Defining the Future of Human Information Consumption

Human evolution depends on an ever-increasing rate of information creation and consumption. From communication to entertainment to education, the more information we create and consume, the stronger our society in total. Communication enhances community. Entertainment encourages creativity. Education builds knowledge. All of these elements build on top of one another like an upside-down pyramid, each new layer built a little bigger on top of the prior. It’s no coincidence that the Information Age of the last several decades has marked both the greatest period of increased information creation and consumption as well as, arguably, the greatest period of human progress.

The explosion of information created in the Information Age came with the tacit understanding that more information was good. The volume of information available to us is unprecedented, so the firehose is beneficial even if some (or perhaps much) of the water misses its target. The advancements of our technological devices that convey information have endeavored to bring the firehose closer and closer to us; from the non-portable PC, to the semi-portable laptop, to the nearly-omnipresent smartphone, to the emerging omnipresent wearable.

Now we’re continuously drowning in information.

The average global consumer spends 82 hours per week consuming information. Assuming an average of seven hours of sleep per night, this means that 69% of our waking hours are engaged in consuming information. For many consumers in developed markets, that number is likely closer to 100%. It’s not often many people disconnect from information sources. Even when we’re not in front of a screen, the nearest one is always in our pocket, or there’s music or a podcast playing in the background. As a result, we consume almost 90x more information in terms of bits today than we did in 1940 and 4x more than we did less than twenty years ago.

Source: Carat, Loup Ventures

Not only are we maxing out time available to spend with information, we’re creating so much information that it’s impossible to keep up. The ratio of the amount of information consumed per year by the average person to the amount created per year in total is the lowest it’s ever been by our analysis. There’s always more information to consume, and the trend toward autonomous systems is only going to amplify that.

Source: Loup Ventures

These two observations don’t paint a very positive picture of our relationship with information or our prospects for continued evolution, but in every challenge there’s an opportunity. We’re now preparing to exit the Information Age and enter two separate eras: The Automation Age and the Experiential Age. The Automation Age represents the natural continuation of the Information Age where artificially intelligent systems act on the vast amounts of information produced and quantity continues to dominate. The Experiential Age will define how the human relationship with information changes, creating new paradigms for communication, education, and entertainment. Out of evolutionary necessity, we will demand information with greater relevance, density, and usefulness than ever before. Meaning and efficiency, not quantity, will be the metrics on which we will measure information for human use over the next several decades.

Reintroducing Meaning + Information

Our current relationship with information is measured in quantity. Internet speeds are calculated in bits per second, as are hard drive speeds. Processor speeds are based on how many instructions they can perform per second, an instruction being a manipulation of bits. We even talk about how many messages we process a day, whether email, text, Snaps, etc. as a derivative of bits. We expect all of these quantitative measurements to improve over time, so we can consume more information faster.

One of the reasons we think about information in quantity is because of how information theory evolved. Claude Shannon developed information theory, built on work from Boole, Hartley, Wiener, and many others (upside down pyramid), to establish a method for accurately and efficiently transferring information in the form of a message from creator to receiver. His work on information theory yielded the bit and created the basis for modern computing. As Shannon developed his theory, he realized that the meaning of a message (the semantic problem) was irrelevant for establishing the efficient transfer of the characters that created the message, and therefore focused on the quantifiable aspects of the message instead.

It’s time to reintroduce meaning to information.

All meaning is established as a consumer’s interpretation of the creator’s intent (i.e. the creator’s version of meaning). The meaning of the same picture or movie or article may differ from person to person, even if the creator of the message might intend a single meaning. Since all interpreted meaning is some derivative of intended meaning, to contemplate “meaning”, you must contemplate both sides.

To help demonstrate the flow of meaning, it’s helpful to overlay the transfer of meaning on Shannon’s diagram from his groundbreaking piece on information theory:

The flow of meaning is analogous to the flow of information as diagrammed

by Shannon in “A Mathematical Theory of Communication”

A creator (human or machine) intends meaning in some message, which is conveyed to the consumer (human for our purposes) for interpretation via information transmission channels. A message is a container of information, which can be digital (e.g. a file) or physical (e.g. a book).

