Expert answer:critical thinking – case study the future of drive
Expert answer:please see attached description of homework, Please make sure questions were answered and there is a conclusion. My professor always want to have examples while answering the questions related to the company in an industry of choice as a business catalyst.Thank you very much!
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REV: OCTOBER 28, 2015
DAVID B. YOFFIE
Mobileye: The Future of Driverless Cars
In 1999, more than a decade before Google captured the imagination of the world with the idea of
a self-driving car, Professor Amnon Shashua of Hebrew University in Jerusalem and entrepreneur
Ziv Aviram had a dream about how to build the next-generation autonomous car. Rather than
focusing on unreliable radar or expensive lasers, they believed that a single, cheap camera combined
with sophisticated software could reduce collisions, prevent accidents, and save lives. Fifteen years
later that dream was coming true: Mobileye went public on the NYSE in August 2014, with a
valuation that quickly exceeded $11 billion. According to Aviram, everyone told them they were on
the wrong track in the early days: they had picked the wrong technology, the wrong functions, and
the wrong customers. But with 285 car models and 20 car manufacturers already committed to their
technology, Mobileye was on a roll. Mobileye forecasted that within a few years it would capture
roughly an 80% share of the autonomous driving systems in the world.
Success meant that Shashua and Aviram were newly minted billionaires—at least on paper. They
were also close personal friends who met through their wives. They enjoyed riding mountain bikes
and motorcycles together and even taking family vacations together. Shashua, as chairman, and
Aviram, as CEO, described their partnership as “two-in-a-box,” an organizational innovation
developed in the 1970s by Intel. Shashua handled all of the technical work in this deeply technical
company, while Aviram managed the business side. On strategy, they made all decisions together.
Sitting around the table in Aviram’s sixth-floor office in a non-descript building in Har Hotzvim
(the high-tech park) on the outskirts of Jerusalem, the two partners debated two dilemmas about the
company’s future. First, car companies were notorious for squeezing their suppliers on price. Aviram
believed that part of Mobileye’s success had come from maintaining stable pricing. Yet Mobileye’s
volumes were about to explode, and some car companies were threatening to look elsewhere if prices
did not come down in the lower-end segments. Shashua and Aviram discussed whether Mobileye
should sacrifice margin in order to retain share, or continue to hold firm on price.
Second, they debated their role in self-driving cars. This debate had immediate relevance because
Shashua was about to give a talk at Google’s campus in Mountain View, California. He also expected
to meet with Google’s team in charge of its self-driving car. Naturally, Google was going to have
many questions about Mobileye’s technology and business strategy. In fact, Mobileye had developed
its own self-driving car. For Shashua and Aviram, this upcoming visit raised obvious questions about
the efficacy of Google’s approach, what role Google vs. Mobileye would play in the future of selfdriving cars, and whether Google was a potential competitor or partner for Mobileye.
Professor David B. Yoffie prepared this case with the assistance of Research Associate Eric Baldwin. It was reviewed and approved before
publication by a company designate. Funding for the development of this case was provided by Harvard Business School and not by the
company. HBS cases are developed solely as the basis for class discussion. Cases are not intended to serve as endorsements, sources of primary
data, or illustrations of effective or ineffective management.
Copyright © 2014, 2015 President and Fellows of Harvard College. To order copies or request permission to reproduce materials, call 1-800-5457685, write Harvard Business School Publishing, Boston, MA 02163, or go to www.hbsp.harvard.edu. This publication may not be digitized,
photocopied, or otherwise reproduced, posted, or transmitted, without the permission of Harvard Business School.
This document is authorized for use only in Kris Michaelson’s MGT579 – WIB17 course at Colorado State University – Global Campus, from November 2017 to May 2018.
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Mobileye: The Future of Driverless Cars
The Vision of Assisted Driving and Self-Driving Cars
Amnon Shashua was described by his partner, Aviram, as a “brilliant computer scientist” who
made Mobileye possible. Soft-spoken but confident, the Hebrew University professor had received
his PhD from MIT’s Artificial Intelligence Lab in 1993. An expert in visual systems and machine
learning, Shashua had previously founded a company that developed camera-based machines to
perform detailed inspections of auto parts. 1 Shashua said that he “learned a lot from my first
company,” where he built a product for Toyota, which only Toyota wanted. “It was a miserable
failure,” noted Shashua. “The venture capitalists (VCs) took control of the company, fired the CEO,
asked me to step down as chairman, and ultimately sold the company for half of the invested
capital.” When he started Mobileye, he wanted to do things differently.
