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9 Developing and Acquiring Information Systems
After reading this chapter, you will be able to do the following:
1. Describe how to formulate and present the business case for technology investments.
2. Describe the systems development life cycle and its various phases.
3. Explain how organizations acquire systems via external acquisition and outsourcing.
Preview
As you have read throughout this book and have experienced in your own life, information systems and technologies are of many different types,
including high-speed Web servers to rapidly process customer requests, business intelligence systems to aid managerial decision making, and
customer relationship management systems to provide improved customer service. Given this variety, when we refer to “systems” in this chapter, we
are talking about a broad range of technologies, including hardware, software, and services. Just as there are different types of systems, there are
different approaches for developing and acquiring them. If you are a business student majoring in areas such as marketing, finance, accounting, or
management, you might be wondering why we have a discussion about developing and acquiring information systems. The answer is simple: No
matter what area of an organization you are in, you will be involved in systems development or technology acquisition processes. In fact, research
indicates that spending on systems in many organizations is controlled by the specific business functions rather than by the information systems (IS)
department. What this means is that even if your career interests are in something other than information systems, it is very likely that you will be
involved in the development and acquisition of systems, technologies, or services. Understanding this process is important to your future success.
Managing in the Digital World: Microsoft Is “Kinecting” Its Ecosystem
How useful would an iPhone or an Android smartphone be without the apps? How useful would a Blu-ray player be without a large selection of movies
available in that format? The value of many devices or systems grows with the size of their ecosystems, including the users, application or content
developers, sellers, and marketplaces. Like a tree standing still in a world without rain, birds, or flowers—a tree that would likely not be able to survive—the
iPhone sans the “apps” would be much less useful, less exciting, and much less successful in the marketplace. Similarly, Google, Microsoft, and, not
surprisingly, Amazon.com (http://Amazon.com) are trying to build large ecosystems around their products and services (Figure 9.1
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09#ch09fig1) ).
FIGURE 9.1 All parts of an ecosystem are interrelated.
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Source: Fotolia.
In the mobile device industry, these ecosystems are based on the products or services developed by the original creators, and are complemented by a pool
of independent developers that expand the ecosystem’s capabilities in the hope of developing the next killer app. This collective expansion in capabilities
generates additional marketing buzz and market demand. To create such an expanded ecosystem, a cooperative development approach is the norm, as has
been common in many successful software, hardware, and, more recently, consumer electronics marketplaces. This approach is characterized by systems
development activities constantly shifting back and forth between the big, well-known product developers like Apple or Microsoft and small, virtually
unknown independent app developers who build creative extensions that broaden the products’ market appeal. One example of an ecosystem evolving
around a device is Microsoft’s Kinect, a US$150 body motion capture device for the Xbox, first launched in 2010. After initially barring individual developers
from tinkering with the Kinect, Microsoft realized the power of ecosystems and released a software development kit (SDK), allowing anyone to build Kinectrelated applications.
In 2013, Microsoft launched a much improved Kinect with its next generation game console, the Xbox One. The Kinect contains a collection of cameras,
microphones, and sensors that enables users to control and interact with the game console using gestures and voice commands. For example, the newest
Kinect can recognize faces so you don’t have to manually log in, and can even read your lips to better understand your needs. Using these new capabilities,
one group developed an easy method to create 3D scans of people and objects. Other applications are being developed to help people try on virtual clothing
or help doctors manipulate images while performing surgery. Just as the iPhone and Android smartphones have gone beyond just being phones, the Kinect
has become far more than a just gaming controller, thanks to the innovative ideas from the Kinect’s ecosystem.
After reading this chapter, you will be able to answer the following:
1. How can a company make a business case for/against allowing access to an SDK?
2. What are potential pitfalls if established practices (such as the systems development life cycle) are not followed when developing third-party
applications?
3. How is the “open sourcing” of systems development different from traditional outsourcing?
Based on:
Anonymous. (n.d.). The Microsoft Accelerator for Kinect. Microsoft.com (http://Microsoft.com) . Retrieved March 20, 2014, from
http://www.microsoft.com/bizspark/kinectaccelerator (http://www.microsoft.com/bizspark/kinectaccelerator) .
Greene, J. (2012, June 28). Turns out Kinect is for fashionistas and surgeons, too. Cnet.com (http://Cnet.com) . Retrieved March 20, 2014, from http://news.cnet.com/830110805_3-57463197-75/turns-out-kinect-is-for-fashionistas-and-surgeons-too (http://news.cnet.com/8301-10805_3-57463197-75/turns-out-kinect-is-for-fashionistas-andsurgeons-too) .
Kinect. (2014, February 25). In Wikipedia, The Free Encyclopedia. Retrieved March 20, 2014, from http://en.wikipedia.org/w/index.php?title=Kinect&oldid=597143263
(http://en.wikipedia.org/w/index.php?title=Kinect&oldid=597143263) .
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9.1 MAKING THE BUSINESS CASE
Before people are willing to spend money to acquire or develop a new system, or spend more money on an existing one, they want to be convinced that this
will be a good investment. Making the business case refers to the process of identifying, quantifying, and presenting the value provided by a system.
Business Case Objectives
What does making the business case mean? Think for a moment about what defense lawyers do in court trials. They carefully build a strong, integrated set of
arguments and evidence to prove that their clients are innocent to those who will pass judgment on their clients. In much the same way, a manager has to
build a strong, integrated set of arguments and evidence to prove that an information system (or any type of investment) is adding value to the organization or
its constituents. This is, in business lingo, “making the business case” for a system.
As a business professional, you will be called on to make the business case for systems and other capital investments, or you will have to make the case for a
new system or application you may need for your work to improve certain business processes. Thus, as a finance, accounting, marketing, or management
professional, you are likely to be involved in this process and will therefore need to know how to effectively make the business case for a system (or other
capital expenditures) and need to understand the relevant organizational issues involved. It will be in the organization’s best interest—and in your own—to
ferret out systems that are not adding value. In these cases, you will need to either improve the systems or replace them. Traditionally, business units turned to
IS departments for new systems or applications. Today, business units often directly purchase applications from outside vendors, and expect these applications
to function in the infrastructure provided by the IS departments. As more and more applications are purchased from external vendors, organizations have to
make sure to go through a proper process in selecting the right applications.
Making the business case is as important for proposed systems as it is for the continued investment in an existing system. For a proposed system, the case will
be used to determine whether the new system is a “go” or a “no-go.” For an existing system, the case will be used to determine whether the company will
continue to fund the system. Whether a new system or an existing one is being considered, your goal is to make sure that the investment adds value, that it
helps the firm achieve its strategy and competitive advantage over its rivals, and that money is being spent wisely.
The Productivity Paradox
Unfortunately, while it is easy to quantify the costs associated with developing an information system, it is often difficult to quantify tangible productivity gains
from its use. Over the past several years, the press has given a lot of attention to the impact of IS investments on worker productivity. In many cases, IS
expenditures, salaries, and the number of people on the IS staff have all been rising, but results from these investments have often been disappointing. For
instance, the information and technology research firm Gartner reports that worldwide spending on systems and technologies will surpass US$3.8 trillion in
2014, and is forecasted to exceed US$4.4 trillion by 2016. American and Canadian companies are spending, on average, around 4 percent of company
revenues on system-related investments. As a result, justifying the costs for IS investments has been a hot topic among senior managers at many firms. In
particular, “white-collar” productivity, especially in the service sector, has not increased at the rate one might expect, given the trillions of dollars spent.
Why has it been difficult to show that these vast expenditures on technologies have led to productivity gains? Have information systems somehow failed us,
promising increases in performance and productivity and then failing to deliver on that promise? Determining the answer is not easy. Information systems
may have increased productivity, but other forces may have simultaneously worked to reduce it, the end results being difficult to identify. Factors such as
government regulations, more complex tax codes, stricter financial reporting requirements (such as the Sarbanes–Oxley Act; see Chapter 10
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch10#ch10) , “Securing Information Systems”), and more complex products can all have major
impacts on a firm’s productivity.
