organization. Examples of
data visualization software include Tableau and Google Data Studio.
Data Warehouses
As organizations have begun to utilize databases as the centerpiece
of their operations, the need to fully understand and leverage the
data they are collecting has become more and more apparent.
However, directly analyzing the data that is needed for day-to-day
operations is not a good idea; we do not want to tax the operations
of the company more than we need to. Further, organizations also
want to analyze data in a historical sense: How does the data we
have today compare with the same set of data this time last month,
or last year? From these needs arose the concept of the data
warehouse.
The concept of the data warehouse is simple: extract data from
one or more of the organization’s databases and load it into the
data warehouse (which is itself another database) for storage and
analysis. However, the execution of this concept is not that simple.
A data warehouse should be designed so that it meets the following
criteria:
• It uses non-operational data. This means that the data
Chapter 4: Data and Databases | 91
Data Warehouse Process (top-down)
warehouse is using a copy of data from the active databases
that the company uses in its day-to-day operations, so the
data warehouse must pull data from the existing databases on
a regular, scheduled basis.
• The data is time-variant. This means that whenever data is
loaded into the data warehouse, it receives a time stamp,
which allows for comparisons between different time periods.
• The data is standardized. Because the data in a data warehouse
usually comes from several different sources, it is possible that
the data does not use the same definitions or units. For
example, each database uses its own format for dates (e.g.,
mm/dd/yy, or dd/mm/yy, or yy/mm/dd, etc.). In order for
the data warehouse to match up dates, a standard date format
would have to be agreed upon and all data loaded into the data
warehouse would have to be converted to use this standard
format. This process is called extraction-transformation-load
(ETL).
There are two primary schools of thought when designing a data
warehouse: bottom-up and top-down. The bottom-up approach
starts by creating small data warehouses, called data marts, to solve
specific business problems. As these data marts are created, they
can be combined into a larger data warehouse. The top- down
approach suggests that we should start by creating an enterprise-
wide data warehouse and then, as specific business needs are
identified, create smaller data marts from the data warehouse.
Benefits of Data
Warehouses
Organizations find data
warehouses quite beneficial for a number of reasons:
92 | Information Systems for Business and Beyond (2019)
• The process of developing a data warehouse forces an
organization to better understand the data that it is currently
collecting and, equally important, what data is not being
collected.
• A data warehouse provides a centralized view of all data being
collected across the enterprise and provides a means for
determining data that is inconsistent.
• Once all data is identified as consistent, an organization can
generate “one version of the truth”. This is important when the
company wants to report consistent statistics about itself,
such as revenue or number of employees.
• By having a data warehouse, snapshots of data can be taken
over time. This creates a historical record of data, which allows
for an analysis of trends.
• A data warehouse provides tools to combine data, which can
provide new information and analysis.
Data Mining and Machine Learning
Data mining is the process of analyzing data to find previously
unknown and interesting trends, patterns, and associations in order
to make decisions. Generally, data mining is accomplished through
automated means against extremely large data sets, such as a data
warehouse. Some examples of data mining include:
• An analysis of sales from a large grocery chain might
determine that milk is purchased more frequently the day after
it rains in cities with a population of less than 50,000.
• A bank may find that loan applicants whose bank accounts
show particular deposit and withdrawal patterns are not good
credit risks.
• A baseball team may find that collegiate baseball players with
specific statistics in hitting, pitching, and fielding make for
Chapter 4: Data and Databases | 93
more successful major league players.
One data mining method that an organization can use to do these
analyses is called machine learning. Machine learning is used to
analyze data and build models without being explicitly programmed
to do so. Two primary branches of machine learning exist:
supervised learning and unsupervised learning.
Supervised learning occurs when an organization has data about
past activity that has occurred and wants to replicate it. For
example, if they want to create a new marketing campaign for a
particular product line, they may look at data from past marketing
campaigns to see which of their consumers responded most
favorably. Once the analysis is done, a machine learning model is
created that can be used to identify these new customers. It is called
“supervised” learning because we are directing (supervising) the
analysis towards a result (in our example: consumers who respond
favorably). Supervised learning techniques include analyses such as
decision trees, neural networks, classifiers, and logistic regression.
Unsupervised learning occurs when an organization has data and
wants to understand the relationship(s) between different data
points. For example, if a retailer wants to understand purchasing
patterns of its customers, an unsupervised learning model can be
developed to find out which products are most often purchased
together or how to group their customers by purchase history. Is
it called “unsupervised” learning because no specific outcome is
expected. Unsupervised learning techniques include clustering and
association rules.
Privacy Concerns
The increasing power of data mining has caused concerns for many,
especially in the area of privacy. In today’s digital world, it is
becoming easier than ever to take data from disparate sources and
94 | Information Systems for Business and Beyond (2019)
combine them to do new forms of analysis. In fact, a whole industry
has sprung up around this technology: data brokers. These firms
combine publicly accessible data with information obtained from
the government and other sources to create vast warehouses of
data about people and companies that they can then sell. This
subject will be covered in much more detail in chapter 12 – the
chapter on the ethical concerns of information systems.
Sidebar: What is data science? What is data
analytics?
The term “data science” is a popular term meant to describe the
analysis of large data sets to find new knowledge. For the past
several years, it has been considered one of the best career fields
to get into due to its explosive growth and high salaries. While a
data scientist does many different things, their focus is generally
on analyzing large data sets using various programming methods
and software tools to create new knowledge for their organization.
Data scientists are skilled in machine learning and data visualization
techniques. The field of data science is constantly changing, and
data scientists are on the cutting edge of work in areas such as
artificial intelligence and neural networks.
Knowledge Management
We end the chapter with a discussion on the concept of knowledge
management (KM). All companies accumulate knowledge over the
Chapter 4: Data and Databases | 95
https://www.forbes.com/sites/louiscolumbus/2019/01/23/data-scientist-leads-50-best-jobs-in-america-for-2019-according-to-glassdoor/#2cb23c4b7474
course of their existence. Some of this knowledge is written down
or saved, but not in an organized fashion. Much of this knowledge
is not written down; instead, it is stored inside the heads of its
employees. Knowledge management is the process of creating,
formalizing the capture, indexing, storing, and sharing of the
company’s knowledge in order to benefit from the experiences and
insights that the company has captured during its existence.