The first difference was that he found a trusted partner in Aviram, who had emigrated from
Russia to Israel when he was nine years old. A former army commander who had led 100 soldiers
into battle, Aviram had a background in industrial engineering. Described by Shashua as a “financial
and managerial genius,” Aviram believed that management was a profession that could be applied
across industries. Before founding Mobileye, Aviram had been CEO of Israel’s largest bookstore
chain, CEO of the country’s biggest shoe retailer, and CEO of a water park.
Shashua and Aviram’s vision was to put Mobileye in the center of Advanced Driver Assistance
Systems (ADAS). The world of assisted-driving and ultimately self-driving cars was replete with
acronyms, such as LDW (Lane Departure Warning), FCW (Forward Collision Warning), and TSR
(Traffic Sign Recognition) (see Exhibit 1 for a list of acronyms). These systems were designed to
actively improve safety and avoid accidents, while airbags and seatbelts were passive safety measures
designed to save lives after an accident. The next phase in ADAS was fully autonomous vehicles,
which were still in the testing stage in 2014. However, many of the underlying technologies were
already available. ADAS ranged from simple systems that warned the driver of an impending
problem (e.g., that the car was beginning to drift out of its lane), to complex systems that actively
took control of the vehicle (e.g., by steering the vehicle back into its lane or applying the brakes to
avoid a collision or hitting a pedestrian). Mobileye used a single camera to scan the road ahead and
identify obstacles, road signs, traffic lights, etc., and then interpret the image and send signals to the
driver or other car systems to take evasive action (see Exhibit 2 for pictures of how Mobileye
worked).
Shashua and Aviram saw many of these capabilities coming before most of their customers and
long before many competitors. They also believed that they could deliver many of these functions
with a single, low-cost camera. Shashua described their theory:
We understood early on that the camera should be the primary sensor. We began
developing vehicle detection from a single camera back in the year 2000, when the
industry believed radar would be primary. We began developing pedestrian detection
back in 2002 when the industry was not even contemplating the necessity. Mobileye was
the first to launch a Pedestrian Collision Warning feature in 2010. We were the first to
launch FCW for detecting licensed vehicles back in 2011. In 2013, we were first to launch
Autonomous Emergency Braking (AEB) on vehicles using only camera processing. In
2013, we were the first to launch Adaptive Cruise Control (ACC), which actively
adjusted the speed of a vehicle to maintain a safe following distance during highway
driving, from a camera. To date, competitors have not introduced any of those functions
on a single camera. [See Exhibit 3 for a list of Mobileye’s pioneering innovations.]
2
This document is authorized for use only in Kris Michaelson’s MGT579 – WIB17 course at Colorado State University – Global Campus, from November 2017 to May 2018.
Mobileye: The Future of Driverless Cars
715-421
Beyond the technology, Shashua said that many of the key elements of the business model were
also clear “from Day 1.” He knew, for example, that regulations would drive demand because the
technology saved lives. He admitted that his biggest surprise was that it took eight years to launch.
“If I thought it could take until 2007,” noted Shashua, “I probably would not have done it.”
Looking forward, Shashua and Aviram believed that the company’s success depended on both
evolutionary and revolutionary changes in cars and trucks. As regulations increasingly forced
companies worldwide to add ADAS to reduce accidents and auto-related deaths, Aviram noted that
“We expect that by 2017–2019 the majority of new cars manufactured worldwide will have a camera
equipped with active safety features.” Perhaps more important, they believed that revolutionary
trends were on the horizon that would, according to Shashua, push the world “in leaps and bounds
[into the] realm of autonomous driving.” Shashua explained: “We know today that the utopian vision
of completely autonomous driving—where the driver can choose to be out of the driving loop for
extended periods of time—is not about to be achieved in a single leap.” In the 2016 time frame,
Mobileye expected the first hands-free-capable driving at highway speeds. Drivers could not go to
sleep or read a book, but Mobileye had already built a prototype car in 2014 that could drive on
highways without driver intervention. Stop-and-go traffic would be next, followed by country roads,
and ultimately, in 2018–2020, city traffic. Shashua and Aviram did not share Google’s optimistic
projections that a self-driving car was only a few years away; they believed that the truly self-driving
car, which allowed the driver to disengage totally, was probably a decade away.
