Read more about how we’re thinking and where we’re investing here.

Debt funding is an interesting option for start-ups in two scenarios: you can increase your funding base while times are good in order to maximize growth or you can use it stretch your runway when equity raises are tougher (or you don’t want to price your equity). But as the equity funding market is cooling down, we see the impact rippling over to the venture debt market as well. To understand this trend, we need to look at the two kinds of venture debt players in the start-up landscape today: <ol> <li style="font-weight: 400;"><span style="font-weight: 400;">Specialized debt funds (e.g. <a href="http://www.wellingtonfund.com/">Wellington</a>, <a href="http://westerntech.com/">WTI</a>, <a href="http://vistaracapital.com/">Vistara</a>) that provide debt based on the start-up’s ability to pay back that debt through either cash flow or - if things don’t go that well - the liquidation value (e.g. assets)</span><span style="font-weight: 400;"> </span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">A number of banks that are focused on start-ups (<a href="http://www.svb.com/">SVB</a>, <a class="zem_slink" title="Comerica" href="http://www.comerica.com/" rel="homepage">Comerica</a>, etc.) that provide venture debt to a start-up often with the expectation that the start-up can pay back that debt with its next round of equity financing. These venture debt providers often consider the fundraising strength of the start-up, including the brand of the existing investors.</span></li> </ol> <span style="font-weight: 400;">When the equity financing market was hot, the banks got much more aggressive in handing out venture debt: they wrote larger cheques, made their loans cheaper, got more creative in lending, and extended credit to companies in earlier stages. As funding rounds came together faster and faster, for larger and larger amounts, this second group of venture debt providers was more than happy to provide bigger debt amounts on top of the equity raises. </span> <span style="font-weight: 400;">At the same time, many of the more traditional venture debt providers found themselves priced out of the market. It became increasingly risky to provide debt to companies that were growing quickly, but also had very high burn rates and sometimes unsustainably low gross margins. And, equity markets were providing cheap alternatives for raising capital. </span> <span style="font-weight: 400;">Now that the equity funding party has stopped (or at least calmed down), the banks are starting to reverse course. They’re now asking start-ups to refinance their venture debt and/or they’re placing very restrictive terms on the debt. As a result, start-ups that have relied on venture debt might feel a bit of a squeeze over the next year or so. </span> <span style="font-weight: 400;">Venture debt can be an important complement to a start-up’s financing strategy, especially after you have found product-market fit and you know how to scale sales &amp; marketing. Before that, there are too many unknowns and debt can be dangerous, in particular when markets turn like they have in the past few months.</span> &nbsp; <em>Thanks to <a href="https://twitter.com/startupcfo">Mark Macleod</a> of <a href="http://www.surepathcapital.com/">SurePath Capital</a> for reviewing an earlier draft of this post.</em>

<span style="font-weight: 400;">Just a few years ago, if you wanted to do something big, you needed to go to Silicon Valley. It meant frequent flights or moving your company to San Francisco to raise money from Bay Area VCs.</span> <span style="font-weight: 400;">Times are changing, and these geographical barriers are beginning to break down. Waterloo has another unicorn with Kik. Toronto has become a hub for the blossoming machine intelligence market. And VC money is rolling into NYC: </span><a href="http://www.wsj.com/articles/venture-funding-gushes-in-new-york-city-1452834060"><span style="font-weight: 400;">NYC companies received 5.95 billion</span></a><span style="font-weight: 400;"> in financing in 2015 (with 395 deals).</span> <span style="font-weight: 400;">At Version One, we’ve always been geographically agnostic, with investments ranging from SF to Halifax, Edmonton to NYC. Over the past month, I’ve spent a lot of time in NYC, Toronto, and Ottawa for board meetings, conferences, meetings with our founders, re-connecting with co-investors, and meeting new entrepreneurs. </span> <span style="font-weight: 400;">A few years ago, Boris wrote that something </span><a href="https://www.versionone.vc/something-special-is-happening-in-the-toronto-waterloo-area/"><span style="font-weight: 400;">special was happening in the Toronto-KW corridor</span></a><span style="font-weight: 400;"> (for those of you non-Canadians, that would be like SF and the Valley). After this month’s travels, I truly believe that these east coast ecosystems are more vibrant than ever.</span> <span style="font-weight: 400;">Yet, having a vibrant ecosystem to seed early stage startups is one thing. There’s still considerable debate on how possible it is to build big companies outside the Bay Area.</span> <span style="font-weight: 400;">If we try to dissect the magic of Silicon Valley, I think there are five key factors at play:</span> <ol> <li><span style="font-weight: 400;"><strong>Great schools</strong>. The Bay Area has powerhouses like Stanford and UC Berkeley for sourcing talent.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Great senior talent</strong>. You’ve got a great number of senior level talent in engineering, sales, marketing, etc. running around the Bay Area.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Great value-add capital</strong>. The Bay Area is home to smart and strategic investors that contribute far more than just dollars.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Great exits</strong>. Success stories increase everyone’s drive and expectations. In addition, with giants like Intel, Google, Apple, Facebook in their backyard, Bay Area startups are more visible for acquisition.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Great collective ambition</strong>, which is driven by a healthy underlying economy (much more on this below…)</span></li> </ol> <span style="font-weight: 400;">Points #2, #3 and #4 are part of a cycle that continues to be reinforced over time. This means that building a big company in a less mature ecosystem requires #1 and #5 at a minimum. The first point on schools is pretty self-explanatory. For example, the University of Waterloo is a top-ranked engineering school known for cutting edge research in quantum physics and nanotechnology. But what about collective ambition? </span> <b>The Power of Collective Ambition</b> <span style="font-weight: 400;">One of my favourite Paul Graham essays is on </span><a href="http://paulgraham.com/cities.html"><span style="font-weight: 400;">Cities and Ambition</span></a><span style="font-weight: 400;">.  It’s an oldie but goodie that I highly recommend reading or re-reading. In essence, he writes that every city has a collective drive: </span> <p style="margin-left: 40px;"><i><span style="font-weight: 400;">Great cities attract ambitious people... In a hundred subtle ways, the city sends you a message: you could do more; you should try harder. The surprising thing is how different these messages can be.</span></i></p> <span style="font-weight: 400;">For example, Graham describes that </span><span style="font-weight: 400;">the “message” of NYC is to be richer; of Boston (Cambridge), to attain knowledge; of LA, to be famous; of DC, to boost your network; of SF, to live better; of the Valley, to be powerful (though he argues that this message is now the one in SF considering all companies are moving up the peninsula).  </span> He also goes on to write: <p style="margin-left: 40px;"><i><span style="font-weight: 400;">What cities provide is an audience, and a funnel for peers. These aren't so critical in something like math or physics, where no audience matters except your peers, and judging ability is sufficiently straightforward that hiring and admissions committees can do it reliably. </span></i></p> <p style="margin-left: 40px;"><i><span style="font-weight: 400;">It's in fields like [...] technology that the larger environment matters. In these the best practitioners aren't conveniently collected in a few top university departments and research labs—partly because talent is harder to judge, and partly because people pay for these things, so one doesn't need to rely on teaching or research funding to support oneself. [...] It helps most to be in a great city: you need the encouragement of feeling that people around you care about the kind of work you do, and since you have to find peers for yourself, you need the much larger intake mechanism of a great city.</span></i></p> <span style="font-weight: 400;">It really takes a village to build a company. Ambition and talent are not unique to the SF Bay Area; my travels over the past month proved this over and over. However, it is important to recognize the advantage of a stronger force driving the collective population to grow together. If you’re not in one of these major metropolises that Graham wrote about (say, Seattle, Toronto, Chicago, Boulder…), what’s your city’s collective drive? What are your peers and environment pushing you to be or do?</span> <span style="font-weight: 400;">I believe you can build a great company anywhere, as long as you have a stream of talent and collective drive (regardless of what the driving force of that ambition is, and it’s probably driven by the underlying industry in the area). Going forward, every time we meet a company that is not from an area we’re familiar with, I’ll ask myself “what’s the collective ambition of this city?” because every startup needs the support of its surroundings while we can’t physically be there.   </span>

