Unlock document.
This document is partially blurred.
Unlock all pages and 1 million more documents.
Get Access
632
– 632 –
TEACHING NOTE
CASE 28
Amazon’s Big Data Strategy
Overview
Over the 20 years since its founding by Jeff Bezos in 1994, Amazon had evolved from being a pure
e-commerce player into a giant Internet services firm, It reached $61 billion in 2012 revenues as well
as $39 billion in net losses in that year. Amazon had grown by product diversification into other on-line
retail categories besides books, via websites in 45 countries, via launches of new products and servicse (Kindle
and Amazon Webstore) as well as by acquisition—Amazon acquired the on-line shoe retailer Zappos.com in
2009, and The Washington Post newspaper in 2013.
Amazon offered a large range of cloud-based and analytical services for individuals and corporations. These
services focused on data gathering, data mining, and analytics, thus Amazon embarked on a transition from
a pure online retailer into a gigantic “big data” company. Amazon not only utilized the historical consumer
purchase data, but also click-stream data to show webpages with uniquely customized information. Using such
data helped Amazon in many ways other than showing the related and alternative products that consumers sought.
By mining vast amounts of data, Amazon helped other e-commerce companies to understand their customers’
inner feelings and preferences.
Due to the limited resources at their disposal, small companies typically faced a lot of difficulties in adopting and
deploying big data. Amazon responded by providing solutions for small companies so that they could implement
big data easily. In November 2013, Amazon Web Service announced a new service for real time processing of
big data—Kinesis—that processed the high volumes of data flowing into Amazon’s web-based storehouses on
a real-time basis. The ability to create big data apps through Kinesis was expected to remove one of the biggest
bottlenecks for smaller companies in using big data. But one limitation of Kinesis was that all the data processing
would be done at the data centers of Amazon itself instead of at the clients’ location.
By early 2014, Amazon appeared to have all the pieces of the big data puzzle, but analysts warned that the
company would have to put those together effectively in order for it to emerge as a dominant player over close
rivals Google and Facebook.
Suggestions for Using the Case
Because of its subject matter, the Amazon case is most versatile in that it can be used directly after your strategy
formulation module or during your strategy implementation module. The case is intended to stimulate debate
about the prospects of a mature, entrepreneurial firm to transform itself to become a leader in the big data
segment of the global information technology (IT) industry against direct rivals Google and Facebook.
To recap your strategy formulation module, students can review techniques they have learned to assess a
company’s tangible as well as intangible resources and capabilities, using the VRIN analysis covered in Chapter
4 (“Evaluating a Company’s Resources, Capabilities, and Competitiveness”).
*
*This teaching note reflects the thinking and analysis of Professor Armand Gilinsky, Sonoma State University. We are most grateful
for his insight, analysis and contributions to how the case can be taught successfully
Case 28 Teaching Note Amazon’s Big Data Strategy
633
To illustrate concepts in your strategy implementation module, the case can be used to illustrate how good
strategy execution is critical to achieving competitive advantage. The case pairs nicely with coverage of the
“Managing Internal Operations” topic in Chapter 11, and serves as an illustration of how resources may be
allocated to promote superior strategy execution, even—in Amazon’s case—at the expense of profits.
Finally, and perhaps most provocatively, a question may arise about the ownership, security, and ultimate
uses of the absolutely massive amounts of customer data being gathered and retained by Amazon’s own
e-commerce divisions as well as from its small business e-commerce clients.
Thus, the “Amazon Big Data” case provides an excellent opportunity to stimulate a debate about the interests of
various stakeholders in data ownership, security, and use, and thus is quite suitable for a review or application of
the material covered in Chapter 9, particularly the sections on Ethics and Corporate Social Responsibility (CSR).
Video for Use with the Amazon’s Big Data Strategy Case There is a McKinsey & Company video
entitled “Applying Advanced Analytics in Consumer Companies” that you can show in class or have students
view on their own. The 4:11 video can be accessed at http://www.mckinsey.com/insights/ consumer_and_
retail/applying_ advanced_analytics_in_consumer_ companies.
To facilitate your use of assignment questions and making them available to students, we have posted a file of
the Assignment Questions contained in this teaching note on the instructor resources section of the Connect
Library. In all instances, these assignment questions correspond to the assignment questions in the teaching
note for the case.