It is also true that information systems introduced with the best intentions may have had unintended consequences. A paramount example is giving employees
access to e-mail and the Internet—now employees are spending excessive amounts of time surfing the Web to check sports scores on the ESPN Web site, read
volumes of electronic junk mail received from Internet marketing companies or from personal friends, post status updates on social networking sites, or use
company PCs to download and play software games (Figure 9.2 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig2) );
recently, it was reported that visits to social networking sites such as Facebook and Twitter cost U.K. firms alone approximately US$2.25 billion in lost
productivity every year. In such situations, information systems can result in less efficient and less effective communication among employees and less
productive uses of employee time than before the systems were implemented. Nevertheless, sound technology investments should increase organizational
productivity. If this is so, why have organizations not been able to show larger productivity gains? A number of reasons have been given for the apparent
productivity paradox (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_484) of technology investments (Figure 9.3
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig3) ). This issue is examined next.
FIGURE 9.2 Unintended consequences can limit the productivity gains from IS
investments.
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MEASUREMENT PROBLEMS.
In many cases, the benefits of information systems are difficult to pinpoint because firms may be measuring the wrong things. Often, the biggest increases in
productivity result from increased effectiveness (i.e., the extent to which goals or tasks are accomplished well). Unfortunately, many business metrics focus on
efficiency (i.e., the extent to which goals are accomplished faster, at lower cost, or with relatively little time and effort).
FIGURE 9.3 Factors leading to the IS productivity paradox.
A good example of measurement problems associated with a technology investment is the use of online banking. How much has online banking contributed to
banking productivity? Traditional statistics might look at the adoption rate of the service and associated reductions in branch-based services and locations.
While informative, such statistics may not work well for evaluating online banking, at least at this point in time. For instance, some older customers may not
want to bank online, so a reduction in the number of traditional branches could threaten a potentially large number of very good customers while at the same
time inflating the percentage of online banking users (i.e., if the number of traditional banking customers leave the bank because of a reduction of branches,
the adoption rate of online customers as a percentage will be increased). So, investing in online banking may be unimportant for an important segment of
customers while essential for others. Nevertheless, can you imagine a bank staying competitive without offering online services? Deploying technologies such
as online banking has become a strategic necessity—something an organization must do in order to survive (see Chapter 2
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(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch02#ch02) , “Gaining Competitive Advantage Through Information Systems”). The value of
necessary investments is often difficult to quantify.
TIME LAGS.
A second explanation for why productivity is sometimes difficult to demonstrate for some technology investments is that a significant time lag may occur from
when a company makes the investment until that investment is translated into improvement in the bottom line. Let us return to our online banking example. In
some markets, it may take years from the first implementation of this new system before the magnitude of benefits may be felt by the organization.
REDISTRIBUTION.
A third possible explanation for why IS productivity figures are not always easy to define is that a new type of system may be beneficial for individual firms but
not for a particular industry or the economy as a whole. Particularly in competitive situations, new innovations may be used to redistribute the pieces of the
pie rather than making the whole pie bigger. The result for the industry or economy as a whole is a wash—that is, the same number of products are being
sold, and the same number of dollars are being spread across all the firms.
MISMANAGEMENT.
A fourth explanation is that the new system has not been implemented and managed well. Some believe that people often simply build bad systems, implement
them poorly, and rely on technology fixes when the organization has problems that require a joint technology/process solution. Rather than increasing
outputs or profits, IS investments might merely be a temporary bandage and may serve to mask or even increase organizational inefficiency. Also, as we
mentioned in Chapter 1 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch01#ch01) , “Managing in the Digital World,” an information system
can be only as effective as the business model that it serves. Bad business models can’t be overcome by good information systems.
If it is so difficult to quantify the benefits of information systems for individual firms and for entire industries, why do managers continue to invest in
information systems? The answer is that competitive pressures force managers to invest in information systems whether they like it or not. Also, for many
organizations, information systems are an important source of competitive advantage. You might ask, then, so why waste time making the business case for a
system? Why not just acquire or develop them? The answer: Given the vast number of potential systems and technologies that could be selected, a strong
business case aids the decision-making process and helps direct resources in more strategic ways.
Making a Successful Business Case
People make a variety of arguments in their business cases for information systems. When managers make the business case for an information system, they
typically
base
their
arguments
on
faith,
fear,
and/or
facts
(Wheeler
&
Marakas,
1999
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12#ch09_bib15) ). (Wheeler also adds a fourth “F” for “fiction,” and notes that,
unfortunately, managers sometimes base their arguments on pure fiction, which is not only bad for their careers but also not at all healthy for their firms.)
Table 9.1 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09tab1) shows examples of these three types of arguments.
Do not assume that you must base your business case on facts only. It is entirely appropriate to base the business case on faith, fear, or facts (Figure 9.4
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig4) ). Indeed, the strongest and most convincing business case will include
a little of each type of argument. In the following sections, we talk about each of these types of arguments for the business case.
FIGURE 9.4 A successful business case will be based on faith, fear, and fact.
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BUSINESS CASE ARGUMENTS BASED ON FAITH.
In some situations, arguments based on faith (or fear) can be the most compelling and can drive the decision to invest in an information system despite the
lack of any hard data on system costs, or even in the face of some data that say that the dollar cost for the system will be high. Arguments based on faith often
hold that an information system must be implemented in order to achieve the organization’s strategy effectively and to gain or sustain a competitive advantage
over rivals.
TABLE 9.1 Three Types of Arguments Commonly Made in the Business Case for an Information System
Type of
Description
Argument
Example
Faith
Arguments based on beliefs about
organizational strategy, competitive advantage,
industry forces, customer perceptions, market
share, and so on
“I know I don’t have good data to back this up, but I’m convinced that having this customer
relationship management system will enable us to serve our customers significantly better
than our competitors do and, as a result, we’ll beat the competition… You just have to take it
on faith.”
Fear
Arguments based on the notion that if the
system is not implemented, the firm will lose
out to the competition or, worse, go out of
business
“If we don’t implement this enterprise resource planning system, we’ll get killed by our
competitors because they’re all implementing these kinds of systems … We either do this or
we die.”
Fact
Arguments based on data, quantitative analysis,
and/or indisputable factors
“This analysis shows that implementing the inventory control system will help us reduce
errors by 50 percent, reduce operating costs by 15 percent a year, increase production by 5
percent a year, and pay for itself within 18 months.”
For example, a firm has set as its strategy that it will be the dominant, global force in its industry. As a result, this firm must adopt a variety of collaboration
technologies, such as desktop videoconferencing and groupware tools, in order to enable employees from different parts of the globe to work together
effectively and efficiently. Similarly, a firm that has set as its strategy a broad scope—producing products and services across a wide range of consumer needs
—may need to adopt some form of an enterprise resource planning system to better coordinate business activities across its diverse product lines.
In short, successful business case arguments based on faith should clearly describe the firm’s mission and objectives, the strategy for achieving them, and the
types of information systems that are needed in order to enact the strategy. A word of caution is warranted here. In today’s business environment, cases
based solely on strategic arguments, with no hard numbers demonstrating the value of the information system under consideration, are not likely to be
funded.
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BRIEF CASE Software Patent Wars
Have you ever used the slide-to-unlock feature on a smartphone? Apple has a patent on that. If your smartphone sends and receives data over a 4G
network, well, Samsung has a patent for that. In the 1970s, when key technologies that made the Internet possible were being developed, intellectual
property and patent claims were not much of a big deal. The idea then was to make the technology an international standard, and open it up for
public use. Come the twenty-first century, things have changed, and battles over patents are constantly being fought, especially in the mobile market
where companies are trying to protect clever technologies and applications and maintain or increase market share.
An overview of the mobile patent wars looks something like this: Microsoft sued Motorola for video encoding, Motorola counter-sued Microsoft’s use
of e-mail, instant messaging, and Wi-Fi; likewise, Google was sued by Oracle for its implementation of the Java programming language in its Android
system. Google then acquired Motorola to gain access to its patent portfolio. Apple has made use of its patent rights to prevent Samsung Electronics
from selling some products with features Apple argues violates its patents. In response, Samsung has retaliated by attempting to ban iPhone sales in
some countries.
With the global smartphone market being estimated around $300 billion in 2014, the stakes are high. However, many feel that too much time, energy,
and money are being wasted fighting these battles, and there is also a growing sense that the patent process itself is flawed. Considering that the U.S.
patent system offers inventors a limited monopoly on their ideas for 20 years, consumers may actually find fewer choices in the market the next time
they look for a new mobile handset.
Questions
1. With millions of software patents in existence, some claim that it is almost impossible to avoid infringing on someone else’s patent. How does
this affect innovation and small startups?
2. Many believe that the patent wars act to destroy small players in the mobile phone marketplace who cannot afford expensive and lengthy legal
battles. What other impacts do the patent wars have on this industry?