Summary
In this chapter, we learned about the role that data and databases
play in the context of information systems. Data is made up of
facts of the world. If you process data in a particular context, then
you have information. Knowledge is gained when information is
consumed and used for decision making. A database is an organized
collection of related data. Relational databases are the most widely
used type of database, where data is structured into tables and all
tables must be related to each other through unique identifiers. A
database management system (DBMS) is a software application that
is used to create and manage databases, and can take the form of
a personal DBMS, used by one person, or an enterprise DBMS that
can be used by multiple users. A data warehouse is a special form of
database that takes data from other databases in an enterprise and
organizes it for analysis. Data mining is the process of looking for
patterns and relationships in large data sets. Many businesses use
databases, data warehouses, and data-mining techniques in order to
produce business intelligence and gain a competitive advantage.
96 | Information Systems for Business and Beyond (2019)
Study Questions
1. What is the difference between data, information, and
knowledge?
2. Explain in your own words how the data component relates to
the hardware and software components of information
systems.
3. What is the difference between quantitative data and
qualitative data? In what situations could the number 42 be
considered qualitative data?
4. What are the characteristics of a relational database?
5. When would using a personal DBMS make sense?
6. What is the difference between a spreadsheet and a database?
List three differences between them.
7. Describe what the term normalization means.
8. Why is it important to define the data type of a field when
designing a relational database?
9. Name a database you interact with frequently. What would
some of the field names be?
10. What is metadata?
11. Name three advantages of using a data warehouse.
12. What is data mining?
13. In your own words, explain the difference between supervised
learning and unsupervised learning. Give an example of each
(not from the book).
Exercises
1. Review the design of the School database earlier in this
chapter. Reviewing the lists of data types given, what data
types would you assign to each of the fields in each of the
tables. What lengths would you assign to the text fields?
Chapter 4: Data and Databases | 97
2. Download Apache OpenOffice.org and use the database tool to
open the “Student Clubs.odb” file available here. Take some
time to learn how to modify the database structure and then
see if you can add the required items to support the tracking of
faculty advisors, as described at the end of the Normalization
section in the chapter. Here is a link to the Getting Started
documentation.
3. Using Microsoft Access, download the database file of
comprehensive baseball statistics from the website
SeanLahman.com. (If you don’t have Microsoft Access, you can
download an abridged version of the file here that is
compatible with Apache Open Office). Review the structure of
the tables included in the database. Come up with three
different data-mining experiments you would like to try, and
explain which fields in which tables would have to be analyzed.
4. Do some original research and find two examples of data
mining. Summarize each example and then write about what
the two examples have in common.
5. Conduct some independent research on the process of
business intelligence. Using at least two scholarly or
practitioner sources, write a two-page paper giving examples
of how business intelligence is being used.
6. Conduct some independent research on the latest
technologies being used for knowledge management. Using at
least two scholarly or practitioner sources, write a two-page
paper giving examples of software applications or new
technologies being used in this field.
98 | Information Systems for Business and Beyond (2019)
http://www.openoffice.org/download/
http://www.saylor.org/site/wp-content/uploads/2014/02/Student-Clubs.odb
http://wiki.openoffice.org/w/images/3/3c/0108GS33-GettingStartedWithBase
http://wiki.openoffice.org/w/images/3/3c/0108GS33-GettingStartedWithBase
http://www.seanlahman.com/baseball-archive/statistics/
http://www.saylor.org/site/wp-content/uploads/2014/02/lahman.odb
- Information Systems for Business and Beyond (2019)
- Title Page
- Copyright
- Book Contributors
- Changes from Previous Edition
- How you can help
- Part I: What is an information system?
- Part II: Information Systems for Strategic Advantage
- Part III: Information Systems Beyond the Organization
- Index
Information Systems for Business and Beyond (2019)
Introduction
Chapter 1: What Is an Information System?
Chapter 2: Hardware
Chapter 3: Software
Chapter 4: Data and Databases
Chapter 5: Networking and Communication
Chapter 6: Information Systems Security
Chapter 7: Does IT Matter?
Chapter 8: Business Processes
Chapter 9: The People in Information Systems
Chapter 10: Information Systems Development
Chapter 11: Globalization and the Digital Divide
Chapter 12: The Ethical and Legal Implications of Information Systems
Chapter 13: Trends in Information Systems
41
3
TeChnology as a
vaRiable anD Responsive
oRg aniz aTional Dynamism
This chapter focuses on defining the components of technology and
how they affect corporate organizations. In other words, if we step
back momentarily from the specific challenges that information tech-
nology (IT) poses, we might ask the following: What are the generic
aspects of technology that have made it an integral part of strategic and
competitive advantage for many organizations? How do organizations
respond to these generic aspects as catalysts of change? Furthermore,
how do we objectively view the role of technology in this context, and
how should organizations adjust to its short- and long-term impacts?
Technological Dynamism
To begin, technology can be regarded as a variable, independent
of others, that contributes to the life of a business operation. It is
capable of producing an overall, totalizing, yet distinctive, effect on
organizations— it has the unique capacity to create accelerations of
corporate events in an unpredictable way. Technology, in its aspect of
unpredictability, is necessarily a variable, and in its capacity as accel-
erator— its tendency to produce change or advance— it is dynamic.
My contention is that, as a dynamic kind of variable, technology, via
responsive handling or management, can be tapped to play a special
role in organizational development. It can be pressed into service as
the dynamic catalyst that helps bring organizations to maturity in
dealing not only with new technological quandaries, but also with
other agents of change. Change generates new knowledge, which in
turn requires a structure of learning that should, if managed properly,
4 2 INFORMATION TECHNOLO GY
result in transformative behavior, supporting the continued evolution
of organizational culture. Specifically, technology speeds up events,
such as the expectation of getting a response to an e-mail, and requires
organizations to respond to them in ever-quickening time frames.
Such events are not as predictable as those experienced by individuals
in organizations prior to the advent of new technologies— particu-
larly with the meteoric advance of the Internet. In viewing technology
then as a dynamic variable, and one that requires systemic and cul-
tural organizational change, we may regard it as an inherent, internal
driving force— a form of technological dynamism.
Dynamism is defined as a process or mechanism responsible for the
development or motion of a system. Technological dynamism charac-
terizes the unpredictable and accelerated ways in which technology,
specifically, can change strategic planning and organizational behav-
ior/culture. This change is based on the acceleration of events and
interactions within organizations, which in turn create the need to
better empower individuals and departments. Another way of under-
standing technological dynamism is to think of it as an internal drive
recognized by the symptoms it produces. The new events and interac-
tions brought about by technology are symptoms of the
dynamism
that technology manifests. The next section discusses how organiza-
tions can begin to make this inherent dynamism work in their favor
on different levels.
