Healthcare's Incentive Misalignment

Just under 15 years ago, I sat down in a conference room with one of my clients, the SVP of Benefits of a self-insured, Fortune 100 company. Like most large companies (his had about 300,000+ employees at the time), they were focused on reducing their health insurance costs as it had become an enormous line item for them that had the attention of their CEO. My company recently launched a product that helped large employers drive enrollment and engagement in voluntary benefit programs (things like smoking cessation, health risk assessments, fitness contests, nutrition counseling, etc.). Like many companies, my client had very low usage of these programs. I spent a few minutes telling him about our product, thinking that if we could increase usage of these programs, his employees would be healthier, bringing down their insurance costs.

Once I was done talking, he looked at me and told me the thing that large self-insured employers and health plans aren't supposed to say:

"Brian, the average employee's tenure at our company is 22 months. I don't want to spend time investing in driving usage in things that will make my employees healthy only to have them leave and have some other employer benefit from that investment."

And in those two sentences, he articulated the #1 structural problem with healthcare in the United States: incentive misalignment.

Misaligned Incentives

There are three major players in US healthcare: the patient, the provider, and the payer. And none of their incentives are aligned.

Patient: The patient's incentive is to live a long, healthy life.

Provider: The provider's incentive is to have lots of sick patients who need billable treatments.

Payer: The payer's incentive (or self-insured employer) is to cover lots of healthy patients who don’t get sick and don’t need treatment. But only for a short period. They only care if the patient is healthy while they're a member of their health plan. Members typically stick with the same plan for 2 to 3 years. Health plans have extremely high churn rates as employees change jobs, patients fall on and off Medicaid, move to lower-cost Medicare plans, etc. Payers don’t have a financial incentive to invest in the long-term health of the patient. They have no incentive to help the patient live a long, healthy life. In fact, they have a disincentive to invest in the long-term health of the patient if that payoff comes after the patient is no longer a member. This dynamic applies to the provider as well in a value-based care model where the provider is taking financial risk. 

To be clear, when I’m talking about incentives, I’m not talking about ethical incentives. Everyone wants people to be healthy. I’m talking about financial incentives. They are not aligned. And that’s a real problem, as payers and providers are businesses that need to make responsible financial decisions. 

For business models and systems to work well, they need incentive alignment. Take the iPhone ecosystem as a simple example. The user wants a great phone at a reasonable price with an unlimited number of functions. Apple wants to sell a lot of high-margin phones and high-margin apps. And the app makers want a huge audience to build apps for. It’s not perfect, but financial incentives are generally aligned, so this ecosystem thrives.

In a system full of problems, this lack of aligned incentives is the core problem in healthcare.

We need to get to a system where the entity caring for the patient and the entity paying for the care of the patient is financially aligned with the patient’s incentive to live a long, healthy life.

Solutions

Ideally, the government could help with some top-down structural changes such as incentivizing longer-term health investments through tax incentives, allowing plans to benefit from long-term preventative investments, or possibly universal coverage of some sort and changing the way care is paid for. However, a big change from the government will be difficult and come with its own complex set of sensitive tradeoffs. That said, It seems the use of HSAs, which allow employees to carry tax-free dollars that can be used for health expenses across employers, has expanded. I’m also very encouraged by the Individual Coverage Health Reimbursement Arrangement (ICHRA) that was launched in 2019, set up through a partnership between HHS, the Department of Labor, and the Department of Treasury, which allows employees to pick their plan outside of their employer and get reimbursed by their employer, allowing them to stick with the same plan as they change jobs. We need more of that. 

The private sector has a huge opportunity to address the incentive problem through real business model disruption. The word “disruption” gets thrown around a lot, especially in health tech. But disruption doesn’t just happen through new technologies. It happens through fundamental business model transformation that changes the way business is done. The hotel industry wasn’t disrupted by the Internet or even by early Internet companies like Orbitz, Expedia, and Kayak. Those services just changed the way consumers book hotels and the way hotels do marketing. AirBnB was actually disruptive by transforming a gigantic B2C business into a peer-to-peer business. That’s disruption.

Of course, these business model transformations take time, and they almost always start by focusing on a very niche part of the market and scaling up from there. We’re seeing some signs of this in healthcare:

Longevity-focused solutions such as Function Health and Neko Health give the patient more control and take a longer-term, consumer-focused focus perspective on health. 

Direct primary care models like Taro Health, where patients pay a flat fee for access to primary care services incentivizing providers to focus on preventative care for the long term.