All intentionally transmitted messages must have some intended meaning, or the creator wouldn’t be able to conceive the message. Even a blank message is a reflection of the creator’s current mindset. Likewise, a message of random characters might imply boredom, or that a machine was programmed to do it, or it was a byproduct of some machine-learned behavior, etc. Messages transmitted by accident are free of this rule.

Since every message must be created with some initial meaning, all messages must therefore be interpreted because there is some underlying meaning to contemplate. A blank message might be interpreted as a mistake or a sign of trouble, a scrambled message might be a pocket dial, etc. This interpretation establishes the meaning from the message to the consumer.

In the process of transferring meaning, holistic noise impacts the interpretation of the intended meaning. It represents the natural disturbance between what a message creator intends and what the message consumer interprets. Holistic noise is created by differing contexts, that is, differing experiential, emotional, and physiological states between the creator and consumer.

Exploring meaning is a philosophical abyss — its precise characterization is engaging to discuss, but extremely hard to define. Nonetheless, the definition we’ve arrived at thus far is sufficient for establishing information utility, and further debate would distract us from the focus of defining utility.

Meaning/Time — The New Measure of Information

Thanks to Shannon, the quantity of information we can transfer is no longer a gating factor to the human consumption of information; the quantity we can process is. Therefore, the amount of meaning we derive from a message is now paramount, as is the time it takes to consume the message. To this end, we would propose that the value of a message in the Experiential Age should not be measured by bits in any way, but by meaning divided by time. We call this measure information utility:


Utility (U) of information is equal to the value of the meaning interpreted by the consumer of the information (m) divided by time it takes to consume the information (t).

Of course, meaning is abstract. How could you ever quantify it?

The closest we may be able to get is to borrow from marginal utility in economics. Just as we all have some innate scale with which we rank the value of consumer goods and that scale theoretically determines where we spend our money, we have a similar innate scale relative to the meaning of messages that should determine where we spend our time. We therefore measure meaning by time to help determine where best to spend our scarce asset of time just as we measure marginal utility by money to determine where best to spend our money.

Any individual’s scale for valuing meaning will likely be different, but that doesn’t matter. It only matters that we all have a scale that can consistently be used to compare the “meaningfulness” of the meaning we consume. In other words, we interpret the meaning of a message and then rank the perceived satisfaction or benefit we got from consuming it on an innate scale based on the aggregate of our prior experiences and expectations therefrom.

In reality, the scale is likely to be fuzzy (ordinal) rather than precise (cardinal). Most of us in any given moment wouldn’t be able to say message A is 11.7625% more meaningful than message B, but we would be able to say message A has more meaning than message B. That said, an information consumer can assign theoretical cardinal values to different messages based on the fuzzy scale, just as in marginal utility. Those cardinal values can be used to create a mathematical determination of information utility for the consumer.

Relevance and Compression: improving Information Utility

The next logical question is: How do we improve information utility?

The underlying intent of a message will always be the greatest factor in utility because all interpreted meaning (m) is a derivative of intent. A message of minimally useful or irrelevant intent will rarely be interpreted to have great meaning and thus usually have minimal utility. The answer may seem to be to improve the intent of the message; however, if you change the intent of a message, you change the message entirely, which is like telling the message creator to just say something else, ignoring their desire to convey their intended meaning.

Improving information utility should not rely on changing the intent of a message and instead focus on matching a consumer’s need or want with a creator’s intent and then optimizing the conveyance of that intent. This leaves us with two core opportunities to improve utility: relevance and compression. Relevance ensures that a consumer is engaging with useful messages while compression enhances the presentation of a specific message to increase meaningfulness. To maintain our hose analogy: Relevance improves the hydrant that the firehose is attached to and compression distills the water itself.

One may argue that relevance is just another measure of meaning since by definition for some message have meaning, it must be relevant to the consumer. However, to argue that relevance is meaning assumes that it can only be applied post message consumption. The problem is that once a message has been consumed, its determined relevance (and by transference, meaning m) is immutable for that given point in time; utility cannot be changed after the fact. Therefore, leveraging relevance to improve utility must happen prior to the message consumption.

We define relevance as the reduction of the total pool of potential messages available for consumption (the consideration set) prior to consumption.

