Data Can Be a Matter of Corporate Life and Death

Data is at the heart of some of the most influential concepts in business management. Authors such as Jim Collins, Geoffrey Moore, and Clayton Christensen have placed data at the center of their theories on why some businesses thrive, and why others crash and burn.

Collins, author of Good to Great, outlines many characteristics of companies that moved from being decent businesses to great investment performers. One characteristic: having a CEO at the helm who is a “Level 5 Executive,” who builds “enduring greatness through a paradoxical blend of personal humility and professional will.” These companies also have a “culture of discipline” and embrace technology, not for technology’s sake but to improve the business.

Another key element of what Collins called “good-to-great” companies is data-driven: they rely on an “economic denominator” that uses data to measure a key performance indicator. At Walgreens, for example, the economic denominator is profit per customer visit. For Nucor, it was profit per ton of finished steel. And for Abbott it was profit per employee.

In the philosophy of Moore, author of Crossing the Chasm and Inside the Tornado: Marketing Strategies from Silicon Valley’s Cutting Edge, data is the key driver in an ever-changing world that marketers, especially in the tech sector, must constantly grapple with. Moore’s law (which was actually formulated in the mid-1960s by a different Moore—Gordon Moore, the cofounder of Intel) holds that the number of transistors on a computer chip will double approximately every two years.

The result of this law’s fulfillment is that the ability to process and store data becomes faster, easier, and cheaper. Progress, as evidenced by products such as smartphones and concepts such as cloud computing, happens quickly in the technology sector. “We have this incredible information-processing engine that has just gotten more and more productive, so network, bandwidth, and storage keep having this exponential reduction in cost and scale,” Geoffrey Moore said. “Pretty soon the next generation comes along, and they just design from a completely different set of assumptions.”

In the past, paradigm shifts used to takes decades. “Now it feels like a single decade is kind of like the unit of a paradigm’s life,” Moore said.

He points to Google as an example of a business model that took advantage of a paradigm shift driven by Moore’s Law. “Historically, companies have been very selective about where to store data and how to process it, but now it’s virtually free,” he said. “You can just store everything, process everything, and it allows you to play the game entirely differently.”

In his books, Moore outlines strategies for technology marketers to deal with the constant hurly-burly of data-driven innovation. At the cutting edge of the cycle, marketers who have gained early adopters of their product or service must “cross the chasm” to gain widespread mainstream acceptance. Counterintuitively, Moore recommends focusing on niche markets to build momentum to cross the chasm.

Once a product begins to gain mainstream acceptance—whether it’s personal computers 30 years ago, laptops 20 years ago, or smartphones and tablets in the past decade—a buying frenzy begins, which Moore refers to as the “tornado.” In this chaotic phase, the most important thing a marketer can do is simply ship product with a focus on becoming the dominant player in the market.

Moore’s approach to marketing is built on the idea that the evolution of data processing makes disruption a near-constant condition. In this ever-changing world, marketers must remain vigilant about data’s opportunities—and its dangers. “This train is moving faster than people appreciate. Now it’s dangerous. These are existential threats, meaning if you don’t react pretty damn quickly, you are coming out of the game entirely,” Moore said.

Christensen’s view, as described in The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fall, is similar. Change, often driven by data, is a constant. Products and services that challenge your business by delivering offerings that are not only cheaper but often better than your own, even if you are a market leader, are going to come along and eat away at your current business. Christensen’s research encompasses businesses ranging from automotive manufacturers to steel companies to the tech sector. Companies too often fail to anticipate future customer needs. Christensen’s counsel: Develop these new offerings yourself before others do. It is better to cannibalize yourself than to be eaten by your competitors.

Splice Machine, a startup aiming to disrupt the relational database management system (RDBMS) market controlled by Oracle, IBM, and Microsoft, is a current example of a company that embodies many of the theories put forward by Christensen, Moore, and Collins. At the same time, Splice Machine demonstrates the power of a business that is data-driven and customer-focused.

