Fintech 2025: The Next Wave

When I first joined Greylock at the end of 2011, Fintech wasn’t even a word that was commonly used in the venture capital community. Less than a decade later, however, Fintech has become almost ubiquitous. The category has not only proven that it can generate real revenues and scale, but also that it can create a large number of multi-billion dollar companies.

Unfortunately, when you are looking at seed stage opportunities, you have to think clearly about markets where there is the potential to build new multi-billion dollar product & companies.

When the bubble burst in 2000-2, there was a lot of thought put into what had worked and what hadn’t worked with Web 1.0, and those insights formed the basis of the next wave of software companies (Web 2.0 / Social). Some of those same issues have plagued Fintech 1.0, and may instruct how to think about Fintech 2.0.

As 2019 drew to a close, I took the opportunity to spend some time thinking about exciting new opportunities in consumer fintech. These continue to be areas that I’m investing against both as an angel and as a founder.

Beyond Millennials

For the last decade, a vast majority of consumer fintech startups have focused on millennial customers. This really isn’t surprising because the traditional financial services industry is so heavily invested in their older customers. By the numbers, households tend to build income and assets as they age, and the incumbents have spent decades servicing this customer base.

Young people, on the other hand, were the perfect market for new, unproven products and services. Young people are less tied to existing brands and services, more likely to be technophilic, and have simpler financial needs.

As we enter the next decade, however, consumer acceptance of new financial products & services will continue to grow, leaving new demographics open to new products & services. This would have been true regardless, but it seems clear that the COVID-19 pandemic has accelerated this opportunity.

These customer segments will be more competitive, but also potentially more valuable, as they collectively are much larger than the millennial market.

Single Player to Multiplayer

Traditional financial products & services are single player, which makes sense since people tend to expect a high degree of privacy around their finances, and products built for individuals are much simpler to design, market, and activate.

However, many new fintech services are built around a subscription-model, where three numbers tend to dominate: acquisition costs, average revenue per user, and churn rate. The last, of course, is a heavy determinate of lifetime value.

Multiplayer products & services have a number of advantages. Multiplayer products are inherently viral, pulling more people into the system and lowering average acquisition costs. More importantly, multiplayer products are fundamentally stickier, leading to lower churn rates and higher lifetime values.

One of the big shifts from Web 1.0 to Web 2.0 was designing products & services to be intrinsically multiplayer. This was one of the fundamental differences between the design of LinkedIn (Web 2.0) and Monster.com (Web 1.0).

Novel Products & Services

When web development began in earnest in the 1990s, most initial product concepts were just moving existing products & services online. Mail order catalogs already existed, but we put them online. Yellow pages already existed, but we put them online. There were a few novel products (eBay), but for the most part, we collectively just moved a lot of products into the cloud, with all the advantages that global reach & distribution brought.

Fintech 1.0 has also mostly replicated existing products, put them on modern technology platforms, and made them broadly available to customers (like young adults) who have been mostly underserved.

However, one of the great opportunities in Fintech long-term is leveraging technology platforms and distribution to create products & services that were not viable, or even possible, in the physical world. With Web 2.0, we saw a large number of products & services that just couldn’t have existed offline.

2020 Examples

Not surprisingly, ambitious founders have already started building products & services along these new dimensions.

Carefull is a novel service that connects Millennial & Gen X adults with the finances of their aging parents. Once connected, it provides peace of mind for customers that if anything unexpected happens with their parents’ or grandparents’ finances, they will be alerted.

PaceIt, led by Prof. Shlomo Benartzi, is working to tackle the problem of retirement income directly by building a service designed with retirees (or near retirees) in mind. This is one of the most challenging and potentially valuable financial services, and PaceIt believes they can deliver a highly differentiated service based on sound insights from behavioral economics.

Braid is a novel debit card designed from the ground-up for households and small groups (e.g. roommates), providing a standard way to transparently share expenses between groups of people.

Pillar Life is a digital platform that helps people protect and care for their aging loved ones. Pillar replaces outdated & messy physical files with a secure online vault where you can easily store, organize, and share all your family’s most important information like financial accounts, legal documents, medical records, and more.

2020 may have been a terrible year on most dimensions, but as an angel investor for over nine years, it turned out to be my most active one yet. Hopefully, this bodes well for the future of Fintech, and for the financial products & services we’ll all be able to enjoy in the coming years.

 

How Will You Measure Your Life?

Source: Deseret News, Jan 24, 2020

On January 23, 2020, Clayton Christensen passed away at the age of 67.

I found out about his passing during my commute home from work on Friday, and it left me reflecting deeply on my experiences with Clay. I enrolled in his class back in 2000 at HBS, and was fortunate enough to have him agree to be an advisor to me on an independent project on the topic of disruption. Over the years, when I would visit HBS for recruiting or for a case study, I would always try to stop by to see him. Ever gracious and thoughtful, he may have been the most influential professor in my life.

There have been some wonderful pieces written about Clay in the past couple of days, mostly reflecting on his impact on management theory or his lifelong dedication to his family and his church. The list of his accomplishments is appropriately long. However, there are a few personal details I’d like to add to the story.

First Meeting

Many people are familiar with Clay’s work on innovation and disruption, made famous by his 1997 book, The Innovators Dilemma. It’s always shocking to me when I meet people in Silicon Valley who haven’t read it – that’s how fundamental it has been in shaping my thinking about business & strategy.

However, the professor I met at Harvard twenty years ago didn’t talk about innovation, disruption or how to build a successful business. He talked about the morality of business, the ethics of leadership and about his own personal journey.

Clay was a warm and friendly person, but when I first saw in him walk into our class, it was hard to ignore just how tall he was. At Harvard, the third row of seating is known as the “Power Deck” because when seated you are eye-level with the professor. I used to joke that in Clay’s class, it was the fourth row that was the Power Deck.

In some ways, Clay’s height made his approachability and humility even more surprising and authentic.

Clay’s class was supposed to be about strategy, but he opened his first lecture with a discussion of people. He spoke about how we spend most of the hours of our adult lives  at work, and how impactful those hours are on the emotional wellbeing of people even outside of work. He asked us to think about great managers we’d had in the past who supported us and gave us energy, and terrible managers who had drained us of it.

