Can you tell us about your background and how you came to work for SignalFire?
My path to venture is a bit different than most VCs. I grew up playing chess, eventually becoming the top female player in Canada and the youngest ever to achieve the Woman International Master title. In high school, that interest led me to found a nonprofit called Chess in the Library that ran more than 30 chess programs in public libraries across Canada. I went on to study economics at Yale, where I co-founded a student-to-student summer subletting marketplace called Sublite. After my entrepreneurial experiences with Chess in the Library and Sublite, I knew that I had a passion for building something from zero to one and also working in agile, nimble teams where we’re often crossing uncharted territories and having to figure things out along the way.
After graduating, I made my way to Blackstone, initially working on the emerging markets team, evaluating macroeconomic and political risks in countries like China, Brazil, and Egypt before eventually working on late-stage and IPO investment opportunities. While those were all great experiences, it was the growth equity deals I got to work on that I enjoyed most because I got to spend time with exciting, innovative companies that reminded me of my own entrepreneurial experiences. That realization, combined with my desire to roll up my sleeves and work alongside startups and founders, led me to move to earlier stage investing and thus join SignalFire four years ago.
Of all of the funds out there, why did you choose SignalFire? What stood out to you about the firm?
SignalFire is a vertically agnostic early stage fund primarily focused on US software companies. What drew me to it is just how differentiated it is. The-data driven approach, the way the firm was built more like a startup than an investment firm — we have our own engineers, project managers, home-built tools, and infrastructure to support our investment process and the companies that we invest in — and that we actually measure our own NPS with our portfolio founders every year to make sure we deliver on our promises.
Tech has always been a part of our DNA and so today we have roughly a dozen data scientists, engineers, and product managers on our team. In addition to helping our portfolio companies directly on specific projects, they work on a proprietary AI data platform called Beacon that tracks more than 80 million companies and over 500 million people worldwide.
And what does Beacon do?
It serves a couple of different purposes, starting with sourcing. Every month it identifies high-potential early-stage businesses that we should be evaluating for potential investment opportunities, effectively narrowing the top of our funnel so that we can be much more targeted about which companies we pursue.
Beyond that, Beacon helps support our portfolio companies post-investment. It does so by ranking the talent of all of the people it tracks, making it easy for us to identify the best candidates for the roles our companies are trying to fill, from individual contributors all the way up to executives. We also have six full-time recruiters in-house, including the former chief people officer at Netflix and Waymo and the former head of executive search at Meta, who help our portfolio companies with all of their hiring needs.
I really appreciate that SignalFire wants to add more value than any other investor, and measures that impact. Last year, we had an average net promoter score of 85 across our portfolio companies.
We know you’re interested in healthcare tech. What trends are you seeing in that space and can you tell us about a couple of your recent investments?
Sure. One of the big challenges in the healthcare system right now is the labor crisis. Not only are people churning out of the industry as a result of pandemic-related burnout, young professionals just aren’t pursuing healthcare jobs as much as they used to. That’s particularly true among nurses and primary care physicians, where the pay isn’t as attractive as in areas like surgery, oncology, or dermatology. Meanwhile, many doctors and nurses are rapidly approaching retirement age, meaning that the gap between supply and demand will only continue to grow as they exit the workforce over the next 10 to 15 years.
Unfortunately, dynamics like these are creating huge problems for the healthcare ecosystem, not least of which is rising labor costs. Over the past two years, healthcare labor costs have increased by between 10 and 15 percent as demand outpaced supply. One of the areas we’re interested in is how technology can be used to address these issues, such as using software to automate specific workflows within the healthcare industry.
One area that’s ripe for disruption is the coding that happens after every doctor’s appointment in order for it to qualify for insurance coverage. After each visit, the doctor writes a note to summarize the appointment and then either has to assign a particular billing code to the visit or pass the note on to someone else to do so. Given that there are more than 10,000 of these billing codes that vary based on the type of appointment, what was discussed, and the diagnosis, picking the right one is an extremely manual process. Fortunately, recent advances in natural language processing and machine learning have paved the way to automate much of this work.
We recently led the Series A investment in a company called CodaMetrix that spun out of Mass General Brigham in Boston and that’s focused on this specific issue. Not only do they have the data and deep natural language modeling capabilities necessary to succeed in this space, they also already have a number of large, bluechip healthcare customers using their platform.
That’s really interesting. What other types of opportunities do you see in healthcare?