Relevance reduces the information consideration set, compression enhances the information itself

Today, relevance is optimized largely by data companies like Google or Facebook. These platforms reduce some large consideration set of messages that may be relevant to the user into something more focused to help reduce the user’s time seeking meaning. The more these systems know about our preferences, the more relevant information they can funnel to us. Of course, this creates a double-edged sword related to privacy, but all technology comes with tradeoffs. While it seems the data wars have been won by the information giants, the privacy wars have just begun. The hidden opportunity here may be for some platform to put privacy first and balance the careful line between keeping consumer data safe while still presenting the most relevant information.

Less time searching for relevant information means more meaning divided by time by avoiding less useful messages in the consideration set. The time saved can be spent consuming other relevant information, creating a greater aggregate value utility given time spent. Note that our version of relevance does not influence m/t for any specific message, only the set of messages considered; only compression can do that.

We define compression as a direct improvement to a given message that either enhances the meaning intended by the creator and/or decreases the time spent consuming it.

While the interpretation of the consumer is what ultimately establishes meaning for calculating utility, the compression of meaning depends on enhancing the intention of the creator and its consequent effect on the consumer’s interpretation. Compression doesn’t change the intent of a message, but makes it clearer and more useful, usually reducing holistic noise in the process. An example might be a set of written directions to a store vs a map. The underlying intent is the same, but the latter message should offer more utility provided the map is legible and accurate.

Historically, compression has happened via transitions to different information formats. With the advent of the written language, we went from the imprecise spoken word to the more precise written word. Writing a book or a letter is a form of compression relative to the spoken word because more thought and contemplation generally goes into writing vs discourse. Greater contemplation of the message should result in greater meaning of the message. More recently, the shift from written word to video is another example of relative compression. Video conveys relatively more meaning with less holistic noise than written words because the images help an information consumer see body language, emotion, and other factors that can be difficult to ascertain through words alone. This doesn’t mean that video is the perfect medium of transmission for every message — the written word can be effective for certain purposes — but there is relative compression when comparing writing as a message format vs video as a message format.

Compressing relatively more meaning into less time will be a prominent factor in the Experiential Age. If we can get more meaning in less time, we will spend more time with the technology that delivers that benefit. To that end, there are several emerging opportunities around compression:

Stacking Information Purposes. Content formats like GIFs and emoji combine communication and entertainment by replacing text. When a message creator picks a specific GIF or emoji to express themselves, it carries not only the underlying intended message, but an added element of emotion and entertainment. These added elements not only increase the meaning transferred, but also reduce the holistic noise between the message creator and consumer. Most obviously, when someone sends a GIF of a shaking fist or a coffin emoji, they probably aren’t seriously mad.

Platform-Enforced Time Restriction. While some content platforms are moving away from time restriction, like Instagram and Twitter, placing an artificial cap on the length of a message will always compress meaning. When an information creator is forced to deliver his or her message in limited time like a 140-character tweet or a six-second Vine (maybe now v2), it demands creativity and precision that results in greater meaning for the consumer. This incurs an additional cost of time to the creator to make their message succinct but still meaningful; however, the burden of quality in a message is always on the creator, and perhaps many messages aren’t worth the time to send in the first place.

Consumer-Enforced Time Restriction. In some cases, information consumers put the restrictions on time they’re willing to spend consuming a creator’s message. This is most apparent in the shift to digital assistants. When an assistant answers a consumer’s query, the consumer is not willing to listen to a painfully long list of ten possible answers. They expect one answer; the right answer. In this sense, the consumer shifts the burden of time he or she previously spent deciding the best answer from a set of options back to the creator that established the options in the first place (i.e. Google, Amazon, Apple, etc.). Relevance has always been important in the consumer Internet, but increasingly so here. Companies with extremely large customer datasets are the only ones able to play in this game because data allows the digital assistant companies to infer the context of the consumer and tailor messages appropriately.