In our experience, it is quite difficult to have an insightful and constructive class discussion of an assigned case
unless students have conscientiously have made use of pertinent core concepts and analytical tools in preparing
substantive answers to a set of well-conceived study questions before they come to class. In our classes, we
expect students to bring their notes to the study questions to use/refer to in responding to the questions that
we pose. Moreover, students often find that a set of study questions is useful in helping them prepare oral
team presentations and written case assignments—in addition to whatever directive question(s) you supply for
these assignments. Hence, we urge that you provide students with assignment questions—either those we have
provided or a set of your own questions—for all those aspects of a case that you believe are worthy of student
analysis or that you plan to cover during your class discussion.
Utilizing the Guide to Case Analysis. If this is your first assigned case, you may find it beneficial to have
class members read the Guide to Case Analysis that immediately follows Case 31 in the text. The content of this
Guide is particularly helpful to students if your course is their first experience with cases and they are unsure
about the mechanics of how to prepare a case for class discussion, oral presentation, or written analysis.
Assignment Questions
1. Evaluate the key strategy implementation efforts at Amazon. Has management allocated sufficient resources
to the strategy execution effort? Exercised strong leadership to propel strategy execution forward? Instituted
polices and procedures that facilitate good strategy execution? Explain.
2. What is the role of information and operating systems at Amazon? Do these enable company personnel
to carry out their strategic roles proficiently? To what extent are these systems providing Amazon with a
competitive advantage?
3. Is the current strategy for Amazon producing good strategic and financial results? What are some key
indicators of performance?
4. In what ways, if any, is the use of big data helping or hindering Amazon? Is the use of big data reflective of a
commitment to corporate social responsibility? Why or why not? Are there any changes to its CSR strategy
that you would suggest? What might be the long-term interests of shareholders and other stakeholders?
Case 28 Teaching Note Amazon’s Big Data Strategy
634
5. What business strategy recommendations would you make to Jeff Bezos, Amazon’s CEO? Should the
company redouble its efforts to broaden its horizontal or vertical scope using big data? Should the company
consider new strategic partnerships or new acquisitions? Are there other potential strategic options that he
needs to consider? Please justify your recommendations by outlining the pros and cons of each.
Teaching Outline and Analysis
1. Evaluate the key strategy implementation efforts at Amazon. Has management allocated
suffcient resources to the strategy execution effort? Exercised strong leadership to
propel strategy execution forward? Instituted polices and procedures that facilitate
good strategy execution? Explain.
This is a good place to review and affirm students’ knowledge of the resource-based view of strategy concepts
covered in Chapter 4. From a review of the four tests of competitive power covered in Chapter 4, it should
be apparent that some of Amazon’s current organizational resources and capabilities are valued and rare as
Of those three tangible resources and capabilities, Amazon’s Web Services’s (AWS) data architecture—
developed and deployed to provide small business customers with services that they cannot or are not
TABLE 1. Resource and Capability Analysis for Amazon.com’s
Information Technology Function
Resource/Capability Data Architecture Customer Service Seasoned IT Developers
Valued
Is the resource (or capability)
competitively valuable?
Yes—Data centralization
critical to control
Yes—Proven track record
with Amazon Web Store &
AWS
Yes
Rare
Is the resource rare—is it
something rivals lack?
Yes Yes—Rivals cannot (or
have chosen not to) match
customer ratings and
algorithms—yet.
No—Google & Facebook
can hire & train IT experts
or poach them from
Amazon
Can the resource be trumped
by different types of resources
& capabilities, i.e. are there
good substitutes available for
the resource?
Facebook in the
advertising space
Facebook are likely to enter
Internet commerce over time
Business-to-business customer service and the recruitment, training, and retention of seasoned IT developers
probably can and may well be trumped over time by rivals such as Google and Facebook, provided those
Case 28 Teaching Note Amazon’s Big Data Strategy
635
2. What is the role of information and operating systems at Amazon? Do these enable
company personnel to carry out their strategic roles proficiently? To what extent are
these systems providing Amazon with a competitive advantage?
Role of information and operating systems at Amazon
n Amazon’s product recommender system which provided product suggestions to customers depending
upon their past purchasing behavior
• Data collected from customers primary driving force behind Amazon’s recommender system
How these enable Amazon personnel to carry out roles
n Customer service executives had speedy access to data regarding past purchases and browsing history
of its customers
big data was also used to check fraud in the organization.