In 2013, I wrote a post titled 15 Reasons Why Healthcare Has A Business Model Problem. Rereading it today, all of those problems still stand. Healthcare is a uniquely challenging problem for all of the reasons I listed in that post. And one thing I’ve learned over the years is that you can complain about it all you want, but when you have to turn your attention to solutions, you realize there simply are not great answers. It’s just a set of very complex, nuanced, and thorny tradeoffs.

As Charlie Munger said, “Show me the incentive, and I’ll show you the outcome.” The negative outcomes have been evident for years. While many of these approaches are early, and it’ll take time to get real traction, it’s exciting to see entrepreneurs focused on root cause incentive alignment to drive long-term and sustainable transformation. We need it now more than ever.

Assets > Wages

Aside from a short period of turmoil during COVID and the inflation that followed the economic stimulus, the US economy has been pretty strong over the last ~15 years. The stock market is at all-time highs. Unemployment is near all-time lows. Inflation is now mostly back in check. The dollar is strong.

But there is a somewhat troubling trend that people — particularly people early in their careers — should be aware of. And that is the expanding gap between the high growth in asset values versus the relatively low growth in wages. 

Since the Great Financial Crisis in 2008, stock prices have increased 540%, home prices have grown 114%, inflation has increased 50%, while wages have only grown 43%. Unfortunately, this trend contributes greatly to the wealth gap in the US. Generally, lower-income people are less likely to own assets and make most or all of their income from their jobs. People with higher incomes own most of the assets. The rich get richer. Literally.

It wasn't always this way. From 1945 to 1973, wages grew nearly twice as fast as home prices. But this new trend of assets growing faster than wages has accelerated significantly, driven by a variety of factors that are unlikely to change:

1/ Home price inflation. Over the last several decades, zoning and other types of laws have made it almost impossible to build large numbers of new homes in areas where people want to live. While there's plenty of land to build on in the US, bureaucracy gets in the way. Meanwhile, to fuel growth, we need more people to come into the country (through immigration or births). That means more and more demand for homes, which means higher prices. 

2/ Stock prices continue to rise rapidly. The US stock market has really stood out lately compared to virtually any other country. Given our democratic system, the rule of law, and our embrace of innovation, we're really outpacing the rest of the world. And while things might be a bit overvalued due to AI and low interest rates, it seems like there's no end to the scale of the large tech companies that are leading the market. When I was a kid, the largest US companies were companies like General Electric and General Motors. Companies that were selling high marginal cost hard goods, mostly in the United States. Now, we have these tech companies with very low marginal costs selling their product to nearly everyone on Earth. These companies are huge. Facebook has something like 6 billion users. And it costs a lot for General Motors to build a car; it costs Facebook next to nothing to display an ad. 

3/ Wage stagnation. While wages will continue to increase, they won't grow nearly as fast as assets. Offshoring and technological innovation (particularly AI) will put downward pressure on wage increases. Again, as I've mentioned in the past, there will be plenty of jobs, and wages will increase, but people who only generate wealth through their time and effort will continue to fall behind. 

Owners of assets have benefited disproportionality over the last couple of decades. And outside of some earth-shattering change, there's little reason to believe that will stop. 

It’s important to understand these trends and act accordingly. The message to younger people is to start getting their money into assets as much as possible sooner rather than later. Trying to get rich on your time and effort is an uphill battle. Be frugal, start saving and investing as early as possible.

Benchmarks & Storytelling

The other day, a founder asked me about financial benchmarks for a company at his stage. He asked about the optimal CAC/LTV, gross margin, and revenue per employee. 

Benchmarks are important. Investors, particularly investors who don't have intimate knowledge of your company, will use them as a guide for how to value your company. There's a temptation for founders to optimize against top-tier benchmarks. But I think that's unwise. Optimizing against benchmarks is actually relatively easy. What's really difficult is knowing what your company needs right now and optimizing against that. That's a lot harder.

‘Revenue per employee’ provides a very simple example of this concept. Top-tier SaaS companies have a revenue per employee of around $300k. It's tempting to chase that number. The problem is that the easiest way to grow your current revenue per employee is to stop innovating. Get rid of all the employees working on stuff that won't impact revenue this quarter or this year. But that's likely not at all what your company needs right now for a variety of reasons.

So, in many cases, you actually don't want to optimize revenue per employee. That might not be what your company needs right now.

The best approach to this problem is to know your metrics and be aware of top-tier benchmarks but to intelligently apply those benchmarks to your business and be able to explain to an investor and your team why that's the right thing for you right now. A great story around why your revenue per employee is lower than a top-tier company because you are thinking about growth 3 to 5 years from now or why your gross margin is low right now because you're overly investing in your early customers, or why your CAC is high because your testing new marketing channels is a lot more impressive than a simple point in time comparison to benchmarks of companies that might need to optimize around something completely different.