Information Layering. The emergence of augmented reality (AR) has enabled the concept of information layering. Now a picture or video can be enhanced by stickers or lenses that add additional information related to the original purpose of the content, most commonly entertainment today. The layered information acts somewhat similarly to stacking information purposes in reducing holistic noise by adding context. As AR continues to evolve, the layered information can become more educational or instructional. For example, AR can compress knowledge about how to do something from a book or 2D video that suffered from the friction of transferring that meaning to the real world, to overlaying that meaning on the real world itself; another example of reducing the holistic noise between creator and consumer and improving meaning in time.

Scarcity. By limiting the number of times someone can send a message or components of a message, content platforms can create artificial scarcity similar to a time restriction. In this case, the restriction applies to the meaning side of the equation. If a message creator chooses to leverage a limited resource in a message (other than time), it should confer greater meaning to the consumer because it comes at an opportunity cost to the creator. An example might be some of the frameworks emerging around the ownership of unique digital goods, which could extend into transference of meaning through those goods. When a creator includes a one-of-a-kind component to a message, the intended meaning increases, which should also increase interpreted meaning.

Time Manipulation. Since the majority of content we consume is digital, much of it can be sped up or slowed down according to the consumer’s preference (i.e. videos, audiobooks, podcasts, etc.). Time manipulation requires no additional effort on the side of the creator; it only requires the consumption tool to enable it. While time manipulation techniques are effective on an individual level, they’re less interesting than the other opportunities because they’re optional to the consumer where the others are common across all consumers.

Brain-Computer Interface (BCI). The development of brain-computer interfaces will, in theory, create a direct way to receive information from and transmit information to the brain. A deeper understanding of how we create meaning from a neurological perspective is embedded in this future, thus BCI should reduce holistic noise and enhance meaning. An example may be that a message transmission mechanism could understand the contextual state of both the message creator and consumer and alter the message as appropriate in an effort to match states. While BCI is exciting technology, it has a long clinical path that is just beginning before we can consider using it for meaningful augmentation.

It bears repeating the message creator’s intent is paramount to utility. A useless message is still useless no matter how you dress it up. However, a more compressed version of a given message should always be more useful than a less compressed one given the same baseline intent, so we should strive to compress messages as much as possible.

The current opportunities in compressing information should be relevant for the next 5-10 years or more, particularly in the case of BCI. That said, the aforementioned concepts and technologies compress information relative to how we consume it today. As they become the standard for future information transmission, the bar must move correspondingly higher, and we will need to find new ways to compress information even more. Therefore, while the human desire for increasing information utility is eternally valid, how we compress more meaning into less time must always evolve.

Embracing Information Utility

It’s popular to lament our overexposure to information, ever-shortening attention spans, and superficiality of what we create and consume, but technology has always been a Pandora’s Box. Now that we’ve gone down the path of near-constant connectivity, it’s impossible to walk it back. While it can be beneficial to spend less time with information when possible, we have to embrace the path we’ve created; embrace the unending flow of information. Discovering ways to leverage new content formats and technologies in ways to transmit useful information is our future. Demanding more meaning from that information we choose to spend time with is the next evolutionary step for humanity.

Improvements in relevance will continue to be driven by technology, but as we think about the opportunities in compression, it’s clear that utility will not be driven purely by hardcore technologists, but also by hardcore creatives. Injecting more creativity into how we convey meaning, something that is unique to the human experience, make up some of the biggest opportunities in improving information utility. After all, the humans that consume information determine the utility of it, not robots.

Some people fear the coming Automation Age will devalue humanity, removing purpose and meaning from our lives. Luckily, we have this survival instinct — this innate need for more information, more knowledge. That curiosity means there will always be a purpose for us. As automation frees us from the constraints of labor, the Experiential Age will bring about a golden era of exploring what it means to be human, and information utility will guide the way.

Disclaimer: We actively write about the themes in which we invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Victory Royale! Fortnite is Exploding

  • Epic Games’ Fortnite has exploded in popularity over the past few months for four reasons.
  • 1. It’s accessible to all (free to play, compared to similar games that cost $60, and easy to play, different than most complicated console games).
  • 2. It’s fun (Battle royale style).
  • 3. It’s high-quality (frequent gameplay, weapon, and skins updates).
  • 4. No pay-to-play advantage (keeps level playing field. Most games make money selling play advantage).
  • We believe these four factors will result in Fortnite being a top 5 game for the next several years.