Financing Mobileye’s Growth
Mobileye had a relatively focused product line: it had developed a custom semiconductor chip
(called EyeQ), a bundle of software applications, and a simple camera and warning display that sold
in the aftermarket (see Exhibit 4 for pictures of Mobileye’s products). Since it took 14 years for the
company to make these products profitable, Aviram needed an unconventional approach to
financing the company. From the very beginning, he didn’t want VC money; he believed that VCs
were “short-term investors,” and Aviram knew that he needed patient capital. Instead, he found a
broker and asked him to find 100 investors who would invest $5,000 each. In the end, he raised
$1 million from 14 angels. His plan was to do small rounds, almost every year, with angels and
friends. “My philosophy,” said Aviram, “[was] take more money than you think you will need. I
wanted at least four years of capital on the balance sheet, but I always ran the company as lean as
possible.” As major car manufacturers began testing Mobileye’s technology for detecting vehicles,
road markings, and road geometry, Aviram raised $30 million in 2002, with a post-money value of
$135 million.2 By 2006, Mobileye began installing systems in trucking fleets that would warn drivers
of imminent collisions or unintentional lane departures.3 In 2007, BMW, GM, and Volvo became the
first automobile manufacturers to include Mobileye technology in safety packages for production
passenger vehicles.
By 2007, Aviram concluded, it was time to take institutional money. Goldman Sachs led the first
institutional round at a $500 million valuation, and took more than 20% of the company on its own
books. The timing was fortuitous: as its competitors retrenched during the Great Recession of 2008–
2010, Mobileye “had money,” according to Aviram, “which allowed us to be aggressive.” Growing
penetration of its technology spurred additional funding that increased the company’s valuation to
$740 million in 2010.4 By 2014, the company proudly announced that it had agreements to implement
its technology in 237 car models from 20 automakers by 2016, plus another 40 or so unannounced
models. With widespread adoption, the company experienced rapid revenue growth: it shipped
1 million of its EyeQ chips from 2007 to mid-2012, and delivered 1.3 million chips in 2013 alone (see
3
This document is authorized for use only in Kris Michaelson’s MGT579 – WIB17 course at Colorado State University – Global Campus, from November 2017 to May 2018.
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Mobileye: The Future of Driverless Cars
Exhibit 5 on chip sales growth). In the summer of 2013, Mobileye raised $400 million, which valued
the company at $1.5 billion.5
When Mobileye did a road show for its IPO in the summer of 2014, it reported that revenues had
doubled in each of the past two years, from under $20 million in 2011 to over $80 million in 2013. On
the strength of that revenue growth, Mobileye reported a profit for the first time in 2013, with net
income of nearly $20 million (see Exhibits 6a and 6b for the P&L and balance sheet).6 Investors and
analysts responded positively when Mobileye went public on the New York Stock Exchange (NYSE)
in the summer of 2014 (under the ticker symbol MBLY). The Jerusalem Post called it “the most
successful share offering an Israeli firm ever managed abroad,” despite the fact that it was during a
war between Israel and Gaza, and the IPO “happened in the heat of the fighting.”7 Indeed, strong
demand led the company to raise its offering price from an initial estimate of $18 per share to $25 per
share when it debuted on August 1; at that price, the company raised $890 million on a market
valuation of $5.3 billion. The price rose 48% on the first day of trading. When Mobileye’s valuation
passed $11 billion in early September, it became the third-largest Israeli company by market
capitalization.8
Post IPO, Mobileye was employing over 400 people in Israel and the Netherlands (its legal
headquarters) in addition to 150 people in quality assurance in Sri Lanka.9 Most of Mobileye’s costs
were in R&D the company had no factories and had a tiny sales force, mostly focused on the
aftermarket. Aviram believed that Mobileye had built a unique team. He argued, “In Israel, the
loyalty to a firm is unparalleled. So far, none of our people have left for competitors. We save lives. It
is so visible and our people love the company. I took 100 people to NYC to ring the bell at the NYSE
on the day we went public. My biggest challenge is to keep them motivated and excited, even though
they are rich. We made 300 people, mostly young engineers, into millionaires.”