Another area we’re following is the spike in the cost of healthcare driven by our aging population. There are 60 million seniors in the US today, which is expected to double over the next two to three decades. Healthcare costs also rise rapidly with age — the cost of caring for someone over the age of 85 averages out to $32,000 per year, while the average is only $5,000 for those between 19 and 44 years old. These facts mean we’re poised for steady growth in healthcare spending in the coming decades, well exceeding the $4 trillion that we already spend per year in the US.
So the question is how do we get ahead of this problem and reduce healthcare costs in a meaningful way, particularly among the oldest part of the population? One possible solution is the concept of home health and aging in place. It’s the idea that instead of seniors going to see their doctor, which they may or may not do regularly as they reach old age, the doctor comes to them. That way it’s possible to proactively screen for and address any medical conditions early, thus avoiding the higher costs associated with providing treatment when it may already be too late.
For example, we invested in Recora Health, which partners with health systems to provide a platform where patients have access to cardiac care at home. It starts with cardiac rehab, a 12-week program that typically requires a patient to go to a rehab clinic three times a week for an hour each. Recora brings this experience to the patient’s home, dramatically increasing the attendance rate of the rehab program, which has been clinically proven to reduce the likelihood of a subsequent heart attack.
Another way to solve the challenge of rising costs in our aging population is to eliminate the $300 billion of excess spending every year on medications that don’t get consumed, more expensive medications vs. generic equivalents, and medications that patients no longer need. We were excited to lead the Series B in Wellth because they’ve figured out how to use behavioral economics principles and big data to engage with patients in a highly personalized way, helping these individuals take their meds every single day.
Given SignalFire’s unique data-driven approach, what insights do you have on what’s happening in healthcare data, analytics and AI applications?
We think there’s a huge opportunity right now in the intersection between data and healthcare. We’re seeing increased adoption of electronic health records (EHRs), regulatory enforcement, and a growing popularity of wearables and other health tracking devices. These are producing a breadth of data types including patient information, clinical notes, test results, imaging data, and claims data. However, managing and analyzing this massive amount of data presents significant challenges. To get anything done with the data, you have to solve the interoperability problem of systems communicating effectively with each other, data normalization, privacy, and security issues — before you even get to the sophisticated applications of data science.
Now’s the time, though. The world just got equipped with fresh AI tooling that can make sense of the seas of data flowing out of healthcare. And with everyone thinking about AI, many slower-moving incumbents will feel a sense of urgency to modernize their data stack.
We have developed an entire thesis on the problem of data and healthcare (see our blog post How AI and analytics could solve healthcare’s big data problems) that outlines what we think about both innovation and investability in data infrastructure (which led to our investment in Health Gorilla) and building AI analytics and models on top of healthcare data to solve the ultimate goals of improving outcomes and patient experience while reducing the costs within our $4 trillion industry.
You mentioned being one of the top female chess players in Canada and achieving the title of Women’s International Master at a young age. How has mastering that game helped you become a better investor?
The benefits of growing up as a chess player are enormous. It has helped me develop so many cognitive and noncognitive skills that are transferable to any analytical career — the ability to see the big picture and not miss the forest for the trees (what’s happening across the whole board, not just in certain squares), conduct scenario analysis (what are the five possible moves my opponent will make and what will I do against each), predicting how the future informs us of our decisions today (calculating 10 moves ahead), etc.
If I had to pick one, I think the most transferable skill that applies to investing is pattern recognition. To get to the master level, you need to spend thousands of hours studying patterns and finding ways to apply those nuanced patterns in each game, which is always unique in nature. The same rule applies to investing — no two companies are ever exactly the same.
What advice are you offering founders to help them navigate the challenges of the current economic environment?
The number one message I keep delivering to our founders is that the next two years won’t be easy from a funding and revenue perspective. Meanwhile, your customers will also be facing challenges and cutting their costs. We try to help companies figure out how they’ll handle different scenarios and to think through the trade-off between growth and burn. Over the last few years, many believed in growth at all costs. Now things have shifted and the focus is on how much it costs to obtain that growth. We try to work with our portfolio companies to think through all of the options. What if, instead of tripling this year, for example, they doubled but maintained a much lower burn rate?
We’re also having a lot of discussions about org design and how companies can use the current environment to proactively restructure the business and make smart decisions to set themselves up for long-term success. I always tell founders that cost-cutting doesn’t have to mean you’re in trouble. In fact, it’s often a sign of strength.
What are you reading right now?
I’m a bit late to the game here, but I just read Crossing the Chasm by Jeffrey Moore. I think it was first published in 2006, but it’s still as relevant as ever in terms of the advice it offers for helping B2B tech companies drive mass adoption for their product. From my vantage point of sitting on the board of eight companies right now, I can tell you just how salient the messages this book conveys are.