And that’s when he told us that he believed that being a great manager was one of great moral responsibility, because your leadership would either make the people who worked for you miserable, or they could bring those people joy & accomplishment.

When Clay talked about leadership, he talked about it with a clarity and conviction that is rare. To this day, when I take on a new leadership position, I talk to my teams about the responsibility I feel to them based on Clay’s words.

Professional Journey

Clay’s professional journey also resonated with me. Most people don’t know that Clay himself was a founder, starting a company focused on advanced ceramics back in the 1980s material science boom. It’s a bit of personal trivia, but my first love at Stanford  wasn’t Computer Science. It was the Introduction to Material Science that made me decide to major in Engineering.

But after that experience, Clay had decided to go back to school. It is unusual for an MBA to go back to get a PhD, but he went back because he wanted to study management and teach. His passion for a more rigorous framework on how managers make decisions led him to the insights that became The Innovator’s Dilemma, and the career that we all know him for. His fundamental belief that managers were intelligent and capable led him to frame an incredible problem: how do large companies continue to fail when they have access to so many smart people and almost unlimited strategic resources?

However, his choice wasn’t purely motivated by academic or professional interest. He talked openly about his family, his wife and his children, and the life he wanted to create for them. He talked about his faith, and how he wanted to be judged in the end.

Not everyone who is religious leads an exemplary life, but for Clay, his faith seemed to amplify and enforce his ethical rigor. In his later work, he would argue that it was easier to hold the line ethically 100% of the time than 98% of the time, because one compromise leads to another, then another.

How Will You Measure Your Life?

Over the years, when I would visit Clay at HBS, he was always warm and encouraging. We would discuss each career move I made: eBay, LinkedIn, Greylock, Wealthfront. The clarity of his strategic thinking was always a gift, and his willingness to engage and debate when we disagreed was always a bit surprising to me. But Clay loved to sharpen his thinking, and had seemingly no ego tied to defending ideas or business strategies. He just loved finding more insight; a twinkle in his eye in the pursuit of a clearer glimpse of the truth. I always left of our conversations feeling amplified by both his support and his energy.

In 2010, Clay published a piece based on these ideas that became a book by the same name, How Will You Measure Your Life.  It is worth reading, and even re-reading.

I have a pretty clear idea of how my ideas have generated enormous revenue for companies that have used my research; I know I’ve had a substantial impact. But as I’ve confronted this disease, it’s been interesting to see how unimportant that impact is to me now. I’ve concluded that the metric by which God will assess my life isn’t dollars but the individual people whose lives I’ve touched.

I think that’s the way it will work for us all. Don’t worry about the level of individual prominence you have achieved; worry about the individuals you have helped become better people. This is my final recommendation: Think about the metric by which your life will be judged, and make a resolution to live every day so that in the end, your life will be judged a success.

Rest in Peace, Clay.

Three Types of Risk: Making Decisions in the Face of Uncertainty

Image result for risk

One of the fond memories I have of my first two years at LinkedIn was coming into the office almost every Sunday to spend a couple of hours with Reid Hoffman.

Our conversations covered a wide range of topics, but the time ensured that we were fully aligned on the strategy of the company and the priorities we were pursuing.

One of the topics that I was most fond of discussing was the nature of risk, and how to best lead teams when facing the various types of risk that are commonplace at hypergrowth startups.

Here, Reid never varied, and I quickly adopted his framework as my own. In the end, most of our productive discussion involved deciding which of three types of risk a particular decision involved.

Three Types of Risk

Categorizing the type of risk you face is incredibly useful in helping teams understand how much effort and consideration to spending on making various types of decision in the face of uncertainty.

For hypergrowth startups, risk can be categorized as one of the following types:

  1. Fatal Risk
  2. Painful Risk
  3. Embarrassment Risk

Fatal risks are true bet-the-company issues. They are not that common, but they deserve clarity and focus. If you get the answer wrong here, the company is dead. These risks are unavoidable in early-stage startups, but as companies grow they become more and more uncommon. In fact, most large companies lose the ability or even recognition of these type of risks as they age.

Painful risks involve decisions that have significant repercussions if they go the wrong way. You might miss a key goal, or lose key people. They are recoverable, but there are real ramifications to getting the answer wrong.

Embarrassment risks have no significant impact if they are missed. All that is necessary is to acknowledge the mistake, change course, and move on.

Embarrassment risks are particularly difficult for smart & ambitious people, largely due to insecurity and ego. People want to be perceived as intelligent and successful, and they incorrectly map that to always being correct.

Unfortunately, most people at hypergrowth startups spend far too much time debating embarrassment risk, and they don’t take enough painful risks.

What About Type 1 & Type 2 Decisions?

Jeff Bezos has more recently popularized a different framework, based on two types of decision. This framework is often described in the context of the decision to move forward with Amazon Prime, which at the time was mostly a judgment call versus a data-driven decision.

In his framework:

  • Type 1 decisions are irreversible. Spend time on them.
  • Type 2 decisions are reversible, like walking through a door. Make them quickly and move on.

Overall, this framework is helpful. Thinking through the reversibility of decisions helps prioritize speed vs. perfection. When it comes to execution, the perfect truly can be the enemy of the good enough.

The problem is that almost every decision at a company is reversible, so it tends to not provide that much insight into why some risks feel harder to take than others.

Lessons in Execution

In some ways, you could describe painful risk & embarrassment risk as two sub-categories of Type 2 decisions. The speed of execution depends on taking these type 2 decisions quickly and aggressively, framing them as risk, and clearly articulating what the team will do if it doesn’t play out as expected.

Leaders need to embody this type of decision making, to give permission to newer employees to take risks and communicate their decision making effectively.

Otherwise, a spiral of low expectations and low-risk options will quickly put you in a vice when faced with more aggressive competitors. Worse, you won’t be taking enough shots on goal to learn fast enough to have high odds of success.

Large companies trend towards this problem because decisions become increasingly about the personal positioning of individuals for their own advancement, rather than optimizing for the best results for the company or their customers.