Based on:
Holbrook, T. (2014, March 16). Is the Supreme Court about to rule that software is ineligible for patent protection? Forbes. Retrieved March 20, 2014, from
http://www.forbes.com/sites/realspin/2014/03/16/is-the-supreme-court-about-to-rule-that-software-is-ineligible-for-patent-protection
(http://www.forbes.com/sites/realspin/2014/03/16/is-the-supreme-court-about-to-rule-that-software-is-ineligible-for-patent-protection) .
Nazer, D. (2014, March 17). Why is the patent office so bad at reviewing software patents? Electronic Frontier Foundation. Retrieved March 20, 2014, from
https://www.eff.org/deeplinks/2014/03/why-patent-office-so-bad-reviewing-software-patents (http://www.eff.org/deeplinks/2014/03/why-patent-office-so-badreviewing-software-patents) .
Phillips, M. (2013, November 22). Apple vs. Samsung: A patent war with few winners. The New Yorker. Retrieved March 20, 2014, from
http://www.newyorker.com/online/blogs/elements/2013/11/a-patent-war-with-few-winners.html (http://www.newyorker.com/online/blogs/elements/2013/11/apatent-war-with-few-winners.html) .
Software patent debate. (2014, March 18). In Wikipedia, The Free Encyclopedia. Retrieved March 20, 2014, from http://en.wikipedia.org/w/index.php?
title=Software_patent_debate&oldid=600233238 (http://en.wikipedia.org/w/index.php?title=Software_patent_debate&oldid=600233238) .
BUSINESS CASE ARGUMENTS BASED ON FEAR.
There are several different factors to take into account when making a business case in which you will provide arguments based on fear. These include a
number of factors involving competition and other elements of the industry in which the firm operates. For example, a mature industry, such as the automotive
industry, may need systems simply to maintain the current pace of operations. While having the newest systems and technologies available may be nice, they
may not be needed to stay in business. However, a company in a newer, expanding industry, such as the green technology industry, may find it more important
to be on the leading edge of technology in order to compete effectively in the marketplace. Likewise, some industries are more highly regulated than others. In
these cases, companies can use technology investments to better control processes and ensure compliance with appropriate regulations. The argument for the
business case here would be something like, “If we do not implement this system, we run the risk of being sued or, worse, being thrown in jail” (see Chapter
10 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch10#ch10) ).
Probably the most important industry factor that can affect technology investments is the nature of competition or rivalry in the industry. For example, when
competition in an industry is high and use of the newest technologies is rampant, as it is in the mobile phone industry, strategic necessity, more than anything
else, forces firms to adopt new systems. Given how tight profit margins are in this industry, Apple, Samsung, and other manufacturers must use inventory
control systems, business intelligence systems, and a host of other systems that help them to be more effective and efficient. If they do not adopt these systems,
they will likely go out of business. As introduced in Chapter 2 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch02#ch02) , a common way for
assessing
the
level
of
competition
within
an
industry
is
the
five
forces
model
(Porter,
1979
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12#ch09_bib9) ). By assessing the various competitive forces, you can determine
which specific technologies may be more or less useful. For instance, in a highly price-competitive market, where buyers have strong bargaining power,
investments to reduce production costs might be advantageous. Business case arguments formulated this way sound something like, “If we do not implement
this system, our competitors are going to beat us on price, we will lose market share, and we will go out of business.”
BUSINESS CASE ARGUMENTS BASED ON FACT.
Many people, including most chief financial officers, want to see the business case for an information system based on a convincing, quantitative analysis that
proves beyond the shadow of a doubt that the benefits of the system will outweigh the costs. The most common way to prove this is to provide a detailed cost–
benefit analysis of the information system. Although this step is critical, the manager must remember that there are inherent difficulties in, and limits to, cost–
benefit analyses for information systems. To illustrate how a cost–benefit analysis could be used to build a fact-based business case, let us consider the
development of a Web-based order entry system for a relatively small firm.
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Identifying Costs
One
goal
of
Print
a
cost–benefit
analysis
is
to
accurately
determine
the
total
cost
of
ownership
(TCO)
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_639) for an investment. TCO is focused on understanding not only the total
cost of acquisition but also all costs associated with ongoing use and maintenance of a system. Consequently, costs can usually be divided into two categories:
non-recurring costs and recurring costs (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_505) . Non-recurring costs are
one-time costs that are not expected to continue after the system is implemented. These include costs for things such as site preparation and technology
purchases. These one-time costs may also include the costs of attracting and training a webmaster or renovating some office space for new personnel or for
hosting the Web servers.
Recurring costs are ongoing costs that occur throughout the life of the system. Recurring costs include the salary and benefits of the webmaster and any other
personnel assigned to maintain the system, electricity, upgrades and maintenance of the system components, monthly fees paid to a local Internet service
provider, and the continuing costs for the space in which the webmaster works or the data center where the servers reside. Personnel costs are usually the
largest recurring costs, and the Web-based system is no exception in this regard. These recurring expenses can go well beyond the webmaster to include
expenses for customer support, content management, ongoing maintenance, and more.
The sample costs described thus far are tangible costs (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_628) that are
relatively easy to quantify. Some intangible costs (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_319) ought to be
accounted for as well, even though they will not fit neatly into the quantitative analysis. These might include the costs of reduced traditional sales, losing some
customers that are not “Web ready,” or losing customers if the Web application is poorly designed or not on par with competitors’ sites. You can choose to
either quantify these in some way (i.e., determine the cost of losing a customer) or simply reserve these as important costs to consider outside of—but along
with—the quantitative cost–benefit analysis.
Identifying Benefits
Next, you determine both tangible benefits (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_627) and intangible benefits.
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_319) Some tangible benefits are relatively easy to determine. For example,
you can estimate that the increased customer reach of the new Web-based system will result in at least a modest increase in sales. Based on evidence from
similar projects, you might estimate, say, a 5 percent increase in sales the first year, a 10 percent increase the second year, and a 15 percent increase the third
year. In addition, you might also include as tangible benefits the reduction of order entry errors because orders will now be tracked electronically and shipped
automatically. You could calculate the money previously lost on faulty and lost orders, along with the salaries and wages of personnel assigned to find and fix
these orders, and then consider the reduction of these costs as a quantifiable benefit of the new system. Cost avoidance is a legitimate, quantifiable benefit of
many systems. Similarly, the new system may enable the company to use fewer order entry clerks or redeploy these personnel to other, more important
functions within the company. You could consider these cost reductions as benefits of the new system.
A Web-based system may have intangible benefits as well. Some intangible benefits of this new system might include improvements in customer service
resulting from faster turnaround on fulfilling orders. These are real benefits, but they might be hard to quantify with confidence. Perhaps an even more
intangible benefit would be the overall improved perception of the firm. Customers might consider it more progressive and customer service–oriented than its
rivals; in addition to attracting new customers, this might increase the value of the firm’s stock if it is a publicly traded firm. Another intangible benefit might be
simply that it was a strategic necessity to offer customers Web-based ordering to keep pace with rivals. While these intangibles are difficult to quantify, they
must be considered along with the more quantitative analysis of benefits. In fact, the intangible benefits of this Web-based system might be so important that
they could carry the day despite an inconclusive or even negative cost–benefit analysis.
COMING ATTRACTIONS: IBM’s 5 in 5
As its catchphrase goes, IBM is focused on building a smarter planet. As part of this campaign, IBM researchers have created the 5 in 5 forecast: five
innovations that will transform our lives within the next five years. At the core of this forecast is Big Data and machine learning. Machine learning is a
branch of artificial intelligence that allows systems to learn by processing massive amounts of data (see Chapter 6
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch06#ch06) , “Enhancing Business Intelligence Using Information Systems”). Because
Big Data and machine learning can help a company better understand customers and therefore better meet their needs, IBM believes that Big Data
will help offline retail stores understand their customers as well as Amazon.com (http://Amazon.com) does, leading to a resurgence of offline
retailing. Likewise, with the continued drop in costs for processing data, your doctor will rely more and more on your DNA to help keep you well.
IBM researchers also predict that a digital guardian will protect your online information from cyber criminals, by better understanding you, your
friends, and your habits and activities. Similarly, the classroom will learn about students, helping students master the necessary skills by tailoring the
educational experience to each individual student. Finally, cities will help you improve your day-to-day lifestyle, by suggesting events based on your
prior behavior. Big Data is often viewed by many as potentially invasive and likened to Orwell’s “Big Brother.” IBM is hoping to make Big Data your big
buddy.