Running a start-up is profoundly different than running a big company. When you’re small, founders are close to the action and can make sure all the important things happen. But as a start-up scales, founders can’t have their hands in everything: many companies lose focus on the customer; decisions get bogged down; and there are hiring mistakes. We’ve all seen these things happen to good start-ups. <span style="font-weight: 400;"><a class="zem_slink" title="Amazon" href="http://amazon.com/" rel="homepage">Amazon</a>’s magic is that it’s a behemoth of a company that still operates like a founder-driven start-up in several key areas. This is partly because Bezos has a strong cultural influence throughout the company. But, he also developed some unique tools to institutionalize his core values in the company. For example…</span> <p style="padding-left: 30px;"><strong>1. Customer Focus</strong></p> <span style="font-weight: 400;">Amazon has a unique product development process: before starting any new project, the product manager</span><a href="http://www.businessinsider.com/heres-the-surprising-way-amazon-decides-what-new-enterprise-products-to-work-on-next-2015-3"> <span style="font-weight: 400;">writes an internal press release</span></a><span style="font-weight: 400;"> ‘announcing’ the product. This working backwards approach helps the team fully understand the product’s value proposition to its customers (e.g. what problem is it solving). A former director at Amazon</span><a href="https://www.quora.com/Amazon-company-What-is-Amazons-approach-to-product-development-and-product-management"> <span style="font-weight: 400;">described the approach</span></a><span style="font-weight: 400;"> this way: “</span><span style="font-weight: 400;">We try to work backwards from the customer, rather than starting with an idea for a product and trying to bolt customers onto it.</span><span style="font-weight: 400;">”</span> <span style="font-weight: 400;">If the team can’t come up with a compelling press release, they either need to refine their thinking or maybe the product just isn’t worth making in the first place.</span> <span style="font-weight: 400;">While distilling the customer needs and benefits in a concise press release is a great exercise, there’s still the question of how the product team come to truly understand these customer needs and challenges. Amazon keeps managers close to the customer by having them</span><a href="https://www.versionone.vc/3-lessons-customer-obsessed-company/#ixzz48dQlZbKj"> <span style="font-weight: 400;">regularly work customer service</span></a><span style="font-weight: 400;">. We had a similar policy at <a class="zem_slink" title="AbeBooks" href="http://www.abebooks.com" rel="homepage">AbeBooks</a>.</span> <p style="padding-left: 30px;"><strong>2. Organization</strong></p> <span style="font-weight: 400;">Amazon’s</span><a href="http://www.fastcompany.com/50106/inside-mind-jeff-bezos"> <span style="font-weight: 400;">Two-Pizza rule</span></a><span style="font-weight: 400;"> is pretty widely known: if a project team can eat more than two pizzas, then it’s too large. This means they break up a big project into smaller projects, where the smaller project teams can stay nimble and be less subject to complex governance.</span> <span style="font-weight: 400;">The supporting piece is that every product at Amazon should have an API, </span><span style="font-weight: 400;">just as if it were developed for an external client. This decouples the speed of development between different product teams, and offers a clean hand-off between the two.</span><span style="font-weight: 400;"> Its Bezos’ vision of a decentralized company where small groups can innovate and move quickly independently of everyone else.</span> <p style="padding-left: 30px;"><b style="line-height: 1.5;">3. Hiring</b></p> <span style="font-weight: 400;">When a company reaches the scale when it’s no longer possible for the founder to be hands-on in each decision, it better have good people in place. </span> <span style="font-weight: 400;">Early on, Bezos implemented “bar raisers” at Amazon. These are Amazon employees who are skilled evaluators and interview job candidates. Bar raisers can veto any candidate, even for positions that are completely out of their area of expertise. Bezos has said this program</span><a href="http://www.wsj.com/news/article_email/SB10001424052702304753504579285133045398344-lMyQjAxMTA0MDAwNzEwNDcyWj"> <span style="font-weight: 400;">helps weed out the “cultural misfits”</span></a><span style="font-weight: 400;"> at Amazon and makes sure the company makes good hiring choices by forcing several diverse employees to sign off on a candidate.</span> <span style="font-weight: 400;">Another important hiring tactic is Amazon’s ability to keep acquired founders on board. For example, Mike George joined Amazon in 1998 through Junglee’s acquisition. He has since become Bezos’ go-to person for many new initiatives: he launched the marketplace, ran payments, and is now heading up the Alexa unit.  </span> <span style="font-weight: 400;">Keeping acquired founders on board is particularly tough: </span><span style="font-weight: 400;">someone founds a company because they want to be a leader, not a follower. Entrepreneurs have a difficult time when the acquiring company tries telling them how to run the business they have created and grown. Amazon has been successful at keeping founders around by giving them lots of latitude.</span> <span style="font-weight: 400;">For founders of early-stage start-ups: you may be thinking more about getting your product out the door or acquiring your first 1,000 or 100,000 customers rather than any challenges associated with scaling. But some of these tools can be really important early on (20-30 employees). It’s never too early to start thinking about implementing the right processes and tools that will help your company grow without losing its focus. </span>

Six months ago, we published<a href="https://www.versionone.vc/marketplace-handbook/"> A Guide to Marketplaces</a>. Marketplace companies comprise an important part of our portfolio and investment thesis and we recognized the shortage of content out there specifically geared toward marketplace startups. We compiled a lot of the insights we learned from working with great marketplace companies and wrote a handbook. It was our first experience with this kind of project and we weren’t sure what the response would be. We’ve been so surprised by the reception: both the <a href="https://www.versionone.vc/marketplace-handbook/">handbook</a> and <a href="https://www.versionone.vc/marketplace-kpi/">marketplace KPI dashboard</a> have been downloaded over 20,000 times.  The guide has been <a href="https://www.dropbox.com/s/asovoreds7g24i1/Marketplace%20guide%20book%20(Japanese).pdf?dl=0">translated into Japanese</a> and a robot even took on the handbook on <a href="https://medium.com/@fredzannarbor/robot-author-tears-down-rebuilds-version-one-s-a-guide-to-marketplaces-c67731fff400#.7owlg7441">Medium</a> (we’re happy to report that our version came out on top). Today, we’re announcing the release of the <a href="//www.slideshare.net/AngelaTranKingyens/a-guide-to-marketplaces-61925260">Guide to Marketplace deck</a>, where we summarized the original guide into a series of slides for a faster read and reference. <span style="font-weight: 400;">You can download the slide deck <a href="//www.slideshare.net/AngelaTranKingyens/a-guide-to-marketplaces-61925260">here</a>. And if you’re interested in the full version of the handbook, it’s available as a </span><a href="https://www.versionone.vc/wp-content/uploads/2015/11/Marketplace-Handbook-11-08-2015.pdf"><span style="font-weight: 400;">PDF</span></a><span style="font-weight: 400;"> or </span><a href="https://www.dropbox.com/s/ze84q6pvquroi8n/Marketplace%20Handbook-Nove%208%202015.epub?dl=0&amp;preview=Marketplace+Handbook-Nove+8+2015.epub"><span style="font-weight: 400;">ePub</span></a><span style="font-weight: 400;">. </span> <p style="text-align: center;"><iframe style="border: 1px solid #CCC; border-width: 1px; margin-bottom: 5px; max-width: 100%;" src="//www.slideshare.net/slideshow/embed_code/key/3jEK6cXnusp0Tv" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" allowfullscreen="allowfullscreen"> </iframe></p> <p style="text-align: left;">Special thanks to <a href="https://www.linkedin.com/in/grant-ognibene-3773aa28">Grant Ognibene</a> who has been interning with us over the past couple of months - he did much of the curation!</p>

Amazon’s Annual Letter to Shareholders has become a must-read for entrepreneurs, investors, and business leaders – and the recent <a href="http://www.sec.gov/Archives/edgar/data/1018724/000119312516530910/d168744dex991.htm">2015 letter</a> provides great insights into how Jeff Bezos thinks and how one of the most successful companies on Earth operates (this year, Amazon became the fastest company ever to reach $100 billion in annual sales). Readers of this blog know that I am a big fan of Jeff Bezos and have taken <a href="https://www.versionone.vc/stubborn-on-vision-flexible-on-the-details/#ixzz46qB0WXem">several key lessons</a> from him over the years. The one thing about Amazon is that they have always been an invention machine. Their ability to innovate is mainly due to two things: the way they look at risks and the way they make decisions at the company. Jeff talked about both in his letter: <strong>Risk taking: you need to be prepared to lose a lot if you want to win big</strong> Jeff talks at great lengths about the importance of failure: “failure and invention are inseparable twins.” To get those outsized returns, you need to be willing to swing-for-the-fences and embrace the string of failed experiments that come along the way. In his words: <em>“One area where I think we are especially distinctive is failure. I believe we are the best place in the world to fail (we have plenty of practice!), and failure and invention are inseparable twins. To invent you have to experiment, and if you know in advance that it’s going to work, it’s not an experiment. Most large organizations embrace the idea of invention, but are not willing to suffer the string of failed experiments necessary to get there. Outsized returns often come from betting against conventional wisdom, and conventional wisdom is usually right. Given a ten percent chance of a 100 times payoff, you should take that bet every time. But you’re still going to be wrong nine times out of ten. We all know that if you swing for the fences, you’re going to strike out a lot, but you’re also going to hit some home runs. The difference between baseball and business, however, is that baseball has a truncated outcome distribution. When you swing, no matter how well you connect with the ball, the most runs you can get is four. In business, every once in a while, when you step up to the plate, you can score 1,000 runs. This long-tailed distribution of returns is why it’s important to be bold. Big winners pay for so many experiments.”</em> In this respect, making investment decisions as a corporation is very similar to making investment decisions in venture capital. Earlier this month, <a href="http://avc.com/2016/04/losing-money/">Fred Wilson wrote</a> about the importance of taking risk, having your share of mistakes and learning from your losers. He summed it up: “Making bad investments is humbling, frustrating, annoying, time sucking, and most of all, a big part of the VC business. I look for VCs who have done it a lot, have done it with grace and respect, and continue to learn from it. They are the best VCs to work with.” <strong>Decision making: how to stay nimble as you scale</strong> Now that Amazon is a giant among giants, they face the same challenges plaguing larger organizations: slowness, aversion to risk, and lower rates of innovation. Jeff discussed this challenge in terms of the decision-making process and how much weight to put on each decision: because not every decision is an irreversible, one-way door. <em>“Some decisions are consequential and irreversible or nearly irreversible – one-way doors – and these decisions must be made methodically, carefully, slowly, with great deliberation and consultation. If you walk through and don’t like what you see on the other side, you can’t get back to where you were before. We can call these Type 1 decisions. But most decisions aren’t like that – they are changeable, reversible – they’re two-way doors. If you’ve made a suboptimal Type 2 decision, you don’t have to live with the consequences for that long. You can reopen the door and go back through. Type 2 decisions can and should be made quickly by high judgment individuals or small groups.</em> <em>As organizations get larger, there seems to be a tendency to use the heavy-weight Type 1 decision-making process on most decisions, including many Type 2 decisions. The end result of this is slowness, unthoughtful risk aversion, failure to experiment sufficiently, and consequently diminished invention. We’ll have to figure out how to fight that tendency.”</em> In the early stages when you’re working hard to get to product-market fit, neither of these two points come into play much: practically everything is an experiment and risk. But as you scale up, remember these lessons from Amazon. Their home runs were scored alongside a long string of experiments and strikeouts.