Monte Zweben, CEO of Splice Machine, was the CEO of Blue Martini Software, an e-commerce and marketing software company that he describes as part of the “first generation of big data companies.” Using data mining and analytics, Blue Martini enabled marketers to analyze customer behavior across channels to identify which segments were performing best. More recently, Zweben is serving as a board member of Rocket Fuel, a programmatic media-buying platform. He saw how Rocket Fuel was using Hadoop, an open-source data architecture platform, to enable real-time decisions about media buying, and he saw an opportunity.

“I looked at the architecture: the system is world class,” Zweben said. “This is unbelievable. But I also looked at the kind of people that Rocket Fuel had, and they had some tremendous specialists, ranging from some of the world’s best Java engineers, database specialists, and Hadoop specialists. I thought to myself, ‘How could an average company ever do this?’”

Zweben wanted to create something that would allow marketers to do what Blue Martini had done—analyze customers and their preferences—but to do this in real time, not hours or days after an individual customer’s last interaction. The ability to interact with customers in real time is critical to many marketing executives.

Zweben said one CMO told him, “In the old days, it was good enough to take last week’s or last month’s or even yesterday’s data and try to build a model of what the customers’ likes and dislikes are, but the real secret is if we know what the customer does in the last 10 minutes, then we can have a profound influence on their behavior.”

So, combining the insight derived from his time on Rocket Fuel’s board and the knowledge that marketers crave real-time data analysis, Zweben and his cofounders believe they have created a way for the average company, and its marketing team, to have the capability to analyze massive amounts of data in real time. The company they founded, Splice Machine, places an SQL database atop Hadoop’s big data architecture, and this creation is outperforming traditional RDBMS products.

“It automatically scales,” Zweben said. “It’s like democratizing relational databases and making every company as powerful as Google or Yahoo! or Rocket Fuel. It’s basically putting that power of distributed computing in the hands of everyone—but in a language they all understand, which is SQL.”

Splice Machine’s solution is faster than traditional RDBMS products, which can take minutes, hours, or even days to handle some queries. Perhaps even more important, Splice Machine is significantly less expensive than traditional RDBMS offerings.

Rob Fuller, managing director of the product innovation center at Harte Hanks, a company that maintains databases for marketers, confirmed that Splice Machine is fast and inexpensive. “We got some queries that were taking 30 minutes down to about eight minutes, so we can run those queries more often,” Fuller said. “It is not about the same query running more often but more variants of that query running more often to do more data discovery—and to find more areas of opportunity to service our clients.”

Fuller added, “We are not talking about huge capital investment based on commodity hardware and the license; it is very reasonable to scale it up for either storage or performance need.” Fuller said that the Splice Machine is about one-tenth of the cost of a comparable Oracle database.

He said, “I would think Oracle database software certainly should be on notice.”

Harte Hanks is not the only company that feels that way. “More companies are testing our ability to replace Oracle and MySQL systems every day,” Zweben said.

In its founding and its ambitions, Splice Machine is attempting to write a story that is familiar to both Moore and Christensen. For Moore, Splice Machine is the product of the inevitable rise of big data and its spawning of new possibilities and new companies taking those possibilities to their logical limits. For Christensen, Splice Machine is a company using disruptive technology (in this case, scale out on commodity hardware) to deliver a more efficient and lower-cost product to take market share from entrenched industry leaders. Splice Machine is clearly taking on Oracle and other established RDBMS players, but it’s unclear if the company is a threat or merely takeover bait.

While the story of Splice Machine is still being written, many other companies have ignored data-driven, customer-focused companies like Splice Machine until it was too late. Companies that don’t embrace a culture of data and don’t have a rigorous data-driven, customer focus are likely to find themselves grouped with once-great brands, such as Blockbuster, Digital Equipment Corporation (DEC), and Tower Records.

