Tableau's Turnaround: Under New Leadership, the Seattle Software Company Is Trending Upward

Tableau's new CEO believes choosy customers will take it back to the top of the charts.

DOING HIS LEVEL BEST. Tableau Software chose Adam Selipsky as its new CEO in August 2016. At the time, Tableau cofounder and departing CEO Christian Chabot said, “Adam is going to take Tableau to the next level.”

This article appears in the June 2018 issue. Click here for a free subscription.

Analytics company Tableau Software was built on an elegant mission to help people “see and understand data.” So, there’s some poetry in how the Seattle company’s fortunes are concisely told through charts and graphs.

Founded in 2003 by three partners from Stanford University, including initial CEO Christian Chabot, Tableau helped bring data visualization out of the murk of mathematics to the everyday manager. Patterns and trends once buried in records of sales, prices or output could be revealed to the eye through assisted clicks and drags.

The delight that met such insights drove Tableau’s success. Its numbers charted a steep and steady rise in customer growth and revenue. After bursting onto public markets in 2013, its stock price mirrored that rise, from an initial $31 to a peak of $126 two years later, giving Tableau a valuation of more than $10 billion.

Courtesy of Tableau and Bernstein Research.

Such enthusiasm seemed justified for the leader in a business intelligence and analytics software market estimated at $17 billion for 2016.

Yet other charts furrowed investors’ brows. Revenue lines trended up, but so did expenditures as Tableau burned through capital. The line charting losses continued to sink.

Courtesy of Tableau and Bernstein Research.

Some analysts were concerned that Tableau had not moved swiftly enough to roll out its cloud platform and software-as-a-service offerings, or adapt to the subscription model that customers increasingly demand.

More troubling still, Tableau’s products seemed unready to fully serve the security needs of the enterprise market where its growth prospects lay, even as experienced competitors such as Microsoft’s Power BI, IBM’s Cognos and Amazon had credibly entered the field, many with lower-priced products.

“They didn’t have their go-to market plan ironed out,” says Zane Chrane, VP and senior equity analyst at Bernstein Research, and investors began to doubt Tableau could make the enterprise leap.

Chabot’s vision was laudable, Chrane says, but “he was not the person to lead the company to a billion-plus in revenue.”

The chart of Tableau’s stock price would tell that story, too: a sharp downward turn in February 2016. Shares already selling over a third less from their peak plummeted in a single day by half following quarterly results that failed to reassure.

Six months later, Chabot stepped aside, handing the CEO reins to Adam Selipsky. Having grown Amazon Web Services into a cloud-computing dynamo, Selipsky might be able to steer Tableau where it needed to go. To succeed, he would have to look beyond the numbers to see the company’s true value.

PICTURE THIS. Tableau Software’s ability to take complex data and turn it into informative, understandable graphics — here for Boeing, Starbucks and KEXP (see below) — remains central to its mission. Courtesy of Tableau. See the visualization here.

Tableau’s innovations might seem small to those already expert at generating graphs and charts from spreadsheets. But just as Lotus and Excel empowered people other than accountants, Tableau sought to bring data visualization to people other than statisticians.

For Elissa Fink, Tableau’s chief marketing officer, that impact was brought home — literally over Christmas dinner — by a family friend who worked for a large pharmaceutical company. A pricing director, the woman had been dependent on reports and competitive analysis produced outside the company. Being able to generate analytics herself through Tableau’s desktop software sped big pricing decisions.

For Fink, the anecdote demonstrates how Tableau helps its own data speak through pictures, opening new doors for those who aren’t mathematically adept. “When they start looking at their world and their data,” she explains, “all of a sudden they are a ‘numbers person.’”

Deploying Tableau directly to nurses and doctors at Seattle Children’s Hospital helped reduce unneeded tests and patient wait times. Analyzing Seattle Sounders players’ biometric data aids each athlete in maximizing performance and recovering from injury. Researchers at Visualize No Malaria help the Seattle-based global health organization PATH eliminate that disease in Zambia.

Hours after the 2011 Fukushima earthquake off the Japanese Pacific coast, science journalist Peter Aldhous used the free online service Tableau Public to rapidly visualize the extent and variety of earthquake activity around Japan. Last year, in the immediate aftermath of Hurricane Harvey, volunteers tracking Houston tweets through Tableau Public helped focus rescue workers’ efforts where most needed. And Fink still marvels at how a customer’s trial usage with old billing records accidentally revealed $1 million in fraud by a major vendor.

But Tableau’s weak spots are apparent to some users. Chris Toomey, of mapping platform creator Mapbox, has used Tableau through jobs in government and as an analyst at Zillow. “They still maintain the gold standard for usability and flexibility,” he says, but Tableau falls behind key competitors in getting data sets to relate to each other. “It’s very difficult to replicate some of the more advanced data modeling patterns that you can do in [Microsoft’s] Power BI.”