<span style="font-weight: 400;">The average </span><a href="http://money.cnn.com/2013/04/09/news/economy/millennial-job-hopping/"><span style="font-weight: 400;">25-year-old has already worked 6.3 jobs</span></a><span style="font-weight: 400;">, and will have 12-15 jobs before their working career is finished. The portrait of the job-hopping millennial is a stark difference to Gen X and Boomer workers who may have stayed with the same job and employer for decades. Another </span><a href="https://www.psychologytoday.com/blog/diverse-and-competitive/201503/are-millennials-more-likely-switch-jobs-and-employers"><span style="font-weight: 400;">study</span></a><span style="font-weight: 400;"> found that millennials have almost twice as many job and organizational changes as Gen Xers, and almost three times as many job changes as the Baby Boomers and Matures.</span> <span style="font-weight: 400;">With the creation of online job boards, there’s unprecedented visibility into all the opportunities around us. This means we’re more likely to question whether we’re working on the “best” thing at the best place at any given time. And now more than ever, many of us have the </span><span style="font-weight: 400;">luxury of working on what we </span><i><span style="font-weight: 400;">want </span></i><span style="font-weight: 400;">to and not just because we have to.</span> <span style="font-weight: 400;">Given the increased movement in the overall job market today, it’s important to look at how we make decisions when it comes to work. The key question is: when are we happy with our jobs and when are we not?  </span> <span style="font-weight: 400;">I believe the answer is rooted in learning: </span><i><span style="font-weight: 400;">we are happiest with and engaged in our work when our personal learning profile matches that of our jobs and tasks at hand.</span></i> <b>Align the learning profiles of employees and jobs</b> <span style="font-weight: 400;">I often characterize an individual’s learning profile in three dimensions:</span> <ul> <li style="font-weight: 400;"><b>Attitude</b><span style="font-weight: 400;">: your passion for learning</span></li> <li style="font-weight: 400;"><b>Capacity</b><span style="font-weight: 400;">: your raw intelligence, IQ, and talent for learning</span></li> <li style="font-weight: 400;"><b>Impact</b><span style="font-weight: 400;">: your ability to apply the theories of what you learn into practice</span></li> </ul> <img class="wp-image-2578 aligncenter" src="https://gregburnison.ca/code/version1v/images/web.001.png" alt="web.001" width="350" height="187" /> <span style="font-weight: 400;">Similarly, a job’s learning profile can be characterized at the very least by:</span> <ul> <li style="font-weight: 400;"><b>Challenge</b><span style="font-weight: 400;">: What does the on-boarding process look like and are you continuously challenged thereafter?  The graph below illustrates different learning curves as a function of time.</span></li> </ul> <span style="font-weight: 400;"><img class=" wp-image-2572 aligncenter" src="https://gregburnison.ca/code/version1v/images/knowledge-418x300.png" alt="knowledge" width="382" height="274" /></span> <ul> <li style="font-weight: 400;"><b>Depth</b><span style="font-weight: 400;">: Are you learning about various subjects that touch many parts of the organization or are you becoming an expert on a particular topic?</span></li> </ul> <img class="size-medium wp-image-2574 aligncenter" src="https://gregburnison.ca/code/version1v/images/impact.001-500x239.png" alt="impact.001" width="500" height="239" /> &nbsp; <span style="font-weight: 400;">My hypothesis: <em>people remain engaged when their learning profile matches that of their job.  </em></span> <b>The takeaway for founders and hiring managers</b> <span style="font-weight: 400;">So, what’s the implication for founders and hiring managers? We all understand the high costs of recruiting, onboarding, and knowledge transfer associated with high employee churn rates.</span> <span style="font-weight: 400;">Can employers </span><span style="font-weight: 400;">assess a candidate based on his or her</span><span style="font-weight: 400;"> learning profile in order to improve employee satisfaction and cut down turnover?</span> <span style="font-weight: 400;">Here are a few hiring examples to consider:</span> <b>Case 1: Over-optimizing for sheer intelligence</b> <span style="font-weight: 400;">This occurs when you hire someone who loves learning and has a great aptitude for it, but you match him or her to a job with little challenge or depth.</span> <span style="font-weight: 400;">A few years ago, when at Insight, a hiring manager told me, “Ange, I don’t need the ‘crème de la crème’ data scientist.  I just need someone who will get the job done”.  In retrospect, I think this manager meant, “I need a competent and efficient person who would be happy with less intellectually-stimulating work every day.”</span> <span style="font-weight: 400;">While it’s natural for us to want to hire the “10x employee”, at what times is this not the best strategy? Is it even possible or sustainable to keep the smartest, highest-desire-to-learn individuals around given that there is also a “cost of switching” within your own company?  How do you systematically engage your </span><a href="https://medium.com/greylock-perspectives/the-mitochondria-in-startups-dc6c33e09d99"><span style="font-weight: 400;">mitochondria</span></a><span style="font-weight: 400;"> employees (Sarah Tavel’s description of employees who add value beyond their job description and responsibility)?</span> <img class=" wp-image-2575 aligncenter" src="https://gregburnison.ca/code/version1v/images/cases-1.jpeg" alt="cases 1" width="350" height="187" /> &nbsp; <b>Case 2: Assuming that people who are really smart want to take on the most challenging tasks  </b> <span style="font-weight: 400;">Just because someone has a great capacity to learn doesn’t necessarily mean that they want to be challenged daily. Some of the smartest people I know prefer to adopt a clock-in/clock-out mentality. There’s nothing wrong with this. At any given stage in life, we each have our own personal reasons and values for what work and life outside of work mean to us. Don’t assume that a smart person automatically wants the most challenging position available.</span> <img class=" wp-image-2576 aligncenter" src="https://gregburnison.ca/code/version1v/images/cases-2.jpeg" alt="cases 2" width="350" height="187" /> &nbsp; <b>Case 3:  Bringing in the specialist who loves the science more than the engineering</b> <span style="font-weight: 400;">We’re starting to see companies working on emerging technologies (VR, blockchain, drones/robotics, etc.) that are founded on hardcore mathematics and science.  As an another example, the excitement around messaging bots have founders looking for expertise in artificial intelligence and machine learning at leading research groups.  While academics can be strong candidates given their passion for and capacity to learn, it’s important to assess where they are on the “impact” scale:  do they enjoy applying their special powers, or do they prefer the rigour of developing more theory (where the latter may be counter to moving the needle for your fast-growing startup)?</span> <img class=" wp-image-2577 aligncenter" src="https://gregburnison.ca/code/version1v/images/cases-3.jpeg" alt="cases 3" width="350" height="187" /> &nbsp; These are just 3 cases; no doubt you can think of several more situations where a learning misalignment happens and may be costly to your organization.  It’s also important to note that there is no “good “ or “bad” profile in describing an individual along these axes.  This is simply a visualization of one’s preferences and hopefully, paints a picture of how differences in learning profiles and opportunities to learn at work may be synergistic or clash. <span style="font-weight: 400;">In all honesty, I don’t know how we can match someone’s learning profile to their job. There is a lot to figure out here: how to quantify something that is naturally “unquantifiable” and then measure job suitability and match it accordingly.  If I were ever to pursue a second PhD, I’m sure I’d end up working on this topic (I took a similar approach in my </span><a href="http://www.sciencedirect.com/science/article/pii/S0377221713006954"><span style="font-weight: 400;">Master’s thesis</span></a><span style="font-weight: 400;"> when I mapped people’s financial risk tolerance to their portfolio of stocks).  </span> While so many companies today are focused on solving the recruiting problem to combat employee churn, I’d love to meet people/startups who are tackling the problem of employee engagement based on learning in a scalable way.  At the very least, I’d like to know if anyone out there is on the same page with me when it comes to the importance of aligning learning profiles. Finally, I’m aware that other important parts of employment lead to churn, like company culture and values, financial compensation, etc. However, I truly believe that learning is an important aspect to this picture and the future of the workplace.