Responsive Organizational Dynamism
The technological dynamism at work in organizations has the power
to disrupt any antecedent sense of comfortable equilibrium or an
unwelcome sense of stasis. It also upsets the balance among the vari-
ous factors and relationships that pertain to the question of how we
might integrate new technologies into the business— a question of
what we will call strategic integration— and how we assimilate the cul-
tural changes they bring about organizationally— a question of what
we call cultural assimilation. Managing the dynamism, therefore, is a
way of managing the effects of technology. I propose that these orga-
nizational ripples, these precipitous events and interactions, can be
addressed in specific ways at the organizational management level.
The set of integrative responses to the challenges raised by technology
4 3teChnolo GY As A vArIAble And resp onsIve
is what I am calling responsive organizational dynamism, which will
also receive further explication in the next few chapters. For now, we
need to elaborate the two distinct categories that present themselves
in response to technological dynamism: strategic integration and cul-
tural assimilation. Figure 3.1 diagrams the relationships.
Strategic Integration
Strategic integration is a process that addresses the business- strategic
impact of technology on organizational processes. That is, the
business-strategic impact of technology requires immediate orga-
nizational responses and in some instances zero latency. Strategic
integration recognizes the need to scale resources across traditional
business– geographic boundaries, to redefine the value chain in the
life cycle of a product or service line, and generally to foster more
agile business processes (Murphy, 2002). Strategic integration, then,
Technology as an
independent
variable
Creates
Organizational
dynamism
Acceleration of events that
require different
infrastructures and
organizational processes
Requires
Strategic
integration
Cultural
assimilation
Symptoms and
implications
Figure 3.1 Responsive organizational dynamism.
4 4 INFORMATION TECHNOLO GY
is a way to address the changing requirements of business processes
caused by the sharp increases in uses of technology. Evolving tech-
nologies have become catalysts for competitive initiatives that create
new and different ways to determine successful business investment.
Thus, there is a dynamic business variable that drives the need for
technology infrastructures capable of greater flexibility and of exhib-
iting greater integration with all business operations.
Historically, organizational experiences with IT investment have
resulted in two phases of measured returns. The first phase often
shows negative or declining productivity as a result of the investment;
in the second phase, we often see a lagging of, although eventual
return to, productivity. The lack of returns in the first phase has been
attributed to the nature of the early stages of technology exploration
and experimentation, which tend to slow the process of organizational
adaptation to technology. The production phase then lags behind
the ability of the organization to integrate new technologies with
its existing processes. Another complication posed by technological
dynamism via the process of strategic integration is a phenomenon we
can call factors of multiplicity — essentially, what happens when several
new technology opportunities overlap and create myriad projects that
are in various phases of their developmental life cycle. Furthermore,
the problem is compounded by lagging returns in productivity, which
are complicated to track and to represent to management. Thus, it is
important that organizations find ways to shorten the period between
investment and technology’ s effective deployment. Murphy (2002)
identifies several factors that are critical to bridging this delta:
1. Identifying the processes that can provide acceptable business
returns from new technological investments
2. Establishing methodologies that can determine these processes
3. Finding ways to actually perform and realize expected benefits
4. Integrating IT projects with other projects
5. Adjusting project objectives when changes in the business
require them
Technology complicates these actions, making them more difficult
to resolve; hence the need to manage the complications. To tackle
these compounded concerns, strategic integration can shorten life
cycle maturation by focusing on the following integrating factors:
4 5teChnolo GY As A vArIAble And resp onsIve
• Addressing the weaknesses in management organizations in
terms of how to deal with new technologies, and how to bet-
ter realize business benefits
• Providing a mechanism that both enables organizations to
deal with accelerated change caused by technological innova-
tions and integrates them into a new cycle of processing and
handling change
• Providing a strategic learning framework by which every new
technology variable adds to organizational knowledge, par-
ticularly using reflective practices (see Chapter 4)
• Establishing an integrated approach that ties technology
accountability to other measurable outcomes using organiza-
tional learning techniques and theories
To realize these objectives, organizations must be able to
• Create dynamic internal processes that can function on a
daily basis to deal with understanding the potential fit of new
technologies and their overall value to the business
• Provide the discourse to bridge the gaps between IT- and
non-IT-related investments and uses into an integrated system
• Monitor investments and determine modifications to the life
cycle
• Implement various organizational learning practices, includ-
ing learning organization, knowledge management, change
management, and communities of practice, all of which help
foster strategic thinking and learning that can be linked to
performance (Gephardt & Marsick, 2003)
Another important aspect of strategic integration is what Murphy
(2002) calls “ consequential interoperability,” in which “ the conse-
quences of a business process” are understood to “ dynamically trigger
integration” (p. 31). This integration occurs in what he calls the five
pillars of benefits realization:
1. Strategic alignment: The alignment of IT strategically with
business goals and objectives.
2. Business process impact: The impact on the need for the organi-
zation to redesign business processes and integrate them with
new technologies.
4 6 INFORMATION TECHNOLO GY
3. Architecture: The actual technological integration of appli-
cations, databases, and networks to facilitate and support
implementation.
4. Payback: The basis for computing return on investment (ROI)
from both direct and indirect perspectives.
5. Risk: Identifying the exposure for underachievement or fail-
ure in the technology investment.
Murphy’ s (2002) pillars are useful in helping us understand how
technology can engender the need for responsive organizational dyna-
mism (ROD), especially as it bears on issues of strategic integration.
They also help us understand what becomes the strategic integration
component of ROD. His theory on strategic alignment and business
process impact supports the notion that IT will increasingly serve as an
undergirding force, one that will drive enterprise growth by identify-
ing the initiators (such as e-business on the Internet) that best fit busi-
ness goals. Many of these initiators will be accelerated by the growing
use of e-business, which becomes the very driver of many new market
realignments. This e-business realignment will require the ongoing
involvement of executives, business managers, and IT managers. In
fact, the Gartner Group forecasted that 70% of new software applica-
tion investments and 5% of new infrastructure expenditures by 2005
would be driven by e-business. Indeed, this has occurred and contin-
ues to expand.