Courtesy of Tableau. See visualization here.

Chief product officer Francois Ajenstat concedes the company’s focus has been on the needs of the less expert user. “It has a transformative power,” he says, “built on the idea that the people who know the data should be able to ask questions about their data.”

The connection to Tableau that these insights provided struck Selipsky once he became CEO.

“I did my due diligence,” he recalls, “but I didn’t fully understand the power of it before I joined.”

He found the intensity of the relationship most apparent at Tableau’s annual conference, where more than 12,000 clients converge upon a major city’s convention center — this year, it’s in New Orleans — to train and share their experience as a community.

“I cannot think of another example in B2B where customers have such passion, loyalty and downright love for a product and a company,” Selipsky says.

Selipsky recognized that fealty as a core strength Tableau could put to good use. He acknowledges that, as a pioneer in modern analytics, Tableau had the early benefit of scant competition. While granting an opportunity to prosper and grow rapidly, this early advantage also fostered complacency among investors and some Tableau executives.

It would be Tableau’s customers who ultimately guided Tableau’s realignment to a shifting landscape. Prosperity, Selipsky adds, will be about “having a maniacal focus on what customers need.”

The immediate actions were to accelerate initiatives already in progress. Tableau sped up its pivot to become a subscription business as traditional perpetual software licenses declined. Since the public launch of subscription services a year ago, they accounted for half of ratable license bookings in the most recent quarter.

The company’s SaaS offering, Tableau Online, had provided cloud-based service on Tableau’s own managed servers — where 10 percent of customers now work — since 2003. But as more companies store their data in public clouds such as Amazon Web Services, Microsoft Azure or Google Compute Engine, they seek to manage their own Tableau platforms there as well. Tableau Online was launched in 2013. Since his arrival in 2016, Selipsky has intensified the company’s commitment to the cloud, where a third of Tableau server trials now happen.

The biggest barrier, notes Ajenstat, is what he calls “data gravity — the need to have analytics close to where the data is,” for speed and security. Meeting those concerns is key to Tableau’s scaling its next peak, the enterprise market, such as Fortune 100 companies and financial institutions, where analytics are deployed at massive scale.

Success at this task will come with some irony: Tableau built an army of devoted users by freeing analytics from gatekeepers like statisticians and data systems managers. Now, it must satisfy IT departments through governance controls that assure valid access for data entry, viewing and publishing.

“The company had been building a number of governance features, but customers were moving even faster to deploy us in that fashion,” says Selipsky. “We needed to double down.”

That reality meant stepping up hiring, development and marketing to meet those demands. It also included the hiring of former Oracle executive Dan Miller as EVP of worldwide field sales, services and support.

Courtesy of Tableau. See visualization here.

Even as it pivots, Tableau hasn’t lost its taste for making data easier to see and understand. As data sets grow larger, speed becomes essential. IT engineer Tony Kehlhofer of Amazon, a longtime Tableau user, explains how customer service records grow exponentially. “Every ticket has dozens of correspondence rows,” he says, “and before you know it, you have billions.”

Hyper, a fleet data engine developed by a German startup incubated at the Technical University of Munich and acquired by Tableau, hopes to relieve this stress. It reportedly performs queries up to five times faster. In the future, suggests Ajenstat, Tableau users can rely on advanced algorithms and artificial intelligence to help them draw insights from their data.

Tableau Prep, announced in April, makes  time-consuming data preparation — aligning fields from multiple data collections to produce meaningful results — much easier. Advanced computing techniques help Prep make smart guesses that can speed data modeling. And the recent acquisition of startup ClearGraph promises future Alexa-like experiences enabling users to ask questions of data through natural language processing.

Eventually, you may not even have to know which questions to ask. Planned features for predictive analytics expect to provide automated insights as Tableau learns about you and your data. In smart data discovery, the platform may suggest unrestricted sources of data in the system that may be useful but unknown to you.

“The strategy we’re taking is that customers want maximum choice,” Selipsky says. “We don’t want to force customers down any one path because we think we know better.”

That attitude encourages analysts like Chrane, especially after Tableau reported $877 million in revenue last year, up from $654 million in 2015. “New-business growth is solid and growing strong, [and] enterprise adoption is improving,” Chrane approvingly observes. He predicts revenue will climb 13 percent annually to $1.12 billion by 2019. He also expects the company’s years of losses to start reversing then, moving Tableau steadily toward profitability.

“The street overreacted,” says Chrane now of Tableau’s earlier stock plunge. “They didn’t fully understand all the moving pieces.”

Ultimately, the data will show whether Selipsky can keep make those pieces work together.

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