Based on:
The 5 in 5. IBM.com (http://IBM.com) . Retrieved on March 28, 2014, from http://www.ibm.com/smarterplanet/us/en/ibm_predictions_for_future/ideas
(http://www.ibm.com/smarterplanet/us/en/ibm_predictions_for_future/ideas) .
Performing Cost–Benefit Analyses
An example of a simplified cost–benefit analysis (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_139) that contrasts the
total
expected
tangible
costs
versus
the
tangible
benefits
is
presented
in
Figure
9.5
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig5) . Notice the fairly large investment up front, with another significant
outlay in the fifth year for a system upgrade. You could now use the net costs/benefits for each year as the basis of your conclusion about this system.
Alternatively, you could perform a break-even analysis—a type of cost–benefit analysis to identify at what point (if ever) tangible benefits equal tangible costs
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(note that break-even occurs early in the second year of the system’s life in this example)—or a more formal net-present-value analysis
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_409) of the relevant cash flow streams associated with the system at the
organization’s discount rate (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_192) (i.e., the rate of return used by an
organization to compute the present value of future cash flows). In any event, this cost–benefit analysis helps you make the business case for this proposed
Web-based order fulfillment system. It clearly shows that the investment for this system is relatively small, and the company can fairly quickly recapture the
investment. In addition, there appear to be intangible strategic benefits to deploying this system. This analysis—and the accompanying arguments and
evidence—goes a long way toward convincing senior managers in the firm that this new system makes sense. For more on cost–benefit analyses, see any
introductory finance or managerial accounting textbook.
FIGURE 9.5 Worksheet showing a simplified cost–benefit analysis for the Webbased order fulfillment system.
Comparing Competing Investments
One method for deciding among different IS investments or when considering alternative designs for a given system is weighted multicriteria analysis
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_707)
,
as
illustrated
in
Figure
9.6
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig6) . For example, suppose
that for a given application being considered for purchase, there are three alternatives that could be pursued—A, B, or C. Let’s also suppose that early
planning meetings identified three key system requirements and four key constraints that could be used to help make a decision on which alternative to
pursue.
In
the
left
column
of
Figure
9.6
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig6)
,
three
system
requirements and four constraints are listed. Because not all requirements and constraints are of equal importance, they are weighted on the basis of their
relative importance. In other words, you do not have to weight requirements and constraints equally; it is certainly possible to make requirements more or
less important than constraints. Weights are arrived at in discussions among the analysis team, users, and managers. Weights tend to be fairly subjective and,
for that reason, should be determined through a process of open discussion to reveal underlying assumptions, followed by an attempt to reach consensus
among stakeholders. Notice that the total of the weights for both the requirements and constraints is 100 percent.
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FIGURE 9.6 Decisions about alternative projects or system design approaches
can be assisted using a weighted multicriteria analysis.
Next, each requirement and constraint is rated on a scale of 1 to 5. A rating of 1 indicates that the alternative does not meet the requirement very well or that
the alternative violates the constraint. A rating of 5 indicates that the alternative meets or exceeds the requirement or clearly abides by the constraint. Ratings
are even more subjective than weights and should also be determined through open discussion among users, analysts, and managers. For each requirement
and constraint, a score is calculated by multiplying the rating for each requirement and each constraint by its weight. The final step is to add up the weighted
scores for each alternative. Notice that we have included three sets of totals: for requirements, for constraints, and for overall totals. If you look at the totals
for requirements, alternative B or C is the best choice because each meets or exceeds all requirements. However, if you look only at constraints, alternative A is
the best choice because it does not violate any constraints. When we combine the totals for requirements and constraints, we see that the best choice is
alternative C. Whether alternative C is actually chosen for development, however, is another issue. The decision makers may choose alternative A because it
has the lowest cost, knowing that it does not meet two key requirements. In short, what may appear to be the best choice for a systems development project
may not always be the one that ends up being developed or acquired. By conducting a thorough analysis, organizations can greatly improve their decisionmaking outcomes.
TABLE 9.2 Characteristics of Different Stakeholders Involved in Making Is Investment Decisions
Stakeholder
Perspective
Focus/Project Characteristics
Management
Representatives or managers from each of the functional areas within the firm
Greater strategic focus; largest project sizes; longest
project durations
Steering
committee
Representatives from various interest groups within the organization (they
may have their own agendas at stake when making investment decisions)
Cross-functional focus; greater organizational change;
formal cost–benefit analysis; larger and riskier projects
User
department
Representatives of the intended users of the system
Narrow, non-strategic focus; faster development
IS executive
Has overall responsibility for managing IS development, implementation, and
maintenance of selected systems
Focus on integration with existing systems; fewer
development delays; less concern with cost–benefit
analysis
Source: Based on Hoffer, George, & Valacich (2014 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12#ch09_bib5) ) and McKeen, Guimaraes, &
Wetherbe (1994 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12#ch09_bib7) ).
Presenting the Business Case
Up to this point, we have discussed the key issues to consider as you prepare to make the business case for a system. We have also shown you some tools for
determining the value that a system adds to an organization. Now you are actually ready to make the case—to present your arguments and evidence to the
decision makers in the firm.
KNOW THE AUDIENCE.
Depending on the firm, a number of people from various areas of the firm might be involved in the decision-making process. People from different areas of
the firm typically hold very different perspectives about what investments should be made and how those investments should be managed (Table 9.2
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09tab2) ). Consequently, presenting the business case for a new system
investment can be quite challenging. Ultimately, a number of factors come into play in making investment decisions, and numerous outcomes can occur (Figure
9.7 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig7) ). For instance, decisions and choices are driven by perceived
needs, resource availability, evaluation criteria, and so on. Numerous outcomes can occur from this decision process. Of course, the project can be accepted or
rejected; often, projects can be conditionally accepted or asked to be revised in order to more carefully consider resource, time, or other constraints.
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Understanding the audience and the issues important to them is a first step in making an effective presentation. Various ways to improve the development of a
business case are examined next.
FIGURE 9.7 Investment selection decisions must consider numerous factors and
can have numerous outcomes.
CONVERT BENEFITS TO MONETARY TERMS.
When making the case for an IS investment, it is desirable to translate all potential benefits into monetary terms. For example, if a new system saves
department
managers
an
hour
per
day,
try
to
quantify
that
savings
in
terms
of
dollars.
Figure
9.8
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig8) shows how you might
convert time savings into dollar figures. While merely explaining this benefit as “saving managers’ time” makes it sound useful, managers may not consider it a
significant enough inducement to warrant spending a significant amount of money. Justifying a US$50,000 system because it will “save time” may not be
persuasive enough. However, an annual savings of US$90,000 is more likely to capture the attention of decision makers and is more likely to result in project
approval. Senior managers can easily rationalize a US$50,000 expense for a US$90,000 savings and can easily see why they should approve such a request.
They can also more easily rationalize their decision later on if something goes wrong with the system.
FIGURE 9.8 Converting time savings into dollar figures.
DEVISE PROXY VARIABLES.
The
situation
presented
in
Figure
9.8
is
fairly
straightforward. Anyone can see that a US$50,000 investment is a good idea because the return on that investment is US$90,000 the first year. Unfortunately,
not all cases are this clear-cut. In cases in which it is not as easy to quantify the impact of an investment, you can come up with proxy variables
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_489) (i.e., alternative measures of outcomes) to help clarify what the impact
on the firm will be. Proxy variables can be used to measure changes in terms of their perceived value to the organization. For example, if mundane
administrative tasks are seen as a low value (perhaps a 1 on a 5-point scale), but direct contact with customers is seen as a high value (a rating of 5), you can
use these perceptions to indicate how new systems will add value to the organization. In this example, you can show that a new system will allow personnel to
have more contact with customers while at the same time reducing the administrative workload. Senior managers can quickly see that individual workload is
being shifted from low-value to high-value activities.
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec1/books/Valacich.3917.17.1/sections/ch09lev1sec1#ch09fig8)
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You can communicate these differences using percentages, increases or decreases, and so on—whatever best conveys the idea that the new system is creating
changes in work, in performance, and in the way people think about their work. This gives decision makers some relatively solid data on which to base their
decision.
MEASURE WHAT IS IMPORTANT TO MANAGEMENT.