AI In Sales & The Jevons Paradox

A month or so ago, I wrote about the emerging AI business model and its potential impact on white-collar employment. As I said in the post, I'm skeptical that AI will reduce the number of white-collar workers, particularly salespeople. With that in mind, I came across a concept called the Jevons Paradox. 

The Jevons Paradox says that when technological improvements increase the efficiency of a resource, that leads to higher consumption of that resource, not less.

A couple of examples:

Technologies like home insulation, in theory, would reduce the need for heating and cooling energy consumption. But the effect was that people invested in larger homes resulting in more overall energy consumption.

Electric/hybrid cars bring down energy costs, leading to more frequent driving and longer trips, and more overall energy consumption.

This concept also applies to work.

Flexible work tools like Zoom have added convenience but also made it possible to work more, increasing the number of hours worked. 

Communication tools like Slack and email make communication more efficient but have also led to far more communications and increased workloads. 

I think we'll see the Jevons Paradox at work with AI in sales. As AI takes on more of the job of a salesperson and does things like lead scoring, opportunity prioritization, CRM automation, communication personalization, sentiment analysis, etc., it will bring down the cost of sales. That means that each salesperson costs less per dollar in sales than they did prior to the adoption of AI. That will cause companies to want to do more sales and hire more salespeople to do the work.

The myth is that automation makes the worker superfluous. In reality, the opposite is true because it’s an opportunity for the ambitious to do more. Marketing automation is a great example. Facebook Ads can effectively run highly targeted, comprehensive marketing campaigns, in theory reducing the need for digital marketers. When, in fact, those platforms made marketing cheaper, which led to major increases in the need for more digital marketers to manage these programs and to do more marketing. The same will be true with AI in sales.

When something gets cheaper, we tend to do more of it.

DOGE, Startups & Political Party Paradoxes

Elon Musk and Vivek Ramaswamy outlined the rationale behind their Department of Government Efficiency project (DOGE) in the Wall Street Journal last week. DOGE is intended to serve as an advisory board to streamline the U.S. federal government and reduce inefficiencies, particularly within three-letter agencies like HHS, EPA, FTC, DOD, etc. While the idea is controversial, it’s also hard not to like. No doubt government isn’t as efficient as it could be, and with the exploding federal deficit, cost reduction sounds like a nice idea. However, it’s worth noting that several presidents have tried similar initiatives in the past with limited success.

What makes this particular effort interesting, though, is its focus on reducing the thousands of regulations federal agencies have implemented over the years. The idea is that fewer regulations would mean reduced headcount to enforce those regulations and taxpayer savings. Many Americans may not realize that unelected federal agency staff write thousands of rules annually governing how businesses across the country operate.

These rules, while rooted in laws passed by Congress, are written and enforced by the agencies themselves. For example, Congress might pass a law like the Safe Drinking Water Act, and the EPA would then draft and enforce specific rules regarding contaminants, pollutant limits, and reporting requirements. This structure makes sense because Congress doesn’t have the bandwidth to dive into the details of implementing every law.

Critics argue that these agencies have amassed too much power, often acting on their own priorities rather than staying accountable to the public.

Musk and Ramaswamy wrote in their piece:

“Our nation was founded on the basic idea that the people we elect run the government. That isn’t how America functions today. Most legal edicts aren’t laws enacted by Congress but “rules and regulations” promulgated by unelected bureaucrats—tens of thousands of them each year. Most government enforcement decisions and discretionary expenditures aren’t made by the democratically elected president or even his political appointees but by millions of unelected, unappointed civil servants within government agencies who view themselves as immune from firing thanks to civil-service protections.

This is antidemocratic and antithetical to the Founders’ vision. It imposes massive direct and indirect costs on taxpayers. Thankfully, we have a historic opportunity to solve the problem.”

Government agencies, like most organizations, grow in size and scope over time. It’s human nature to want to do more with more influence, more budget, and more people. Rarely do people within these organizations prioritize limiting their scope or shrinking their footprint. It’s just not in our nature.

As a result, millions of pages of regulations now govern nearly every aspect of American business. While many of these rules are undoubtedly necessary, it’s reasonable to assume there’s significant overreach.

All of this reminds me of a talk Bill Gurley gave a while back on regulatory capture. Regulatory capture occurs when agencies tasked with regulating an industry become overly influenced by the interests of the organizations they regulate.

Gurley talked about a classic example of this in healthcare. Epic Systems, the healthcare software giant, benefited enormously from the Affordable Care Act (ACA). The ACA’s HITECH Act incentivized healthcare providers to adopt electronic medical records (EMR) software. A new agency, the Office of the National Coordinator for Health Information Technology (ONC), now renamed to the Assistant Secretary for Technology Policy and Office of the National Coordinator for Health Information Technology (ASTP/ONC), was established to administer this program.

