Hoping to wrestle with “information overload” and make more intelligent and informed decisions, businesses have quickly gravitated to business intelligence solutions. Today, businesses of all shapes and sizes consider business intelligence a “need to have”. Nearly half (48%) consider business intelligence to be “critical” or “very important” to their operations. It’s no wonder that the global market for business intelligence is slated to balloon from approximately 17 Billion in 2016 to more than 147 billion by 2025, representing a CAGR of 27%.
For Sudheesh Nair, CEO of leading business intelligence company ThoughtSpot, the growth of business intelligence is no surprise. Like many others, he considers business intelligence to be a prerequisite for success in today’s business environment. I recently had the chance to sit down with Nair to discuss the past, present, and future of the business intelligence space.
Built for a different era
“Business intelligence” processes have “Big Brother”-esque connotations. For Nair, they are reminiscent of “monikers like military intelligence”. These surreptitious connotations are no coincidence—they are deeply rooted in business intelligence’s origins. Traditionally, business intelligence was restricted to the purview of a select few individuals at a company. A dedicated team of executives decided what insights were desired and charged a team of data scientists to produce the results. The process often took weeks or months and resulted in a series of (usually opaque) charts. By all accounts, the process was laden with secrecy. “Very few people in the organization actually knew what this team was doing, though they knew it was valuable,” explains Nair.
Early business intelligence software was built in a different, more prehistoric, era. Importantly, legacy software was built before the recent explosion of data that saw 90% of the world’s data generated over a span of two years. This data explosion has resulted in companies needing—and demanding—new methods to interact with data in a meaningful way. Workers today simply don’t have the skills necessary to analyze the masses of data at their disposal.
The birth of ThoughtSpot
Nair quickly realized the implications—and potential—of the data explosion. He immediately gravitated towards ThoughtSpot due to its ability manage the intense volume of data, as well as to empower everyone in a company to harness insights and make more intelligent decisions, In joining ThoughtSpot as its CEO in August 2018, Nair knew that companies needed to make a fundamental shift in their approach to business intelligence operations. Specifically, they needed to shift from a “top-down” approach, whereby decisions are managed exclusively by the executive chamber, to a “middle-out’ approach, whereby decisions are made by all employees.
The transition from “top-down” to “middle-out” doesn’t just require a change in technology. It also demands a change in company culture. Traditional organizational power structures are a handicap under “middle-out” approaches. When business intelligence is democratized in an organization, decision-making is pushed further and further from the executive chamber. Nair is adamant that company leaders must become comfortable with the new reality—”you’re not the top dog, your data is”. With the pace of business escalating, top-down decision-making processes aren’t practical. Employees at lower levels will need to execute decisions more autonomously. When this happens, the time involved in making data-driven decisions plummets from days to minutes.
This focus on democratization is ThoughtSpot’s core differentiator. Unlike many of its competitors, ThoughtSpot emphasizes self-service. Nair explains, “We want every single user to be comfortable retrieving relevant data with natural language and to find hidden insights through a simple search.” ThoughtSpot differs notably from other business intelligence players, the majority of which operate according to an “if it ain’t broke…” mentality.
With the acquisition of Looker by Google for $2.6 billion and Tableau by Salesforce for an eye-popping $15.7 billion, the business intelligence space has experienced tremendous validation. While ThoughtSpot operates in the same market, its approach is distinct. Unlike Tableau, ThoughtSpot doesn’t rely on pre-built dashboards or visualizations that limit the scope of available data. And unlike Looker, the use of ThoughtSpot isn’t predicated on learning a new programming language. The result is that the time to value afforded by ThoughtSpot decreases, while adoption rates increase. An approach validated by both investors and customers, most recently with the close of the company’s hefty $248M Series E financing round.
Nair does not feel intimidated by the acquisitions of Looker and Tableau. Instead, he sees opportunity. He expects that the companies will quickly direct their energy toward the platform offerings of their parent companies. Tableau, for example, will quarrel with Mulesoft to hammer together Salesforce workflows. Looker, on the other hand, will focus its efforts on integrating with the Google Suite and the Google Cloud Platform. The marriage to a parent company and the resulting diversion of focus creates tremendous opportunity for independent players such as Thoughtspot to expand on current offerings and create platform-agnostic products that offer truly innovative analytics.
The privacy debate
Business intelligence and artificial intelligence are complementary technologies. Over time, business intelligence will adopt more features that are driven by artificial intelligence. As a result, the ethical implications that we’ve seen emerge in the context of artificial intelligence are likely to have a direct impact on the business intelligence ecosystem.
According to Nair, one of the most pressing challenges for business intelligence companies will involve developing an industry safeguard against the misuse of artificial intelligence so that innovation is not hindered due to external regulation. Nair believes that the solution involves the formation of a group of industry leaders who can review the ethics of different artificial intelligence innovations in the industry. This sort of peer review is well established in the context of scientific advancements. Why should software innovation be any different? While Google set out to create such a group with its Advanced Technology External Advisory Council, designed to debate the ethics of different artificial intelligence use cases such as facial recognition and bias in machine learning, its function was to philosophize and advise, not to unite members of one industry to ensure long-term success. The group was disbanded a mere two weeks after its formation.
From Nair’s perspective, it’s critical that business intelligence leaders come together to find the balance between velocity and self-regulation. Failure to do so will threaten the progress of the business intelligence industry. Nair recommends that business intelligence leaders follow the lead of the pioneers of the autonomous vehicle industry. These leaders successfully formulated a well-articulated list of capabilities, including definitions for different levels of autonomy. The framework moved mountains in helping individuals outside the industry understand the differences and craft appropriate and highly-tailored laws regulating certain applications for certain levels of autonomy. It also dramatically improved consumer trust. A similar set of frameworks for business intelligence could prove invaluable.
ThoughtSpot has a bold mission—to create a more fact-driven world. This would mean that each worker is afforded a data scientist ally to help them ask meaningful, measurable business questions and make decisions based on the results. As more workers begin to interact with data tools, Nair expects the tools will be increasingly influenced by the consumer mindset. He expects that the hyper-criticalness that workers have for non-work technology will bleed into the workplace. Nair suspects that usability and intuitiveness inherent in consumer technologies will be key factors in driving the adoption of enterprise analytics tools.
In the future, Nair predicts that every team within an organization—including DevOps, Sales Ops, and Marketing Ops—will have a business intelligence or data analytics lead. He also anticipates that the role of the Chief Data Officer (CDO) will begin to change. As more and more employees and teams are hooked into the data environment at work, the role data analytics is likely to shift from a centralized effort to one the entire organization participates in. Inevitably, data team leads will need to act in a more operational capacity. Nair expects that within a few years, the CDO will take on a new meaning— “Chief of Data Operations”.
ThoughtSpot is fundamentally attempting to change the status quo of business intelligence. It aims to create the most democratic, transparent, user-friendly data analytics experience on the market. Accomplishing this mission requires great technology. But it also requires a great culture. ThoughtSpot’s culture emphasizes selfless excellence—the removal of ego—as it collectively chases perfection on its path to become the world’s top data analytics company. Nair is well aware that, as organizations grow, there is a tendency to adopt “big heads and feelings of entitlement”. At ThoughtSpot, Nair has enacted cultural policies to prevent this crippling tendency. As part of its hiring process, for example, ThroughtSpot allows family members of prospective employees to interview the company. For Nair, this strategy has proved effective in removing egotistical tendencies. “Let me tell you, getting interrogated by a child can really keep your ego at bay!”