Why It's So Hard To Measure Healthcare Technology's Impact

With the thousands of healthcare technology companies that have raised hundreds of billions of dollars in venture capital and other financing over the last couple of decades to make healthcare more efficient, you'd think we'd be seeing the cost of healthcare delivery come down. Of course, this hasn't happened at all. A lot of people like to point to this chart, which shows that the price of things like TVs is dropping while the price of things like healthcare is going up.

This chart has always annoyed me a bit because it lacks so much of the nuance of each of these industries, but let's go with it for a second and understand why the cost of healthcare isn’t dropping like the cost of a television.

Clearly, televisions have become much cheaper and much better over the last several years. Many technological advances such as LCD, OLED, automated mass production, and labor cost reduction have brought down the cost of producing a TV. Add to that significant global competition, perfect pricing transparency, and the right incentives among consumers, and it’s no surprise that prices have dropped dramatically.

Let's apply that logic to healthcare. Imagine a health system that employs 500 primary care providers. They go out and buy AI software products that make their primary care providers, say, 100% more efficient. Because of technological advancement, it now costs the health system 50% less to supply a PCP appointment to a patient. That's great news. But how does that cost reduction actually show up and become visible to an end consumer?

Well, first of all, it's highly likely that rather than reducing costs, consumption would go up, and costs would stay the same if not increase. More appointments mean more patients, which means more downstream referrals to higher-cost services. The end consumer doesn't buy their own personal set of healthcare services like their own TV for their living room; they buy into a pooled group of patients under an insurance plan. If that pool increases their consumption of healthcare services, each person's premium increases. More healthcare consumption means higher insurance premiums. So, it's possible that technological advancements actually increase the cost of healthcare, which is good in some cases and not so great in others.

But put that aside, let's say demand and consumption stay the same, and the health system can deliver on that demand more efficiently because of the AI they've procured and that they have material savings to do something with. If the health system is for-profit, they might be inclined to return that money to shareholders without impacting the price for consumers. If the health system is nonprofit, they might just reinvest it back into upgrading a building or hiring more specialists, which would also keep prices flat. 

When a television company makes a technological advancement that allows it to make better TVs at a lower cost, it might also be inclined to invest in growth or return money to shareholders. However, because of intense competition and price transparency, it is also very likely they will pass those savings on to consumers, lowering the price of the TV for everyone. But health systems don't have the same incentives as the television company in several important ways:

• Demand for their services isn't elastic (people don't shop for PCPs on price). 

• Their prices are regulated and negotiated with payers and aren't dynamic like television's.

• The price actually being paid isn't clear to the patient, as they only pay a portion that depends on their specific health plan. 

I wrote about all of these issues in 15 Reasons Why Healthcare Has a Business Model Problem and Healthcare's Incentive Misalignment, so I won't rehash them here. 

The point of this post is that there are a ton of amazing healthcare tech companies that are reducing costs for providers, payers, and patients, improving the quality of life for clinicians, improving the quality of care across the board, and doing absolutely amazing things for the American healthcare ecosystem. But, for the reasons described above, these savings are unlikely to appear in high-level cost metrics. At least not until the incentives change.

Systems Thinking

Last week, I wrote about the importance of leaders creating cultures that embrace transparency and context. An equally important skill for all great leaders is high proficiency in systems thinking.

From Wikipedia:

“Systems thinking is a holistic approach to problem-solving that views issues as part of a larger, interconnected system, focusing on understanding the relationships, interactions, and interdependencies between different components within that system, rather than just analyzing individual parts in isolation; it prioritizes seeing how elements within a system influence each other to produce emergent behaviors.”

Most of the problems an executive needs to solve are complex and involve several components interacting with one another. People who are good at systems thinking can zoom out and grasp all of these components and empathize with all of these stakeholders, rationalize the complexity, and make good decisions. This is sort of the opposite of linear thinking, where an individual component is thought through without strongly considering interconnections with other components or the broader context of the problem being solved.

A simple example of this is creating a sales commission plan. You might want to pay employees when the deal signs immediately in their next paycheck. Reward the seller immediately, as it’s more likely to drive the sales behavior you want. This makes sense. Simple cause and effect. That’s linear thinking.