One of the most important things you can do to show the benefits of a system is one of the simplest: Measure what senior managers think is important. You
may think this is trivial advice, but you would be surprised how often people calculate impressive-looking statistics in terms of downtime, reliability, and so on,
only to find that senior managers disregard or only briefly skim over those figures. You should concentrate on the issues senior business managers care
about. The “hot-button” issues with senior managers should be easy to discover, and they are not always financial reports. Hot issues with senior managers
could include cycle time (how long it takes to process an order), regulatory or compliance issues, customer feedback, and employee morale. By focusing on
what senior business managers believe to be important, you can make the business case for systems in a way that is more meaningful for those managers,
which makes selling systems to decision makers much easier. Managers are more likely to buy in to the importance of systems if they can see the impact on
areas that are important to them. Now that you understand how to make the business case for new information systems, we now examine the development
process.
ETHICAL DILEMMA: Ethical App Development
In the past, systems development was in the hands of large software companies, with large development teams and legal departments that would
scrutinize new functionalities for legal and ethical compliance. With the advent of the smartphone and social media came the promise of getting rich
quick by developing the next Facebook, WhatsApp, Pinterest, or some other killer app. Nowadays, it’s not only large companies building those apps,
but individuals with a creative idea, aided by easy-to-use development tools.
However, with the hope of developing the next killer app, ethical implications are often overlooked or outright ignored, as evidenced by examples
such as Facebook or Path. Throughout its history, Facebook has changed its privacy policies, at times grossly violating its users’ privacy expectations.
Similarly, in 2012 it became known that the iOS version of the social media app Path secretly sent the users’ complete address book data to Path’s
servers. Not only was this not mentioned in the apps’ Terms of Use, the data was also sent in an unencrypted way, potentially subjecting the app’s
users to security problems.
In addition, mobile devices offer various tempting ways of collecting user data, with many apps requesting access to functionalities such as your
phone book, location, and so on. Given these vulnerabilities, a new code of conduct for app development is needed. “Just because you can collect
data, should you?” Many argue that an app should only be allowed to collect and utilize information it needs, nothing more. Developers should also
carefully consider the consequences of personal data being compromised. Who would be affected, and how serious might the consequences be?
Given the high value of your personal data, the maxim of the app development industry should be: “Even though you can, maybe you shouldn’t!”
Based on:
Allamsetty, T. (2013, March 19). User privacy and the ethics of app data collection. [X]Cubelabs. Retrieved March 27, 2014, from
http://www.xcubelabs.com/blog/user-privacy-and-the-ethics-of-app-data-collection (http://www.xcubelabs.com/blog/user-privacy-and-the-ethics-of-app-datacollection) .
Grothaus, M. (2013, December 4). Do developers need a standardized code of ethics? Co.LABS. Retrieved March 27, 2014, from
http://www.fastcolabs.com/3022968/do-developers-need-a-standardized-code-of-ethics (http://www.fastcolabs.com/3022968/do-developers-need-a-standardizedcode-of-ethics) .
Phillips, J. (2012, December 8). Path social media app uploads iOS address books to its servers. Wired. Retrieved March 27, 2014, from
http://www.wired.com/gadgetlab/2012/02/path-social-media-app-uploads-ios-address-books-to-its-servers (http://www.wired.com/gadgetlab/2012/02/pathsocial-media-app-uploads-ios-address-books-to-its-servers) .
Siegel, E. (2014, February 5). Becoming an ethical app developer at Renaissance IO. Apptentive. Retrieved March 27, 2014, from
http://www.apptentive.com/blog/ethical-app-developer-at-renaissance-io (http://www.apptentive.com/blog/ethical-app-developer-at-renaissance-io) .
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9.2 THE SYSTEMS DEVELOPMENT PROCESS
No matter if a software company such as Microsoft is planning to build a new version of its popular Office software suite, or if a company such as Netflix is
trying to build a system to improve its movie recommendations, companies follow a standardized approach. This process of designing, building, and
maintaining
information
systems
is
often
referred
to
as
systems
analysis
and
design
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_612) . Likewise, the individual who performs this task is referred to as a
systems analyst (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_613) . Because few organizations can survive without
effectively utilizing information and computing technology, the demand for skilled systems analysts is very strong. In 2014, U.S. News named being a systems
analyst one of the top jobs; in fact, it was ranked as number 2, just behind software developer. Likewise, the U.S. Bureau of Labor Statistics ranks systems
analysts near the top of all professions for job stability, income, and employment growth through 2016, with average growth exceeding 29 percent.
Organizations want to hire systems analysts because they possess a unique blend of managerial and technical expertise—systems analysts are not just
“techies.” Systems analysts remain in demand precisely because of this unique blend of abilities.
Custom Versus Off-the-Shelf Software
When deciding to deploy new systems to support their operations in order to gain or sustain a competitive advantage, organizations can typically choose
between custom and off-the-shelf software. For example, many types of application software (such as word processors, spreadsheet, or accounting software)
can be used by a variety of businesses within and across industries. These types of general-purpose systems are typically purchased off the shelf. Often,
however, organizations have very specific needs that cannot be met by generic technologies. This is especially true for companies trying to capitalize on a firstmover advantage, and therefore may not be able to purchase a preexisting system to meet their specific needs. For example, pioneers in online retailing (such
as Amazon.com (http://Amazon.com) ) or budget air travel (such as Southwest Airlines) needed entirely new systems and technologies to support their
revolutionary business models and had to develop (or have someone else develop) custom solutions. The approaches to developing or acquiring custom and
off-the-shelf software are quite different, but they also have many similarities. Before going into the details of developing or acquiring such systems, we’ll first
contrast these two types of systems.
CUSTOM SOFTWARE.
Custom software is developed to meet the specifications of an organization (it is thus also sometimes called tailor-made, or bespoke, software). Such software
may be developed (or configured) in-house by the company’s own IS staff, or the development may be contracted, or outsourced, to a specialized vendor
charged with developing the system to the company’s contractual specifications. Custom software has two primary advantages over general purpose
commercial technologies:
1. Customizability. The software can be tailored to meet unique organizational requirements. Such requirements, for example, can reflect a desire to
achieve a competitive advantage through a specific type of system (e.g., Amazon.com’s (http://Amazon.com’s) one-click ordering) or to better fit business
operations, characteristics of the organizational culture, or proprietary security requirements, or to better interface with existing systems. Further,
company- or industry-specific terms or acronyms can be included in a new software application, as can unique types of required reports. Such
specificity is not typically possible in off-the-shelf systems that are targeted at a more general audience.
2. Problem Specificity. The company pays only for the features specifically required for its users. In contrast to software packages such as Microsoft
Office, which include a wide range of individual programs (some of which may never be used), only those components that are really needed can be
implemented.
Today, building a complete system from scratch is quite rare; most information systems that are developed within an organization for its internal use typically
include a large number of preprogrammed, reusable modules as well as off-the-shelf hardware technologies that are purchased from development
organizations or consultants.
OFF-THE-SHELF SOFTWARE.
Although custom software has advantages, it is not automatically the best choice for an organization. Off-the-shelf software (or packaged software) is typically
used to support common business processes that do not require any specific tailoring. In general, off-the-shelf systems, whether hardware or software, are
less
costly,
faster
to
procure,
of
higher
quality,
and
less
risky
than
custom
systems.
Table
9.3
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09tab3) summarizes examples of off-the-shelf application software.
TABLE 9.3 Examples of Off-the-shelf Application software
Category
Application
Description
Examples
Business information
systems
Payroll
Automation of payroll services, from the optical reading of time sheets to generating
paychecks
ZPAY
Intuit Payroll
Inventory
Automation of inventory tracking, order processing, billing, and shipping
Intuit
QuickBooks
InventoryPower
5
Personal
productivity
Support for a wide range of tasks from word processing to graphics to e-mail
OpenOffice
Corel Office
Microsoft Office
Office automation
Traditionally, the most common option for packaged software was so-called commercial off-the-shelf (COTS) software; this type of software is typically
developed by software companies that spread the development costs over a large number of customers. An alternative to commercial off-the-shelf software is
open source software.