We have found it valuable to perform a post-mortem on some companies that faltered because they lacked a data-driven customer focus. We have also explored a cross-section of brands that are still breathing or even thriving, but, because they have not embraced a data-driven customer focus, may find themselves on life support in the future.

The Dead

If a company ignores data showing a trend that could fatally wound it, it’s likely that the company will be wounded and that the wound will be fatal. DEC, Tower Records, and Borders Books & Music are prime examples of this phenomenon.

Digital Equipment Corporation

Digital Equipment Corporation (DEC), a pioneering computer manufacturer, was founded by Ken Olsen in 1957. Three years later the company introduced the first in a long line of PDP minicomputers. The innovative product, which was eventually followed by the VAX minicomputer, fueled DEC’s rise by taking market share from mainframe computers. By 1988, DEC was a $14 billion company and the second-largest computer company in the world, behind IBM. But even when it seemed to be all green fields for DEC, the seeds for its demise had been sown: a decade later the company was sold to Compaq (which itself was eventually sold to Hewlett-Packard), and the DEC brand vanished.

DEC was slow to see the potential of the personal computing market. Olsen, who was DEC’s CEO until 1992, famously said in 1977, “There is no reason for any individual to have a computer in his home.” That quote actually refers not to PCs but to larger computers that would control an entire household, but the fact remains that DEC was slow to enter the PC market. The company eventually did develop PCs and entered the market in 1982, a year after IBM did and seven years after Apple helped establish this market. DEC had three main problems that led to its ultimate downfall.

First, it found itself faced with Christensen’s “innovator’s dilemma,” which says innovative companies must cannibalize their own high-end products with less expensive products, even if they control the market, because if they don’t their competitors or a start-up will. In “Good Days for Disruptors,” an April 2009 interview with MIT’s Sloan Management Review, Christensen said thatDEC found itself in a classic innovator’s trap.

“Digital Equipment Corp.,” Christensen said, “had microprocessor technology, but its business model could not profitably sell a computer for less than $50,000. The technology trapped in a high-cost business model had no impact on the world, and in fact, the world ultimately killed Digital. But IBM Corp., with the very same processors at its disposal, set up a different business model in Florida that could make money at a $2,000 price point and 20 percent gross margins—and changed the world. It’s a combination of the technology and business model that makes formerly complicated, expensive, inaccessible things affordable and accessible.”

Close attention and reaction to the data would have told DEC that it couldn’t survive with the existing business model—that it was driving into a wall and it needed to course correct or it would crash. Second, DEC wasn’t customer focused. It was competitor focused. It was set on doing battle with IBM.

“There was also a slow recognition of the shift in the computer industry as Digital Equipment Corporation set their sights on IBM,” Dave Goodwin and Roger Goodwin wrote in a short online history called “The Rise and Fall ofDigital Equipment.” “This chasing of IBM resulted in the hiring of a large number of personnel in the 80s which in turn resulted in the earnings per man being 30% less than HP.”

And third, DEC did not collect and analyze data that would have informed it of this market shift. The evidence that the minicomputer market was stagnating and the PC market was surging was hiding in plain sight. And when DEC did enter the PC market, it did so after IBM and with a strategy of creating a closed operating system. Although that approach worked for Apple, it was not what the large market wanted at that time, as the triumph of Microsoft Windows in the 1990s made clear.

Blockbuster

In the 1990s and early 2000s, you couldn’t walk a few city blocks without passing a Blockbuster store. The video rental chain was the Starbucks of its era. At its peak in 2004, the company had 60,000 employees and 9,000 stores.

But Blockbuster’s fall was fast. Facing competition from Netflix and Redbox, it declared bankruptcy in 2010. It was acquired by Dish Networks in 2011, which closed the remaining company-owned stores in 2014.