Ironically, taking painful risks may be the only way to set yourself up for exceptional outcomes.

The next time you see your team facing a decision in the face of uncertainty, try to quickly agree on what type of risk you are facing and what type of decision you are making. In most cases, you’ll be able to make decisions more quickly and save your time for the rare, but very real, risks that you have to navigate with your product and your business.

 

The Future of Drone Safety

Every time I go to the CODE Conference, I learn something new. There is something about watching some of the most prominent technology executives and founders responding to questions from talented journalists that gets me thinking.

Four years ago, I wrote about the transition technology CEOs needed to make from economics to politics. Coming back from this year’s gathering, there  is no question in my mind that this insight turned out to be true. Responsibility was a significant theme this year. As the technology industry continues to grow and mature,  more and more people are looking to investors and technology leaders to think ahead about potential issues that will happen when their creations become ubiquitous.

It got me thinking about drones.

The Problem with Drones

The FAA projects that the number of drones will reach 7 million in just the US alone by 2020. The growth rates for both consumer and commercial drones continue to grow at a rapid rate. The FAA estimates that there will be over 3.5 million hobbyist drones in the US by 2012.

Over the past few years, I’ve made a few investments in startups in the drone space. But until last year, I hadn’t given significant consideration to all of the safety issues around drones, particularly as they fly over large crowds or critical infrastructure.

The problem is fairly simple. Large venues, like sports stadiums, and critical infrastructure are largely defenseless against drones. Whether it’s a music festival, a weekend football game or anything of that sort, most people don’t realize that event managers really have no solution to protect a crowd. Whether accidental or intentional, there is a real risk that a malfunction or crash could harm people.

The Need for Active Measures

Long term, of course, we can imagine a world where drones can be programmed to avoid these spaces, (Airmap is a great example of a company making this happen). However, We can’t just assume or depend on this to be universally true – that risks the mistake of being overly idealistic. There needs to be an active solution to protect critical areas.

There are a number of companies working on solutions that involve intercepting and disabling drones that enter space that needs to be protected. In fact, there are solutions like drone on drone capture (with nets) 🕷, projectile solutions (shoot it down) 🔫, even flamethrowers! 🔥

Unfortunately, these kinetic measures make little sense in cases where the drones are flying over areas that need protection. If the concern is a drone crashing into a crowd or important infrastructure, these solutions run significant additional risk of the drone or pieces of the drone causing damage on impact. While there is definitely a market for kinetic solutions in the military and related markets, but it seems like a bad fit for the majority of the simple but real threats out there.

A Software-Based Solution for Drone Protection

Last year, as the co-chairman of ICON, I had the good fortune to meet Gilad Sahar, the co-founder and CEO of Convexum. With the unique insight that comes from military experience with both the costs & benefits of active solutions, they have developed a non-violent, software-based active measure to help automate perimeter protection from drones.

The concept is fairly simple.

Convexum has developed a device that allows companies & governments to detect when a drone is entering a restricted space, take control of the drone, and land it safely. A cloud-based service ensures that all Convexum devices have up-to-date signatures for known drones.

Initially, they are seeing significant demand for this solution around critical infrastructure, like energy development, and sporting venues. Long term, I can easily imagine a future where a non-violent solution for drone protection would be highly desirable anywhere we don’t want to bear the safety risk (like schools).

Working with Government

Europe has already provided a clear path for companies and government entities to receive the permits & exemptions needed to deploy this type of solution. (In fact, Enel has already deployed a solution to protect power plants.) Congress & Senate debating this now in the US, but seems to be one of the few remaining areas of true bi-partisan alignment.

I’ve personally been so impressed with Gilad & Convexum, I’ve decided to help them by becoming an advisor to the company.

Let’s hope this is part of an increasing pattern of entrepreneurs and investors thinking ahead about safety and regulation, and supporting technologies early that can help solve these eventual problems.

 

 

Every Function Has a Superpower. What’s Yours?

Over the course of my career, I’ve been fortunate enough to work in a variety of different functions.  No matter whether it is engineering, design, product, or service, every role has its own unique set of requirements and challenges.

Maybe that’s why I have always believed strongly that software is a team sport. If you want to build exceptional products, you have to find a way to harness the unique and diverse viewpoints of a team of professionals across a wide variety of functions.

Unfortunately, even at great companies, there is a repeated pattern where people in some functions feel disempowered. This doesn’t need to be the case.

Every function has a superpower. Make sure you know what yours is.

Every Function Has Value

Hypergrowth software companies are relentless in their pursuit of efficiency. Everyone who joins a new company dreams of building something new, something better than the companies that came before it. As a result, startups are always questioning the breakdown of functions in older, more established companies. In addition, resources are always tight, as companies stretch to make every dollar of funding count.

Unfortunately, this also means that many startups repeat the same mistakes over and over again when it comes to recognizing the value of different functions in a modern software company. This can be compounded by having a founding team or early employees who have never worked in those functions before.

You don’t really know a function until you know someone who is exceptional at it.

Inevitably, most startups, even when they have grown to hundreds of people, have gaps in their understanding and appreciation of some functions.

Avoiding Decision By Committee

Besides the lumpy build-out of different functions at fast-growing companies, the need for fast decision making also tends to bias the product process.

Great companies tend to be opinionated in their decision-making process around product, and those processes can vary significantly. Some companies may overweight decisions from engineering, others might look to a strong product function. There are companies that are largely sales-driven, and others that rely on general managers. There are companies where decision-making is hierarchical, deferring to the CEO or founder for key product calls, and others where decision-making is distributed broadly to the teams.

This isn’t surprising, however, because there is a direct tension at companies between the speed of execution and the exhaustiveness of a process. As a result, almost every product-centric company seeks to avoid “decision by committee” by assigning decision responsibility to a function or a hierarchy.

No matter what system exists, there are always people and functions that feel disempowered by the process.

Know Your Superpower

While you may not be the one to make the final product decision, it is a mistake to feel disempowered. Your function has unique value, and you can dramatically shape any product decision through your efforts.

The key is to know your superpower.