<span style="font-weight: 400;">In the past, we typically wait until the end of the year to recap what’s happened here at V1. But with a group of incredible startups doing great things, we’re determined to provide more frequent updates.</span> <span style="font-weight: 400;">If you’re not already familiar with the startups and founders making up the V1 portfolio, here’s a summary of some of this quarter’s news clippings. Keep in mind that these are just the things that have been announced publicly; there’s been a lot of cool stuff happening behind the scenes too.</span> <span style="text-decoration: underline;"><b>Funding and Follow-ons</b></span> <span style="font-weight: 400;">This past quarter, three of our portfolio companies closed funding rounds (we participated in all three):</span> <span style="font-weight: 400;">First, <strong>Booster Fuels</strong> raised a </span><a href="http://techcrunch.com/2016/01/28/booster-fuels-fills-up-your-car-while-youre-working-raises-9m-series-a-round/"><span style="font-weight: 400;">$9 million Series A</span></a><span style="font-weight: 400;"> from Maveron, Madrona Venture group, RRE Ventures, and V1. Booster partners with large businesses to offer on-demand gas fill-ups on their corporate parking lots. We don’t always like defining companies as the “Uber for X,” but if you think of Booster as the “Uber for gas,” you’ll get a good sense of what they do.</span> <span style="font-weight: 400;">There’s a lot of hassle involved with stopping at a gas station: looking for a station that’s on the same side of the road, waiting for an open fuel pump, getting out of the car, worrying about safety and cleanliness, etc. That’s why we believe there’s such a strong opportunity here: with Booster, you can park your car at work, request a fill-up on their app, and when you’re done for the day, your car is ready to go with a full tank.</span> <span style="font-weight: 400;">In other funding news, <strong>Front Desk</strong> </span><a href="http://www.geekwire.com/2016/front-desk-raises-3-5m/"><span style="font-weight: 400;">raised a $3.5 million round</span></a><span style="font-weight: 400;"> from existing investors: </span><span style="font-weight: 400;">Floodgate, Second Avenue Partners, V1, and Rich Barton. Front Desk is powering the personal services economy, helping providers manage their scheduling, payments, and admin from their mobile device. Whether you’re an owner of a gym or music school, Front Desk offers an easy way to keep track of your weekly appointments and billing. There are around five million businesses in the U.S. that sell personal services, so there’s a lot of potential here.</span> <span style="font-weight: 400;">And, <strong>Mattermark</strong> </span><a href="https://mattermark.com/mattermark-series-b/"><span style="font-weight: 400;">closed its Series B round</span></a><span style="font-weight: 400;">, with $7.3 million from Foundry Group and Jon Hallet, with participation from existing investors. CEO Danielle Morrill wrote a fantastic synopsis of Mattermark’s journey, from shutting down Referly and restarting as Mattermark to launching with a 12-week old prototype, raising their Series A, and evolving into a full sales intelligence platform. She’s always a tough writer to try to follow, so we’ll just point you to </span><a href="https://mattermark.com/mattermark-series-b/"><span style="font-weight: 400;">her own words and story</span></a><span style="font-weight: 400;">. There’s a powerful message for any of you who are currently experiencing the lower points in your own journey.  </span> <span style="text-decoration: underline;"><b>Portfolio companies in the news</b></span> <span style="font-weight: 400;">Beyond funding announcements, several portfolio companies made the news this quarter. <strong>Frank &amp; Oak</strong> </span><a href="http://en.louloumagazine.com/news/loulou-news/three-new-stores-for-frank-oak/"><span style="font-weight: 400;">is opening</span></a><span style="font-weight: 400;"> three different stores: a Surplus store in Quebec City and two new concept boutiques in Laval and Toronto. The Frank &amp; Oak experience will be front and center, for example, a bar and area dedicated to Frank &amp; Oak’s personal styling services, a barbershop, and lounge/coffee area.</span> <span style="font-weight: 400;"><strong>Shippo</strong> <a href="http://www.ecommercebytes.com/cab/abn/y16/m03/i17/s02">integrated with USPS ePostage</a></span><span style="font-weight: 400;">, making them one of only a few public APIs for purchasing US postage online. If you’re not familiar with Shippo, they’re a shipping API for ecommerce platforms and stores: stores can check rates across multiple carriers, get discounted shipping labels, track parcels, etc.</span> <span style="font-weight: 400;">In January, <strong>HandUp</strong> announced a </span><a href="http://blog.handup.org/posts/looking-back-reaching-1-million-donations-in-2015"><span style="font-weight: 400;">very important milestone</span></a><span style="font-weight: 400;">: they raised $1 million in donations from 3,375 donors. HandUp launched as a way to give directly to homeless people to meet important needs not covered by the basic system of care. In many cases, these needs are critical to escaping homelessness.</span> <span style="font-weight: 400;">And, <strong>Outreach</strong>, a </span><span style="font-weight: 400;">sales automation tool for SMB and enterprise organizations, was recognized as the </span><a href="https://ambition.com/blog/2016/02/25/inside-sales-software-guide-sales-acceleration/"><span style="font-weight: 400;">top-ranked sales automation/acceleration software</span></a><span style="font-weight: 400;"> by Ambition Sales.  </span> <span style="text-decoration: underline;"><b>Exits</b></span> <span style="font-weight: 400;">In February, <strong>Talentbuddy</strong> was </span><a href="https://blog.udemy.com/embracing-the-power-of-experiential-learning-through-talentbuddy-acquisition/"><span style="font-weight: 400;">acquired by Udemy</span></a><span style="font-weight: 400;">, an online learning and teaching marketplace headquartered in San Francisco. This is Udemy’s first acquisition and marks an important milestone toward accelerating the integration of coding exercises and strengthening the experiential learning capabilities for their 10 million+ students. </span><span style="font-weight: 400;">Talentbuddy founders, Octav Druta and Andrei Soare, joined on as Udemy employees. </span> <span style="text-decoration: underline;"><b>Our new investments and refined investment thesis</b></span> <span style="font-weight: 400;">We welcomed two new companies to our portfolio in Q1; both will be announced at a later date but fall into the themes we have been exciting about:  AI/ML/bots and vertical social networks.</span> <span style="font-weight: 400;">Earlier this year, we published a more </span><a href="https://www.versionone.vc/our-refocused-investment-thesis/"><span style="font-weight: 400;">focused investment thesis</span></a><span style="font-weight: 400;">: </span><b>we like to invest in businesses with potentially large network effects built around people and/or data.</b> <span style="font-weight: 400;">Network effects can </span><span style="font-weight: 400;">provide a long-lasting competitive advantage and be very capital-efficient. Connecting people and data over the web and mobile also creates something that wasn’t possible before – the end result is new and unique, not just something faster, cheaper, or better.</span> <span style="font-weight: 400;">Moving forward, we’re excited to meet great founders working on interesting ideas that leverage strong network effects – whether that’s on a marketplace, social, SaaS, or big data platform.</span>

One of the biggest challenges for first-time founders with little work experience is that they don’t always know what “great” looks like in every area required to build and run a successful business. Understanding “great” is one of the single most important levers to push your team to greatness, hire the best people possible for a specific job, and build a world-class organization. It’s hard to steer your company if you don’t have a clear picture of what your destination should be. But, does this mean you need to spend decades in every department of a company before you can launch your own business? Definitely not; there are several things you can do to gain a clearer picture of what great looks like. Here are a few: <strong>See as many candidates as possible</strong> When hiring for an important senior position, try to see many, many candidates. Talking with a wide range of people will help you better understand the landscape and how different candidates think differently about the job in question. You can also leverage your Board of Directors or investors to get a second opinion on leading prospects. <strong>Hire people who have already seen “great”</strong> It’s helpful to hire people from top-notch start-ups who have actually seen what great looks like. When I was running <a class="zem_slink" title="AbeBooks" href="http://www.abebooks.com" rel="homepage">AbeBooks</a>, my Director of Product Management came from <a class="zem_slink" title="Amazon" href="http://amazon.com/" rel="homepage">Amazon</a> and he had a completely different (and more ambitious) perspective on product and growth opportunities. <strong>Talk to top experts in a specific field</strong> At Version One, we connect some of our start-ups to world-class growth hackers, designers, and other leaders in their field. By spending a few hours with these kinds of experts, you’ll gain a better understanding of what’s possible and what you should strive toward in any given field. <strong>Get feedback and input from your peers</strong> Some of your peers may have already figured out what great looks like and the best practices to get there. At Version One, we try to facilitate these conversations through direct introductions (“you should talk to founder x, he/she has learned a lot in this space over the past few months”) as well various platforms to connect our portfolio founders: Slack, portfolio dinners and vertical-specific get-togethers. The bottom line is if you haven’t already seen great, you at least need to learn what it looks like.