ONC mandated payments of $44,000 per doctor to purchase EMR software and an additional $17,000 for demonstrating "Meaningful Use" — proof they were actively using it. Epic’s CEO played a pivotal role in designing the requirements for Meaningful Use, which aligned closely with Epic’s existing products. This created high barriers to entry, forcing smaller competitors out of the market or to incur major penalties for being out of compliance with the new regulations.

ONC has gone on to write more and more rules on top of the EHR standards for things like health IT certification, interoperability standards, and information blocking. If you work at a health tech startup, it’s more likely than not that these rules impact your company in some way.

Perhaps the best examples of regulatory capture came out of the Great Financial Crisis in 2008. Financial regulations, like Dodd-Frank, reinforced the dominance of the large incumbent banks. These rules imposed strict capital and compliance requirements, which big banks could absorb but smaller ones could not.

The result was that large institutions like JPMorgan Chase and Goldman Sachs emerged stronger than ever, making it difficult for smaller banks and new entrants to thrive.

Again, while many of these rules are valuable, many are not. And the overarching structure of the system generally favors large incumbents. This is true for two reasons:

1/ Lobbying Power: Large companies have the resources to influence Congress and federal agencies through lobbying and campaign donations. Many of them house large government affairs and public policy staffs in Washington.

2/ Established precedents: Policymakers often are reluctant to implement big changes to the way businesses operate and as a result design their programs and rules around the existing establishments.

If DOGE succeeds in reducing federal agency regulations, it would inherently challenge rules designed to protect the country’s largest companies that have benefited from the regulatory capture dynamic — ExxonMobil, Microsoft, Boeing, UnitedHealth, Walmart, etc. 

This is a rather surprising effort to come out of a Republican administration that has typically supported big business, but it makes sense in the context of some of Trump’s other non-traditional decisions since winning the election. Take some of the comments he made when nominating RFK for Secretary of HHS:

“For too long, Americans have been crushed by the industrial food complex and drug companies who have engaged in deception, misinformation, and disinformation. HHS will play a big role in helping ensure that everybody will be protected from harmful chemicals, pollutants, pesticides, pharmaceutical products, and food additives.”

This statement sounds more like left-wing activism than traditional Republican rhetoric.

Back to the DOGE effort. No doubt the purpose of this effort is to reduce the cost of the federal government, but by unraveling many of the regulations that protect incumbents, this also starts to shift the balance of power back towards startups. Multiple VCs have talked about how these regulations have paralyzed the work of many startups, particularly in fintech, crypto, and AI. While Musk and Ramaswamy have run big businesses that have undoubtedly benefited from these regulations, they’re both founders and entrepreneurs as opposed to traditional, big company managers. Much of this effort feels like an indirect backlash against the “managerial revolution” where professional managers hold the primary power in organizations and economies as opposed to inventors, entrepreneurs, and founders. So, in some ways, DOGE isn’t just an effort to reduce the size of government; it’s also very much an effort to support a thriving and innovative startup ecosystem. 

This won’t be easy. In fact, it might be impossible. There will be endless lawsuits, and large, powerful businesses with enormous lobbying budgets will scramble to protect the status quo.

But if it’s successful, DOGE has the potential to reduce the size of government and weaken the big established incumbents, creating more opportunities for startups to drive innovation. And it may realign some aspects of the American political party system. If it doesn’t succeed, it may simply underscore and reinforce how entrenched the existing system and structure have become.

AI & Sales

A few weeks ago, Tomas Tunguz from Theory Ventures gave an insightful talk on the state of SaaS Go-to-Market. One key takeaway was the explosive growth of AI use among sales teams. This isn’t surprising. Sales teams, by nature, are quick to adopt new tools because they’re profit centers. Anything that works will be adopted quickly because it impacts the top line. AI is helping sales teams in several areas—lead scoring, customer research, training, follow-up automation, competitive intelligence, and price optimization, to name a few.

Sales leaders are reporting lots of efficiency gains thanks to AI, but despite the boost in productivity, AI hasn’t moved the needle when it comes to deal conversions or bookings growth.

The reality today is that AI in sales — as it is in many functions — is really like having a bunch of productive interns. They can handle lots of grunt work, but their output needs to be checked, they’re tough to train, they lack company and situational context, and they’re not equipped to make important decisions. AI can’t yet do what great salespeople do. It can’t build emotional connections, navigate complex negotiations, leverage intuition, adapt in real-time to low-information situations, or respond to subtle cues or nuanced human emotions surrounded in layers of context. In short, AI is really good when it has lots of great training data to work with, which is the polar opposite of what a good salesperson does: they shine and show their real value when they lack data, and the next step is unclear, and they have to jump over hurdles to acquire more information or rely on their emotional intelligence, intuition, instincts, and human connection to make a good decision without it.