The combination of evolving business drivers with accelerated and
changing customer demands has created a business revolution that
best defines the imperative of the strategic integration component of
ROD. The changing and accelerated way businesses deal with their
customers and vendors requires a new strategic integration to become
a reality rather than remain a concept discussed but affecting little
action. Without action directed toward new strategic integration,
organizations would lose competitive advantage, which would affect
profits. Most experts see e-business as the mechanism that will ulti-
mately require the integrated business processes to be realigned, thus
providing value to customers and modifying the customer– vendor
relationship. The driving force behind this realignment emanates from
the Internet, which serves as the principle accelerator of the change
in transactions across all businesses. The general need to optimize
47teChnolo GY As A vArIAble And resp onsIve
resources forces organizations to rethink and to realign business pro-
cesses to gain access to new business markets.
Murphy’ s (2002) pillar of architecture brings out yet another aspect
of ROD. By architecture we mean the focus on the effects that technol-
ogy has on existing computer applications or legacy systems (old exist-
ing systems). Technology requires existing IT systems to be modified
or replacement systems to be created that will mirror the new busi-
ness realignments. These changes respond to the forces of strategic
integration and require business process reengineering (BPR) activi-
ties, which represent the reevaluation of existing systems based on
changing business requirements. It is important to keep in mind the
acceleration factors of technology and to recognize the amount of
organizational effort and time that such projects take to complete. We
must ask the following question: How might organizations respond to
these continual requirements to modify existing processes? I discuss
in other chapters how ROD represents the answer to this question.
Murphy’ s (2002) pillar of direct return is somewhat limited and nar-
row because not all IT value can be associated with direct returns, but
it is important to discuss. Technology acceleration is forcing organiza-
tions to deal with broader issues surrounding what represents a return
from an investment. The value of strategic integration relies heavily on
the ability of technology to encapsulate itself within other departments
where it ultimately provides the value. We show in Chapter 4 that
this issue also has significance in organizational formation. What this
means is simply that value can be best determined within individual
business units at the microlevel and that these appropriate-level busi-
ness units also need to make the case for why certain investments need
to be pursued. There are also paybacks that are indirect; for example,
Lucas (1999) demonstrates that many technology investments are non-
monetary. The IT department (among others) becomes susceptible to
great scrutiny and subject to budgetary cutbacks during economically
difficult times. This does not suggest that IT “ hide” itself but rather
that its investment be integrated within the unit where it provides the
most benefit. Notwithstanding the challenge to map IT expenditures
to their related unit, there are always expenses that are central to all
departments, such as e-mail and network infrastructure. These types
of expenses can rarely provide direct returns and are typically allocated
across departments as a cost of doing business.
4 8 INFORMATION TECHNOLO GY
Because of the increased number of technology opportuni-
ties, Murphy’ s (2002) risk pillar must be a key part of strategic
integration. The concept of risk assessment is not new to an organiza-
tion; however, it is somewhat misunderstood as it relates to technology
assessment. Technology assessment, because of the acceleration factor,
must be embedded within the strategic decision-making process. This
can only be accomplished by having an understanding of how to align
technology opportunities for business change and by understanding
the cost of forgoing the opportunity as well as the cost of delays in
delivery. Many organizations use risk assessment in an unstructured
way, which does not provide a consistent framework to dynamically
deal with emerging technologies. Furthermore, such assessment needs
to be managed at all levels in the organization as opposed to being an
event-driven activity controlled only by executives.
Summary
Strategic integration represents the objective of dealing with emerg-
ing technologies on a regular basis. It is an outcome of ROD, and it
requires organizations to deal with a variable, that forces acceleration
of decisions in an unpredictable fashion. Strategic integration would
require businesses to realign the ways in which they include technol-
ogy in strategic decision making.
Cultural Assimilation
Cultural assimilation is a process that focuses on the organizational
aspects of how technology is internally organized, including the role
of the IT department, and how it is assimilated within the organiza-
tion as a whole. The inherent, contemporary reality of technologi-
cal dynamism requires not only strategic but also cultural change.
This reality demands that IT organizations connect to all aspects of
the business. Such affiliation would foster a more interactive culture
rather than one that is regimented and linear, as is too often the case.
An interactive culture is one that can respond to emerging technology
decisions in an optimally informed way, and one that understands the
impact on business performance.
4 9teChnolo GY As A vArIAble And resp onsIve
The kind of cultural assimilation elicited by technological dyna-
mism and formalized in ROD is divided into two subcategories: the
study of how the IT organization relates and communicates with
“ others,” and the actual displacement or movement of traditional
IT staff from an isolated “ core” structure to a firm-wide, integrated
framework.
IT Organization Communications with “ Others”
The Ravell case study shows us the limitations and consequences of
an isolated IT department operating within an organization. The case
study shows that the isolation of a group can lead to marginalization,
which results in the kind of organization in which not all individuals
can participate in decision making and implementation, even though
such individuals have important knowledge and value. Technological
dynamism is forcing IT departments to rethink their strategic posi-
tion within the organizational structure of their firm. No longer can
IT be a stand-alone unit designed just to service outside departments
while maintaining its separate identity. The acceleration factors of
technology require more dynamic activity within and among depart-
ments, which cannot be accomplished through discrete communica-
tions between groups. Instead, the need for diverse groups to engage
in more integrated discourse, and to share varying levels of techno-
logical knowledge, as well as business-end perspectives, requires new
organizational structures that will of necessity give birth to a new
and evolving business— social culture. Indeed, the need to assimilate
technology creates a transformative effect on organizational cultures,
the way they are formed and re-formed, and what they will need from
IT personnel.
Movement of Traditional IT Staff
To facilitate cultural assimilation from an IT perspective, IT must
become better integrated with non-IT personnel. This form of inte-
gration can require the actual movement of IT staff into other depart-
ments, which begins the process of a true assimilation of resources
among business units. While this may seem like the elimination of
5 0 INFORMATION TECHNOLO GY
the integrity or identity of IT, such a loss is far from the case. The
elimination of the IT department is not at all what is called for here;
on the contrary, the IT department is critical to the function of cul-
tural assimilation. However, the IT department may need to be struc-
tured differently from the way it has been so that it can deal primarily
with generic infrastructure and support issues, such as e-mail, net-
work architecture, and security. IT personnel who focus on business-
specific issues need to become closely aligned with the appropriate
units so that ROD can be successfully implemented.
Furthermore, we must acknowledge that, given the wide range of
available knowledge about technology, not all technological knowl-
edge emanates from the IT department. The question becomes
one of finding the best structure to support a broad assimilation of
knowledge about any given technology; then, we should ask how that
knowledge can best be utilized by the organization. There is a pitfall
in attempting to find a “ standard” IT organizational structure that
will address the cultural assimilation of technology. Sampler’ s (1996)
research, and my recent research with chief executives, confirms that
no such standard structure exists. It is my position that organizations
must find their own unique blend, using organizational learning con-
structs. This simply means that the cultural assimilation of IT may
be unique to the organization. What is then more important for the
success of organizational development is the process of assimilation as
opposed to the transplanting of the structure itself.