We have all seen Jeff Bezos’ great quote on being <a href="http://www.forbes.com/sites/johngreathouse/2013/04/30/5-time-tested-success-tips-from-amazon-founder-jeff-bezos/#55b21eba3351">stubbornly flexible</a> at Amazon: <p style="padding-left: 30px;"><em>"We are stubborn on vision. We are flexible on details…. We don’t give up on things easily. Our third-party seller business is an example of that. It took us three tries to get the third-party seller business to work. We didn’t give up."</em></p> Whether you’re building a business or your own career, a long-term focus creates the most successful outcomes. And this requires two things: <ol> <li>You need a clear vision of where you want to go and the values that will guide you towards that place.</li> <li>You need to be opportunistic (aka flexible) when it comes to all the details of how to get there.</li> </ol> Looking back on my personal journey, I realize that I was firm on my vision (being an entrepreneur), but flexible on how to get here. As the oldest son of two pharmacists in Germany, I was expected to follow my parents’ footsteps - at least in terms of having a steady, long-term and successful career. But I always knew I wanted to be an entrepreneur. First, I tried to commercialize my parents’ hobby vineyard; then I tried to import cars. Neither were too successful. I was all set to begin a solid, executive-level job at a German telco in 1999, but it just didn’t feel right. I still wanted to build a business, and at that time there were tremendous opportunities around the Internet. Literally overnight, I decided to pass on the corporate job, telling my would-be employer that I needed to figure out the Internet thing. I co-founded <a class="zem_slink" title="JustBooks" href="http://www.justbooks.de/" rel="homepage">JustBooks</a>, which was bought by <a class="zem_slink" title="AbeBooks" href="http://www.abebooks.com" rel="homepage">AbeBooks</a>, which was <a href="http://techcrunch.com/2008/08/01/amazon-to-acquire-abebooks/">bought by Amazon</a> - all in all, an incredible entrepreneurial journey of 8 years from start to exit. It’s (relatively) easy to have a vision. Some of the details might evolve over time, but once you reach a certain level of maturity, you most likely know what you want to be as a business or in your career. But getting there is the hard part. What is a good opportunity and what’s a distraction? When should you stop banging your head against the wall and move on? Unfortunately, there are no easy answers to these questions. It ultimately comes down to good intuition. When building a career, you need this intuition to answer these questions. And when building a business, you need to hire leaders with good intuition to scale that decision making in the company.

Over the past few years, self-driving cars have received a lot of attention and the buzz has intensified this month with the announcement that <a href="http://techcrunch.com/2016/03/11/gm-buys-self-driving-tech-startup-cruise-as-part-of-a-plan-to-make-driverless-cars/">GM plans to acquire</a> San Francisco startup Cruise Automation for reportedly <a href="http://fortune.com/2016/03/11/gm-buying-self-driving-tech-startup-for-more-than-1-billion/">more than $1 billion</a>. When people talk about self-driving cars, the discussion typically centers around a few important topics: 1) <em>When will we see self driving cars on the market</em> (e.g. In January, <a href="https://medium.com/@scobleizer/don-t-worry-uber-lyft-drivers-self-driving-cars-won-t-take-your-job-for-at-least-a-decade-3b8c58a7f102#.t5mld12x0">Robert Scoble wrote</a> that we’re at least a decade out). GM’s acquisition of Cruise has some thinking that GM could add Cruise’s technology and have cars ready for market in the next couple of years. 2) <em>How will the market progress</em>: Will it be a gradual evolution starting with certain self-driving features to assist drivers like auto-parking, lane keeping assistance, radar-assisted cruise control, etc.? Or will it be a hard-switch over (Google-style) to cars that can drive around town without a human inside. 3) <em>What are the </em><a href="https://www.technologyreview.com/s/542626/why-self-driving-cars-must-be-programmed-to-kill/"><em>ethical questions surrounding autonomous cars</em></a> – such as how should a car be programmed to deal with an unavoidable accident: should it act to minimize the overall loss of life or try to protect the car’s occupants at all costs? To be sure, these are all important questions, but I’m most curious about the matter of how self-driving cars will change human behavior and society. For example, when we’re not forced to pay attention to the road, how will we spend all this newfound free time? Will we end up working more, where the car becomes another extension of the office? Will we spend more time on entertainment and social interactions? That’s probably the only way to push daily media consumption beyond today’s already high <a href="http://qz.com/416416/we-now-spend-more-than-eight-hours-a-day-consuming-media/">8 hours per day</a>. Or, will we take the time to look out the window, enjoy nature and people-watch? And, will self-driving cars impact where we live? If commuting becomes less of a nuisance, will people start moving back to the suburbs, reversing today’s urban trend? The invention of the automobile pushed us into the suburbs, but starting in 2011, the rate of urban population growth <a href="http://ideas.time.com/2013/07/31/the-end-of-the-suburbs/">outpaced suburban growth</a>. Now will self-driving cars push us back out to the suburbs once again? Lastly, the case for self-driving cars usually includes the idea that people will start sharing cars more and there will be fewer cars on the road. An autonomous driving system could become like public transportation at scale, with a self-driving car picking you up within minutes at any corner and dropping you off wherever you want to go, while you share the ride with a few other people that have a similar trip at that time. However, what if the enjoyment of not having to drive means that people get the convenience of public transport without having to sit next to the guy with the flu? And this means that instead of reducing the total number of cars on the road (and the associated traffic and environmental effects), we will see a dramatic increase of cars on the road? I don’t have the answers for these questions right now, but I’m certain that self-driving cars will create a profound shift in human behavior and society beyond what we’re thinking about today. &nbsp;

When <a href="http://www.nytimes.com/2016/03/16/world/asia/korea-alphago-vs-lee-sedol-go.html">DeepMind’s AlphaGo</a> defeated South Korean master Lee Se-dol, it was a historic stride for AI. The depth of this development, coupled with higher computing power and cheaper data storage, is moving AI into the mainstream. Perhaps the most popular application of AI today comes in the form of virtual assistants and bots, or “agents” as my good friend Shivon <a href="http://www.shivonzilis.com/machineintelligence">defines them</a>. An agent can schedule your meetings, manage your finances, book your travels, order your meals, and more. And even though these agents are typically focused on one specific task, it’s remarkable to consider how much progress we have made outsourcing mundane work for a fraction of the cost. At Version One, we get excited about the data network effects associated with AI and machine learning (ML): products and services become more valuable to users as more and more people use the service. Earlier this year, Boris introduced a <a href="https://www.versionone.vc/whats-your-data-strategy-defining-the-data-hierarchy/">data hierarchy</a> and wrote that building a defensible product requires access to unique user data. For virtual assistance, this unique data is user feedback and it’s absolutely core to a “smart” agent. In order to build a smarter agent that is capable of getting all the personalized preferences and nuances right, the agent needs to learn directly from its users. And for agents to learn most effectively, they require user trust:  trust in agents to make decisions and complete tasks on their behalf. Even more critical, users must be tolerant of mistakes that agents may make during the learning process. And this is the crux of the problem. I recently admitted to my other good friend <a href="http://www.iaventures.com/team/jesse">Jesse</a> that I have trust issues with my scheduling agent (n.b. at Version One, we use <a href="https://claralabs.com">Clara</a> and Jesse is an investor in <a href="https://x.ai">x.ai</a>). These trust issues mean that I heavily constrain Clara’s power. For example, I only let her schedule calls during specific time windows. On one hand, I’m pre-emptively minimizing any scheduling errors. But at the same time, I’m limiting the opportunities for Clara to learn. Ironically, as a user, I’m the one who is learning what I should and shouldn’t trust the AI for. <strong>If you are building an agent, ML is rooted in the trust of your users</strong> For the most part, mistakes by current agents are forgivable because we’re not yet outsourcing mission critical tasks. But what happens when agents aspire to handle more complex tasks and the associated cost of error increases? I imagine that users will further limit their agents’ power, making it difficult for the company building the agents to learn and create a great (and defensible) product. <p style="text-align: center;"><strong>User Trust &#8660; Smarter Agent</strong></p> Perhaps the only way to overcome this hurdle is to collect as much user feedback as possible, both actively and passively. Some examples: <ul> <li><em>Actively</em>: Ask for confirmation on a per-task basis during the workflow. The challenge is to figure out the right cadence for soliciting feedback without being too invasive and annoying.</li> <li><em>Passively</em>: Last month, we talked to <a href="https://peruse.io">Peruse.io</a> (which auto-templates emails). With Peruse.io, users give feedback as to whether they want to send the email drafted by the AI as is or make any changes first. The AI then gets smarter by seeing the difference between what it recommended and what was actually sent.</li> </ul> To be honest, I’m not exactly sure how scheduling agents can earn more of my trust but I am looking forward to seeing how companies like Clara and x.ai move beyond <a href="https://x.ai/how-to-teach-a-machine-to-understand-us/">trainers</a> in their human-in-the-loop system, since there is no better validation of AI than getting feedback from users directly. Ultimately, a company wins when their user becomes the human-in-the loop. Why? This cuts down on costs and gives you objective feedback. The bottom line is that earning users’ trust is crucial to learning and building a better product. <em>What approaches / implementations to your UI/UX are you taking to earn your users’ trust and get those much-needed learning opportunities?</em>