That said, I do believe the efficiency gains AI provides will eventually translate into better conversions and growth. But I’m skeptical how high up the chain it can go in terms of high value sales activity.

AI in sales will be a fun one to watch. Sales results are pretty measurable, and teams will quickly adopt what works. We’ll see.

Breaking Down $4.5 Trillion

Healthcare is a $4.5 trillion dollar industry.

I can’t tell you how many startup pitch decks start by stating this fact. Unfortunately, without more details, this number is somewhat meaningless with regard to the vast majority of healthcare companies. Better to break the $4.5t down into parts and talk about the share that your company will seek to impact or how it may shift dollars across categories. Here’s how the $4.5t breaks down at a high level:

• Hospitals and Healthcare Facilities – 31% (~$1.4 trillion)

• Physician and Clinical Services – 20% (~$900 billion)

• Prescription Drugs and Pharmaceuticals – 10% (~$450 billion)

• Health Insurance and Payers – 29% (~$1.3 trillion)

• Medical Equipment and Devices – 6% (~$270 billion)

• Healthcare IT and Digital Health – 4% (~$180 billion)

• Home Healthcare and Long-Term Care Services – 5% (~$225 billion)

Even these categories are way too broad to tell a good story around (as an example, the EHR industry is about $35 billion out of the $180 billion healthcare IT industry; cancer drugs are about $200 billion out of the $450 billion pharma industry).

I love a company story that starts at a high level that everyone can understand and then zooms in deeper and deeper, educating the listener along the way. So it’s a great idea to start with the $4.5t, but that’s just the start of a much more interesting drill down into what you plan to do and how you plan to do it.

Fundraising & Incentive Alignment

There was a really interesting discussion on the “state of venture capital” on the BG2 podcast this week. It's definitely worth listening to the entire episode, but here are three key insights for founders that I thought were worth highlighting, along with some brief commentary:

1/ $100M+ exits are incredibly rare but can be life-changing for founders. Taking 15% of a $100M exit is $15M—not bad at all. But if you've raised $100M in venture capital, a $100M exit is off the table due to the preference stack where VCs get paid first. If you've raised $500M, a $500M exit is off the table. $1bn, etc. Raising more money than you need makes great exits harder and harder to achieve. This is also true of valuations: a high valuation sets a new benchmark for success. There's an important trade-off between driving up valuation (so investors take a smaller portion of your company per dollar invested) and setting expectations so high that even a strong exit may not satisfy investors. I wrote a post a while back about how employees should think about this topic when joining a startup.

2/ Raising too much can lead to a loss of focus, spreading talent too thinly across initiatives. Companies often say they won’t use all the capital they raise, but that’s tough to avoid in practice. If you’re an entrepreneur with a bank full of funds and a head full of ideas, you’re likely going to pursue those ideas. The discipline to keep the money in the bank is inconsistent with the mindset of a creative, ambitious, high-growth leader. And early on, focus is everything, and it’s one of the major advantages a startup has. You only have a small team of top performers that can create outsized value, so spreading them too thin can significantly reduce their impact.

3/ The incentive structure in venture capital has shifted a bit, impacting the alignment between VCs and founders. The venture model, traditionally known as "2 and 20," means firms typically charge a 2% management fee and take a 20% carry (their share of profits when a portfolio company exits). In the past, venture capital was sort of a boutique asset class, with a few players managing smaller funds and relying heavily on that 20% carry to make a profit. Today, due to companies going public later and seeing more value creation in the private markets and the fact that starting a company has become much easier, venture capital has become a far larger asset class with more capital, more investments, and lower margins. As a result, that 2% management fee can become a substantial source of income — 2% of a $1 billion fund is $20 million per year. This structure incentivizes VCs to deploy capital more quickly as they don’t earn that management fee until the money is deployed. It's not a huge deal, but this can lead to some incentive misalignment between a VC and founder, so it’s worth being aware of.

Writing

“I’ve seen many people shy away from writing because it doesn’t come naturally to them. What they overlook is that writing is more than a vehicle for communicating—it’s a tool for learning. Writing exposes gaps in your knowledge and logic. It pushes you to articulate assumptions and consider counterarguments. Unclear writing is a sign of unclear thinking.”

-Adam Grant, Hidden Potential: The Science of Achieving Greater Things

Why Is It So Hard To Sell To Health Systems?