Fortnite 101. Fortnite is a battle royale game, where 100 players parachute onto an island with the goal of being the last one standing at the end. A “storm” serves as a boundary that closes in at set intervals, shrinking the playable area and forcing players closer and closer together. Players begin with no equipment and must scavenge around the island looking for weapons and supplies to give them an advantage over the opposition. Fornite has screamed to the top of gaming titles recently and is the number 1 most viewed title on Twitch as of this writing.

Easily accessible to all. Fortnite is an extremely accessible game in a number of ways. For one, it’s free, making it easy to convince friends and family to try it out versus console games that usually run about $60. This is a major reason for its fast ascension to cultural phenomenon. When gamers see their friends playing a game or want to try a new one, they often must consider if it’s worth the investment. With Fortnite, users are able to play the online multiplayer without any upfront cost.

Another facet of its accessibility is the graphics and visuals. The aesthetic of Fortnite is cartoony and a little silly, which makes it much easier for parents to get on-board and expands the audience of the game to a younger demographic. There is no gore, no dead bodies lying around and the weapons feel less like instruments of destruction and more like they’re made by NERF or SuperSoaker. PlayerUnknown’s Battlegrounds (PUBG), the first major battle royale title, has a much grittier, more realistic aesthetic that is targeted to an older audience. Fortnite looks and feels like it’s directed at kids, but has enough complexity and a high enough skill ceiling that it keeps older, more competitive players interested as well. It’s an example of the old adage, “easy to learn, difficult to master.”

Furthermore, it’s playable across platforms. It is available on PS4, Xbox One, PC, and iPhone, with Android support coming soon. Fortnite also supports cross-platform play, so players on the PC can play with their friends or family who play on Xbox (though PS4 and Xbox players can’t play together, Sony is blocking the option). This is the first time that this has been possible for any video game and could prove to be a major milestone for online gaming.

It’s fun, battle royale’s rise. Battle royale games are a relatively new phenomenon. One of the keys to Fortnite’s meteoric rise is that this genre is inherently fun. The longer the game lasts – and the closer you get to victory – the higher the stakes and the higher the stress. The exhilaration of being one of the few remaining players is a significant factor in the game and the genre’s popularity. Ultimately winning a game, emerging as the lone victor out of a hundred other players is an incredible feeling not found in other game modes. While Fornite was not the first game to embrace this format it was one of the earliest and brought its own unique spin by allowing in-game building of walls, ramps, and roofs. The building mechanic adds another layer to the game for players, giving them the ability to quickly reach previously inaccessible locations and create cover or an escape route under fire.

High-quality game. Fortnite’s battle royale format and accessibility would be non-factors if it weren’t for the fact that Fortnite is a high-quality product. The game is still in early access (i.e. it’s not a finished game), so there are some kinks here and there, but the Epic team is committed to the product and is visibly working hard to make sure the game is running smoothly and keeps players engaged. They have continued to add new weapons, equipment, locations, and other features to the game free of charge so one can continue to play and get the full experience without paying a cent. Fortnite brings in revenue is by selling cosmetics for players to personalize their in-game character, and a 10-week ‘Battle Pass’, essentially a subscription that gives players more challenges to complete and cosmetics to unlock during that period. The game looks good, feels good, and is free. It’s not a tough sell to get people to try, and once they do they are hooked. Below is an example of two of the latest in-game character skins that can be purchased.

No pay-to-play advantage. While it’s hard to say how much the approach to in-game purchases contributes to Fortnite’s success, it is starkly different from how some major publishers approach in-game purchases. Electronic Arts has been successful with in-game purchases, especially with their FIFA games, but also faced notable backlash from the way the in-game purchases for Star Wars: Battlefront II were setup. EA allowed players to spend money to unlock items that grant a competitive advantage over those who elect not to spend extra. Fornite takes a different approach, offering its 10-week Battle Pass and limited-time character skins, items, and emotes, which are completely cosmetic and provide no competitive advantage. Some of these items are only available for purchase in a 24-hour window before they disappear from the store, driving users to get the items they like while they can. Despite the game being released for free, and in-game purchases providing no competitive advantage, Fornite earned $126M in revenue in the month of February alone. Since then, Epic Games has launched Fornite Mobile, which has reportedly reached $1.8M in revenue per day. Needless to say, their unique in-game purchase strategy seems to be working.

