For the last 30 years, Peter Gassner has been at the center of various shifts in enterprise software. While at IBM Silicon Valley Lab, he worked in the mainframe market. Then he moved over to PeopleSoft, which was a pioneer of client-server platforms.
Yet he knew these technologies had major flaws. They were often rigid, clunky and complex. There was also the challenge of working with large amounts data, which was often spread across silos.
But when Peter saw the emergence of cloud computing, he knew this technology was the answer. So in 2003, he joined Salesforce.com as the VP of Technology. He got a first-row seat on how the cloud could scale and transform organizations.
As with any new technology megatrend, the first applications were broad. And yes, this presented some complications. This is why, in 2007, Peter launched Veeva Systems, which focused on providing cloud services for the healthcare industry. This became part of a new wave called the “industry cloud.” The timing was spot on as Veeva saw strong adoption.
Fast forward to today: The company has a market cap of $16.5 billion and more than 600 life sciences customers. During the latest quarter, revenues jumped by 27% to $224.7 million and net income came to $64.1 million, up from $34.9 million in the same period a year ago.
AI and Healthcare?
When I first met Peter six years ago, I mentioned his company’s latest quarterly results. But he remarked: “I’m more concerned about where Veeva will be five years from now.”
This long-term thinking has certainly been critical for the success of Veeva, allowing for breakthrough innovations in the product line.
OK then, what about AI (Artificial Intelligence)? How will this be a part of Veeva’s product roadmap?
Well, of course, this is something that Peter has been thinking a lot about. “The industry is a gold rush,” he said. “And there will be more losers than winners.”
This should be no surprise. Whenever technology undergoes seismic change, there is overinvestment. Eventually this leads to a shakeout, with consolidation and shutdowns.
Now as for AI, Peter believes that success requires a key ingredient: data. Without it, a startup will have an extremely difficult challenge in standing out from the competition.
But this is not an issue for Veeva. Consider that its platform includes 70% of healthcare sales reps across the globe.
However, Peter did not rush to build an app to leverage the data. He instead first built a solid data layer, called Nitro. The goal was to make it easy to organize and classify data (based on industry-specific standards). To develop Nitro, Peter used Amazon.com’s Redshift as the core database. It is a petabyte-scale data warehouse service in the cloud. The bottom line: insights can be accessed much quicker (a traditional system could have lags of several weeks).
“It would have taken us much longer to build Nitro without Redshift,” said Peter.
But Nitro is just the first step. Veeva is currently working on an AI engine called Andi, which is a 24/7 assistant. It will crunch a wide variety of data about a life science company’s customers and suggest the best actions to take. “Some days Veeva Andi will recommend a field rep go see a particular doctor, send an email, share a piece of content, or invite them to an event,” said Peter. “It might also send things directly to the customer on behalf of a pharmaceutical company. Keep in mind that the amount of data needed to drive intelligent engagement is overwhelming. Humans can’t consume all that data, find patterns, and make sense of it. Veeva Andi will solve this, learn, and get smarter over time.”
For the most part, AI is still in the early days. But Peter does not want to take any shortcuts. He understands that any technology takes awhile to get adoption and to make a real impact. The enterprise market also requires that things be done right – and that there be a clear-cut return on investment. And no doubt, such things can easily get lost when there is a gold rush among technology vendors.