As a seller, you want to sell to an organization with a single decision-maker who’s free from regulatory constraints, has high margins, a risk-taking mindset, plenty of cash, and no legacy systems in place to slow things down. This is the exact opposite of a typical health system.

Many salespeople claim their market segment is the toughest. But those who sell to health systems might just take the prize. Health systems are notoriously challenging to sell into. To sell to these organizations more effectively, it’s helpful to consider why that is.

1. Complex Organizational Structure

Health systems have very complex ownership and decision-making structures. There are multiple layers of authority, often with competing interests, incentives, and priorities: executive leadership, service line leadership (orthopedics, cardiology, nephrology, etc.), procurement leadership, and technology leadership, all of whom can veto a decision. Clinical needs can also quickly shift priorities, sometimes sidelining other initiatives. And then there’s the troublesome “innovation” team, often connected to a venture investment fund with its own set of disjointed incentives. Selling a product to a health system often requires buy-in, alignment, and approval from all of these stakeholders. A key part of the job for a salesperson is to help the buyer navigate their own internal processes to enable a purchase.

2. Regulatory and Compliance Constraints

Health systems face numerous layers of regulatory oversight that can significantly slow down procurements. Requirements include HIPAA, accreditation standards, state licensing, anti-kickback laws, and CMS guidelines, to name a few. On the technology side alone, there are the HITECH Act, EHR incentive programs, FDA software regulations, FISMA, and interoperability standards. Vendors must undergo rigorous vetting and compliance processes, which can radically slow and often end a sales cycle. It’s crucial that sellers have a deep understanding of the regulatory and compliance issues that overlap with their products.

3. The Dominance of the EHR

Few industries have a software vendor that wields as much influence over internal decision-making as EHR vendors do in healthcare. These are giant, long-term contracts, and depending on where a health system is in its EHR implementation, dozens to hundreds of EHR employees can be embedded within the health system. Often, if you’re selling a software product, someone in the health system will consult their EHR vendor before even considering a conversation. These EHR vendors frequently have ancillary or directly competing products, and there’s a saying among health tech salespeople that the large EHR Account Managers are trained to respond to any new software procurement by saying, “We already do that.” And often, once you get approval to move ahead, a lengthy integration conversation must be waded through, both in terms of feasibility and timing.

4. Low Risk Tolerance

Given the life-and-death nature of their work, inherent low margins, litigious concerns, mostly not-for-profit structures, and heavy regulatory burdens, health systems rightfully prioritize avoiding mistakes over taking risks. This makes selling a new, unproven product quite challenging. They want free trials, extensive case studies, flexible contract terms, and numerous customer references. Their ROI standards are stringent, and they rely heavily on evidence-based data before making a decision. Also consultants are often brought into the process as well to help reduce risk and add rigor, adding further scrutiny and potentially misaligned incentives. A healthy cautiousness is a key part of the culture of a health system.

5. Health Systems Are (Mostly) Local

Over time, most industries will consolidate down to a few national or global players. This isn’t true in healthcare. There are 2 to 4 dominant health systems in each large metropolitan area in the country. There is some overlap via large regional players or national health systems, but not a ton; it’s a highly fragmented space. There are a bunch of very large health systems businesses scattered across the US. There are 5 US airlines whose annual revenue exceeds $5 billion. There are nearly 10 times as many US health systems that meet that threshold. These factors make selling more difficult for a variety of reasons. You don't have a consistent set of priorities across markets to sell into. There's often allegiance to local or regional vendors. It's hard to leverage competition because a New York health system doesn’t care much about that big account you won in Houston. More broadly, the lack of scale in these local health systems trims margins and makes budgets much tighter than they might be on a national scale. 

6. Supply & Demand Mismatch

Over the last decade, more than $100 billion in venture capital has poured into health tech startups, creating a vast supply of vendors that need to show a return on that capital by selling their products to health systems. The supply of products far exceeds the demand, leading to vendor overload for health systems. There’s a lot of noise out there that buyers are forced to wade through. Many health systems have responded by launching innovation teams, some with venture funds attached, which attract vendors to test products using health system staff and provide the fund with deal flow. These innovation teams often wield outsized influence, creating incentive misalignment and internal conflict. Even when these aren't in place, you can bet that the health system you're selling to is pretty sophisticated at sidestepping salespeople.

Starting Up & Scaling Up: Turning Duct Tape Into Steel

I heard a great metaphor for building companies the other day.

When you start a company, you're scrambling, trying to find your way, and building lots of new things. You find that when things work, the company is held together with duct tape. A large part of the job in making it into a great company is turning that duct tape into steel so that it can sustain itself without requiring superhero levels of daily effort. It's worth stepping back to understand this metaphor and how the priorities of an organization change over time.