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Open Source Software
Open source is a philosophy that promotes developers’ and users’ access to the source of a product or idea. Particularly in the area of software development,
the open source movement has taken off with the advent of the Internet; people around the world are contributing their time and expertise to develop or
improve software, ranging from operating systems to application software. As the programs’ source code is freely available for use and/or modification, this
software is referred to as open source software (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_430) . Open source
software owes its success to the inputs from a large user base, helping to fix problems or improve the software. One of the great success stories of open
source software is the Android operating system. In 2014, Android’s share of the global smartphone shipment market—led by Samsung products—was over
80 percent! Android is based on another open source operating system called Linux, developed as a hobby by the Finnish university student Linus Torvalds in
1991. Linux has since become the operating system of choice for Web servers, embedded systems (such as TiVo boxes and network routers), and
supercomputers alike (as of June 2014, 97 percent of the world’s 500 fastest supercomputers ran Linux operating systems [Top 500, 2014]). In addition to the
Linux operating system, other open source software has been gaining increasing popularity because of its stability and low cost. For example, in 2014, 38
percent of all Web sites were powered by the Apache Web server, another open
source
project (Netcraft,
2014
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12#ch09_bib8) ). Other popular examples of open source application software
include the Firefox Web browser and the office productivity suite Apache OpenOffice.
How do large open source projects such as Firefox work? Typically, most contributors can only suggest modifications for changes; for example, they can
contribute to program code or provide new designs for the system’s user interface, but only a small group of carefully selected “committers” can implement
these modifications into the official releases of the software, which helps to ensure the quality and stability of the software.
While there are many benefits to open source software, vendors of proprietary software are still highlighting “hidden” costs of running open source software,
such as obtaining reliable customer support. On the other hand, however, commercial open source vendors are providing customer support, installation,
training, and so on to their paying customers. Men’s Wearhouse, the State of Oregon, and many other large organizations are using a CRM system offered by
SugarCRM, Inc., a commercial open source vendor that offers free “community editions” as well as other, more feature-rich paid editions of its software.
Similarly, the popular MySQL database, which is used by Yahoo!, Facebook, the Associated Press, and many other companies, is provided under an open
source license for personal use, but the company employs its own developers and offers commercial licenses (including dedicated 24/7 technical support,
consulting, and indemnification clauses) to business users. Further, many open source projects are now backed by major information technology (IT)
companies such as IBM, which give money and human resources to Linux projects, or Oracle, which donated the source code of the OpenOffice productivity
suite to the Apache Software Foundation.
Combining Custom, Open Source, and Off-the-Shelf Systems
It is possible to combine the advantages of custom, open source, and off-the-shelf systems. Companies can purchase off-the-shelf technologies and add custom
components for their specific needs. For example, an online retailer may want to purchase an off-the-shelf inventory management system and then add tailormade modules it needs to conduct its day-to-day business. This system could be based on the open source database MySQL; further, the online retailer could
use the open source Apache Web server to power its online shopping site. In some cases, for example, with large ERP systems, companies selling off-the-shelf
software make customized changes for a fee. Other vendors, however, may not allow their software to be modified (as is the case with generic, all-purpose
software, such as Microsoft Office).
Commercial, off-the-shelf systems are almost always acquired from an external vendor, whereas custom systems can be either developed in-house or
developed by an outside vendor (Figure 9.9 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig9) ). Regardless of the
source of the new system—custom, open source, or off-the-shelf—the primary role of managers and users in the organization is to make sure that it will meet
the organization’s business needs. This may be especially important in the case of end users developing systems. End users typically do not program elaborate
systems, but frequently use spreadsheet or database software to create solutions for accomplishing narrow, well-defined tasks; while such applications may be
useful for accomplishing certain tasks, end user development may cause problems related to the adherence to standards, lack of documentation, security
concerns, or a lack of continuity if the employee who built the spreadsheet or database leaves the organization.
FIGURE 9.9 There are a variety of sources for information systems.
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IS Development in Action
The tools and techniques used to develop information systems are continually evolving with the rapid changes in IS hardware and software. As you will see, IS
development is a fairly disciplined and structured process that moves from step to step. Systems analysts become adept at decomposing large, complex
problems into many small, simple problems. The goal of the systems analyst is to design the final system by piecing together many small software modules and
technologies into one comprehensive system (Figure 9.10 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig10) ). For
example, think about using LEGOâ„¢ blocks for building a model of a space station. Each individual block is a small, simple piece that is nothing without the
others. When put together, the blocks can create a large and very complex design (Google co-founder Larry Page had gained some notoriety for building a
working printer out of LEGO bricks). When systems are built in this manner, they are much easier to design, build, and, most important, maintain.
FIGURE 9.10 Problem decomposition makes solving large, complex problems
easier.
Although many people in organizations, such as managers and users, are responsible and participate in a systems development project, the systems analyst
has primary responsibility. Some projects may have one or several systems analysts working together, depending on the size and complexity of the project.
The primary role of the systems analyst is to study the problems and needs of an organization in order to determine how people, methods, and information
technology can best be combined to bring about improvements in the organization. A systems analyst helps systems users and other business managers
define their requirements for new or enhanced information systems.
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systems
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analyst
typically
also
manages
the
development
project.
As
the
project
manager
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_485) , the systems analyst needs a diverse set of management, leadership,
technical, conflict management, and customer relationships skills. The project manager is the person most responsible for ensuring that a project is a success.
The project manager must deal with continual change and problem solving. Successful projects require effective resource and task management as well as
effective communication as the project moves through its various steps. Project management is an important aspect of the system development or acquisition
process and a critical skill for successful systems analysts. The focus of project management is to ensure that projects meet customer expectations and are
delivered within budget and time constraints. Clearly, a systems analyst is an agent of change and innovation in modern organizations.
The Role of Users in the Systems Development Process
Many organizations have a huge investment in transaction processing and management information systems. These systems are most often designed,
constructed, and maintained by systems analysts within the organization, using a variety of methods. When building and maintaining information systems,
systems analysts rely on information provided by system users, who are involved in all phases of the system’s development process. To effectively participate
in the process, it is important for all members of the organization to understand what is meant by systems development and what activities occur. A close,
mutually respectful working relationship between analysts and users is key to project success.
Steps in the Systems Development Process
Just as the products that a firm produces and sells follow a life cycle, so do organizational information systems. For example, a new type of tennis shoe follows
a life cycle of being designed, introduced to the market, being accepted into the market, maturing, declining in popularity, and ultimately being retired. The
term systems development life cycle (SDLC) (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_616) describes the life of an
information
system
from
conception
to
retirement
(Hoffer
et
al.,
2014
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12/books/Valacich.3917.17.1/sections/ch09lev1sec12/books/Valacich.3917.17.1/sections/
). The SDLC has four primary phases:
1. Systems planning and selection
2. Systems analysis
3. Systems design
4. Systems implementation and operation
FIGURE 9.11 The SDLC defines the typical process for building systems.
Figure
9.11
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
is a graphical representation of the SDLC containing four boxes connected by arrows. Within the SDLC, arrows flow from systems planning and selection, to
systems analysis, to systems design, and, finally, to systems implementation and operation. Once a system is in operation, it moves into an ongoing maintenance
phase that parallels the initial development process. For example, when new features are added to an existing system, analysts must first plan and select which
new features to add, then analyze the possible impact of adding these features to the existing system, then design how the new features will work, and, finally,
implement these new features into the existing system. While some consider maintenance another SDLC phase, it is really a repeated application of the core
SDLC phases. In this way, the SDLC becomes an ongoing cycle. During ongoing systems maintenance, the entire SDLC is followed to implement system repairs
and enhancements.
WHO’S GOING MOBILE: Creating Mobile Apps
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With the rapid rise of smartphone usage, various useful and entertaining apps are rapidly being developed, greatly enhancing the phones’
capabilities. In 2013, both Google and Apple announced that they had over 1 million apps in their app stores, with many more apps appearing every
day. The primary reason there are so many apps is that anyone can build and try to sell apps, from software companies focused on translating their
existing products (such as Adobe Reader) onto mobile platforms, to individuals who have a clever idea for a game.
Owing to the intense competition between these apps, it is not surprising that only relatively few are highly successful. However, if you have the right
idea, creating a winning app can be surprisingly easy. In fact, it is estimated that it took the maker of the widely successful game Flappy Bird a mere
two to three days to create that game (alone, that is). At its peak, the game netted US$50,000 per day for the person who built the game. Given that
games for popular consoles such as the PlayStation or the Xbox cost millions of dollars to develop, how did Flappy Bird’s creator manage to pull that
off?
In the past few years, a number of marketplaces have sprung up where anyone can purchase game templates for as low as US$199. These templates
typically include certain game mechanics, which the buyer can modify to create a functioning game. Typically, there’s not even a need to write a single
line of code; all that is needed is a winning idea, coming up with a good story, game title, and key words, and the skills needed to create the graphics.