Disclaimer: We actively write about the themes in which we invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

The Empathy Economy

Op-ed published February 7, 2018 on Business Insider

Throughout history, different eras have begotten different heroes of productivity in industry. In the 80s, the stock broker was the rock star of the business world. In the late 90s and 2000s, it was the computer programmer. For the last decade or so, it’s been the data scientist. As the work of data scientists and engineers creates the Automation Age, the next industrial rock star will be the customer service specialist.

Before you scoff at the idea of what may be considered a lower-level job today, ask yourself what happened to the stock broker? When’s the last time you talked to one or even heard of one? Jobs ebb, flow, and disappear. The importance of a function today is not equivalent to the importance of that same function tomorrow, and it never will be.

Humans have three core capabilities with which robots cannot compete: creativity, community, and empathy. As we enter the Automation Age, where the fear of robots replacing human work is likely to come true, those three skills will enable the future of human productivity. The last of the three, empathy, should well be considered the most important.

Empathy is what most makes us human – the capacity for mutual understanding. As the Automation Age eliminates rote and some not-so-rote tasks, it will create an opportunity for humans to capitalize on empathy. The manifestation of empathy in industry is through unique and memorable customer service, no matter the business. Welcome to the Empathy Economy.

The Empathy Economy is an intentional spin on the Sharing Economy. Just as the Sharing Economy was a byproduct of a super connected world via the Internet and smartphones, the Empathy Economy will arise through the result of job loss from automation. Uber, Airbnb, WeWork, and countless other business have changed the way humans think about asset ownership and even asset leasing. If users own assets, they want to get more out of them. If users need assets, they want instant access to them on demand without the burden of ownership. The Sharing Economy, as with all functional economies, is efficient in matching two complementary desires. The Empathy Economy will similarly match humans or businesses who desire empathic services with those willing to offer them.

We see 3 core opportunities within the Empathy Economy:

  1. Services that augment human empathy: For example, a lightweight CRM tool that enables employees to instantly recognize customers when they walk in the door, remember details about their lives, and know their preferences for service at the business.
  2. Services that build empathy: For example, a simulated environment that puts trainees through various situations to help them understand why another person feels a certain way and how to best serve them.
  3. Marketplaces that match buyers and sellers of empathy: For example, a platform that makes freelance customer service experts available for various tasks that might require a human touch to differentiate and enhance a particular service.

Today’s businesses must adopt automation technologies and embrace the Empathy Economy simultaneously by leveraging empathic customer service specialists as the face of their automated tools. In other words, people will act as a truly human skin on the work being produced by robots.

In the future, H&R Block will leverage AI to automate every customer’s taxes, but it’s also likely that they’ll need a human, who may only have cursory knowledge about accounting, present the sensitive reality that a customer owes the government a few thousand dollars in taxes; or perhaps the joy that they’ll be getting a few thousand dollars in refund. Either way, the human presentation creates a differentiated customer experience that can be distinctly H&R Block. Using only automation as their selling point, which every other tax prep service will also have and may only vary slightly, will necessitate a race to the bottom in price. In this example, H&R Block could benefit by adopting services that help augment and build empathy as the core skill of their customer service specialists.

Another outcome of the Empathy Economy could be Target leveraging a marketplace for freelance workers with specific product expertise and high empathic qualities to deliver orders to local customers with personalized service. Similar to the tax example, this moves the discussion away from price towards experience, which can command a premium.

You may be wondering why empathy is the greatest opportunity in the triumvirate of uniquely human traits. Creativity and community already exist in a structured sense in our societies. Creativity has always been a democracy, but the Internet made the distribution of creativity available to all. There are numerous ways, both online and offline, to share creativity and get paid for it, YouTube and Patreon as examples. These platforms will only become more important in the Automation Age. As for community, traditional institutions provide this now – governments, churches, schools, local businesses, etc. Technology will help these institutions continue to evolve with automation; however, trusting relationships between people will remain the heart of community because, by definition, it has to.  Empathy doesn’t yet seem to have a defined structure for application in our world. We know it’s important and the best businesses find ways to implement empathy into their culture, but it’s still a nebulous, unmeasurable thing. The Empathy Economy will change that.