<a class="zem_slink" title="Chris Dixon" href="http://cdixon.org/" rel="homepage">Chris Dixon</a> wrote a <a href="https://medium.com/@cdixon/what-s-next-in-computing-e54b870b80cc#.wj2fyc9v2">great post</a> discussing what’s next in the computing industry. Historically, there’s been a major new tech cycle every 10 to 15 years that brings along a new era of computing: we saw this with personal computers in the 80s, the Internet in the 90s, and now with the smartphone era. <a href="https://www.versionone.vc/is-aws-the-next-computing-platform/screen-shot-2016-03-15-at-7-20-49-am/" rel="attachment wp-att-2550"><img class="aligncenter size-full wp-image-2550" src="https://gregburnison.ca/code/version1v/images/Screen-Shot-2016-03-15-at-7.20.49-AM.png" alt="Screen Shot 2016-03-15 at 7.20.49 AM" width="510" height="227" /></a> If this 10-15 year pattern continues, it means we should be entering the growth phase of the next big era in just a few years. It also means that we should already be in the early stages of that next big era. The question is: what is it? What’s the next big computing platform? In my opinion, there are five key trends shaping the computing industry today (and Chris touched on the first three): <span style="text-decoration: underline;">1. Computing everywhere:</span> In the semiconductor industry, we’ve seen chips get progressively faster and cheaper (Moore’s law) for the past five decades. Plus, as <a href="https://medium.com/@cdixon/what-s-next-in-computing-e54b870b80cc#.wj2fyc9v2">Chris points out</a>, we’re moving more toward systems-on-a-chip architectures which drop the price of a computing system from $100 to $10. You can buy a Raspberry Pi Zero for five dollars. The end result is that it’s now cost effective to put a computer in virtually anything. With smartphones, wearables, tablets, drones, kiosks, IoT, etc., computing is taking place, non-stop, all around us. <span style="text-decoration: underline;">2. Cheaper data gathering &amp; storage at scale:</span> Now that computing endpoints are everywhere and anywhere, it’s cheaper than ever to gather data. For example, there are sensors in your phone and smartwatch; sensors on industrial equipment in a manufacturing plant, on a warehouse shelf in a distribution center or your refrigerator at home. Drones can cheaply gather large amounts of data. All of this means that there’s widespread availability of large data sets that can be stored inexpensively through cloud storage providers. <span style="text-decoration: underline;">3. Better insights through AI:</span> We have seen incredible progress in AI over the past years, especially through the application of deep learning algorithms. Those AI systems <a href="https://www.versionone.vc/data-not-algorithms-is-key-to-machine-learning-success/">will get even better as more data is collected</a>, so cheaper data gathering should lead to better, smarter, and more useful AI products. <span style="text-decoration: underline;">4. Innovation in the user interface through voice:</span> Better interfaces drive more effortless experiences for users. We’re already seeing the rise of <a href="https://medium.com/intercom-inside/why-conversational-design-is-the-future-2c05f65aa68e#.9z4m16p60">conversational design</a> beyond messaging apps and into the products and apps we use every day. With conversational UI, we don’t just chat with other people, but with services as well. Speech, like we’re beginning to see with Amazon Echo, is the <a href="https://www.quora.com/Is-Amazon-Echo-and-or-Siri-and-other-voice-assistants-actually-useful-or-is-it-just-a-novelty-Are-usage-and-retention-of-these-products-growing/answer/Brian-Roemmele?srid=Pi3&amp;share=531ff6d3%0A">ultimate conversational interface</a>. Asking a question aloud requires much less cognitive load and lets you do something else at the same time (as opposed to typing on the computer). In addition, products with speech-based interfaces can be scaled down to much smaller and cheaper form factors than products that require displays and keypads. New user interfaces will dramatically reduce the friction to access data and insights. <span style="text-decoration: underline;">5. Rise of connected services:</span> Microservices represent the next big leap in the API economy. Instead of dealing with a single API or technology stack, an app now is made up of many fine-grained services (each with its own tech stack), enabling dev teams to decouple services and update/deploy faster. In this way, computer services are performing more and more specialized roles, just as humans are too. <strong><em>What’s next?</em></strong> The big question is what does all this mean in terms of the next computing platform? In a follow up to Chris Dixon’s post, <a href="http://avc.com/2016/02/whats-next-in-computing/">Fred Wilson wrote</a>: “…I wonder if there is something more fundamental in the combination of ubiquitous computing and artificial intelligence that would be the next big computing platform. We are due for one soon... What is the dos/windows, Netscape, and iOS of this coming era? If we can figure that out, then we are onto something.” Over the past few months, I have grown to believe that one of the large cloud platforms – <a class="zem_slink" title="Amazon Web Services" href="http://aws.amazon.com/" rel="homepage">AWS</a>, Google, MS Azure – can grow into this next computing platform. And, AWS is the most likely candidate given its scale and mindshare among developers. AWS is still considered pretty low level, mainly offering on-demand computing capacity and storage. But, to its advantage, AWS (unknowingly) did the right thing by first building an infrastructure as a service business and not starting with a platform-style set of services like <a class="zem_slink" title="Google App Engine" href="https://developers.google.com/appengine/" rel="homepage">Google’s App Engine</a>. It’s much easier to build on AWS’ fundamentals rather than having to do it the other way around: Compute Engine was pretty late to the party. AWS has been adding more and more intelligent building blocks over time, climbing up the stack with services that abstract the underlying infrastructure and help with specific tasks in the value chain. Lambda, API Gateway, and Amazon Machine Learning are great examples of this. But, for AWS to become <strong>THE</strong> computing platform of the AI age, two things will need to happen: <ul> <li>AWS will need to keep moving up the stack towards the intelligence layer (ML, AI)</li> <li>AWS needs to spawn an even broader ecosystem of apps on top of it (beyond the <a href="https://aws.amazon.com/marketplace">current AWS marketplace</a>)</li> </ul> If AWS can do these two things, it might be in the best position to become the OS of the next big computing cycle.

Last week I attended the <a href="http://www.nfx.com/">NFX demo day</a>.  For me, it is one of the most fun demo days to attend as NFX, <a href="https://www.versionone.vc/our-refocused-investment-thesis/">like Version One</a>, focuses on network effect businesses, particularly <a href="https://www.versionone.vc/marketplace-handbook/">marketplaces</a> and social platforms. During the day, NFX partners shared their insights from having worked with dozens of businesses over the first 2 cohorts and one of the most interesting takeaways was hearing about how they try to help companies move faster. As a startup, moving fast is probably THE biggest competitive advantage you have. Large companies may have a huge budget, name recognition, and customer base, but they’re also slow. Facebook, arguably one of the most successful companies of all times, had the famous motto, “move fast and break things.” They kept this mantra for a very long period of time, until they felt compelled to switch over to “<a href="http://mashable.com/2014/04/30/facebooks-new-mantra-move-fast-with-stability/#0UvVrabtFsql">Move fast with stable infra</a>.” But the question is, if the ability to move quickly is your key advantage, what can you do to move faster? <strong style="line-height: 1.5;">1. Be ruthless about prioritization</strong> In order to move fast, you can only work on the things that truly matter. Be ruthless about prioritizing and chop out everything that doesn’t make the cut. Some startups incorporate prioritization activities into their daily routine. At the start of the day, every day, each team member should know exactly what their goals are for the day, and how they fit into the team’s weekly/big picture goals. Of course, the clearer you are about your vision, business model, and key drivers, the easier it will be to prioritize. <strong style="line-height: 1.5;">2. Shorten the product release cycle</strong> In the very early stages, you should be shipping product as fast as possible, potentially even daily. Remember that many small steps are better than one mega launch. Ship the simplest and smallest thing (that adds value to your users). You’ll get a better sense of what works, what’s important, and what’s not. <strong style="line-height: 1.5;">3. Remove the bottlenecks</strong> Everything moves faster when people don’t have to wait around for other people. <a href="https://www.versionone.vc/stay-nimble-scale/">Internal APIs</a> help in a big way to decouple teams, giving each team ownership over everything it builds. As Bezos pushed Amazon to do, every internal product should have an API, just as if it were developed for an external client. Then, teams don’t need permission to do something, and they don’t have to wait to get the okay before touching code. <b>4. Do you know what moving fast actually means?</b> It’s important to know where you stand. If you have only worked at big companies or startups with a ‘big company’ culture, you might not completely understand what ‘moving fast’ actually means. The bottom line is that speed and agility are the biggest advantages you have at the beginning. You’re only going to get slower as you scale up, so make sure you start out at the fastest speed you possibly can.