Today, many departments still operate within “ silos” where they
are unable to meet the requirements of the dynamic and unpredictable
nature of technology in the business environment. Traditional orga-
nizations do not often support the necessary communications needed
to implement cultural assimilation across business units. However,
business managers can no longer make decisions without considering
technology; they will find themselves needing to include IT staff in
their decision-making processes. On the other hand, IT departments
can no longer make technology-based decisions without concerted
efforts toward assimilation (in contrast to occasional partnering or
project-driven participation) with other business units. This assimi-
lation becomes mature when new cultures evolve synergistically as
opposed to just having multiple cultures that attempt to work in con-
junction with each other. The important lesson from Ravell to keep
51teChnolo GY As A vArIAble And resp onsIve
in mind here is that the process of assimilating IT can create new
cultures that in turn evolve to better support the requirements estab-
lished by the dynamism of technology.
Eventually, these new cultural formations will not perceive them-
selves as functioning within an IT or non-IT decision framework
but rather as operating within a more central business operation that
understands how to incorporate varying degrees of IT involvement
as necessary. Thus, organizational cultures will need to fuse together
to respond to new business opportunities and requirements brought
about by the ongoing acceleration of technological innovation. This
was also best evidenced by subsequent events at Ravell. Three years
after the original case study, it became necessary at Ravell to inte-
grate one of its business operations with a particular group of IT staff
members. The IT personnel actually transferred to the business unit
to maximize the benefits of merging both business and technical cul-
tures. Interestingly, this business unit is currently undergoing cultural
assimilation and is developing its own behavioral norms influenced by
the new IT staff. However, technology decisions within such groups
are not limited to the IT transferred personnel. IT and non-IT staff
need to formulate decisions using various organizational learning
techniques. These techniques are discussed in the next chapter.
Summary
Without appropriate cultural assimilation, organizations tend to have
staff that “ take shortcuts, [then] the loudest voice will win the day, ad
hoc decisions will be made, accountabilities lost, and lessons from suc-
cesses and failures will not become part of … wisdom” (Murphy, 2002,
p. 152). As in the case of Ravell Corporation, it is essential, then, to
provide for consistent governance that fits the profile of the existing cul-
ture or can establish the need for a new culture. While many scholars
and managers suggest the need to have a specific entity responsible for
IT governance, one that is to be placed within the operating structure
of the organization, such an approach creates a fundamental problem.
It does not allow staff and managers the opportunity to assimilate tech-
nologically driven change and understand how to design a culture that
can operate under ROD. In other words, the issue of governance is
misinterpreted as a problem of structural positioning or hierarchy when
5 2 INFORMATION TECHNOLO GY
it is really one of cultural assimilation. As a result, many business solu-
tions to technology issues often lean toward the prescriptive, instead of
the analytical, in addressing the real problem.
Murphy’ s (2002) risk pillar theory offers us another important
component relevant to cultural assimilation. This approach addresses
the concerns that relate to the creation of risk cultures formed to deal
with the impact of new systems. New technologies can actually cause
changes in cultural assimilation by establishing the need to make cer-
tain changes in job descriptions, power structures, career prospects,
degree of job security, departmental influence, or ownership of data.
Each of these potential risks needs to be factored in as an important
part of considering how best to organize and assimilate technology
through ROD.
Technology Business Cycle
To better understand technology dynamism, or how technology acts as
a dynamic variable, it is necessary to define the specific steps that occur
during its evolution in an organization. The evolution or business cycle
depicts the sequential steps during the maturation of a new technology
from feasibility to implementation and through subsequent evolution.
Table 3.1 shows the five components that comprise the cycle: feasibil-
ity, measurement, planning, implementation, and evolution.
Table 3.1 Technology Business Cycle
CYCLE COMPONENT COMPONENT DESCRIPTION
Feasibility Understanding how to view and evaluate emerging technologies, from a
technical and business perspective.
Measurement Dealing with both the direct monetary returns and indirect nonmonetary
returns; establishing driver and support life cycles.
Planning Understanding how to set up projects, establishing participation across
multiple layers of management, including operations and departments.
Implementation Working with the realities of project management; operating with political
factions, constraints; meeting milestones; dealing with setbacks; having
the ability to go live with new systems.
Evolution Understanding how acceptance of new technologies affects cultural
change, and how uses of technology will change as individuals and
organizations become more knowledgeable about technology, and
generate new ideas about how it can be used; objective is established
through organizational dynamism, creating new knowledge and an
evolving organization.
5 3teChnolo GY As A vArIAble And resp onsIve
Feasibility
The stage of feasibility focuses on a number of issues surrounding
the practicality of implementing a specific technology. Feasibility
addresses the ability to deliver a product when it is needed in com-
parison to the time it takes to develop it. Risk also plays a role in
feasibility assessment; of specific concern is the question of whether
it is possible or probable that the product will become obsolete before
completion. Cost is certainly a huge factor, but viewed at a “ high
level” (i.e., at a general cost range), and it is usually geared toward
meeting the expected ROI of a firm. The feasibility process must be
one that incorporates individuals in a way that allows them to respond
to the accelerated and dynamic process brought forth by technological
innovations.
Measurement
Measurement is the process of understanding how an investment in
technology is calculated, particularly in relation to the ROI of an
organization. The complication with technology and measurement
is that it is simply not that easy to determine how to calculate such
a return. This problem comes up in many of the issues discussed by
Lucas (1999) in his book Information Technology and the Productivity
Paradox. His work addresses many comprehensive issues, surround-
ing both monetary and nonmonetary ROI, as well as direct ver-
sus indirect allocation of IT costs. Aside from these issues, there
is the fact that for many investments in technology the attempt to
compute ROI may be an inappropriate approach. As stated, Lucas
offered a “ garbage can” model that advocates trust in the operational
management of the business and the formation of IT representatives
into productive teams that can assess new technologies as a regu-
lar part of business operations. The garbage can is an abstract con-
cept for allowing individuals a place to suggest innovations brought
about by technology. The inventory of technology opportunities
needs regular evaluation. Lucas does not really offer an explana-
tion of exactly how this process should work internally. ROD, how-
ever, provides the strategic processes and organizational– cultural
needs that can provide the infrastructure to better understand and
5 4 INFORMATION TECHNOLO GY
evaluate the potential benefits from technological innovations using
the garbage can model. The graphic depiction of the model is shown
in Figure 3.2.