Many reasons contributed to Blockbuster’s demise, but front and center was the fatal lack of a relentless data-driven focus on its customers. Among Blockbuster’s many faults was a draconian late-fee policy, which bothered many customers, although in the short term it had minimal impact on Blockbuster’s bottom line. But when that late fee was fatefully levied against one customer, it changed the movie rental landscape forever. After being fined the exorbitant late fee of $40 on a copy of the movie Apollo 13, Blockbuster customer Reed Hastings decided there had to be a better way.

So in 1997 Hastings cofounded Netflix, which delivered movie DVDs to subscribers by mail. On the face of it, the Netflix idea seems to offer no great advantages over Blockbuster. The mail delivery did have convenience, and the business model included no late fees no matter how long you kept a movie, but it did not offer the immediacy of getting a movie from Blockbuster that a consumer could watch that day. In almost every other aspect, however, Netflix trumped Blockbuster, because it had a data-driven focus on the customer.

Netflix is a digital business, so it knows what its more than 33 million customers are watching—in the aggregate and as individuals. And with the Queue, where customers listed the movies and shows they wanted to watch, Netflix had a clear window into customers’ future desires. It also, in the manner of Amazon.com, used this data to build a strong customer recommendation engine.

Additionally, because it was a digital business, Netflix was poised for success in the impending era of video streaming that followed—an advancement Blockbuster, of course, was not prepared for. More, because of its intimate knowledge of its customer preferences, Netflix was also able to develop a branch of the business focused on TV series production, which it did with astounding success with the debut of the 2013 television series House of Cards.

Netflix’s conquering of Blockbuster is an amazing business story. The most amazing part, however, may be this: Blockbuster passed up the opportunity to buy Netflix for $50 million in 2000. The temptation is to think that acquisition would have saved Blockbuster from doom, but this move would have done so only if Blockbuster had adopted Netflix’s data-driven customer focus—unlikely given that it would have involved a 180-degree cultural shift.

Tower Records and Borders

Tower Records and Borders experienced a similar rise and fall.

Both delivered great retail experiences. Both were the kind of place where book lovers and music fans could browse the inventory for an entire day and never realize the time: fantastic atmosphere; great, broad selection; reasonable prices.

The business models of both Tower Records and Borders included a focus on the customer needs and customer experience. The focus, however, wasn’t data-driven, which resulted in an outsized contribution to their downfall.

Tower Records

At its peak, Tower Records, which started in Sacramento, California, had stores in virtually every major U.S. city and had outlets around the globe. In its best years, it posted revenue of more than $1 billion. As U.S. music sales plunged from $14.6 billion to $6.3 billion between 1999 and 2009, according to Forrester Research, Tower Records continued what had worked for it in the past—expansion.

Tower Records founder Russ Solomon believed that customers would never stop visiting his stores. The Internet, he said, “would never take the place of our stores.” But that strategy of expanding the number of stores failed to address what the hard data showed about Tower Records’ customers. They didn’t care if their music came from a store or was on a CD or vinyl record; they wanted to have access to and listen to music easily—a need being served by the new technology of downloadable MP3s and other electronic delivery systems. They wanted to share it easily, and they were willing—even eager—to visit websites such as Napster that the Recording Industry Association of America characterized as criminal enterprises that were pirating music.

Tower Records was in an ideal position to develop a solution to this problem of how to satisfy customers with downloadable music while generating revenue for the record labels creating the products it was selling. Tower had direct relationships with its customers, the record buyers, as well as with the record labels. The opportunity to build an online e-commerce engine for downloadable music was available to Tower Records, but it was Steve Jobs and Apple who seized that opportunity with the launch of the iTunes platform. Tower Records filed for bankruptcy in 2004 and again in 2006, when the retailer finally went out of business.

Borders Books & Music

In its early years Borders, which launched in Ann Arbor, Michigan, in 1971, was renowned for its advanced inventory system, but that focus eroded as the company grew.