Last week I wrote about how the <a href="https://www.versionone.vc/the-next-wave-of-enterprise-apps-effortless-and-smart/">next wave of enterprise apps</a> will stand out in two ways: they’ll be smart and make experiences as effortless as possible for the end user. As machine learning and predictive modelling become more of a mainstream reality, apps will shift from being reactive “sense and respond” to more predictive and pre-emptive solutions. They’ll evolve (or should evolve) along the following framework: Reactive &gt; Proactive &gt; Predictive &gt; Pre-emptive: <strong style="line-height: 1.5;">1. Reactive apps: </strong><span style="line-height: 1.5;">These are web-based tools that give users a way to create the outcomes they need. For example, a web app that makes it possible to book flights or hotels on the web. In these cases, the app just follows the user’s direction; the user is in the driver’s seat.</span> <strong>2. Proactive apps: </strong>The next stage adds a little more intelligence to proactively notify end users of changes in outcome or other information they should know. Staying with the travel theme, an example of a proactive app is a mobile app that notifies you of a flight delay for your upcoming flight. <strong>3. Predictive apps: </strong>Here’s where machine learning kicks in. These tools use machine learning/predictive modeling to predict outcomes or potential changes to expected outcomes. For example, an app that tells you that the price of a flight you’re looking at will most likely increase in the next week. <strong style="line-height: 1.5;">4. Pre-emptive apps: </strong><span style="line-height: 1.5;">The last stage in app evolution is artificial intelligence. Here, the app doesn’t just notify customers of changes in outcomes, but can also take the actions needed based on those changes. For example, an app rebooks you on the next available flight when it detects a problem (e.g. flight cancellation) with your current itinerary.</span> For app startups, it’s in this last stage where you can provide the most value and delight your users. But, this is also the stage where you need the most amount of data to make sure your app is taking the right pre-emptive action.

We’ve all talked about the consumerization of enterprise apps for several years. Yet while it’s been a popular trend, there still aren’t many enterprise apps out there that can rival the user experience of the best consumer ones. Most enterprise apps are still plagued with clunky, form-driven interfaces; require too much data entry from the user; and don’t offer much in the way of automation. There’s a big opportunity to create enterprise apps that are just as easy and enjoyable to use as consumer apps. The next wave in enterprise software will be driven by two criteria: effortless and smart: <strong><u>Effortless</u></strong> Better interfaces can drive a more effortless experience for users. Some enterprise apps can benefit from adopting a conversational-style/chat UI. For example, <a href="https://www.and.co/">And Co</a>, an invoicing app for freelancers, does a really good job of helping their users take care of administrative tasks in a fast and efficient way through a chat interface. But, the best interface is no interface at all as artificial intelligence can make data entry unnecessary. <a href="https://www.tripit.com/">TripIt</a> is still one of the best ways to create a thorough travel schedule by simply forwarding your booking emails. There’s no reason why expense management can’t be as easy: give an app access to your credit card statements and calendar, and it should be able to churn out a nearly perfect expense report for you. There are hundreds of tasks within every department of a large enterprise that are completely repetitive and could be automated by a bot. We are already seeing some bots emerge on Slack to tackle these repetitive tasks. For example, bots can take care of asking for weekly status reports, or creating and sending out meeting notes. There’s a really interesting opportunity for apps on the Slack platform to use chat and data automation to create effortless experiences. <strong><u>Smart</u></strong> <a class="zem_slink" title="RelateIQ" href="http://www.relateiq.com/" rel="homepage">RelateIQ</a> (now <a href="https://www.salesforceiq.com/">SalesforceIQ</a>) was an early attempt at creating a CRM that not only stored customer information, but also offered smart insights for whom to reach out to and when. The new generation of enterprise apps will differentiate themselves by both the quality and speed of their insights. We’ll see smart be real-time. For example, <a href="https://textio.com/">Textio</a> is a service that uses AI to uncover key phrases and spots gender bias as you type your job description. For any entrepreneurs thinking about this space… there’s a great opportunity here. However, machine learning and AI will only work once you reach a certain scale. This makes it all the more important to create an effortless experience and a strong use case to attract users. Your app needs to eat up enough data to become smart (and thus, make things even more effortless).

Over the years, we have invested in almost every category out there: from ad tech and content, to gaming, hardware, marketplaces, e-commerce, and SaaS. We’re constantly revisiting the types of businesses we should be investing in and refining our investment thesis driven by three key questions: <ol> <li>Which markets/business types do we understand the best?</li> <li>Where can we be value-add investors?</li> <li>What are the most capital-efficient opportunities for a fund of our size? We recognize that we’re investing a relatively small pool of capital: a $35m fund for approximately 25 initial investments plus follow-ons in at least 50% of those investments.</li> </ol> Looking back, we feel that we made the best decisions with (and hopefully provided the most help to) businesses displaying strong network effects. This brings us to our refocused thesis: <strong>we like to invest in businesses with potentially large network effects built around people and/or data.</strong> We think that <a href="https://www.versionone.vc/network-effects/">network effects</a> can provide a long-lasting competitive advantage and can be very capital-efficient. Connecting people and data over the web and mobile also creates something that wasn't possible before - the end result is new and unique, not just something faster, cheaper, or better. Network effects can be found in many categories, from <a href="https://www.versionone.vc/tag/marketplaces/">marketplaces</a>, to <a href="https://www.versionone.vc/tag/platforms/">(social) platforms</a> or <a href="https://www.versionone.vc/tag/saas/">SaaS</a>, and in many products built specifically <a href="https://www.versionone.vc/data-not-algorithms-is-key-to-machine-learning-success/">around (big) data</a>. Since we’re typically investing at the seed stage, and companies usually don’t have network effects this early, we’re taking a higher risk that our investment may not work out the way we imagine. But, we’re happy to take this risk in exchange for a greater upside potential. Important businesses can be built in many verticals and with many different approaches – but we believe we are better investors in network effect businesses than in any other business.

Last year, we quietly invested in the seed round of Booster Fuels, a then-stealth on-demand gas delivery service.  Today, we're excited to officially announce our investment as they raise their Series A financing from Maveron, Madrona, and RRE, and other invests, as well as expand into Silicon Valley. Much has been written about the Uberification of the economy over the past year. Last May, Boris said that we <a href="https://www.versionone.vc/why-there-wont-be-an-uber-in-every-vertical/">shouldn’t expect an Uber in every vertical</a>. That’s because in order for the “Uber for X” model to truly work, three underlying factors need to hold true: the service needs to be commoditized, have a high purchase frequency, and be truly time sensitive. A lot of startups claiming to be the next Uber for X just don’t fit those criteria. In fact, there are probably just a few categories where on-demand (as in “need it now”) is truly necessary - and two of those are transportation and food. That’s where Booster comes in. The service delivers gas to drivers, solving the many pain points of trips to the gas station: safety concerns, weather, timing, lines, germs, etc. This is a huge market that’s up for grabs. A few stats for perspective: <ul> <li>Passenger car fuel represents a half trillion dollar market in the US alone.</li> <li>As much as 11% of consumer spending is on gasoline each year.</li> <li>Despite increasing urbanization, 9 of 10 working Americans still commute to work by car.</li> </ul> As a result, Booster is not the only company to recognize the opportunity;  there are at least three other “Uber for gas” startups have launched.  The company<span style="font-weight: 400;"> currently operates in the SF Bay Area and the Dallas Fort Worth metroplex, servicing clients at suburban campuses of large cap corporations.  </span> So why did we invest? <span style="font-weight: 400;">Ultimately, we love the end vision in terms of how energy moves globally. There are big implications for the decentralization of fuel and we’re excited to be working with CEO Frank Mycroft and the incredible Booster team on this mission.  </span> <span style="font-weight: 400;">To learn more, visit their </span><a href="https://www.boosterfuels.com"><span style="font-weight: 400;">website</span></a><span style="font-weight: 400;"> and follow them on </span><a href="https://twitter.com/BoosterFuels"><span style="font-weight: 400;">Twitter</span></a><span style="font-weight: 400;">.</span>