Every function has one. Here are just a few examples:

  • Engineering. Every engineer has the ability to take what is and isn’t possible off the table. I’ve seen product strategy discussions completely changed in a single weekend by engineers building something that no one else had even considered. The power to create is an awesome one, and the best engineers use this power to open the eyes of their teammates to what can be accomplished.
  • Design. Most people can’t visualize the different options that are possible around a given feature or product, and design has the power to reshape discussions completely based on visualization. Design can eliminate theoretical options, define the choices available, and most importantly trigger a deep, emotional response to certain choices in decision makers.
  • Product. At some companies, product managers have procedural power to make decisions. However, the most effective product managers use their power to frame the discussion with strategy and metrics to help drive decisions. The power to define the framework for a decision often is the power to control the decision.
  • Client Service. If you spend your day talking to real customers about real problems every day, you have amazing power to bring issues to the fore. Sometimes a decision is swayed by the scale of the problem, other times by the severity. Never underestimate the power of narrative, driven by real customer stories, to shape decisions on product and prioritization.

Every function has a superpower and everyone has the ability to do the extra work necessary to tap the unique capabilities and resources of their function to use that power to shape decisions. It requires work, but no matter what your function or role is, you can heavily influence critical decisions.

You just need to find your superpower.

 

Solve the Product Maze Backwards

As the father of young children, I can tell you that there is a special place in my heart for restaurants that provide puzzles and crayons for small children to pass the time.

On a recent trip out to The Counter in Mountain View, Jordan (who is 8)  was really struggling with a large maze puzzle on one of these activity sheets. It was a fairly large maze, and he was frustrated by his inability to see the dead ends ahead, forcing him to retrace his somewhat tortured crayon path.

I told him to try to solve the maze backwards.

As you can probably guess, he began at the end, and was able  to find a path back to the beginning in just a few seconds . He was delighted, and a bit surprised, to see how simple the puzzle looked like from a different perspective.

Surprisingly, I find that both entrepreneurs & product leaders miss this important lesson when evaluating ideas for either their company or their products.

Three Questions in Product Prioritization

In my experience, there are three common questions that often come up when product features are being debated:

  1. Should we build this?
  2. When should we build this?
  3. How should should we build this?

Unfortunately, even highly talented teams can become  get bogged down in debate and uncertainty when all of these questions become entangled. As engineers & designers are professionally trained to answer the question of “How,” the worst debates tend to happen around the questions of  “Should” and “When.”

Too often, when debating what feature to work on next, debates around timing quickly devolve into debates about whether the feature is needed at all.

Solving the maze backwards does a fantastic job of disentangling these two questions. Simply asking the question of “If we are successful, will we have this feature in 3 years?” tends to illuminate whether the debate is about “Should” or “When.”

If the answer is yes, you will have that feature, then the question is simple. You are just debating priority.

Avoid the Local Maximum

One of the well known issues with iterative processes for delivering product features is the “local maximum” problem.

The assumption is that where ever you start with your product, your team keeps working on improvements. Each improvement is measured to ensure it is “better” than the product before the change. However, you can reach a point where every change you make hurts the metrics that you measure. The fear is that there is a better version of your product (the absolute maximum), but it requires a change bigger than you can get to from the current design.

It’s called a local maximum problem because of the similarity to the concept in mathematics when you are traveling along the curve. From the local maximum, every move is down, even though the curve ends up higher eventually.

Solving the maze backwards can help.

By asking the simple question about whether or not your product in the far future has a given capability, it can unblock your thinking about what leaps and changes will be necessary. Whether the limitations are in technical architecture or product design, clarity on your long term vision can help your team visualize a future not trapped by their current constraints.

Too often, the real limitation is not related to either technical or design constraints, but rather a lack of clarity and imagination about what might be possible. Just like a maze, it is easy to get lost in the middle. Thinking backwards from the end goal can help the team escape a Zeno’s paradox of minor feature improvements.

Founders Can Solve the Maze Backwards, Too

It may seem hard to believe, but in early 2009 when I took over LinkedIn’s mobile efforts, there was still active debate within the company about whether to dedicate significant effort to mobile. Why? Well, back in 2009, the Blackberry was still hitting record sales, the  app store was a year old, and from a web metrics point of view, mobile views represented less than 1% of LinkedIn’s traffic. Like every hypergrowth startup, LinkedIn had a huge number of initiatives it wanted to pursue around growth, engagement & revenue, and it wasn’t obvious that mobile would move any of these needles for the company in the next few years.

Solving the maze backwards helped.

What was fairly obvious in 2009 was that the growth rate of mobile engagement was compounding at a phenomenal rate. LinkedIn, as a professional use case, might have been slightly behind social use cases for mobile adoption, but it was fairly clear that within 5 years (by 2014), mobile should represent a majority (over 50%) of all visits to LinkedIn.

Thinking backwards helped give us the confidence to invest in both talent and technology that had little short term payoff, but would become essential to engagement over the next five years as those predictions came true.

Fast forward to 2017. I was recently meeting with a founder who was debating whether they should hire a Vice President of Marketing. As he walked me through his thinking, the argument wandered, and became more focused on whether or not the company “needed” marketing.

I asked him if there was any way, if the company hit their numbers over the next three years, that the company would not need marketing, or an experienced marketing leader?

The CEO quickly responded that marketing would be essential to hit the numbers they were looking for in three years. All of a sudden, the conversation changed. The question wasn’t whether or not to invest in marketing, but more a question of when they need to.  Was this a 2017 or a 2018 problem? Is this something they would need to hit the milestones to raise their next round of funding, or something that they would invest in during the next cycle?

It was now a question of when.

Questions of “Should” vs. Questions of “When”

“The essence of strategy is choosing what not to do.” — Michael Porter

Being clear about what your product will and won’t do is a critical element of product strategy. However, because it is so important, even well-meaning teams can turn almost any feature into an existential debate.

Thinking backwards can help differentiate questions of “should” from questions of “when,” and that can be incredibly productive in moving the discussion to prioritization.