How these provide Amazon with a competitive advantage
n Outclasses rival companies that do not concentrate on the importance of big data
• Amazon quick to cash in on the invaluable database of people who shopped on its e-commerce
portals around the world
n Makes the right products available to customers
3. Is the current strategy for Amazon producing good strategic and financial results?
What are some key indicators of performance?
The two best indicators of how well a company’s strategy is working are: (1) whether the company is
achieving its stated financial and strategic objectives and (2) whether the company is an above-average
industry performer. There are neither sufficient financial and operating data in the case nor comparative
Case 28 Teaching Note Amazon’s Big Data Strategy
636
TABLE 2. Common Size Income Statements and Growth Rates
for Amazon, FY 2008–2012
FYE—all
amounts in $
millions 2012 2011 2010 2009 2008
Total net sales $61,093 100.0% $48,077 100.0% $34,204 100.0% $24,509 100.0% $19,166 100.0%
Total operating
expenses 60,417 98.9% 47,215 98.2% 32,798 95.9% 23,380 95.4% 18,324 95.6%
Income from
operations 676 1.1% 862 1.8% 1,406 4.1% 1,129 4.6% 842 4.4%
Interest
income 40 0.1% 61 0.1% 51 0.1% 37 0.2% 83 0.4%
Interest
expense (92) -0.2% (65) -0.1% (39) -0.1% (34) -0.1% (71) -0.4%
Data calculated from case Exhibit 2
Amazon is apparently scaling up to own the big data space, as opposed to scaling for profits. The whys and
wherefores of Amazon’s approach to top-line vs. bottom-line growth will be discussed in Questions 4 and 5.
Case 28 Teaching Note Amazon’s Big Data Strategy
637
4. In what ways, if any, is the use of big data helping or hindering Amazon? Is the use
of big data reflective of a commitment to corporate social responsibility? Why or why
not? Are there any changes to its CSR strategy that you would suggest? What might
be the long-term interests of shareholders and other stakeholders?
How use of big data helps Amazon
n Used best practices from the customer service strategies of Zappo’s (after Amazon purchased that
company in 2009) to provide a personal touch to its customers and turn them into its fans and cheerleaders
n Gave customers highly customized suggestions to make them buy more
n Enabled product related recommendations to be customized based on many factors such as the customer’s
location and demography
n Made it possible for Amazon to show more relevant and reliable reviews to the customers just as it
suggested relevant products
n Could revitalize the newly-acquired Washington Post news business and find new revenue sources for
the ageing business
n Provided “an immediate lift of 40 percent in revenue and average order size,” according to Amazon’s
e-commerce director Cal Clough
On the one hand…
n Some would conclude that the benefits (ends, or results) of Amazon’s actions indeed justify the costs
(means) in terms of revenue growth, increased market power, and a first-mover competitive advantage
(even if the latter is only temporary)
Case 28 Teaching Note Amazon’s Big Data Strategy
638
On the other …
n A utilitarian might come to the opposite conclusion if he or she valued customer privacy highly and
viewed Amazon’s data gathering, storage, and analytics efforts as an invasion of privacy.
On the one hand …
n Amazon took ownership of the data and opinions of its customers and for its own ends without returning
those rewards directly to customers
n If data can be considered “property,” Amazon jeopardized the property rights of customers by mining
and reselling data
Justice-based analysis. A person or entity using utilitarian reasoning adds up costs and benefits to see if
one is greater than the other; if benefits exceed costs, then the action would probably be considered ethical.
n The company and its managers and stockholders and small business customers all benefit directly, and
consumers benefit indirectly via customized solutions and better services.
1See http://247wallst.com/technology-3/2014/09/06/the-10-biggest-data-hacks-of-all-time/
Case 28 Teaching Note Amazon’s Big Data Strategy
639
5. What business strategy recommendations would you make to Jeff Bezos, Amazon’s
CEO? Should the company redouble its efforts to broaden its horizontal or vertical
scope using big data? Should the company consider new strategic partnerships or new
acquisitions? Are there other potential strategic options that he needs to consider?
Please justify your recommendations by outlining the pros and cons of each.