What if your idea is for an app other than a game, such as a productivity tool for students, or a better way to keep track of your passwords? There
are tools to help develop these as well. Once the app is created, all that is needed is uploading the app to the various marketplaces, and watching the
download count. Good luck!
Based on:
Anonymous. (2014 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12#ch09_bib2) ). AppMachine. Retrieved March 27, 2014, from
www.appmachine.com (http://www.appmachine.com) .
Rubens, P. (February 18, 2014). Flap happy: How you too can become a mobile games mogul. BBC. Retrieved March 27, 2014, from
http://www.bbc.com/news/business-26224428 (http://www.bbc.com/news/business-26224428) .
Phase 1: Systems Planning and Selection
The first phase of the SDLC is systems planning and selection (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_620) (see
Figure
9.11
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
). Understanding that it can work on only a limited number of projects at a given time because of limited resources, an organization must take care that only
those projects that are critical to enabling the organization’s mission, goals, and objectives are undertaken. Consequently, the goal of systems planning and
selection is simply to identify, plan, and select a development project from all possible projects that could be performed. Organizations differ in how they
identify,
plan,
and
select
projects.
Some
organizations
have
a
formal
information
systems
planning
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_307) process whereby a senior manager, a business group, an IS manager,
or a steering committee identifies and assesses all possible systems development projects that the organization could undertake. Project managers present the
business case for the new system and it is accepted or rejected. Others follow a more ad hoc process for identifying potential projects. Nonetheless, after all
possible projects are identified, those deemed most likely to yield significant organizational benefits, given available resources, are selected for subsequent
development activities.
Just as there are often differences in the source of systems projects within organizations, there are often different evaluation criteria used within organizations
when classifying and ranking potential projects, such as strategic alignment, costs and benefits, resource availability, project size and duration, or technical
difficulties and risks. During project planning, the analyst works with the customers—the potential users of the system and their managers—to collect a broad
range of information to gain an understanding of the project size, potential benefits and costs, and other relevant factors. After collecting and analyzing this
information, the analyst builds the business case that can be reviewed and compared with other possible projects. If the organization accepts the project,
systems analysis begins.
Phase 2: Systems Analysis
The second phase of the SDLC is called systems analysis (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_611) (see Figure
9.11
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
). One purpose of the systems analysis phase is for designers to gain a thorough understanding of an organization’s current way of doing things in the area for
which the new information system will be constructed. The process of conducting an analysis requires that many tasks, or subphases, be performed. The first
subphase focuses on determining system requirements. To determine the requirements, an analyst works closely with users to determine what is needed from
the proposed system. After collecting the requirements, analysts organize this information using data, process, and logic modeling tools.
COLLECTING REQUIREMENTS.
The collection and structuring of requirements is arguably the most important activity in the systems development process because how well the IS
requirements are defined influences all subsequent activities. The old saying “garbage in, garbage out” very much applies to the systems development process.
Requirements collection (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_514) is the process of gathering and organizing
information from users, managers, customers, business processes, and documents to understand how a proposed information system should function.
Systems analysts use a variety of techniques for collecting system requirements, including the following (Hoffer et al., 2014
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12/books/Valacich.3917.17.1/sections/ch09lev1sec12/books/Valacich.3917.17.1/sections/
):
â–  Interviews. Analysts interview people informed about the operation and issues of the current or proposed system.
â–  Questionnaires. Analysts design and administer surveys to gather opinions from people informed about the operation and issues of the current or
proposed system.
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â–  Observations. Analysts observe system users at selected times to see how data are handled and what information people need to do their jobs.
â–  Document Analysis. Analysts study business documents to discover issues, policies, and rules, as well as concrete examples of the use of data and
information in the organization.
â–  Joint Application Design (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_351) . Joint application design (JAD)
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_351) is a group meeting–based process for requirements collection
(Figure 9.12 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig12) ). During this meeting, the users jointly define and
agree on system requirements or designs. This process can result in dramatic reductions in the length of time needed to collect requirements or specify
designs.
FIGURE 9.12 A JAD room.
Source: Based on Wood & Silver (1989
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12#ch09_bib16) ); Hoffer et al.
(2014
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec12/books/Valacich.3917.17.1/sections/ch09lev1sec12/books/Valacich.391
).
MODELING DATA.
Data are facts that describe people, objects, or events. A lot of different facts can be used to describe a person: name, age, gender, race, and occupation, among
others. To construct an information system, systems analysts must understand what data the information system needs in order to accomplish the intended
tasks. To do this, they use data modeling tools to collect and describe the data to users to confirm that all needed data are known and presented to users as
useful information. Figure 9.13 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig13) shows an entity-relationship diagram,
a type of data model describing students, classes, majors, and classrooms at a university. Each box in the diagram is referred to as a data entity, and each entity
is related to other entities. Data modeling tools enable the systems analyst to represent data in a form that is easy for users to understand and critique. For
more information on databases and data modeling, see the Technology Briefing.
FIGURE 9.13 A sample entity-relationship diagram for students.
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MODELING PROCESSES AND LOGIC.
The next step in this phase is to model how data are being input, processed, and presented to the users. As the name implies, data flows
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_159) represent the movement of data through an organization or within an
information system. For example, your registration for a class may be captured in a registration form on paper or in an interactive form on the Web. After it is
filled out, this form probably flows through several processes to validate and record the class registration, shown as “Data Flows” in Figure 9.14
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
. After all students have been registered, a repository of all registration information can be processed for developing class rosters or for generating student
billing
information,
which
is
shown
as
“Data”
in
Figure
9.14
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
. Processing logic (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_480) represents the way in which data are transformed.
Processing logic is often expressed in pseudocode (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_490) , which is a
representation of the program’s internal functioning, independent of the actual programming language being used. As there are no standards for pseudocode,
the level of detail can vary. For example, pseudocode to calculate students’ grade-point averages at the conclusion of a term is shown in the “Processing Logic”
section
in
Figure
9.14
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
.
After the data, data flow, and processing logic requirements for the proposed system have been identified, analysts develop one or many possible overall
approaches—sometimes called designs—for the information system. For example, one approach for the system may possess only basic functionality but has
the advantage of being relatively easy and inexpensive to build. An analyst might also propose a more elaborate approach for the system, but it may be more
difficult and more costly to build. Analysts evaluate alternative system design approaches with the knowledge that different solutions yield different benefits
and different costs. After a system approach is selected, details of that particular system approach can be defined.
Phase 3: Systems Design
The third phase of the SDLC is systems design (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_615) (see Figure 9.11
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
). As its name implies, it is during this phase that the proposed system is designed; that is, the details of the chosen approach are elaborated. As with analysis,
many different activities must occur during systems design. The elements that must be designed when building an information system include the following:
â–  Processing and logic
â–  Databases and files
■ Human–computer interface
DESIGNING PROCESSING AND LOGIC.
The processing and logic operations of an information system are the steps and procedures that transform raw data inputs into new or modified information.
There are typically different ways to complete each process, with some being more efficient or effective than others. Modeling the processes thus includes not
only specifying what is to be done, but also the specific algorithms, which outline the steps, or set of rules, to be followed (that is, how a certain process is
accomplished). For example, when calculating your grade-point average, your school needs to perform the following steps:
FIGURE 9.14 Four key elements to the development of a system: requirements,
data, data flows, and processing logic.
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1. Obtain the prior grade-point average, credit hours earned, and list of prior courses
2. Obtain the list of each current course, final grade, and course credit hours
3. Combine the prior and current credit hours into aggregate sums
4. Calculate the new grade-point average
The logic and steps needed to make this calculation can be represented in many ways, including structure charts, decision trees, pseudocode, programming
code,
and
so
on
(see
Figure
9.14
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
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). Regardless of how the logic is represented, the process of converting pseudocode, structure charts, or decision trees into actual program code during
system implementation is a relatively straightforward process.
DESIGNING DATABASES AND FILES.
To design databases and files, a systems analyst must have a thorough understanding of an organization’s data and informational needs. For example, Figure
9.15 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig15) shows the database design to keep track of student information
in a Microsoft Access database. The database design is more complete (shows each attribute of the student) and more detailed (shows how the information is
formatted)
than
a
conceptual
data
model
built
during
systems
analysis
(as
was
shown
in
Figure
9.14
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
).
DESIGNING THE HUMAN-COMPUTER INTERFACE.