When’s the last time you sent out or requested a CV? Chances are it was quite awhile ago. In today’s reputation economy, we evaluate one another based on what people have done and how we’re connected. What you’ve built is becoming more important than where you’ve worked and the school you attended. If you’re a professional applying for a job or an entrepreneur applying for funding, here’s how the typical evaluation process looks today. Someone will glance at your CV/resume/bio, then quickly turn to Google to track down your digital footprint. They’ll look at your <a class="zem_slink" title="GitHub" href="https://github.com/" rel="homepage">GitHub</a> account (if you’re a programmer) and any other links. Then, if they like your work, they may seek out your personal blog/Twitter to figure out if you’d be the right culture fit for the company. In this process, the CV and its lines of text are pretty inconsequential. They are artifacts of an older time, before the Internet made it so easy for people to share their work with the world. LinkedIn seems to be stuck in the middle of the old and new reality. The company is trying to modernize its product with groups and Influencers, but it’s very obvious that the platform’s roots are in resumes and recruiting and all other activities are built on top of a resume platform. For many of us, LinkedIn has never been much more than a database of stale resumes. Over the past few years, we’ve seen a number of start-ups try to carve away parts of LinkedIn by being the “LinkedIn for x” – where x ranges from doctors, teachers, finance professionals, academics, lawyers, engineers, etc. These vertically-focused platforms cater to the specific needs of their users, offering a close networking community around shared interests. They also give their users a better way to develop and curate their personal online brand beyond the LinkedIn resume. One of the most obvious examples of the online portfolio is within the creative community. There’s no good way to share a portfolio of work on <a class="zem_slink" title="LinkedIn" href="http://www.linkedin.com/" rel="homepage">LinkedIn,</a> which is why sites like <a class="zem_slink" title="Behance" href="http://www.behance.net/" rel="homepage">Behance</a> and Dribble have become popular among graphic designers, illustrators, photographers, web designers, and art directors. Similarly, developers use GitHub as a public portfolio to showcase their best work, rather than a repository for half-finished projects. Recruiters and job ads now commonly ask for GitHub profiles. Spiceworks lets IT professionals add videos to help explain their experience to people without a deep IT background. On sites like <a href="https://figure1.com/">Figure 1</a> (<a href="https://www.versionone.vc/new-investment-figure1/">a V1 portfolio company</a>) or <a class="zem_slink" title="Doximity" href="http://www.doximity.com" rel="homepage">Doximity</a> (healthcare), <a class="zem_slink" title="ResearchGate" href="http://researchgate.net/" rel="homepage">ResearchGate</a> (academia), and Casetext (legal), people are building their professional authority by helping others and answering questions. LinkedIn still has the advantage of network effects and this won’t change anytime soon. However, the real threat for LinkedIn is that these hundreds of vertical platforms are becoming more and more relevant for their users on a daily basis than LinkedIn ever was. LinkedIn is the place where you dump your resume, while the vertical site is where you build your brand, spend your time, and actually network.

If you’re building a software/social/ecommerce startup, then at one point or another, you have been advised to start in a niche market and expand into the masses. This is solid advice: when your product is focused on a slice of the market, it’s much easier to customize your solution for the specific needs of those users and capture more market share than if you tried to build a general ‘all things for all people” solution. But, the key question is: after you nail down a niche, how do you expand into the mainstream and capture a bigger piece of the pie? There are three strategies: <strong style="line-height: 1.5;">1. Expand categories (it worked for Amazon)</strong> With e-commerce platforms, adding new categories is usually the best way to get to a mass audience. Amazon is a good example here. They started out as bookseller. And today, if a product has a SKU, you can buy it on Amazon. The interesting piece in Amazon’s strategy is how they use the marketplace activity to determine what to sell themselves. When a third party has success selling a particular product, it captures Amazon’s attention and they’re usually interested in adding this product to their own offerings. Likewise, crafting supplies became one of the largest categories on Etsy after the team saw tons of activity on the marketplace around such goods and decided to create a dedicated category for supplies. This is one reason why category expansion can be such a successful strategy for marketplaces: they can see activity on their own platform and decide where to expand. However, not every marketplace has the same results of Amazon. With my startup, AbeBooks, we didn’t have any success trying to expand out from the niche of selling used and rare books. The main reason is that Amazon was already too strong a player in the general book category. So, we ended up selling the company to Amazon in 2008. <strong style="line-height: 1.5;">2. Expand audiences (it worked for Facebook)</strong> Social platforms usually try to expand into related audiences. For example, Facebook started connecting college students and at some stage decided to open up the platform to everybody. The secret to Facebook’s success was that they made the product very mainstream to use from the start. This is different than other social platforms that either have very tight communities that aren’t always welcoming to new users (e.g. Reddit) or have developed very specific UI/language that isn’t mainstream (e.g. Twitter with retweets and Snapchat with disappearing photos). In my opinion, Reddit and Twitter failed to expand into more mainstream audiences, and the jury is still out as to whether Snapchat will be able to do so. The bottom line: if you want to expand your social platform to a mainstream audience, be sure to build a mainstream product experience in the first place. <strong style="line-height: 1.5;">3. Grow by expanding the niche audience (it worked for Lululemon and Etsy)</strong> In some cases, you don’t have to expand into different categories or new audiences if your underlying target audience grows rapidly enough. For example, Lululemon got started right at the time when Yoga was taking off in the mainstream. As the number of people interested in Yoga grew, so did Lululemon’s target customer. They also did a great job of developing their company into a lifestyle brand that attracts people who don’t actually practice yoga. In a similar way, Etsy has been riding the wave (and maybe fueling it) for artisan/handcrafted goods. <strong>Final thoughts</strong> Even when you know your strategy for moving from niche to masses, it is still hard to know when is the right time to expand categories or audiences. In the case of AbeBooks, we were too late, as Amazon had already won too much mindshare. But, many other startups never can scale in the first place because their experience is too broad and they can’t win any market.

Over the past decade, startups and enterprises have devoted hefty resources to collecting and analyzing huge volumes of big data. For some, data is used to fine-tune a product; in other cases, data forms the foundation of the product itself. When it comes to building a startup around data, the more unique that data, the better. As I wrote last week in reference to <a href="https://www.versionone.vc/data-not-algorithms-is-key-to-machine-learning-success/">machine learning startups</a>, algorithms have mainly become a commodity these days. Building a company around publicly available data just isn’t defensible. What are the different types of data and where do they rank on the ‘uniqueness hierarchy’? We see four major classifications (in order of increasing uniqueness): <strong>1. Accessible public data</strong>: This is data that’s readily accessible on the web and you just need an API to access it. Examples are Google Maps and open government data like <a href="https://publicdata.eu/">Europe’s public data</a> and <a href="https://data.sfgov.org/">San Francisco data</a>. <strong style="line-height: 1.5;">2. Raw public data:</strong> This is data that’s available to the public, but requires a lot of legwork (e.g. cleaning and scrubbing) to be usable. For this reason, its accessibility is limited to those with the technical know-how and resources. <strong style="line-height: 1.5;">3. Proprietary user data:</strong> This is data that users create or share and can be used according to the site’s Terms of Service. In all cases, users are ‘opting in’ to share their data, whether by creating a product review on Amazon, liking a post on Facebook, or sharing their bank account activity with Mint.com. Keep in mind that while this data is proprietary, it’s not necessarily exclusive as users can share the same kind of content on multiple platforms. <strong style="line-height: 1.5;">4. Exclusive user data:</strong> This is behavioral data that tracks how a user interacts with a product/site. Such data is typically captured in the background and is site-specific - and is hence a very valuable and exclusive feed-back loop that can be used to improve the product. An example is tracking a user’s search behavior to deliver better search results in the future (more on this below). <em><u>How are companies using data?</u></em> Here are two examples that best illustrate how companies are using data across the various levels of the ‘uniqueness hierarchy.’ The first example is Google. Google started with publicly available data (type 2), but as they developed their product, they had access to exclusive user data (type 4). They used to data to refine and personalize a user’s search results to create a vastly superior product. They became the de facto search product. And, as more people use the product, they get more user data –further strengthening their moat. Google was able to build their initial product with publicly available data, since no one else was aggressively pursuing the same space at the time. They then built a daily use case product that throws off tons of exclusive data to fuel their growth. The second example are user reviews on Amazon (as well as sites like Netflix, TripAdvisor…). Amazon has found a way to incentivize its users to share lots of proprietary data in the form of product reviews (type 3). The real-added value for Amazon, however, is when you combine these reviews (type 3) with behavioral data (type 4) – e.g. what does the user buy, what do they look at but not buy. This has enabled Amazon to develop truly personalized and effective recommendations. Can anyone else recreate a recommendation system at Amazon’s level? It depends on how individual tastes are and how many data points there are to start with. In my opinion, it’s much easier to build a recommendation system for movies than a broad product marketplace, since personal tastes for films are more mainstream and the underlying dataset is much smaller. In addition, companies that only have reviews, but no transaction data (e.g. Yelp), have less valuable datasets. <span style="text-decoration: underline;"><em>What does all this mean for your startup and data strategy?</em></span> There are a few takeaways from all this: <ol> <li>Building a startup on publicly available data is hard unless you can come up with a killer daily use case and very quickly accumulate user data that helps improve the product significantly and enables you to build a moat (the Google example).</li> <li>Access to unique data is crucial, but combining it with user data is even more important. The incremental value of this depends on how unique the personalized tastes/preferences are and how complex the underlying data set is.</li> <li>And lastly, true data network effects can be built with data types 3 and 4.</li> </ol>