Like Tower Records, Borders was a powerhouse brand. In 2003, the Borders Group operated more than 1,200 bookstores. The company kept expanding its brick-and-mortar stores even when it was clear that Amazon.com was taking market share and continuing to grow. Borders didn’t launch its own proprietary website until 2008. Prior to that, the company was content with an affiliate relationship with Amazon.

Even after establishing its own proprietary e-commerce site, Borders wasn’t able to compete with the rigorous data-driven customer focus that Amazon had established many years earlier.

With its one-click ordering process and its recommendation engine algorithm, Amazon simply provided a better experience than Borders did—and you didn’t even have to leave your house. Borders declared bankruptcy in 2011.

Near-Death Experience

BlackBerry is fighting, but the rise of touchscreen phones with the iOS and Android operating systems cut quickly into the company’s market share. BlackBerry didn’t react to the customer adoption data that showed its competitors making great gains until it was almost too late.

BlackBerry, formerly Research in Motion, began manufacturing smartphones in 2000, and it was the dominant smartphone player after the turn of the century, with its user base in the United States peaking in 2010 with about 21 million users, according to comScore figures. In the wake of the introduction of the first iPhone in 2007, its market share began to erode slowly. With its physical keyboard built right into the phone, BlackBerry devices were elegant and effective e-mail machines—perfect for salespeople, investment bankers, and lawyers. The only problem was that when a BlackBerry user tried to use apps or surf the Internet, the BlackBerry wasn’t as elegant or effective.

With its iPhone launch, Apple attacked BlackBerry’s weak points. The iPhone could make phone calls you could actually hear (even though they often dropped because of the high usage volumes driven by the popularity of the iPhone on its then dedicated AT&T network). It delivered better Internet access.

And it fostered an app environment that transformed how consumers (and developers) perceived the mobile opportunity.

Consumers loved the iPhone, which sold its 1 millionth unit just 74 days after its unveiling. Apple took a customer-centric approach to building the iPhone. In Walter Isaacson’s biography, Steve Jobs (Simon & Schuster, 2011), he writes that Jobs “had noted something odd about the cell phones on the market: They all stank, just like the portable music players used to [before the iPod].” So drawing on the data that the iPod had sold 20 million units in 2005 and there were 825 million cell phones in use at that time, Jobs decided to embark on the iPhone project.

Once the iPhone hit the market, BlackBerry, for its part, did not recognize the data that indicated high adoption rates of the iPhone.

BlackBerry dismissed the touch screen as a niche product that would not cut into what it thought was its unassailable market share among businesses. But the bring your own device (BYOD) phenomenon demonstrated that the iPhone (and soon Google’s Android phone) was hacking away at BlackBerry’s grip on the business market.

BlackBerry made a number of mistakes, but its primary one was not adapting the business based on the data indicating that the strong growth of the iPhone would cut into its market share.

BlackBerry also didn’t take a strong enough customer focus and was satisfied with building excellent e-mail machines but allowing the phone reception and web surfing aspects of its product to be mediocre at best.

BlackBerry is building better products now. Its phones get great reviews, but the damage to the brand incurred by Apple and Android leapfrogging its products may have been fatal. In 2014, BlackBerry’s web usage in North America fell to fourth behind Android, Apple, and Microsoft.

Culture Clash

The data has long shown that newspapers are struggling in the digital age, especially for advertising dollars. The data is obvious, but do newspapers, such as the New York Times, have the culture to do what is necessary to adapt to the changing world?

It is common knowledge that newspapers have been struggling since the launch of the World Wide Web in 1993. That perspective is mostly—but not completely—right.

Some analyses about the decline of newspapers have put the onus on the value of the content, which, it is claimed, doesn’t rival some distant Golden Age, such as the Watergate era when breaking a story in the Washington Post and other newspapers could bring down a president. But the fact is that the Internet has enabled newspaper content to reach a larger audience than ever before. Nielsen Online data shows that the top 25 U.S. news websites reached an average of 342 million unique monthly visitors in 2011.

