Noosheen Hashemi was a vice president at Oracle by age 27 and rode that “fast train” into the tech-world stratosphere.
As the leader of the company’s finance and administration team, Hashemi helped the database software giant grow from $26 million in revenue in 1985 to $3 billion by 1995. But these days the mother of two is focused on January.ai, her precision health company in Menlo Park that’s using machine learning to help health care become more preventive. It’s currently trying to use technology to improve health for the 114 million people on the diabetes spectrum.
You’ve been an investor, board member, and/or advisor to dozens of companies, from bioscience firms to digital freight networks and movie studios. What lessons have you learned from having a ringside seat to so many types of businesses?
Ultimately, these are human endeavors, and getting a new idea launched involves collaboration of many people who have their own perspectives and career trajectories. Getting the vertical part, which requires domain expertise, can be challenging. But underlying all of that is always the human factor — how you recruit, how you encourage people to collaborate, what kind of teams you build, and whether people have a high level of satisfaction with what they’re doing at the same time you’re building a successful business.
You’ve been involved with a lot of early-stage companies. What’s the single most predictable mistake they make?
In very early-stage companies, there is sometimes confusion around who is supposed to do what. I’ve invested in a company, for example, where the cofounders are two brothers. You’d ask them, “Well, what’s your hat? What’s his hat?” They’d say, “We both run engineering. We both run sales. We both do everything.” That can create confusion in terms of how companies interact with customers and employees. That’s not necessarily a predictor of failure, but that lack of clarity can become unproductive.
You joined Oracle about eight months out of college. Did you have any idea at the time what that company might become?
No one did. We referred to the company as a fast train. We didn’t know how fast it could ultimately go, or how far. It never stopped for anyone, you kind of had to hop on and pick up velocity. Our maddening growth was very much by design — it didn’t happen by accident. For five years between 1985 and 1990, the company doubled revenues every year. That’s not trivial. That means everything I just said about building teams, collaborating, and having a purpose toward a goal was very much the Oracle story, on steroids. Oracle had one of the most productive sales forces ever, and it was able to eliminate competitors and rise as the leader in relational databases. It was a very purposeful journey with Larry Ellison as our guru, not just as our CEO. When he would finish talking to the sales force, people would be levitating. He was our god and we dutifully executed.
What specific choices enabled the company to grow so quickly?
We were singularly focused on growth and the self-selecting culture favored those who quickly figured out their contribution to it — and kept on delivering outsize contributions. The company was uncompromising in its selection of people. Larry personally approved every offer letter. We believed that A players hire A players, and B players hire C players, so you should never let B players in, not even one. We used to say that it takes just one bozo to hire a bunch of their friends and destroy the company.
Are there downsides to that kind of laser focus?
One could argue that the company should have also optimized for things like customer satisfaction or employee satisfaction. No one can tell you where that would have taken us, because it was a road not taken. Certainly, new companies being built today have to be concerned with many more things than just revenue. Culture of work has been compromised, for example. I worked 18-hour days for seven years straight and had a three-day honeymoon. Some people look down on hard work these days, which is unfortunate.
Any particular books, professors, or experiences you took away from Stanford that you found particularly helpful?
I took a small business strategy class from Jim Collins, who went on to write Built to Last [coauthored with Stanford GSB professor Jerry I. Porras] and Good to Great. Jim’s class was probably my most memorable because he was obsessed with the process of teaching. He started the class on time, he recorded the class so when he was grading he could reconstruct it and make sure he was not just favoring the last person who spoke. I love that. I still remember to this day a lot of the things Jim said, like “overnight success takes 15 years.” And of course Jeffrey Pfeffer. I’ve stayed in touch with him for 26 years. Some of my biggest revelations came in Jeff’s power-and-politics class. I learned that people in power are terrified of whistleblowers who have loyalty to a cause but not to a person. When you refuse to overlook their indiscretions, they become intimidated. Big light bulbs went off in that class.
You’ve said “the most important building block of a startup is the team.” Why do you think that’s the case?
Technology doesn’t get itself out there. You need humans to work together and deploy, to spread the gospel, to implement, to put something new into the world and make it part of the everyday fabric of life. The team is critically important. I want to make sure people look forward to coming to work in the morning, that work is a part of their lives in a natural and positive way, that they get satisfaction from their work. And that they have the space to be agile. If something doesn’t work, they should try something else, troubleshoot, pivot. Tackling big problems with brilliant, determined, and hard-working people is thrilling.
And the second most important building block for a small startup?
Clearly your product has to be the next big important thing — what you’re giving to the world, how differentiated it is, and how much of a need in the world it addresses. I’ve always been interested in broad impact. I like to work on things that a lot of people will use. For example, currently there are 114 million people in the U.S. on the diabetes spectrum. Seventy-five million people have prediabetes and don't know it. Research shows that 58% of these folks will tip over into diabetes unless they make a dramatic lifestyle change. Complications from diabetes are serious and include cardiovascular disease, and nerve and organ damage. Furthermore, Type 2 diabetes might be associated with depression and even Alzheimer’s disease. Obesity, which is correlated with diabetes, is growing in every country in the world.
That’s why January.ai is using machine learning to help people manage blood sugar levels?
Yes. Both genetic and environmental factors play a role in the development of Type 2 diabetes, and only one of them — lifestyle — is modifiable. Research by my cofounder and Stanford professor Michael Snyder shows that we can potentially observe pre-prediabetes in people’s glucose curves from continuous glucose sensors long before diabetes symptoms appear or doctors notice elevated hemoglobin A1C levels. January.ai’s product unifies several data streams from continuous glucose monitors, heart rate monitors, and logged data from food, activity, and water to provide insights on managing blood sugar. Glycemic response to foods differs from person to person and varies even for a single person. We can help people figure out whether they should be eating more or less of certain foods, and when or how much to exercise. Our health AI recommends lower glycemic food choices from 16 million foods including grocery items, recipes, and menus. The opportunity to help people improve energy, focus, and health span is tremendous.
What convinced you to focus your family’s philanthropic efforts on what you call “the vulnerable and disenfranchised”?
That’s the purpose of philanthropy, to help those that can’t do for themselves. Child sexual abuse has been one of our foci. It’s the ultimate derailment of life. And it’s everywhere. One of every four girls and one of every six boys before the age of 18 in America is sexually abused. There’s a lot of pain there that people don’t talk about. Children are one of the most vulnerable populations the world over, because they’re small and don’t have power, they are preyed upon — institutionally, structurally, but also in families. To say it’s heartbreaking doesn’t begin to describe it
You moved to the U.S. from Iran as a teenager in 1977. Did that immigration experience influence the way you’ve approached your life and career?
By all means. I feel very lucky to have landed in the United States and in Silicon Valley. I have achieved the American dream and am determined to perpetuate it for others. A healthier population means more productivity, lower health care costs, and stronger national defense. With new sensors, novel diagnostics, and modern machine learning, we are able to predict chronic disease and spare people the savagery of surprise diagnosis. Why wait to be told you have diabetes or stage-four colorectal cancer? We can help people improve their short game, which dramatically improves their long game. The promise of precision health is to help people predict, postpone, and prevent diseases, precisely, and it’s here today. In my first career, I helped build a monopoly. In my second career, I got people to give more of their time and money through philanthropy. In my third career, I am excited to combine the two: Do well and do good.