Systems thinking encourages you to step back, think more broadly, and ask lots of questions. Questions like: If we pay the seller on the signature, what if the implementation team can’t get the customer to onboard quickly, why would the seller help with that if they’ve already been paid? Who’s going to collect the money from the customer? If the seller isn’t incentivized to help, do we need a larger accounts receivable team? How much will that cost? What will delays in collection do to our working capital? What effect does that decrease in working capital have on our ability to invest in new products? Conversely, do we want salespeople worried about collections? We don’t pay other teams so quickly; what cultural effect might this have?

Systems thinkers can quickly gather all these points in their minds, consider them, and come up with a good recommendation. You know this skill when you see it. And you know when you don’t.

I think this skill comes naturally to some people, but it also can be learned, and it improves as you work on more complex problems. Linear thinking works well with tasks that follow a clear, sequential progression with predictable cause-and-effect relationships. So, if you’re following a clear set of instructions all day, you’re not going to get lots of experience with systems thinking. But if you’re managing a large organization in a multi-stakeholder, regulated, fast-changing, competitive business environment, then you better get good at it really quickly.

To get good at this, I’ve found it’s a lot about having high amounts of empathy, being curious, and asking good questions. As an example, if a competitor releases a new product, don’t just think about how you will position your product pitch against theirs. Think about the larger system. Think about your company’s unique strengths, your long-term plan, what you’re incentivizing, what the competitor’s product strategy is, how other competitors might react, how customers might react, and what advantages their focus on this particular thing might give you. Don’t just react to what you see, think about the systems that led to the thing you see.

As leaders, honing our systems thinking skills can set us apart in an increasingly complex and interconnected world where the ability to get our arms around complex problems and connect dots is more difficult (and critical) than ever.

High Context Companies

One of the more interesting insights in The Nvidia Way, the book on Nvidia’s rise under CEO Jensen Huang, is his use of the weekly Top 5 Things emails (T5Ts). In these emails, employees across the company send him their top five updates about their work, observations, and priorities, providing Huang with an unfiltered view of what’s happening. The book notes that he pours a glass of scotch every Sunday night and reads hundreds of them. 

A while back, a mentor explained to me that one of the most important attributes of a leader is their ability to see the company through the eyes of the people who aren’t in the room. If you can’t do this well, you’ll lose the trust of your team, and their engagement will fall. And you’ll probably make a lot of bad decisions. Tools like the T5T and things like skip-level meetings, mini town halls with Q&A, engagement surveys, and insisting on a culture of transparency and openness where people feel comfortable telling hard truths can help leaders get their arms around the problems and opportunities on the ground and ensure they’re seeing the world accurately.

This goes the other way as well. I’ve written before about how important it is for employees to understand the context around decisions made at high levels. I once had a job where I wasn’t on the senior management team, but I had a lot of access to the senior management team. I’d often hear employees at lower levels being very critical of decisions being made at the top. I remember thinking, “These people just don’t have the context; I wish they could somehow get it...” It’s crucial that leaders take the time to give their teams the context around their decisions. The aspiration should be that the lowest-level employee would make the same decision as the highest-level employee because they’re operating with the same information and context.

The key to all of this is that for anyone to make good decisions, they must operate with a strong understanding of the truth — of what’s actually happening. You could probably directly measure an executive's success by how capable they are at this because it’s literally the only way they can make good decisions. This obviously scales to the company, too. I’d bet you could tightly correlate the quality of shared context across an organization directly with its financial success.

It sure is working for Nvidia.

Return on Capital Vs. Cost Of Capital

A company's value is equal to the present value of the cash investors can take out of it over time. Investors want to put their money into things that will provide them with lots of future cash flows. Technically speaking, they want to put money in companies whose return on capital exceeds their cost of capital. For an equity investment, the cost of capital for a company is the return that the investor expects; for a debt investment, the cost of capital is the interest rate the company has to pay.