The problem is monetizing that readership.

The economic downsides for newspapers since the advent of the Internet have been many. With its long-tail display advertising, the Internet also brought with it inexpensive ad inventory that has driven down cost per thousand (CPM) prices and made it difficult to generate online revenue for newspaper sites (as well as most other Internet sites).

What may have been even worse is the rise of brands that compete with newspapers’ cash cow—the classified section. Companies like Monster.com snatched money from newspapers’ help wanted sections. And then Craigslist, which offers online classified ads for free siphoned money away from the rest of the classified section.

Overall classified revenue in U.S. newspapers has not increased since the first quarter of 2006, according to the Newspaper Association of America (NAA). Similarly, overall newspaper advertising revenue in the United States has declined every quarter since the second quarter of 2006, also according to the NAA’s data.

Newspapers do have a customer focus in general. They, however, have two distinct customer groups they serve: advertisers and readers. This duality makes it difficult to have a laser focus on any single segment of customers.

But newspapers’ true downfall has been one of a shift in the culture of both of those audiences. As a rule, newspapers have not embraced data-driven cultures. Let’s look at the New York Times as an example. If the New York Times had had a data-driven culture at its core, it might have acquired Monster.com and preserved its job listings stronghold.

The people who are attracted to the New York Times Company are more concerned with the New York Times, the newspaper, than the New York Times, the company. Even if the data indicated that acquiring Monster.com was a good business move, it wasn’t really on the radar of most newspapers, whose culture focused on creating good journalism first and making money second. The culture regards Pulitzers and Polks more highly than it does shrewd revenue decisions.

The New York Times—despite building a top-notch website and embracing the metered access model, which has produced more than 700,000 paying digital subscribers—is, by its own account, still struggling with the digital world. An internal report, “Innovation,” leaked in March 2014, fingered the New York Times’ own culture as playing the key role in the company not taking full advantage of digital opportunities.

The report began, “The New York Times is winning journalism.. . . At the same time, we are falling behind in a second critical area: the art and science of getting our journalism to readers.”

The report said the Times’ newsroom had not embraced a “digital first” view of the world, and the front page of the print newspaper still ruled the minds of the editors. The newsroom, the report said, needs “to become a more nimble, digitally focused newsroom that can thrive in a landscape of constant change.”

Still, while the New York Times may be perceived to be in financial trouble, it increased its revenue in the first quarter of 2014 and posted a small profit of $1.7 million on revenue of $390.4 million. The fact that the report exists is a sign that maybe the newspaper (and the company) can shift its culture and continue, despite competition from Buzzfeed, the Huffington Post, ProPublica, and Vox, to be profitable in the future.

Missed Opportunity

Even data-driven, customer-focused companies such as General Electric (GE) don’t always take advantage of every opportunity, as this tale of a missed chance demonstrates.

General Electric has a reputation as a data-driven business with a customer focus, and deservedly so. But that doesn’t mean it hasn’t overlooked an opportunity every once in a while.

In 2010, GE said it wanted to create a solar power business that would rival its $6 billion wind energy business. But as prices plunged and American manufacturers were undercut by Chinese solar panel manufacturers, GE delayed the opening of a solar panel manufacturing plant two years later.

Despite data indicating that a form of Moore’s law had taken hold in solar panels, with the cost of photovoltaic cells decreasing as their power increased, GE didn’t make the investment in the business that it had planned. But while GE sat on the sidelines, a start-up called SolarCity developed a business model that is taking advantage of the sudden boom in solar panels, according to “As Solar Panels Boom, It Was the Simple Business Model That the Big Energy Players Missed,” an insightful story written by Katie Fehrenbacher for GigaOm in 2014.

SolarCity finances and installs solar panels for residences and businesses. As such, it rides the sudden wave in interest in solar panels. In the first quarter of 2014, solar power accounted for 70 percent of the new energy that went on line, according to the Solar Energy Industry Association.