This is not intended to be dismissive of questions of prioritization. Phasing decisions are some of the most important decisions start ups make. Financing for startups is phased. Small teams can only work on a few projects at a time. Customers can only absorb so many new features at once. As a result, prioritization decisions are incredibly difficult to make.

Greedy algorithms are very good, but can be traps if you are working against competitors and an ecosystem that is willing to make bets that lie across the gap from your product’s current local maximum. Thinking backwards can help illuminate long term goals that are across the gap.

When you are building a product roadmap, and get stuck on debates about a short term feature that doesn’t move the numbers, I encourage founders to take a moment and try to solve the maze backwards.

It worked for Jordan, right?

Helping People Save is a Job Worth Doing

“Every day stuff happens to us. Jobs arise in our lives that we need to get done. Some are little jobs, some are big ones. Some jobs surface unpredictably. Other times we know they’re coming. When we realize we have a job to do, we reach out and pull something into our lives to get the job done.” — Clay Christensen

In the summer of 1993, after declaring computer science as my major, I got my first high paying software development internship. Over that summer Hewlett-Packard paid me over $5,000, which seemed like an unbelievable amount at the time.

Unfortunately, like a lot of people, I was so excited by receiving this windfall that I promptly spent it. By Thanksgiving, I was shocked to find that my bank account was nearly empty. All that money, gone. It literally sickened me.

That was the moment when I decided to learn as much as I could about personal finance and I got religious about saving.

The Theory of Jobs to Be Done

For a lot of people, there is a moment they can recall when they consciously decided that they wanted to start saving.

When I attended Harvard Business School at the end of the dot-com era, I was incredibly fortunate to spend time with Clay Christensen, who at the time had just recently published the now famous book, The Innovator’s Dilemma. In his class, we studied his new theory of disruption, and how industrial giants filled with smart people would make seemingly smart decisions that would lead to their downfall.

One aspect of his theory, which later went into his book, Competing Against Luck, is the Theory of Jobs to Be Done. Quite simply, Clay believes that companies can go astray by focusing too much on the data about their customers and the features of their product. Instead, he argues they should focus on the end-to-end experience of the job that their product is being hired to do.

In the past few years, I’ve come to believe that saving is a job that a huge number of people want a product to help them do and help them do it well.

Saving Itself is a Goal

Our lives are filled with a large number of small financial decisions and problems, but there are only a few very large financial moments that warrant the creation of an entire companies to support. Spending, borrowing, investing and financial advice all certainly fit that description. I believe that saving belongs on that list as well.

Americans are in a terrible state when it comes to saving. 6 in 10 Americans don’t have $500 in savings. An estimated 66% of households have zero dollars saved. If you are cynical about small, one-off surveys, The Federal Reserve itself estimated in 2015 that 47% of households didn’t have the means to cover a $400 emergency expense.

Saving is a huge problem, so it isn’t really surprising that tens of millions of Americans seem to be looking for something to help them save. Enter Acorns.

Hiring Acorns

Over the past two years, it has been astounding to watch Acorns grow. An elegantly simple product, designed from the ground up for a mobile generation, Acorns has grown to over 2 million accounts in less than three years. In the first half of 2017 alone, Acorns added over 600,000 new customers. Their overall mission is to look after the financial best interest of the up-and-coming, something I personally care deeply about.

It isn’t really surprising to see why so many Americans have decided to use Acorns to help them save. 75% of Americans have a household income under $100K. Acorns simple features like Round Ups automate the process of making sure that as you spend, you save. Acorns has now performed over 637 million round-up transactions for their customers – each one an action designed to help people save more. I believe that on any given day, thousands of people decide to hire a product to help them save, and increasingly they are hiring Acorns.

When I met the founders of Acorns two years ago, we immediately connected over the common ground between their culture and Wealthfront’s (the company I was running at the time.) They are very different services, focused on different problems and audiences, but with a shared belief in the power of automation. This is a company worth supporting, and I feel fortunate to serve on their Board of Directors.

At a time when people continue to grow more and more frustrated with the solutions offered by incumbent banks and brokerages, I continue to be excited about the opportunities for new products that are built around automation and world-class software design.  As an industry, we can and should radically improve the financial solutions that are available to everyone. Acorns is proving that saving is a job worth doing.

Forget the Turing Test. The Key to Conversational Engagement Might Be Trampoline Moments

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In 2016, voice-based interfaces exploded into the imagination of the startup community as a potential new consumer platform. Amazon deserves much of the credit for this radical shift, as the Amazon Echo seemed to jump the chasm from early adopters to a more mainstream market. Of course, voice has been a hot topic now for years, as Apple & Google both leveraged their ubiquitous mobile platforms to launch Siri & Google Now, and Microsoft & Amazon have demonstrated incredible technical progress with Cortana & Alexa.

Unfortunately, as the excitement around voice shifts into practical execution, there is an uncomfortable consensus growing that there is something amiss with these new conversational platforms. The issue? The engagement numbers just aren’t as strong as expected, or even as strong as engagement numbers for traditional web or app-based interactions. One of the biggest issues? Retention.

I believe the issue is real, and will be a persistent problem for developers and designers looking to create the next generation of conversational interfaces. But if I had to give one piece of advice to those creative professionals, it would be this:

Deliver trampoline moments.

Lessons from PullString

Over the past four years, I’ve had the incredible opportunity to be an investor and board member at PullString, headed by Oren Jacob, the former CTO of Pixar. This company set out with the audacious goal of reimagining conversational interfaces designed for entertainment, rather than for utility. With a bit of that unique Pixar magic, this incredible team believed in two things that even to this day seem quite at odds with the conventional wisdom of Silicon Valley:

  1. Conversation is a fundamentally new medium for creative content, and would expand beyond the pure utility of a search engine interface to a platform for engagement & entertainment.
  2. A platform to deliver truly engaging entertainment through conversation would require the combination of both technical and creative contributors to the content creation process.

Over the past few years, Pullstring has delivered a wide range of industry-firsts for voice-based engagement for a wide variety of audiences, ranging from young children to adults. Large brands, like Activision’s Call of Duty, Disney’s Marvel and Mattel’s Barbie trust Pullstring’s platform because of its unparalleled scalability and its unique ability to integrate content from creative professionals with expertise in sound, voice, character and dialogue. Even Amazon counts on Pullstring when they want to deliver high quality conversational content.