The Duct Tape Days

The "duct tape" days are tough. You have to tackle a bunch of new and challenging things: raise money, convince great people to join you, figure out how to build something new, find product/market fit, implement it, and make customers happy—along with dozens of other little things you need to do to get a company off the ground.

The hardest part of this phase is that you're breaking ground on something new. All along the way, you know in the back of your mind that it might not actually work. This is stressful and hard to manage. However, the best part of this phase is the high level of alignment with your team. You probably don't have many customers (if any), you don't have a lot of employees, and everyone is mostly rowing in the same direction. The highest priority for any given employee at this stage is the same (or very close to the same) as the highest priority for the company. That's a great thing.

When you get past this initial phase and find that you have something that works and that people want, you quickly start to encounter a new set of problems. Your problems shift from building something new to scaling it. And the better the company performs, the more problems you will have. If you talk to people at startups, most (actually, all) will tell you it's a sh*t show. The faster the growth, the bigger the sh*t show.

The reason is that a company takes on more commitments as it grows—commitments to customers, investors, governments, auditors, partners, vendors, and one another via cross-functional teams. In the early days of scaling, these commitments grow linearly with the company. All of these commitments are new, and the workflows to manage them must be built from scratch. You probably expected some of them, but you'll also discover commitments you never imagined at the outset due to the compounding complexity that comes with scale.

Scaling Up

To manage these commitments effectively, the company will soon start to split into teams and add managers, new job titles, and levels. This structure becomes necessary because specialized groups can more effectively focus on specific areas, make faster decisions, enhance accountability, communicate more efficiently, and take ownership of the new workflows built around the growing set of commitments.

Pretty soon, you have a structure and a long list of commitments and priorities that looks something like this:

• Finance: Budget management, financial reporting, cash flow management, compliance and audits

• Sales: Revenue targets, customer acquisition, CRM management, territory or account management

• Operations: Customer onboarding, process optimization, logistics and fulfillment, vendor management

• Product: Product roadmap, feature development, quality assurance, user feedback integration

• Marketing: Brand management, lead generation, content creation, market research

• HR: Talent acquisition, employee onboarding, performance management, employee development

That's a lot of duct tape.

Quickly, the distance between the highest priority for any individual employee starts to diverge from the highest priority for the company, and that distance only continues to grow over time. You start to have lots of competing priorities and people rowing in different directions.

Competing priorities naturally lead to confusion and miscommunication among team members, resulting in unclear roles and conflicting work. This misalignment often causes inefficiencies and duplication of efforts, as teams may unknowingly work on similar tasks independently. Frustration can build, decreasing morale and motivation among employees who feel their efforts are not well aligned with company goals. Decisions get delayed, and things might feel like they’re standing still, leading to missed opportunities and slowed progress.

Tech people like to lovingly refer to this as "thrash."

Ultimately, this thrash can lead to poor performance and poor culture.

Turning Duct Tape Into Steel

Companies need to get ahead of all of this natural and inherent side effect of growth. They need to start turning the duct tape into steel by putting goals, processes, metrics, and communication systems in place to ensure a high-performance standard against all of these new commitments. They also need to align the work being done with the company’s strategy and financial objectives. Tools like vision and mission statements, OKRs, company values, cultural principles, financial targets, team offsites, company-wide meetings, cross-functional meetings, accountability and reporting systems, and management processes need to be implemented to solidify strong systems and prioritization around the company’s commitments.

There are multiple frameworks and playbooks on how to do this well. However, every company is different, and each should publish and regularly communicate its systems to their teams. Doing this well can become an enormous competitive advantage over time. I’ll write more over time about some of the things I’ve seen work well.

The Cadence

One of the most common and dangerous areas of misalignment in this phase—particularly for b2b companies—is between product, marketing, and sales. In consumer-focused companies, a natural glue pulls these teams together. Often, there’s no sales team, and large parts of marketing are embedded within the product (algorithm-based merchandising, social sharing features, cart abandonment targeting, etc.). This glue doesn’t exist or is far less sticky inside a b2b company. In b2b, these teams are often separated under different leaders but are the commercial lifeblood of the company. The product team builds things that create TAM, the marketing team builds a pipeline out of that TAM, and the sales team closes that pipeline pipeline. Without tight alignment between these three teams, things can quickly fall apart.

To help manage this, one framework I love and highly recommend borrowing and wanted to highlight today is "The Cadence: How to Operate a SaaS Startup" as described by David Sacks in his somewhat dated but enormously valuable Medium post.

In it, Sacks recommends putting sales and finance on a shared cadence and calendar and product and marketing on another shared cadence and calendar.