The growth stems from a combination of things: high energy costs in general and decreasing costs of solar power, in part because of the decline in the price of silicon.

In the spring of 2014, GE CEO Jeffrey Immelt acknowledged that GE had missed an opportunity. “My God, I wish I had thought of that,” Fehrenbacher quoted Immelt saying in her story.

The thing is that Immelt was already familiar with the SolarCity model, because SunEdison had pioneered the approach in 2003. Immelt had spoken at an event with SunEdison founder Jigar Shah in 2007.

In a tweet subsequent to the GigaOm story, Shah said of Immelt, “He didn’t miss SunEdison, he ignored it.”

Whistling Past the Graveyard?

Comcast’s pending acquisition of Time-Warner Cable indicates that the company has a clear understanding of the data that shows Netflix and other brands beginning to eat away at its market share. But can Comcast change its culture enough to become customer focused and maintain its dominance?

Is Comcast a customer-focused company? That would be hard to argue for Comcast or any other cable TV provider. It’s hard to pass yourself off as customer focused when there was a feature film, The Cable Guy, inspired by your reputation for poor service. It doesn’t help, either, that a Consumerist poll found that Comcast was voted “Worst Company in America.”

If Comcast isn’t customer focused, is it data driven? It may be. Comcast appears to know that the pay TV market may have reached its peak. The number of pay TV subscribers declined by 251,000 to about 100 million in 2013, according to SNL Kagan.

That may be one reason why Comcast has agreed to merge with Time-Warner Cable in a deal valued at $45.2 billion, according to a press release issued by Comcast in February 2014. It wants to show growth one way or another and as quasi-monopolies in many markets, cable companies have reason to want to combine—they can better control pricing.

The problem with Comcast and other pay TV operations is that their customers don’t like them and are looking for any way to get their television elsewhere, especially if it’s cheaper. Connected TVs may provide that opportunity. While just 27 percent of TVs shipped in 2011 were connected TVs, 80 percent of TVs shipped in 2015 will be connected TVs, according to Futuresource Consulting.

Devices like Roku and services like Netflix provide a much more customer-friendly experience and may one day have traditional pay TV companies, such as Comcast, on the run.

Schadenfreude?

Start-ups in Silicon Valley are wading into financial technology, known as fintech. Can these new companies combine a data-driven and customer-focused approach to oust the current banking leaders?

As a Wall Street investment bank, Goldman Sachs is data driven and employs scores of quants. The question is whether Goldman Sachs is customer focused.

Goldman Sachs was data driven enough to realize in 2008 that collateral debt obligations—yes, the CDOs that helped cause the global financial crisis—were a bad investment. But if the bank is customer focused, that didn’t stop it from selling those questionable CDOs to its customers.

From Goldman Sachs to local banks, which charge fees even for so-called free checking, Americans are largely dissatisfied with banks. Financial institutions seem much more like data-driven shareholder-focused businesses than data-driven customer-focused businesses.

The banking industry’s lack of focus on the customer may give a start-up a chance to disrupt the banking industry. Silicon Valley is trying, according to a June 1, 2014, New York magazine article, “Is Silicon Valley the Future of Finance?” written by Kevin Roose. “Financial start-ups—known collectively as ‘fintech’—are spreading like kudzu, each with a different idea about how to usurp the giants of Wall Street by offering better services, lower fees, or both,” Roose wrote in the article.

He noted that these fintech start-ups raised $1.3 billion in the first quarter of 2014. Perhaps one day one or more of these startups will generate a data-driven innovation that will make consumers happy and Wall Street uncomfortable. If that day comes, it may provide some schadenfreude to taxpayers still angry at bailing out Goldman Sachs and the rest of Wall Street in the wake of the financial crisis.

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Chapter 11 of The Big Data-Driven Business (Wiley).