When Business Intelligence Meets Artificial Intelligence
Working in information technology is only great up until you decide to stop. While actively working in the business, you’re constantly exposed to the latest and greatest tools of the trade. Leave that domain, and suddenly you’re completely lost as to what’s hot and what’s not. Maybe it’s not even called information technology anymore (it isn’t), but if you worked in that capacity back when the term was relevant, you’ll know how to use structured query language (SQL). It’s how we can ask relational databases questions. (Big data is a whole different story.) For example, your human resources department might run the below query:
SELECT TOP 10 Corporate_Slave_ID,
WHERE Corporate_Slave_Location = “Manila”
AND Corporate_Slave_Active = TRUE
SORT BY Daily_Call_Average ASC
This shows which people in your Manila call center are about to be replaced by the next ten people waiting in line. Seems straightforward until you throw in a few OUTER JOINS and suddenly you’re outsourcing the whole thing to John-in-Mumbai because you can’t find a decent database administrator (DBA). Or, you can save yourself that headache and turn to a company we wrote about before in our piece on Making Artificial Intelligence Easy to Use – ThoughtSpot.
Founded in 2012, Silicon Valley startup ThoughtSpot has taken in $554 million in funding so far with their most recent round – a $248 million Series E – placing the company squarely in the midst of 411 other unicorns grazing away on all that delicious venture capital funding. The company’s Co-founder, Ajeet Singh, knows a thing or two about growth having previously co-founded Nutanix, a cloud computing software company that had an IPO in 2016 and now sports a market cap of around $5.5 billion. In a candid interview published on Medium, he talks about the importance of entrepreneurial spirit and says what every information technology manager knows all too well – “It’s harder than you’d think to hire good engineers.”
You’d certainly need to hire some exceptionally talented software engineers to build a business intelligence tool from scratch that’s now being used by Rolls-Royce, Walmart, 7-11, Chevron, Tyson Foods, Exxon Mobil, and De Beers along with hundreds of other firms, many of which choose to remain anonymous. From a coffee shop idea to $100 million in run rate from enterprise clients in under seven years’ time, that’s what separates the “growth hacker wannabe types” from execution experts like Mr. Singh. The tool his company built democratizes business intelligence so that everyone can hack their own growth.
BI, Meet AI
Another term IT people will be familiar with is business intelligence (BI) which often manifests itself in the form of a skunkworks project being driven by a C-level “sponsor” who constantly demands an ever-changing
KPI report TPS report for the next board meeting. According to some MBAs over at Gartner, only 35% of businesses have successfully adopted BI while the rest wait in frustration as “analysts spend countless hours and costly resources just to deliver one report or dashboard.” ThoughtSpot goes on to say:
To bridge this divide, a second wave of “self-service” desktop visualization tools entered the market in the ‘90s and early 2000s to try to meet the needs of data-hungry business users. Unfortunately, these tools created data sprawl and a governance nightmare. And despite their promise, they were still too complicated for the average business person to use without training or hours of BI support.
We’re disheartened to hear that all those BI implementations we worked on over the past two decades have largely sucked and created “data sprawl.” (H/T to ThoughtSpot for a buzzword that makes us sound relevant again.) The solution is what ThoughtSpot calls a “third wave of modern analytics solutions,” artificial intelligence to search at the speed of thought.
The auto-suggest feature you see in the above picture is where some of the magic happens. If you’re a new hire in enterprise software sales, there are certain reports you’ll want to see at a certain frequency based on what others in your same job function find useful. Company-specific nomenclature can be converted into customizable synonyms, real-time keyword validation makes sure you don’t fat-finger anything, and spell checking helps you communicate like an adult. They’re all out-of-the-box features, just plug in your data and start using. Business people can engage with the platform via messaging app using natural language querying, and the “spotbot” even offers up fun facts.
Over time, the artificial intelligence algorithms get better at figuring out intent so people don’t even need to ask questions.
SpotIQ: AI-Driven Insights
In their latest funding announcement, ThoughSpot talks about approaching a “$100 million run-rate, driven by 100% software subscriptions and multi-cloud deployments.” But it’s not just about empowering business users with a “simple Google-like search to instantly analyze billions of rows of data,” it’s about moving closer to the company’s vision of “autonomous” analytics. ThoughtSpot wants to change the paradigm by “using AI and machine learning to automatically find and deliver insights to users they didn’t even know to look for.” SpotIQ is the name for algorithms that can figure out instantly what you and your colleagues would need three brainstorming sessions to figure out.
Says Mr. Singh in a press release this month announcing some of ThoughtSpot’s new AI capabilities:
With every new release, we add capabilities in our platform to reduce the effort required from users while increasing the value they get from their data. We call it LIMO, or less input, more output.
Simply identify what you are interested in following, such as an answer or data point, then click to “watch” the data over time. SpotIQ actively tracks these metrics with snapshots, regularly analyzing them for important changes, and sends you alerts on variations. A thumbs up or down feature puts humans-in-the-loop who provide feedback as to the usefulness of the insights being pushed out. It also lets the machine decide what to do and when to do it which helps the whole thing scale (anyone remember the limits they used to impose on refreshing Salesforce dashboards?) When you’re running queries on billions of rows at scale, it quickly becomes all about LIMO.
Finding the Exit
We were recently scoping some robots at a fruit packing warehouse when the COO started talking about how Salesforce was the backbone of their whole operation. What used to be a simple CRM solution with configurable dashboards has now exploded into something much more, including business intelligence. This past summer, Salesforce bought publicly traded business analytics software company Tableau for $15.7 billion in stock just days after Google made their own BI investment, the $2.6 billion cash purchase of BI startup Looker. In the face of those acquisitions Mr. Singh sees opportunity according to a recent interview with Forbes:
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.
Another thing everyone in information technology knows well: acquisitions are a nightmare. Mr. Singh knows that once his company gets swallowed by a bigger fish, it’s likely that the acquiring company will have a different idea of how things need to be run. That “diversion of focus” is perfectly normal, and that’s why he’ll probably seek a path to IPO as opposed to being chewed up and spit out by the Ginni Romettys of the world.
Large corporations become incredibly burdened by all the rules and processes that need to be put in place because at that size, you’re not able to only hire the best engineers. Pressure to fill large open headcounts and an increasing desire by recruiters to take away decision making from hiring managers means you will be forced to work with incompetent morons who need rules and regulations to keep them from wreaking havoc. Sometimes it’s these types who you depend on for the data you need to make decisions with. With ThoughtSpot, that risk is removed – everyone has access to the data, no matter how large your enterprise is. Come to think of it, we’re not sure if that’s a good thing or a bad thing.
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