Mobileye Technology
One day in 1999, Shashua was giving a lecture on visual computing to a leading car manufacturer
in Japan, when he was asked whether two cameras were required to help a car “see.” After a moment
of reflection, Shashua said, “Why do you need two cameras? If a driver can drive with one eye, why
can’t a car do pattern recognition with one camera?” On his return to Israel, Mobileye was born. The
breakthrough insight was that Mobileye could design chips and software algorithms for imageprocessing using a single, low-cost camera. With a small camera mounted on the windshield behind
the rearview mirror, Mobileye’s custom-designed “EyeQ” System-on-Chip (SoC), combined with
powerful software, would perform pattern recognition. Shashua noted that “only a camera sensor can
capture the complexity and richness of the visual world and cost a few dollars.” At the same time,
Shashua explained that cameras had to overcome variability in lighting and weather conditions,
which posed great challenges for extracting a stable and consistent interpretation under all driving
conditions. A monocular camera posed the greatest challenge because it did not provide depth
perception. As a result, cameras played a limited role in early ADAS. The primary sensor at the time
was radar, which was largely used for adaptive cruise control.
Early Strategic Decisions: Chips and Software
Mobileye never manufactured the camera. Instead, Shashua and Aviram made two big strategic
decisions very early in the company’s history. Aviram recounted:
The first decision was to develop all the apps in one unit.
4
This document is authorized for use only in Kris Michaelson’s MGT579 – WIB17 course at Colorado State University – Global Campus, from November 2017 to May 2018.
Mobileye: The Future of Driverless Cars
715-421
Amnon and I were in the middle of a motorcycle ride, standing on a cliff overlooking
the Dead Sea. While standing there, we received a call from one of our customers, a Tier
1 auto supplier. [For the definitions of Tier 1 and Tier 2 auto suppliers, see “Mobileye’s
Role in the Automotive Value Chain” below.] The customer asked us to bid with them
on a Lane Departure Warning system. At the time, we had only developed the software
for a collision warning system, which used a single camera to recognize a car was in
front of you. Nonetheless, we decided to develop the LDW application, and won the bid.
During this process, we realized that a full suite of applications is the key for the
automotive industry. In order to achieve this, we needed to bundle lane detection,
vehicle detection, pedestrian detection, and other features into a full suite of applications
in one unit—and not go the traditional path of one app at a time.
Our second decision was related to the development of our own System-on-Chip.
When we founded the company, our initial strategy was to develop software and use
pre-existing hardware. We agreed with a microprocessor manufacturer that they will
adapt one of their chips to automotive grade that could be used for our purposes. Then
our supplier missed its first two deadlines to deliver the chip. At that point, we realized
that we had to develop our own SoC, even though we had zero expertise in chip design.
The decision to develop their own chip meant $3–$5 million in added investment and more than a
three-year delay. Many in the industry were certain this was a mistake. Aviram recalled, “One of the
car companies called us to Germany and told us to drop our plans for the SoC and stick to software.
But we were convinced that integrating hardware and software would allow us to highly optimize
power and performance for a vision system.” Mobileye found STMicroelectronics, a large
semiconductor firm based in Geneva, to manufacture the chip at automotive grade and guarantee
reliability. The chip cycles were roughly three to four years, and with each new generation of
product, Mobileye’s EyeQ SoC was six to eight times more powerful than its predecessor. The added
performance empowered increasingly sophisticated visual processing, which partly compensated for
the lack of depth perception, and enabled more complex driver assistance and autonomous driving
functionality.
The Single-Camera System
One crucial differentiator for Mobileye’s technology was the ability to support a wide variety of
driver-assistance functions using a single camera. Bosch, Continental, and Autoliv promoted socalled “stereo cameras,” which used two cameras for triangulation and greater depth. Their theory
was that two cameras were better than one. Shashua argued that there was a small niche for stereo,
but it was “shrinking.” Most OEMs (excluding Mercedes), he noted, were “phasing out stereo”
because of the added cost (an extra 40%), increased complexity of the software, difficult calibration,
poor aesthetics, and poor performance. Mobileye’s monocular camera dramatically lowered the cost
for an auto manufacturer compared to multi-camera systems, as well as competing technologies
(such as radar and lidar, which are discussed …
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