Early-stage technology companies aren’t yet generating cash for investors. They typically lose money as they build up a set of products that can deliver cash back to shareholders at some point in the future. In the context of a new technology company and how an investor thinks about these financial returns, you could see two phases:

Phase 1: Building something that can deliver cash. Once a new venture has found product/market fit, it starts growing quickly. If you generate $1,000 in revenue in your first year, it's not that difficult to 10x that growth and get to $10,000 the next year. In this phase, companies aren't thinking about delivering cash back to investors; they're using all of their capital to invest in the company to grow their revenue and market share so that someday they have something that can deliver cash returns. In this phase, the cost of capital (the return the investor expects) exceeds the return on capital because there aren’t any returns yet. Investors are ok with this because they’re betting on big returns that will happen in the future.

This is why SaaS companies experiencing high growth don’t really worry too much about profits. They worry about growth so that they know they’re building something big, and they worry about unit economics (the profitability of providing a single unit of their product to a customer versus the cost of providing that unit). So, the high-growth SaaS company is happy to be unprofitable and burning through investor capital as long as it knows that it’s acquiring customers that will generate profits in the long term. So when the company has saturated the market and growth has slowed, they can pull back on sales & marketing expenses and R&D investments, and the unit economics then show up in the actual profitability of the company through previously acquired customers. So, this type of company isn’t yet delivering cash; it’s building something that will someday be able to deliver cash.

Phase 2: Delivering cash. Eventually, growth slows as the market saturates, and it gets harder to grow quickly on a larger base of revenue. Companies then find that continuing to invest investor capital and operating profits back into the business is no longer a good idea. That is, they can’t generate a return on capital that is higher than the cost of that capital. That’s when companies slow down their investments and start returning some cash to shareholders through dividends, share buybacks, or paying down debt, such that the investor can go invest in things that are more likely to exceed their expectations for an investment return.

The reason I’m going through all of this context is that one of the hardest things for a company to do, especially a technology company, is to identify the moment when it’s better to start returning cash to shareholders than it is to keep investing in new growth. There’s a saying that “profitable companies that have lots of cash have run out of ideas.” Leaders in companies don’t want to appear like they don’t have new ideas or that they can’t successfully execute them. And not investing in new stuff and just trying to get more profitable to pay out dividends isn’t nearly as fun as deciding to build a self-driving car or placing some other type of big bet. It’s even harder in today’s environment, where so many companies raised capital when growth multiples were super high. Case in point: ServiceTitan, which went public a few weeks ago, priced its IPO share price well below its last round of venture capital financing in 2021. Telling your investors that you think you’ve saturated growth when the company is likely valued less than it was when they invested is a really hard thing to do.

So, hundreds of companies have found themselves between a rock and a hard place. Growth has stalled as they've saturated their core market. But they’re a long way from getting above their last valuation (or “mark” in VC parlance), so they’re continuing to try to grow back into that valuation and, in some cases, destroying shareholder value in the process, where the investments they’re making will not exceed their cost of capital — especially because their cost of capital is now higher as their valuation has dropped. Some companies are betting too aggressively on their ability to produce high growth and are also speculating that if they do deliver on that high growth, the market will value it as it did in previous years. The median public SaaS company is now valued at 6x revenue, a long way from the 20x to 30x multiples of 2021. Getting a company’s valuation above its last mark is a a great thing to try to do, but destructive if done unprofitably.

I’ve simplified this issue a bit, as there are other options besides growing and returning cash. Companies can also invest in efficiency, reposition themselves strategically, and make profitable acquisitions. But all of this comes back to this super important topic of knowing who you are, knowing what’s best for your company right now, and having the courage to pursue that direction. A dollar is a dollar, whether invested in new growth or given back to shareholders as a dividend or share buyback. One approach is not inherently better than the other. As a responsible capital allocator, the key is knowing which one is better for you.

Greatest Strength = Greatest Weakness

Early in my career, managers were traditionally expected to tell their employees their weaknesses and how to improve them. Then, they would check in every few months to discuss their progress. It took me a long time to realize that this was a mistake. Over and over, in my career, I've found that a high-performing person's weaknesses are what actually make them great at what they're great at. Identifying how an individual’s weaknesses actually support their strength can you give a lot of insight into how to best interact with and manage that person.