Planning
Planning requires a defined team of user and IT representatives. This
appears to be a simple task, but it is more challenging to understand
how such teams should operate, from whom they need support, and
what resources they require. Let me be specific. There are a number
of varying types of “ users” of technology. They typically exist in three
tiers: executives, business line managers, and operations users. Each
of these individuals offers valuable yet different views of the benefits
of technology (Langer, 2002). I define these user tiers as follows:
1. Executives: These individuals are often referred to as execu
tive sponsors. Their role is twofold. First, they provide input
into the system, specifically from the perspective of pro-
ductivity, ROI, and competitive edge. Second, and per-
haps more important, their responsibility is to ensure that
users are participating in the requisite manner (i.e., made
Garbage can
model of IT value
Failed systems
Direct
benefits
Indirect
benefits
User
needs, etc.
C
on
ve
rs
io
n
eff
ec
ti
ve
ne
ss
�e IT value pipeline
Figure 3.2 Garbage can model of IT value. (From Lucas, H.C., Information Technology and the
Productivity Paradox. Oxford University Press, New York, 1999.)
5 5teChnolo GY As A vArIAble And resp onsIve
to be available, in the right place, etc.). This area can be
problematic because internal users are typically busy doing
their jobs and sometimes neglect to provide input or to
attend project meetings. Furthermore, executive sponsors
can help control political agendas that can hurt the success
of the project.
2. Business line managers: This interface provides the most
information from a business unit perspective. These indi-
viduals are responsible for two aspects of management.
First, they are responsible for the day-to-day productivity
of their unit; therefore, they understand the importance
of productive teams, and how software can assist in this
endeavor. Second, they are responsible for their staff. Thus,
line managers need to know how software will affect their
operational staff.
3. Functional users: These are the individuals in the trenches who
understand exactly how processing needs to get done. While
their purview of the benefits of the system is relatively nar-
rower than that of the executives and managers, they provide
the concrete information that is required to create the feature/
functions that make the system usable.
The planning process becomes challenging when attempting to
get the three user communities to integrate their needs and “ agree to
agree” on how a technology project needs to be designed and managed.
Implementation
Implementation is the process of actually using a technology.
Implementation of technology systems requires wider integration
within the various departments than other systems in an organization
because usually multiple business units are affected. Implementation
must combine traditional methods of IT processes of development
yet integrate them within the constraints, assumptions, and cultural
(perhaps political) environments of different departments. Cultural
assimilation is therefore required at this stage because it delves into
the structure of the internal organization and requires individual
participation in every phase of the development and implementation
5 6 INFORMATION TECHNOLO GY
cycle. The following are some of the unique challenges facing the
implementation of technological projects:
1. Project managers as complex managers: Technology projects
require multiple interfaces that often lie outside the traditional
user community. They can include interfacing with writers,
editors, marketing personnel, customers, and consumers, all
of whom are stakeholders in the success of the system.
2. Shorter and dynamic development schedules: Due to the dynamic
nature of technology, its process of development is less lin-
ear than that of others. Because there is less experience in
the general user community, and there are more stakeholders,
there is a tendency by those in IT, and executives, to underes-
timate the time and cost to complete the project.
3. New untested technologies: There is so much new technol-
ogy offered to organizations that there is a tendency by IT
organizations to implement technologies that have not yet
matured— that are not yet the best products they will eventu-
ally be.
4. Degree of scope changes: Technology, because of its dynamic
nature, tends to be prone to scope creed — the scope of the orig-
inal project expanding during development.
5. Project management: Project managers need to work closely
with internal users, customers, and consumers to advise
them on the impact of changes to the project schedule.
Unfortunately, scope changes that are influenced by changes
in market trends may not be avoidable. Thus, part of a good
strategy is to manage scope changes rather than attempt to
stop them, which might not be realistic.
6. Estimating completion time: IT has always had difficulties in
knowing how long it will take to implement a technology.
Application systems are even more difficult because of the
number of variables and unknowns.
7. Lack of standards: The technology industry continues to be a
profession that does not have a governing body. Thus, it is
impossible to have real enforced standards that other pro-
fessions enjoy. While there are suggestions for best prac-
tices, many of them are unproven and not kept current with
5 7teChnolo GY As A vArIAble And resp onsIve
changing developments. Because of the lack of successful
application projects, there are few success stories to create new
and better sets of best practices.
8. Lessspecialized roles and responsibilities: The IT team tends to
have staff members who have varying responsibilities. Unlike
traditional new technology-driven projects, separation of roles
and responsibilities is more difficult when operating in more
dynamic environments. The reality is that many roles have not
been formalized and integrated using something like ROD.
9. Broad project management responsibilities: Project management
responsibilities need to go beyond those of the traditional IT
manager. Project managers are required to provide manage-
ment services outside the traditional software staff. They need
to interact more with internal and external individuals, as well
as with non-traditional members of the development team,
such as Web text and content staff. Therefore, there are many
more obstacles that can cause implementation problems.
Evolution
The many ways to form a technological organization with a natural
capacity to evolve have been discussed from an IT perspective in this
chapter. However, another important factor is the changing nature
of application systems, particularly those that involve e-businesses.
E-business systems are those that utilize the Internet and engage
in e-commerce activities among vendors, clients, and internal users
in the organization. The ways in which e-business systems are built
and deployed suggest that they are evolving systems. This means
that they have a long life cycle involving ongoing maintenance and
enhancement. They are, if you will, “ living systems” that evolve
in a manner similar to organizational cultures. So, the traditional
beginning-to-end life cycle does not apply to an e-business proj-
ect that must be implemented in inherently ongoing and evolving
phases. The important focus is that technology and organizational
development have parallel evolutionary processes that need to be in
balance with each other. This philosophy is developed further in the
next chapter.
5 8 INFORMATION TECHNOLO GY
Drivers and Supporters
There are essentially two types of generic functions performed by
departments in organizations: driver functions and supporter func-
tions. These functions relate to the essential behavior and nature of
what a department contributes to the goals of the organization. I
first encountered the concept of drivers and supporters at Coopers
& Lybrand, which was at that time a Big 8* accounting firm. I stud-
ied the formulation of driver versus supporter as it related to the role
of our electronic data processing (EDP) department. The firm was
attempting to categorize the EDP department as either a driver or a
supporter.