From the post on the sales and finance cadence:

"Every company runs on a fiscal year as an accounting requirement. This finance calendar should be synchronized with the sales calendar for reporting reasons. When the books close on a fiscal quarter, the numbers should reflect a complete quarter’s sales activity, not an incomplete mid-quarter picture. The leadership and board will have a much better sense of what’s happening in the business if sales plans are snapped to fiscal quarters."

And on the marketing and product cadence:

"When rapidly scaling startups don’t have effective product management, one of two things happens. First, they just ship sand. They polish and fix bugs and usability issues, but they don’t ship tentpole features, new products, and major releases. Or when they do, they end up going wildly over schedule. A product that was supposed to take one quarter will still be in development multiple quarters later. ‘V2s’ that were supposed to take a couple of quarters end up being years late and paralyze the company. This happens because the product was never scoped correctly. The quarterly discipline ensures that you do big stuff—rocks, not just sand—while scoping correctly."

"None of this is to say that code can’t be shipped weekly or even daily for code management reasons, but PM planning should revolve around quarterly or seasonal releases. Now that you know there will be a major quarterly product release, you can plan marketing around that. This is why marketing and product are on the same calendar. Startups are product-driven, and most news that the company puts out will feed off of new product releases."

While I’m a huge fan of this approach, the brilliance isn’t necessarily in the details but in two very important concepts:

1. The notion of internal teams making solid commitments to one another and

2. Tying that commitment to a calendar and firm timeline.

Getting teams to hold one another accountable and rely on each other with specific timelines is a giant step in turning duct tape into steel.

That said, I’ve historically found that product teams can sometimes be reluctant to commit to firm timelines, as they’re described in this framework. Product development processes from companies like Google or Spotify often prioritize agility and rapid iteration to respond to changing user preferences and market trends. This can cause them to favor less rigid timelines, which makes a shared calendar with the marketing team challenging to operationalize.

Conversely, companies like Oracle or SAP, which deal with large customer expectations, integration requirements, buying cycles, budget cycles, and program cycles, require fixed timelines and have more structured environments. You can almost view Google and Oracle as two sides of a spectrum.

The right approach to this spectrum isn’t to be philosophical (e.g., is Google better than Oracle?) but should be based on the unique characteristics and attributes of the buyer and the way the product is bought, sold, and implemented. Before adopting this approach, I’d encourage all commercially focused teams to dive deep on this point.

Ultimately, every company is built on a foundation of duct tape in the beginning—it’s messy, thrashy, and fragile, and it feels like it could fall apart at any moment. It’s important to understand how and why this happens so you can get ahead of its pitfalls. The companies that succeed are the ones that learn to replace duct tape with steel methodically and with intention. Time-based, cross-functional accountability is an incredibly valuable tool and tactic to manage through this crucial transition.

Asking Great Questions

Pushing oneself to ask great questions is extremely important. It forces you to think critically, accelerates your learning, improves decision-making, and helps build trusting relationships. Here are some things that have helped me ask better questions:

Tell yourself a story and use questions to fill in the gaps.

When I'm interviewing someone, being interviewed, or just having a conversation with a colleague or founder about a business problem, I typically take what the other person is saying and try to tell a story that makes sense in my mind. If someone is explaining a new company they'd like to start, I'm listening, but as I hear them talk, questions pop into my head about things I want to know more about or inconsistencies with my preconceptions. This is the trigger for most of the questions I ask, and it’s a useful way to generate dozens of questions in a single conversation.

Of course, you have to temper your questions and prioritize the most important ones so you don't sound like a nut. But forcing yourself to tell your own story based on what you're hearing—and fitting it into your worldview, or using it to learn something new and adjust your worldview—is a great way to ensure you're asking high-value questions.

Be ruthlessly authentic and ask “dumb” questions.

Have you ever noticed that whenever you ask a “dumb” question, it often turns out to be a great one? Dumb questions are wonderful. They typically simplify the topic, challenge assumptions, align the conversation at a high level, and enhance inclusivity. The trick is having the humility and courage to risk showing that you don’t know something that others do. This is definitely a risk worth taking. Try to never hesitate to do this. Be authentic. The best questions are about the things you really want to know. As someone once said, “Not knowing is not ignorance; not seeking to know is.”

Ask what people think, feel, or would do—not what they know.

I almost always find that opinions based on facts are way more interesting than simple facts. Instead of asking a job candidate, “What is our competitor's product strategy?” try asking, “What do you think of our competitor's product strategy?” Similarly, don’t ask your real estate broker, “How can I get a better price?” Instead, ask, “How would you go about getting a better price?”

This tactic encourages the person to really think about the answer and provides you with genuine insights rather than just reciting what they know. Also, give them time to think and express their full answer. Rushing them only leads to less interesting responses.