• People who are perfectionists and demand extremely high work quality spend too much time on unimportant things and have trouble prioritizing.

• People who are great strategic thinkers struggle with on-the-ground execution plans. 

• People who are extremely adaptable and can respond quickly to challenges struggle with focus and stability. 

• People who are really optimistic ignore potential obstacles and can be unprepared for setbacks. 

• People who are highly competitive can create friction in their team and struggle with collaboration.

Hire people who are the best in the world at what they do and let them run after that thing. Spending time having them focus on improving something that they don't do well and probably don't enjoy doing is a low ROI effort. Of course, they should know their weaknesses and how they might impact others and should develop the flexibility and self-awareness to know when to dial them back or complement them with other traits. But doubling down on a high performer’s strengths will lead to much better outcomes and a much happier team.

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 & 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.

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.

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.

Tradeoffs

Over the years, I've found that leaders (and people in general) are often resistant to facing the tradeoffs that come with the difficult decisions they make.

You see this a lot with public policy. A simple example is governments mandating that tech companies implement encryption to protect user data and sensitive information. On the surface, this is a great thing. However, several tradeoffs come with encrypted data, the most noteworthy being that law enforcement can't access information related to criminal activities by users or the company itself. So regulators will also ask companies to encrypt their data and provide a back door so it can be accessed when required by law. But, of course, you don't have encryption if you have a back door. Regulators are often unwilling to face the natural tradeoffs associated with the regulations they create.

Similarly, I recently talked with a small group about Chapter 11 bankruptcy (the legal process that allows a business to reorganize its debts while continuing to operate). Some were arguing that it shouldn't be allowed. If someone is going to run their company into the ground, they shouldn't be allowed to have a court step in and save them. At first glance, this also makes sense. So perhaps we should do away with Chapter 11 bankruptcy? Maybe, but only as long as we're willing to face the painful tradeoffs.

With Chapter 11, a business leader is incentivized to raise their hand and ask for help before they become completely insolvent and run out of cash so that debtholders can salvage at least some of their money. Without it, if a leader knows there's no way out, they'll keep the company going until it’s down to its last dollar, hoping to survive somehow, meaning debtholders get nothing. Ironically, Chapter 11 protects debtholders. Further, what would happen to innovation in America if founders of companies knew that if they failed, they were done for good? What would that do to the amount of risk entrepreneurs take? How many companies never would've been founded? There's a reason you see a lot more innovation come out of countries that provide some form of protection to risk-taking inventors. 

Of course, one of the most common tradeoffs in business is deciding how much to invest in growth versus how much to expand profit margins. If a leader asks their board, the advice is very often to do both. Said differently, ignore the tradeoffs.

A large part of leadership is making difficult decisions, which are typically just a set of tradeoffs that must be managed. Great leaders know that it’s not just about what you gain; it’s also about surfacing and dealing with downstream consequences and what you’re willing to lose.

A Finance Deep Dive

A couple of weeks ago, I completed a Finance for Senior Executives course at Harvard Business School. I took the course because, while I feel like I have a pretty good grasp of finance from business school and work experience, I wanted to refresh my brain on the fundamentals and go a bit deeper than I've been able to over the last several years. The course was excellent, and I highly recommend it for operating executives who find themselves in a similar spot. The content was designed for senior executives who don't work directly in the finance function. The course had a virtual portion followed by four days of in-person living and studying on the HBS campus. The class was grounded in the case study method, with 13 real-life case studies (including a great one where we had to try to rationalize Peloton's stock price in the Summer of 2019...). The class was filled with an incredible group of intelligent, thoughtful, energetic, and self-motivated students who were really fun and inspiring to get to know — 89 students from 21 countries. Just a great group. The syllabus covered six primary topics:

• Measuring Performance and Financial Ratios

• Discounted Cash Flow 

• Valuation

• Capital Structure and Leverage

• Mergers, Distress, and Recapitalizations

• Capital Allocation and Pursuing Margin and Growth

As we went through the coursework, I made a note of some of the more insightful reminders, ideas, concepts, and topics that stuck with me. I thought I'd share some of them here:

1/ The primary job of finance is to ensure that the company doesn't run out of cash and makes good financial investments. Watching working capital (current assets - current liabilities) closely is crucial — lots of very profitable companies run out of cash. I’ve seen this quickly become an issue for tech companies that don’t hold inventory and have taken their eye off working capital, as well as tech enabled healthcare service companies that have a revenue cycle lag.