Drivers were defined in this instance as those units that engaged
in frontline or direct revenue-generating activities. Supporters were
units that did not generate obvious direct revenues but rather were
designed to support frontline activities. For example, operations such
as internal accounting, purchasing, or office management were all
classified as supporter departments. Supporter departments, due to
their nature, were evaluated on their effectiveness and efficiency or
economies of scale. In contrast, driver organizations were expected to
generate direct revenues and other ROI value for the firm. What was
also interesting to me at the time was that drivers were expected to
be more daring— since they must inevitably generate returns for the
business. As such, drivers engaged in what Bradley and Nolan (1998)
coined “ sense and respond” behaviors and activities. Let me explain.
Marketing departments often generate new business by investing
or “ sensing” an opportunity quickly because of competitive forces
in the marketplace. Thus, they must sense an opportunity and be
allowed to respond to it in a timely fashion. The process of sensing
opportunity, and responding with competitive products or services,
is a stage in the cycle that organizations need to support. Failures in
the cycles of sense and respond are expected. Take, for example, the
* The original “ Big 8” consisted of the eight large accounting and management con-
sulting firms— Coopers & Lybrand, Arthur Anderson, Touche Ross, Deloitte
Haskins & Sells, Arthur Young, Price Waterhouse, Pete Marwick Mitchell, and
Ernst and Whinney— until the late 1980s, when these firms began to merge. Today,
there are four: Price Waterhouse Coopers, Deloitte & Touche, Ernst & Young, and
KPMG (Pete Marwick and others).
5 9teChnolo GY As A vArIAble And resp onsIve
launching of new fall television shows. Each of the major stations
goes through a process of sensing which shows might be interesting to
the viewing audience. They respond, after research and review, with a
number of new shows. Inevitably, only a few of these selected shows
are actually successful; some fail almost immediately. While relatively
few shows succeed, the process is acceptable and is seen by manage-
ment as the consequence of an appropriate set of steps for competing
effectively— even though the percentage of successful new shows is
low. Therefore, it is safe to say that driver organizations are expected
to engage in high-risk operations, of which many will fail, for the sake
of creating ultimately successful products or services.
The preceding example raises two questions: (1) How does sense
and respond relate to the world of IT? and (2) Why is it important?
IT is unique in that it is both a driver and a supporter. The latter is the
generally accepted norm in most firms. Indeed, most IT functions are
established to support myriad internal functions, such as
• Accounting and finance
• Data center infrastructure (e-mail, desktop, etc.)
• Enterprise-level application (enterprise resource planning, ERP)
• Customer support (customer relationship management, CRM)
• Web and e-commerce activities
As one would expect, these IT functions are viewed as overhead
related, as somewhat of a commodity, and thus are constantly man-
aged on an economy-of-scale basis— that is, how can we make this
operation more efficient, with a particular focus on cost containment?
So, what then are IT driver functions? By definition, they are those
that engage in direct revenues and identifiable ROI. How do we define
such functions in IT because most activities are sheltered under the
umbrella of marketing organization domains? (Excluding, of course,
software application development firms that engage in marketing for
their actual application products.) I define IT driver functions as those
projects that, if delivered, would change the relationship between the
organization and its customers; that is, those activities that directly
affect the classic definition of a market: forces of supply and demand,
which are governed by the customer (demand) and the vendor (sup-
plier) relationship. This concept can be shown in the case example that
follows.
6 0 INFORMATION TECHNOLO GY
Santander versus Citibank
Santander Bank, the major bank of Spain, had enjoyed a dominant
market share in its home country. Citibank had attempted for years to
penetrate Santander’ s dominance using traditional approaches (open-
ing more branch offices, marketing, etc.) without success, until, that
is, they tried online banking. Using technology as a driver, Citibank
made significant penetration into the market share of Santander
because it changed the customer– vendor relationship. Online bank-
ing, in general, has had a significant impact on how the banking
industry has established new markets, by changing this relationship.
What is also interesting about this case is the way in which Citibank
accounted for its investment in online banking; it knows little about
its total investment and essentially does not care about its direct pay-
back. Rather, Citibank sees its ROI in a similar way that depicts
driver/marketing behavior; the payback is seen in broader terms to
affect not only revenue generation, but also customer support and
quality recognition.
Information Technology Roles and Responsibilities
The preceding section focuses on how IT can be divided into two dis-
tinct kinds of business operations. As such, the roles and responsibili-
ties within IT need to change accordingly and be designed under the
auspices of driver and supporter theory. Most traditional IT depart-
ments are designed to be supporters, so that they have a close-knit
organization that is secure from outside intervention and geared to
respond to user needs based on requests. While in many instances
this type of formation is acceptable, it is limited in providing the IT
department with the proper understanding of the kind of business
objectives that require driver-type activities. This was certainly the
experience in the Ravell case study. In that instance, I found that
making the effort to get IT support personnel “ out from their com-
fortable shells” made a huge difference in providing better service
to the organization at large. Because more and more technology is
becoming driver essential, this development will require of IT per-
sonnel an increasing ability to communicate to managers and execu-
tives and to assimilate within other departments.
61teChnolo GY As A vArIAble And resp onsIve
The Ravell case, however, also brought to light the huge vacuum of
IT presence in driver activities. The subsequent chief executive inter-
view study also confirmed that most marketing IT-oriented activities,
such as e-business, do not fall under the purview of IT in most orga-
nizations. The reasons for this separation are correlated with the lack
of IT executive presence within the management team.
Another aspect of driver and supporter functions is the concept of
a life cycle. A life cycle, in this respect, refers to the stages that occur
before a product or service becomes obsolete. Technology products
have a life cycle of value just as any other product or service. It is
important not to confuse this life cycle with processes during devel-
opment as discussed elsewhere in this chapter.
Many technical products are adopted because they are able to deliver
value that is typically determined based on ROI calculations. However,
as products mature within an organization, they tend to become more of
a commodity, and as they are normalized, they tend to become support-
oriented. Once they reach the stage of support, the rules of economies
of scale become more important and relevant to evaluation. As a prod-
uct enters the support stage, replacement based on economies of scale
can be maximized by outsourcing to an outside vendor who can provide
the service cheaper. New technologies then can be expected to follow
this kind of life cycle, by which their initial investment requires some
level of risk to provide returns to the business. This initial investment
is accomplished in ROD using strategic integration. Once the evalua-
tions are completed, driver activities will prevail during the maturation
process of the technology, which will also require cultural assimilation.