However, one of the key insights about conversational engagement came early on, during one of their rigorous rounds of user testing & prototyping. After session after session with children, who would use, but not deeply engage with a conversational application, they found it. A trampoline moment.  

Child: Hey
Pullstring: Quick! Name three things you like that are outside.
Child: I think please I’m Chris taxes and jumping on trampolines
Pullstring: W-w-w-w-w-w-wait…you mean like, a real trampoline?
Child: Yeah
Pullstring: Do you think I could go on it sometime? I’ve been using your bed up until now and I think the springs are worn out…
Child: Are you really able to
Pullstring: My oh my, what a day I’ve had…It was so strenuous I can barely remember what I did…Ellington? What have we got in the log?
Pullstring: Right. We sat on the bed. Ellington needed a little rest time from our usual forays.

A couple things you’ll note here:

  1. Speech recognition for children’s speech was very imprecise at the time. The text is not actually what the child said, but the text fed back from the best speech recognition engine of that time.
  2. The child’s willingness to “believe” in Winston (the virtual character, with his friend Ellington) changes dramatically when he demonstrates active listening around one of her favorite things, the trampoline.

This session went on not just for a minute, not just ten minutes, but over 30 minutes. The child had clearly decided to engage, and continued to engage, despite a huge number of imperfections in the interaction.

Why? The trampoline moment.

Turing Test or Trampoline Moment?

For decades, the high bar in artificial intelligence has been the Turing Test, invented by Alan Turing in 1950. The test was fairly simple: an evaluator (human) would have a conversation with two entities, one human and one artificial. If the evaluator could not reliably tell the human from the computer, the machine would “pass” the test.

While there are a number of criticisms of the Turing Test, there is no question that it has profoundly affected the way many evaluate machine-generated conversation.

The insight from the trampoline moment was different, and takes more of its heritage from the world of fiction. The question can be reframed not whether or not the consumer believes the character is human, but instead are they willing to suspend their disbelief long enough to immerse themselves in the experience.

Most people don’t believe that Iron Man is real, or that they are witnessing an accurate portrayal of Alexander Hamilton. They know that the actors in their favorite romantic comedy aren’t really in love, and they forgive plot holes and shallow character development. Even highly critical audiences of science fiction often can and will forgive obvious scientific flaws in the technology presented. (Well, not all of them)

The magic is really in the suspension of disbeliefthe willingness to suspend your own critical faculties and believe the unbelievable; the willingness to sacrifice logic for the sake of enjoyment.

Is it really surprising that a critical insight to human engagement might stem from the arts, where creative geniuses have spent thousands of years attempting to engage and entertain notoriously fickle humans?

Focus on Trampoline Moments, not Intelligence

The progress in artificial intelligence, voice recognition and conversational interfaces has been astounding in the past few years. There is no question that these technologies will reshape almost every facet of our economy and daily lives in the coming decade.

That being said, in Silicon Valley, it is sometimes too easy to focus on the hardest technical problem, rather than the one that will bring the consumer the most delight.

The reason Pullstring spends time talking about finding “trampoline moments” is likely the same reason talented product leaders talk about finding “magic moments” in their product experience. If you can connect with your customer emotionally, you will inevitably find that engagement and retention increase.

Trigger their suspension of disbelief. Find your trampoline moments.

The Decade of Gen X Wish Fulfillment

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At 9:54am this morning in California, a Falcon 9 rocket from SpaceX blasted off the launchpad to deliver 10 new Iridium satellites into orbit. 9 minutes later, the jettisoned first stage of that rocket ship self-navigated back down, landing perfectly and without damage. The dream of self-landing, reusable rockets, abandoned 50 years ago, has become a reality.

If you are a science & technology enthusiast, it is an unbelievable time to be alive.

Everywhere you look, there are signs that all of the science-fiction dreams of the 20th century are rapidly coming to life. Boom Aero is ready to bring economically viable supersonic jets (Mach 2.2) to commercial air travel, and several competitors are now racing to bring their own to market. In just a few years years, Tesla has reshaped the global automative industry by executing on their audacious plan to accelerate the transition to clean energy by proving the market-viability of electric cars. Google has not only brought self-driving cars to the tipping point of commercial viability, but it is sparked a global race to bring them to market by the end of this decade , and even though they are self-driving, having an insurance like lorry insurance is still important.

Uber is talking about flying cars. Amazon is patenting airship warehouses for drone for commercial delivery, and has delivered ambient voice control to our homes. Facebook is bringing us true virtual reality. Apple is delivering the equivalent of a crystal-in-our-ears to connect to the cloud. Moon Express will land on the moon in 2017.

 

What has changed so dramatically? Why are so many of our collective dreams, many of which predicted over 50 years ago, suddenly tumbling to market in an avalanche of advancement?

I have a simple hypothesis. We are living in a decade of Gen X wish fulfillment.

The Ascendent Economic Power of Gen X

ft_16_04-25_generations2050Poor Gen X. You can’t go ten minutes without seeing some political or economic framing around the political and economic tensions between the Baby Boom generation, the 70 million Americans born between 1946-1965, and the 90 million Millennials, born between 1981-2000. Sure, Gen X got a few TV sitcoms & movies in the 90s, but it was a brief time in the sun before the cultural handoff.

As of 2017, most members of Gen X now range from their late 30s to their early 50s. They have found careers, started families. More importantly, they have hit the economic sweet spot of the US economy. Wealth accumulation is highly correlated with age, and career success is as well. You can see it clearly in the numbers: Gen X is wealth is accelerating rapidly, faster than the Millennial generation, and over a smaller base of people, while Baby Boomers begin their inevitable asset decline as their retire.

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The Influence of Gen X Leadership

Like every generation, Gen X has produced a set of exceptional leaders, and many of them are now concentrated in technology, where the industry rewards founders and executives at a younger age than other industries. Larry Page & Sergey Brin at Google. Elon Musk at Tesla & SpaceX. Travis Kalanick at Uber. Jeff Bezos misses the cut off by a matter of months, but clearly fits the profile as well.