It’s cliché to say that empathy is in short supply today because every generation probably has the same sentiment. The good news is that automation will force humans to be more human, and the Empathy Economy will create opportunities for humans to monetize a uniquely human capability. True empathy isn’t easy, but it’s the most powerful expression of humanity. In a world full of robots, empathy can only become more valuable.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Do You Have What It Takes to Be a Great Founder?

Every VC says they only invest in great founders, but the majority of venture-backed businesses still end in relative failure. Does that mean we as VCs are just bad judges of founders or do we not know what great founders look like? This is a question we’ve obsessed over since we started Loup Ventures — trying to define what makes a great founder and how to test for it. It’s hard. Great founders come from a host of different backgrounds, educations, genders, ethnicities. We’ve identified 10 traits across two categories that make great founders at the seed stage: Innate and Dynamic.

Innate Qualities of a Great Founder

Innate traits are character elements that are difficult to impossible to learn — either the founder has them or they don’t. Regardless of the type of business a founder starts, there are five imperative innate traits for all great founders:

  • Intelligence
  • Integrity
  • Commitment to suffering
  • Focused curiosity
  • Resourcefulness

Warren Buffett has talked about a few of these traits as things he looks for in his managers. Naval Ravikant has also talked about a few of them, so they shouldn’t come as much of a surprise. Intelligence is probably the most obvious of the innate traits. To start a valuable company, a founder must have some kind of smarts because intelligence leads to interesting insights about a market (see the next section). These insights translate into vision, which is the only truly defensible element and most important asset of any startup business. Vision is how an entrepreneur attracts talent and creates strategy.

 

Pure book smarts matter, but emotional intelligence is important too. A founder has to deeply understand his or her customers to deliver products they want, not just products the founder wants to build. A founder also has to deeply understand his or her employees and what motivates them to sustain high levels of productivity.

Integrity is the current buzz word in the startup world. We used to think about integrity as honesty, but that doesn’t seem to fully encompass the spirit of the trait. Honesty is a requirement because it means the founder learns from his or her mistakes. Dishonesty assumes problems are someone else’s fault, which means it’s impossible to learn. Ownership is a popular modern term for honesty – taking responsibility for things that happen whether they’re purely in your control or not.

The interesting component about integrity as it relates to startups is that great founders need to be willing to break rules to build valuable businesses. However, there’s a line between what’s acceptable and what’s not, and sometimes it’s blurry. Salesforce.com hired fake protestors to disrupt a Siebel conference in its early days. Clever guerilla marketing. The cases of Hampton Creek, Theranos, and Zenefits are clearly in the unacceptable camp. The ride sharing legal disputes are blurrier, although we agree that the laws are outdated and ride sharing is a significant net positive to the world. In any case, dishonesty and unethical behavior are contagious, so integrity must come from the top and be a guiding light for any startup.

The third quality of great founders is a commitment to suffering for at least five years. This might sound more extreme than necessary, but starting a company is a rollercoaster of suffering. You need to be comfortable with hearing no over and over and not let that destroy your will. You need to be able to withstand low periods that are inevitable — unexpected customer or employee losses, investor rejections, tax bills, fights with cofounders. Entrepreneurs don’t necessarily need to revel in difficulty, but it helps. We like to track the number of times we hear no during the week to reduce the negative reinforcement of it.

Why five years of suffering? It usually takes at least two years before you have any reasonable traction to show that your business might be working, then another few years of driving growth to create something that looks like a moat. Then you can afford to breathe. A little.

Focused curiosity might seem like an oxymoron, but curiosity that is targeted at a specific market leads to a commitment to testing new things. Testing new things leads to new business opportunities and products. Curiosity may be particularly necessary for seed stage founders (our focus) because their businesses are so nascent and require constant iteration. A lack of curiosity at the early stage leads to stagnation, which leads to death.