Inevitably, technology will change organizational behavior and struc-
ture. However, once the technology is assimilated and organizational
behavior and structures are normalized, individuals will use it as a per-
manent part of their day-to-day operations. Thus, driver activities give
way to those of supporters. Senior managers become less involved, and
line managers then become the more important group that completes
the transition from driver to supporter.
Replacement or Outsource
After the technology is absorbed into operations, executives will seek
to maximize the benefit by increased efficiency and effectiveness.
6 2 INFORMATION TECHNOLO GY
Certain product enhancements may be pursued during this phase; they
can create “ mini-loops” of driver-to-supporter activities. Ultimately, a
technology, viewed in terms of its economies of scale and longevity,
is considered for replacement or outsourcing. Figure 3.3 graphically
shows the cycle.
The final stage of maturity of an evolving driver therefore includes
becoming a supporter, at which time it becomes a commodity and,
finally, an entity with potential for replacement or outsourcing. The
next chapter explores how organizational learning theories can be
used to address many of the issues and challenges brought forth in
this chapter.
Mini loop technology enhancementsTechnology
driver
Evaluation
cycle
Driver
maturation
Support
status
Replacement or
outsource
Economies
of scale
Figure 3.3 Driver-to-supporter life cycle.
- Cover
- Half Title
- Title Page
- Copyright Page
- Contents
- Foreword
- Acknowledgments
- Author
- 1: The “Ravell” Corporation
- 2: The IT Dilemma
- 3: Technology as a Variable and Responsive Organizational Dynamism
- 4: Organizational Learning Theories and Technology
- 5: Managing Organizational Learning and Technology
- 6: Organizational Transformation and the Balanced Scorecard
- 7: Virtual Teams and Outsourcing
- 8: Synergistic Union of IT and Organizational Learning
- 9: Forming a Cyber Security Culture
- 10: Digital Transformation and Changes in Consumer Behavior
- 11: Integrating Generation Y Employees to Accelerate Competitive Advantage
- 12: Toward Best Practices
- 13: Conclusion
- Glossary
- References
- Index
Introduction
Introduction
A New Approach
The Blueprint for Integration
Enlisting Support
Assessing Progress
Resistance in the Ranks
Line Management to the Rescue
IT Begins to Reflect
Defining an Identity for Information Technology
Implementing the Integration: A Move toward Trust and Reflection
Key Lessons
Defining Reflection and Learning for an Organization
Working toward a Clear Goal
Commitment to Quality
Teaching Staff “Not to Know”
Transformation of Culture
Alignment with Administrative Departments
Conclusion
Introduction
Recent Background
IT in the Organizational Context
IT and Organizational Structure
The Role of IT in Business Strategy
Ways of Evaluating IT
Executive Knowledge and Management of IT
IT: A View from the Top
Section 1: Chief Executive Perception of the Role of IT
Section 2: Management and Strategic Issues
Section 3: Measuring IT Performance and Activities
General Results
Defining the IT Dilemma
Recent Developments in Operational Excellence
Introduction
Technological Dynamism
Responsive Organizational Dynamism
Strategic Integration
Summary
Cultural Assimilation
IT Organization Communications with “ Others”
Movement of Traditional IT Staff
Summary
Technology Business Cycle
Feasibility
Measurement
Planning
Implementation
Evolution
Drivers and Supporters
Santander versus Citibank
Information Technology Roles and Responsibilities
Replacement or Outsource
Introduction
Learning Organizations
Communities of Practice
Learning Preferences and Experiential Learning
Social Discourse and the Use of Language
Identity
Skills
Emotion
Linear Development in Learning Approaches
The Role of Line Management
Line Managers
First-Line Managers
Supervisor
Management Vectors
Knowledge Management
Change Management
Change Management for IT Organizations
Social Networks and Information Technology
Introduction
Methods of Ongoing Evaluation
Balanced Scorecards and Discourse
Knowledge Creation, Culture, and Strategy
Introduction
Status of Virtual Teams
Management Considerations
Dealing with Multiple Locations
Externalization
Internalization
Combination
Socialization
Externalization Dynamism
Internalization Dynamism
Combination Dynamism
Socialization Dynamism
Dealing with Multiple Locations and Outsourcing
Revisiting Social Discourse
Identity
Skills
Emotion
Introduction
Siemens AG
Aftermath
ICAP
Five Years Later
HTC
IT History at HTC
Interactions of the CEO
The Process
Transformation from the Transition
Five Years Later
Summary
Introduction
History
Talking to the Board
Establishing a Security Culture
Understanding What It Means to Be Compromised
Cyber Security Dynamism and Responsive Organizational Dynamism
Cyber Strategic Integration
Cyber Cultural Assimilation
Summary
Organizational Learning and Application Development
Cyber Security Risk
Risk Responsibility
Driver /Supporter Implications
Introduction
Requirements without Users and without Input
Concepts of the S-Curve and Digital Transformation Analysis and Design
Organizational Learning and the S-Curve
Communities of Practice
The IT Leader in the Digital Transformation Era
How Technology Disrupts Firms and Industries
Dynamism and Digital Disruption
Critical Components of “ Digital” Organization
Assimilating Digital Technology Operationally and Culturally
Conclusion
Introduction
The Employment Challenge in the Digital Era
Gen Y Population Attributes
Advantages of Employing Millennials to Support Digital Transformation
Integration of Gen Y with Baby Boomers and Gen X
Designing the Digital Enterprise
Assimilating Gen Y Talent from Underserved and Socially Excluded Populations
Langer Workforce Maturity Arc
Theoretical Constructs of the LWMA
The LWMA and Action Research
Implications for New Pathways for Digital Talent
Demographic Shifts in Talent Resources
Economic Sustainability
Integration and Trust
Global Implications for Sources of Talent
Conclusion
Introduction
Chief IT Executive
Definitions of Maturity Stages and Dimension Variables in the Chief IT Executive Best Practices Arc
Maturity Stages
Performance Dimensions
Chief Executive Officer
CIO Direct Reporting to the CEO
Outsourcing
Centralization versus Decentralization of IT
CIO Needs Advanced Degrees
Need for Standards
Risk Management
The CEO Best Practices Technology Arc
Definitions of Maturity Stages and Dimension Variables in the CEO Technology Best Practices Arc
Maturity Stages
Performance Dimensions
Middle Management
The Middle Management Best Practices Technology Arc
Definitions of Maturity Stages and Dimension Variables in the Middle Manager Best Practices Arc
Maturity Stages
Performance Dimensions
Summary
Ethics and Maturity
Introduction
Organizational Learning Definitions
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