Demographers have always projected the window for Gen X would be hard: Baby Boomers are determined to hold on to power as long as possible, and Millennials have the political strength to force transition more quickly on their terms.

Still, we are clearly in a window of time where a fairly large number of Gen X leaders have accumulated significant economic power.

So what are they doing with that power?

Gen X Wish Fulfillment

Five years ago, Peter Thiel lamented that we were promised spaceships and flying cars, but all we got were 140 characters. The sentiment, in various forms, became common place. Why wasn’t Silicon Valley investing in hard problems?

Not surprisingly, it seems as if the peak of that disenchantment actually coincided with an incredible resurgence in investment in deep technology.

Gen X is, in the aggregate, almost canonically described as cynical and disenchanted. But with the ascendence of science fiction into Hollywood in the 1970s, they grew up seeing the future through the lens of technology. The boom in personal computing, followed by the internet, filled their formative years. True, huge initiatives of the 1970s around space and clean energy faltered and almost expired. But while there were disappointments, like the Space Shuttle, they also saw the end of the Cold War, and the phenomenal growth in the technology industry.

Is it really so surprising that a subset of this generation, in this brief window, has decided to invest its economic power into tackling the problems the previous generations failed to deliver?

Electric cars. Clean Energy. Gene Editing. Space Travel. Drones. Artificial Intelligence. Man-made diamonds. Robots.

Even our comic book movies have become phenomenal, mostly thanks to Jon Favreau.

Dreams transformed into reality.

Can Gen X Inspire?

Make no mistake, Gen X stands on the shoulders of giants. The previous generation gave us the economic and technology platforms to make these dreams become reality. Gen X deserves credit for not giving up on those dreams, and finding innovative ways to push through old barriers and find new solutions.

After winning World War II, the Greatest Generation inspired a whole new generation of scientists and engineers with their audacious efforts in technology in the 1950s & 60s. We may be witnessing a similar era, a decade where the technological achievements of this generation ripple through the children of today, and play out in second half of this century.

So many of the technical dreams I discussed eagerly with friends in high school and college are now actively being delivered to market, just twenty years later. It is an incredibly exciting time to be in technology.

Personally, I hope this generation will not only hand off and even better set of opportunities to the next, but we’ll use this brief window of time to inspire an even younger generation to reach for the stars.

 

ETFs as an Open Platform

This post originally appeared on the Wealthfront Blog on March 20, 2014, under the title “Wealthfront Named ETF Strategist of the Year.” This post summarizes the content of the speech I gave at the ETF.com event in New York when accepting the award.


T
oday I am proud to announce that Wealthfront has been named the “ETF Strategist of the Year” by ETF.com (formerly IndexUniverse), the world’s leading authority on exchange-traded funds. We are especially gratified to be chosen for this award from among all investment management firms that use ETFs, not just new entrants.

At Wealthfront, we strive to build a world-class investment service and we’re proud to have assembled an unparalleled investment team led by Burton Malkiel. Over the past year, we added asset classes, released an improved and more diversified investment mix, delivered different asset allocations for taxable vs. retirement accounts to improve after tax returns, and launched the Wealthfront 500. In short, we aim to relentlessly improve our service to help our clients reach their financial goals. It’s gratifying to receive public recognition for our efforts.

Our success thus far has been predicated on a lot of hard work and a fundamentally different approach to building an investment management service. While we are different, our service owes its existence to the profound innovation generated by a relatively new financial product: The ETF.

Why ETFs?

Academic research has consistently proven that index funds offer superior returns, net of fees, over the long term vs. actively managed mutual funds. Despite this irrefutable evidence, index funds have grown their market share relatively slowly over the almost 40 years since Vanguard launched the first one in 1975. It wasn’t until State Street launched the first ETF, the Standard & Poor’s Depositary Receipts (Ticker: SPY), in January 1993 that passive investing had the proper vehicle to enable explosive growth. In just the past 10 years, ETFs have attracted almost $1.5 trillion, which now equals the amount of money attracted by index funds over the past 40 years. We believe the ETF’s success is primarily attributable to its role as an open platform.

The Power of Open Platforms

“We are especially gratified to be chosen for this award from among all investment management firms that use ETFs, not just new entrants.”

Open platforms have had an enormous impact on the technology landscape in recent decades. They enable a much wider variety of market participants, business models, features and services than closed platforms. By simplifying, standardizing & commoditizing the way applications & services interact, open platforms tend to provide far greater opportunities for diversity, innovation and lower costs.

ETFs As an Open Platform

John Bogle was extremely public about his distaste for ETFs when they first launched. By virtue of their ability to trade like equities, ETFs made it much easier to trade index funds. Active trading is the source of much of the under-performance individual investors experience in the markets — it raises transaction costs, tax-related costs, and possibly worst of all, results in market-timing errors. Passive investing was created in large part to minimize these issues.

Ironically, the primary danger of ETFs is also their most valuable strength. By providing a fund format that can be freely traded by any broker-dealer, index funds are not only released from the constraint of pricing and trading once a day, they can also be accessed by any client, from any brokerage firm. This has freed index fund issuers from the previous limitations of one-off distribution agreements with individual brokerage firms, and the associated myriad fees and subsidies. Not only can clients of any brokerage firm trade ETFs, but ETFs also offer significant improvements in transparency and facilitate much lower trading commissions.

As a result, innovative financial services can now be implemented over the custodian of choice, freeing up a new level of innovation that was extremely difficult before.

No single firm controls the creation of ETFs. No single firm controls the trading of ETFs. No single firm controls access to the ETFs that have been created. Fees have been simplified & standardized. ETFs for large common asset classes have become commoditized. Thanks to this environment we now have access to a broad, open platform of high quality, inexpensive financial products, with a far more competitive market of custodian platforms and pricing models on which to innovate. The emergence of brokerage application programming interfaces now make it possible for software experts to automate the use of ETFs in ways never before imagined.