Students should engage in an active and freewheeling discussion to defend their recommendation to Amazon
to (1) continue building out its existing business model using big data, (2) propel growth and profitability
TABLE 3. Pros and Cons of Strategic Options Related
to Amazon.com’s Big Data Strategy
Option Pros Cons
Continue Preserves entrepreneurial can-
do spirit, company culture,
and investments in information
technology and operating systems
Rival firms such as Google or
Facebook may catch Amazon by
developing similar or stronger data
analytics, customer service & IT
capabilities
Instructors can wrap-up the discussion by asking students if they strongly feel that Amazon’s development
and deployment of big data is a good example of how companies get an important boost from investing in
IT and operating systems. It seems clear to us that Amazon’s efforts to recruit and train IT employees in
Case 28 Teaching Note Amazon’s Big Data Strategy
640
n Rivals Google and Facebook, have business models primarily based on advertising
n Well-conceived state-of-the-art operating systems not only enable better strategy execution, but also
Epilogue
Amazon’s business remained highly capital-intensive in terms of spending on technology and content, as the
company added about $3.4 billion in capital expenditures in 2013. As a result, barriers to entry in big data
were raised. However, Amazon faced intense price competition from bricks and mortar retailers as well as
other Internet retailers. Other challenges and weaknesses inherent in Amazon’s business model included low
switching costs for consumers when shopping online, and the roll-out of search engines by Yahoo! and Google
that simplified and enabled comparison shopping.
Strengths of the company included: strong brand name recognition; the breadth and depth of the company’s
product lines; a user feedback feature that helped to build trust and increase customer loyalty; a strong balance
sheet, with over $11.4 billion in cash and marketable securities and no long-term debt (not mentioned in the case
but students will probably look this up); and efficient deployment of capital on technology to help promote a fast,
user-friendly shopping experience.
In 2012, only about 8% of total U.S. retail sales were estimated to be e-commerce transactions, totaling $231
billion. Forrester Research anticipates that figure will rise to 10% by 2017, to $370 billion. Another opportunity
is the growing use of the Internet internationally, with penetration rates at 33% at the end of 2011 (latest
available), according to Internet World Stats. This compares to 78% penetration in the U.S., and demonstrates
strong potential for increased Internet usage and e-commerce sales abroad.
On June 19, 2014, Amazon unveiled Fire, the company’s first smartphone. The Fire smartphone combined
existing Amazon technologies such as X-Ray, WhisperSync, Audible and MayDay customer support. In addition,
the phone supported Firefly technology, which enabled users to scan anything with the camera. Users could use
the Firefly technology, similarly to Dash, and shop for almost anything with purchases directed back to Amazon.
Amazon saw an initial spike in its share price, but has (as of October 2014) seen share prices drift downwards
as much as two percent.
On August 26, 2014, Amazon agreed to acquire privately held Twitch, a live streaming platform for games, for
$970 million in cash. With over 55 million monthly unique visitors, Twitch allowed users to upload and watch
free ad-supported live game videos on gaming consoles, and also offered some monthly subscriptions, serving
to further Amazon ‘s recent forays into the video game space since its latest of launches of Fire TV and branded
smartphones.
On September 8, 2014, China-based Alibaba Group, kicked off a U.S. roadshow ahead of a much-heralded
IPO, in what analysts thought could presage intensifying head-to-head competition between the world’s largest
e-commerce companies. Amazon recently set its own plans for a new cross-border hub in Shanghai’s free trade
zone, the latest of which has thus far seemed like somewhat feeble efforts to connect with consumers in China,
where Alibaba holds sway.
Case 28 Teaching Note Amazon’s Big Data Strategy
641
TABLE 4. Financial Summary for Amazon.Com,
Fiscal 2012–Fiscal 2013 ($ in millions)
FYE 12/31/13 % of revenue FYE 12/31/12 % of revenue
Revenue $74,452 100.00% $61,093 100.00%
Operating Inc. 3,547 4.76% 2,835 4.64%
Depreciation 2,802 3.76% 2,159 3.53%
Interest Exp. 141 0.19% 92 0.15%
Pretax Inc. 435 0.58% 389 0.64%
Tax Rate 37.00% 31.00%
Net Income 274 0.37% (39) -0.06%
EPS $0.59 ($0.09)
Source: Amazon.com 2013 Annual Report