2/ Terminal value of a company (its value in perpetuity) should be used carefully, as there's never really a company that runs forever. That said, over the long term, the discount rate will balance this and make the calculation more reasonable. The terminal value of a company should be calculated after growth and margin have stabilized.

3/ Net present value measures the dollar value an investment adds or subtracts by comparing the present value of cash inflows and outflows. Internal rate of return calculates the percentage rate of return that makes net present value zero.

4/ There's really no such thing as a "good" growth rate or margin or financial ratio. It all depends on the context and the particular situation. It's sort of like a size 10 shoe. Does it fit? Well, it depends. 

5/ You should care a lot more about the market value of a company than the book value of a company as that’s the value that investors will pay assign to the firm, though the latter is a lot easier to calculate and make sense of.

6/ Bad economics in an industry almost always beats great management over the long term. 

7/ Don't discount the fact that your debtholders are important stakeholders and investors. While interest payments cap their upside, they are the first investors to get paid in a liquidation, and returning their capital and providing them with interest payments drives substantial value. Too often, we only consider equity holders when we think about enterprise value creation.

8/ A good formula to memorize is valuing a company using its free cash flow projections. As I've written here many times, the value of a company is the present value of the discounted free cash flow you can take out of it. Free cash flow can be calculated using the balance sheet and income statement with the following calculation: EBIAT (earnings before interest after taxes) + depreciation - cap expenditures - change in working capital. It's not about memorizing the formula; it's about understanding how the balance sheet and income statement interact and how to use them to calculate the cash flows a company will generate.

9/ Debt is a government-subsidized form of capital. The tax deduction on interest is the major value in financing an investment with debt over equity. This is really meaningful. Obviously, it is less relevant for startups that still need to produce profits. 

10/ The "irrelevance hypothesis" says that in an ideal world with no market imperfections, the dividend policy of a company is irrelevant to its overall valuation because shareholders can create their own homemade dividends by selling their shares. Of course, real-life market imperfections always need to be logically applied when creating a dividend policy. 

11/ Operating leverage is an important metric to watch over the long term. High operating leverage means that small changes in sales lead to disproportionate increases in operating profit because fixed costs remain constant while revenue increases. 

12/ Businesses can be placed on a spectrum from "high tech," which are high growth/low profit, to "cigar butt" businesses which are low to no growth/high profit (companies that only have a few puffs left). There’s nothing thing wrong with a company that isn’t growing but is throwing off cash and not all companies need to stay in business forever. It's important to understand where a company is on this spectrum to guide where to place capital — invest in growth, return to shareholders, or pay down debt. 

13/ Dividend payments are effectively the same as a corresponding investment in growth when the dollars generated and value creation are the same (the only relevant difference is that in one scenario, the money is in the investor's pocket versus the company's pocket). But the value is the same. This is a good reframing, similar to the importance of returning capital to debtholders. Capital is capital regardless of whether the investor holds it in your company or puts it in an index fund.

14/ Generally, markets value growth increases over margin increases because growth compounds on itself. The exception is low-margin businesses. You'll get more upside there from growth. All should be calculated through discounted cash flow analysis.

15/ High discount rates favor high-margin businesses, and low discount rates favor high-growth businesses. 

16/ Detailed discounted cash flow rates often aren’t used on a practical basis inside of companies. The reason, generally, is that there are often more ideas that exceed the discount rate hurdle than can be executed. That said, it’s crucial that all leaders understand discounted cash flow, NPV, and IRR.

I'm really glad I took the class. I'll look into other courses like this to deepen my knowledge in areas where I haven’t gone as deep as I’d like in recent years.