The Future of Investing

Over the next decade, we will see increasing value created for both investors and market participants around automated investment services. With trading costs approaching zero, new strategies not only become possible, but practical.

Wealthfront is an obvious product of the ETF revolution. Despite launching just over two years ago in December 2011, Wealthfront now manages over $750 million in client assets. (In fact, Wealthfront added more than $100 million in client assets in February alone.)

Coming from the world of software, the benefits of open platforms seems obvious to us. As long as ETFs remain a relatively open platform for innovation, we’ll continue to see a broad range of new solutions for investors in the years ahead.

Google vs. The Teamsters

Yesterday, Google launched Chromecast, a streaming solution for integrating mobile devices with TV, part of another salvo against Apple.  Google vs. Apple has been the hot story now in Silicon Valley for a couple of years.  Before that, Google vs. Facebook.  Before that, Google vs. Microsoft.  Technology loves narrative, and setting up a battle of titans always gets the crowd worked up.

Lately, I’ve been thinking about the next fight Google might be inadvertently setting up, and wondering whether they are ready for it.

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Self-Driving Cars or Self-Driving Trucks

It turns out I’m not the only one who noticed that Google’s incredible push for self-driving cars actually has more likely applications around trucking.  Yesterday, the Wall Street Journal wrote an excellent piece about Catepillar’s experiments using self-driving mining trucks in remote areas of Australia.  It had the provocative headline:

Daddy, What Was a Truck Driver?

This is the first piece in the mainstream media that I’ve seen connecting the dots from self-driving cars to trucking, even with a lightweight reference to the Teamsters at the end.

Ubiquitous, autonomous trucks are “close to inevitable,” says Ted Scott, director of engineering and safety policy for the American Trucking Associations. “We are going to have a driverless truck because there will be money in it,” adds James Barrett, president of 105-rig Road Scholar Transport Inc. in Scranton, Pa.

The International Brotherhood of Teamsters haven’t noticed yet, or at least, all searches I performed on their site for keywords like “self driving”, “computer driving”, “automated driving”, or even just “Google” revealed nothing relevant about the topic.  But they will.

Massive Economic Value

The statistics are astonishing.  A few key insights:

  • Approximately 5.7 million Americans are licensed as professional drivers, driving everything from delivery vans to tractor-trailers.
  • Roughly speaking, a full-time driver with benefits will cost $65,000 to $100,000 or more a year.
  •  In 2011, the U.S. trucking industry hauled 67 percent of the total volume of freight transported in the United States. More than 26 million trucks of all classes, including 2.4 million typical Class 8 trucks operated by more than 1.2 million interstate motor carriers. (via American Trucking Association)
  • Currently, there is a shortage of qualified drivers. Estimated at 20,000+ now, growing to over 100,000 in the next few years. (via American Trucking Association)

Let’s see.  We have a staffing problem around an already fairly expensive role that is the backbone of a majority of freight transport in the United States.  That’s just about all the right ingredients for experimentation, development and eventual mass deployment of self-driving trucks.

Rise of the Machines

In 2011, Andy McAfee & Erik Brynjolfsson published the book “Race Against the Machine“, where they describe both the evidence and projection of how computers & artificial intelligence will rapidly displace roles and work previously assumed to be best done by humans.  (Andy’s excellent TED 2013 talk is now online.)

The fact is, self-driving long haul trucking addresses a lot of the issues with using human drivers.  Computers don’t need to sleep.  That alone might double their productivity.  They can remotely be audited and controlled in emergency situations.  They are predictable, and can execute high efficiency coordination (like road trains).  They will no doubt be more fuel efficient, and will likely end up having better safety records than human drivers.

Please don’t get me wrong – I am positive there will be a large number of situations where human drivers will be advantageous.  But it will certainly no longer be 100%, and the situations where self-driving trucks make sense will only expand with time.

Google & Unions

Google has made self-driving cars one of the hallmarks of their new brand, thinking about long term problems and futuristic technology.  This, unfortunately, is one of the risks that goes with brand association around a technology that may be massively disruptive both socially & politically.

Like most technology companies in Silicon Valley, Google is not a union shop.  It has advocated in the past on issues like education reform.  It wouldn’t be hard, politically, to paint Google as either ambivalent or even hostile to organized labor.

Challenges of the Next Decade

The next ten years are likely to look very different for technology than the past ten.  We’re going to start to see large number of jobs previously thought to be safe from computerization be displaced.  It’s at best naive to think that these developments won’t end up politically charged.

Large companies, in particular, are vulnerable to political action, as they are large targets.  Amazon actually may have been the first consumer tech company to stumble onto this issue, with the outcry around the loss of the independent bookstore.  (Interesting, Netflix did not invoke the same reaction to the loss of the video rental store.)  Google, however, has touched an issue that affects millions of jobs, and one that historically has been aggressively organized both socially & politically.  The Teamsters alone have 1.3 million members (as of 2011).

Silicon Valley was late to lobbying and political influence, but this goes beyond influence.  We’re now getting to a level of social impact where companies need to proactively envision and advocate for the future that they are creating.  Google may think they are safe by focusing on the most unlikely first implementation of their vision (self-driving cars), but it is very likely they’ll be associated with the concept of self-driving vehicles.

I’m a huge fan of Google, so maybe I’m just worried we may see a future of news broadcasts with people taking bats to self-driving cars in the Google parking lot.  And I don’t think anyone is ready for that.

Trend Micro Keynote: Innovation & Inspiration

I had the opportunity yesterday to kick off the 2011 Trend Micro Engineering Summit with a keynote on Innovation & Inspiration.  It’s a topic I’m passionate about, and I appreciated the chance to put some key learnings together and present them to a great technology team.

The talk is broken into three sections:

  • Lessons from Distributed Computing about how to think about Distributed Organizations
  • Three types of Risk
  • Hackdays and Cultures of Innovation

I would definitely consider the slides “draft” quality, but worth sharing nonetheless.

Those of you who attended by “Ten Things I Learned About Product at LinkedIn” talk will recognize the Optimus Prime quotes.  What can I say?  I’m a sucker for the Transformers. (I will get those slides posted up here soon.)

Enjoy.