An early stage startup is an unending series of challenges. This is doubly true for first time founders who not only have to figure out how to deliver their specific offering to market, but how to operate a business in general. The final innate trait, resourcefulness, gives founders the ability to thrive in the face of persistent tests. A great founder is not one that says he or she couldn’t do something because they didn’t have enough capital or it was too difficult. They figure it out and keep figuring it out.

Dynamic Qualities of a Great Founder

Where the innate traits are binary and fixed, the dynamic traits of a great founder are five qualities that exist on a spectrum and evolve over time:

  • Market insight
  • Operational capability
  • Product sense
  • Growth
  • Leadership

Market insight is our term for the popular “founder/market fit.” What we want to see from a founder is that he or she has spent a lot of time thinking about and experimenting on a problem they’ve identified. In that sense, market insights are a byproduct of the innate intelligence trait being applied to a specific problem over a length of time. Founder/market fit to us implies that the founder has spent time involved in a market, thus the fit; however, prior market experience isn’t necessary for great founders. Jeff Bezos didn’t have founder/market fit when he started Amazon. He never ran a bookstore before, but he had a market insight about the Internet changing the way people shopped. The founders of Uber never worked in the livery business, but they had an insight about mobile changing the way people arranged transport. Airbnb is another example, and there are many others.

The other four traits are relatively straight forward business-related qualities. Operational capability is the founder’s ability to deliver their product or service and serve customers. Product sense is the founder’s ability to create a product or service that unexpectedly delights consumers. Product sense is what enables a founder to reach product/market fit. Growth is the founder’s ability to market and sell the product or service. Leadership is the founder’s ability to organize his or her team to meet objectives.

All five of these traits work in conjunction with one another, and all five are necessary for an early stage founder to possess in some degree. However, numerous factors influence the relative importance of the dynamic qualities of a founder. In other words, some of the dynamic traits need to be more developed depending on type of the founder’s company. For example, in a highly social company, a founder’s product sense seems to matter more than any other trait because user growth will have to be organically rapid for the company to service. The immediate experience of the users will be what keeps them engaged and sharing the product with others. An enterprise founder should require stronger growth capabilities to directly sell their B2B product, software or otherwise. Hardware companies tend to need stronger operational capability given the manufacturing requirements of their product.

The above observations were specific to seed stage companies, but stage of the investment also impacts the relative importance of the dynamic qualities in a founder. At the A/B round, product should be somewhat established, so market insights and growth might matter more as the founder tries to leverage his or her unique vision into some sort of durable advantage. In a pre-IPO or public company, the importance of leadership matters significantly more because of the likely larger number of employees at the company.

If You’ve Got It, Go for It

It’s boring to hear every VC say they only fund great founders, but it really is true, and their criteria probably isn’t much different from ours. Early stage companies are extremely fragile. VCs obsess over the quality of founders because it’s one of the few variables we can control. Recognizing these qualities in oneself is also an important variable an entrepreneur can control. Whether you’re running a small business or hoping to build the next Google, you must have all the innate traits and the correct balance of dynamic traits to be great. If you know you have them, then focus on your goal and be great. Hopefully we can help you along the way.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Manifesto

The Future Perfect: Rediscovering Utopia

Technology ruined our utopia. When did humans have it better than the dawn of time? We were born with everything and nothing. The entire world was ours. Since everyone had nothing, everyone had everything. We had no property, no houses. We were free to roam and inhabit as we pleased. We only worried about survival — finding enough food and avoiding dangerous predators. We didn’t have to worry about 401(k)s or what car the neighbors just bought. There wasn’t a 1 percent or 99 percent. We didn’t have politics. We just had survival. Humanity at its purest. Then invention doomed us. It was innocent at first. Innovation made it easier to survive. Food and safety became essentially guaranteed, so we needed to find other things to define our lives. Then inventions became those things. Things not for survival, but for status. For having something someone else didn’t. For benefitting unequally based on that ownership. For handing down to the next generation so they didn’t start with nothing. Things became the new goal of survival and they defined our differences. People who had things treated people without them differently. We went to war with others who had things we wanted.

Now most of us are born with nothing. We have to earn everything, buy everything. We’re trapped in a system that forces us to chase things that maintain our differences. We innovated ourselves out of utopia and into industry, and innovation is the only way to get our utopia back.

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