Just as people have different ways of interacting with other people, information systems can have different ways of interacting with people. A human–
computer interface (HCI) (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_290) is the point of contact between a system
and users. With people being used to interacting with easy-to-use systems and Web sites like Facebook, Twitter, and Amazon.com (http://Amazon.com) , their
expectations
in
terms
of
ease
of
use
are
ever
increasing.
In
addition,
increasing
a
system’s
usability
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_655) —that is, whether the system is easy to use and aesthetically pleasing
—can lower error rates, increase efficiency, or increase customer satisfaction (in the case of customer-facing systems). Thus, analysts also take great care in
designing data entry forms and management reports. A form is a business document containing some predefined data, often including some areas where
additional data can be filled in (Figure 9.16 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig16) ). Similarly, a report is a
business
document
containing
only
predefined
data
for
online
viewing
or
printing
(Figure
9.17
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig17) ). For more on forms and reports, see Chapter 6
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch06#ch06) .
Phase 4: Systems Implementation and Operation
Many separate activities occur during systems implementation (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_617) , the
fourth
phase
of
the
SDLC
(see
Figure
9.11
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch09lev1sec2/books/Valacich.3917.17.1/sections/ch
). One group of activities focuses on transforming the system design into a working information system. These activities include software programming and
testing. A second group of activities focuses on preparing the organization for using the new information system. These activities include system conversion,
documentation, user training, and support. This section briefly describes what occurs during systems implementation.
SOFTWARE PROGRAMMING AND TESTING.
FIGURE 9.15 The database design for student information from an Access
database.
Source: Courtesy of Microsoft Corporation.
Programming is the process of transforming the system design into a working computer system. During this transformation, both programming and testing
should occur in parallel. As you might expect, a broad range of tests is conducted before a system is complete, including developmental testing
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_179)
,
alpha
testing
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_9)
,
and
beta
testing
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(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_40)
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09tab4) ).
(Table
9.4
FIGURE 9.16 A data entry form.
FIGURE 9.17 Sales summary report.
SYSTEM CONVERSION, DOCUMENTATION, TRAINING, AND SUPPORT.
System conversion (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_609) is the process of decommissioning the current way
of doing things (automated or manual) and installing the new system in the organization. Effective conversion of a system requires not only that the new
software be installed but also that users be effectively trained and supported. System conversion can be performed in at least four ways, as shown in Figure
9.18 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig18) .
TABLE 9.4 General Testing Types, Their Focus, and Who Performs Them
Testing Type
Focus
Performed by
Developmental
Testing the correctness of individual modules and the integration of multiple modules
Programmer
Alpha
Testing of overall system to see whether it meets design requirements
Software tester
Beta
Testing of the capabilities of the system in the user environment with actual data
Actual system users
Many types of documentation must be produced for an information system. Programmers develop system documentation that details the inner workings of
the system to ease future maintenance and to ensure reliability of the system. A second type of documentation is user-related documentation, which is
typically written not by programmers or analysts but by users or professional technical writers. The range of documents can include the following:
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FIGURE 9.18 Software conversion strategies.
â–  User and reference guides
â–  User training manuals and tutorials
â–  Installation procedures and troubleshooting suggestions
In addition to documentation, users may also need training and ongoing support to use a new system effectively. Different types of training and support
require different levels of investment by the organization. Self-paced training and tutorials are the least expensive options, and one-on-one training is the most
expensive. Table 9.5 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09tab5) summarizes various user training options.
Besides training, providing ongoing education and problem-solving assistance for users may also be necessary. This is commonly referred to as system
support, which is often provided by a special group of people in the organization who make up an information center or help desk. Support personnel must
have strong communication skills and be good problem solvers in addition to being expert users of the system. An alternative option for a system not
developed internally is to outsource support activities to a vendor specializing in technical system support and training. Regardless of how support is
provided, it is an ongoing issue that must be managed effectively for the company to realize the maximum benefits of a system.
Repeating the SDLC: Systems Maintenance
TABLE 9.5 User Training Options
Training Option
Description
Tutorial
One person taught at a time
Course
Several people taught at a time
Computer-aided instruction
One person taught at a time by the computer system
Interactive training manuals
Combination of tutorials and computer-aided instruction
Resident expert
Expert on call to assist users as needed
Software help components
Built-in system components designed to train users and troubleshoot problems
External sources
Vendors and training providers offering tutorials, courses, and other training activities
After
an
information
system
is
installed,
it
is
essentially
in
the
systems
maintenance
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_619) phase. A system does not wear out in the physical manner that cars,
buildings, or other physical objects do, but it must still be systematically repaired and/or improved. The types of maintenance are summarized in Table 9.6
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09tab6) .
TABLE 9.6 Types of Systems Maintenance
Maintenance Type Description
Corrective
maintenance
Making changes to an information system to repair flaws in the design, coding, or implementation
Adaptive
maintenance
Making changes to an information system to evolve its functionality, to accommodate changing business needs, or to migrate it to a
different operating environment
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Maintenance Type Description
Preventive
maintenance
Making changes to a system to reduce the chance of future system failure
Perfective
maintenance
Making enhancements to improve processing performance or interface usability, or adding desired but not necessarily required system
features (in other words, “bells and whistles”)
During systems maintenance, it is typical that one person within the systems development group is responsible for collecting maintenance requests from
system users. Periodically, these requests are analyzed to evaluate how a proposed change might alter the system and what business benefits might result
from such a change, and are prioritized accordingly (Figure 9.19 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig19) ).
As with adaptive maintenance (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_4) , both perfective maintenance
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_458)
and
preventive
maintenance
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_474) are typically a much lower priority than corrective maintenance
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_138) , which deals with repairing flaws in the system. Corrective
maintenance is most likely to occur after initial system installation as well as over the life of a system after major system changes. This means that adaptive,
perfective, and preventive maintenance activities can lead to corrective maintenance activities if they are not carefully designed and implemented.
FIGURE 9.19 Change request management is used during systems maintenance.
As with developing or acquiring new systems, any changes to an existing system need to be carefully managed. Unmanaged change can have a variety of
negative consequences, including system malfunction, system failure, increasing unreliability (as errors tend to build up over time, making the system more
fragile), or opening the door for fraud or deliberate misuse (e.g., if a “backdoor” is introduced during changes to a system). If the change request is approved,
a system change is designed and then implemented. As with the initial development of the system, implemented changes are formally reviewed and tested
before
being
installed
into
operational
systems.
Thus,
change
request
management
(http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/bm02#bm02_gloss_88) is a formal process that ensures that any proposed system changes are
documented, reviewed for potential risks, appropriately authorized, prioritized, and carefully managed (to establish an audit trail; to be able to trace back who
reviewed, authorized, implemented, or tested the changes). In other words, the systems maintenance process parallels the process used for the initial
development of the information system, as shown in Figure 9.20 (http://content.thuzelearning.com/books/Valacich.3917.17.1/sections/ch09lev1sec2#ch09fig20) .
Interestingly, it is often during system maintenance that the largest part of the system development effort occurs.
KEY PLAYERS: Game Development Studios
Have you ever wondered how and where tech companies generate so much money each year? For example, in 2012, some of the largest tech
companies, including mainstays like IBM (US$104 billion in total revenue) and Apple (US$164 billion in total revenue), generated their massive
revenues with a mix of hardware, services, and software sales. For these giants, however, software revenue was a relatively modest portion,
amounting to 27.6 percent (US$29 billion) for IBM, and only 1.0 percent (US$1.6 billion) for Apple. In contrast, software giant Microsoft, with total
https://content.uagc.edu/print/Valacich.3917.17.1?sections=ch09,ch09lev1sec1,ch09lev1sec2,ch09lev1sec3,ch09lev1sec4,ch09lev1sec12&content…
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revenue topping US$73 billion, generated about 80 percent (US$58 billion) of its revenue through software sales, making Microsoft the highestgrossing software company in the world.
A closer analysis of the sources of revenue of the largest “software companies” shows that most derive income from a variety of sources beyond
software sales. Few software companies are capable of standing out solely by relying on software revenue—that is, with the exception of gaming. Top
game developers such as CAPCOM (e.g., Resident Evil), and Rockstar North (Grand Theft Auto) generate nearly 100 percent of their revenue from
software sales.
While all software development follows a methodology like the SDLC, game development has some unique characteristics given the high
entertainment or educational goals of this type of software. In a normal SDLC, analysis and design activities are car…
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