A Few Non-Obvious Things I Learned as a New VC

I joined FirstMark as a partner a little over 18 months ago now, and it’s been a thrilling ride.  It’s also felt like a steep learning curve: lots of nuances, and lots of institutional memory to absorb.  Below is a glimpse into what I’ve seen happening “behind the scenes” on the VC’s side to the table – stuff that was not obvious to me in my former roles as entrepreneur, angel investor or corporate incubator/strategic.

1.  A real commitment.  Like for many new VCs operating at the Series A level,  the biggest shock to the system was the realization that one gets to make very, very few investments – basically two or three a year.  You quickly find yourself having to choose between a number of opportunities you really like. Making a new investment is a big deal, and a decision that one has to live with for years to come. You also get to work with an entrepreneur very closely, and live up to their level of trust and expectations.  In a way, it feels like a marriage, except one where divorce is not really an option.  There’s an occasionally brutal asymmetry between the fundraising process (which can be quick and intense, especially if it is competitive) and what happens afterwards, which is a lot of hard work over a long period of time.  Both the entrepreneur and the VC would be well advised to get to know who they’re about to work with for the next few years of their lives.  You don’t need to be friends with your VC (although friendships develop over years of working together), but you do need a core of mutual respect and commitment to hard work and excellence, as well as a shared vision of the future.

 

2.  Conviction, not data. Early stage VCs (seed and Series A) operate in a daunting scarcity of data points. You get a few numbers, a few meetings with the founders, and also you see a bunch of companies, so you get a sense of how an opportunity compares to others. Other than that, and for all the thinking about data driven VC investing, the reality is that investment decisions are mostly about storytelling and forming personal conviction – painting a vision of the world where a company becomes hugely important. One consequence for entrepreneurs to bear in mind: VCs are really hungry for any data point that can help them.  It’s certainly true about the “big things” (revenue, traction, etc., especially as they compare to other opportunities the VC is seeing), but it’s also true for the “small things”, which can become become disproportionately important  (particularly if they add up), as the VC is trying to piece together a story: whether that’s signs of possible greatness (e.g., your former boss really insisted on putting $50k in your new venture) or trouble (being rude to the receptionist, consistently taking forever to reply to emails, etc).

 

3.  Not a single way to reach conviction:  VCs come in all sorts of flavors – some successful investors are deeply analytical (build roadmaps and investment thesis, get into details) while others are more “social” (relying on networks of trusted experts they’ve built over years to help them identify signal from noise).  What’s been interesting to me is that you find very successful investors on both sides of the spectrum, and also find those different types happily co-existing within the same firm.   Naturally, everyone is also heavily influenced by their professional history (what worked for them in the past as an operator or investor), as well as all sorts of personal criteria that often have nothing to do with the intrinsic merits of an opportunity – for example, the bar for a new investment will be naturally higher if an investor is already on 12 boards and always on the brink of being overwhelmed by the amount of work they face.   For the entrepreneur, it’s always a good idea to understand who they’re pitching to, as in any sales process, as an investor’s personal circumstances and background matter immensely.

 

4. VC firms are not a monolith. Once an individual investor has reached personal conviction, they need to sell it internally to get the deal done.  Because of the scarcity of data points and the range of personal styles, most investment decisions can be argued either way, and they often are. VCs are opinionated people, and there’s a fair amount of disagreement behind the scenes happening at firms during the discussions leading to an investment decision, which is a healthy thing, as you need checks and balances.  Many firms have reported that the most successful investments in the long run are the ones that were initially the most polarizing internally.  Depending on the firm, internal politics may come into play as well (glad to report that FirstMark is remarkably immune to this).  But, bottom line, decisions can come out either way quite easily, so for entrepreneurs, there’s certainly a numbers game involved.  Unless no one wants to take a first or second meeting (in which case there’s probably a deeper problem), it’s quite possible to get turned down by many firms before finding the one that will say yes (which can absolutely be a bigger name firm that the ones that said no).

 

5.  “Deal dynamics” matter a lot.  One really interesting aspect of seeing “how the sausage is made” on the VC side is to realize that the intrinsic merits of the opportunity is only a part of the equation. There’s also this thing called “deal dynamics” that VCs talk about all the time —  basically a catch all for all sorts of criteria related to timing, valuation, competition and to some extent, stage, geography and seasonality as well.  Because they see so many opportunities, VCs need to have strong filters in place about what makes sense for them – how they think about portfolio construction, ownership percentages, etc., matters a lot.  Here as well, this means that there is a number of reasons why an opportunity may not be a fit for a specific firm which have little to do with the fundamental merits of that opportunity.  Sounds like horrible VC bullshit, but it’s very true: a VC’s decision to “pass” is quite often not personal.

 

6. The VC world is really small.  While there are thousands of startups around at any point in time, there are only a few hundred active VC firms, which typically only have a handful of General Partners.  People come in and out of the industry all the time, VC firms rise and fall, but for the most part, the core remains the same and many people are around for years (or decades).   And it’s a pretty tight knit world:   there’s all sort of ways for VCs to meet (panels, industry conferences), socialize (informal small group dinners) and work together (sitting on boards together, switching firms, occasionally personally investing in each other’s funds, etc.). As a result, the industry is characterized by a deep connective tissue, full of history, institutional memory, cliques and alliances.   There’s this interesting “coopetition” dynamic where people sometimes compete, sometimes collaborate, but overall everyone tends to know each other well.  As a result, information often travels easily and quickly, although not necessarily reliably.  Facts can be checked, and reputations matter immensely.  For entrepreneurs and VCs alike, there are some real  benefits in handling difficult situations elegantly, fairly and transparently, as it’s all a long term game in a small echo chamber.

 

7.  VCs do things I hadn’t realized they did.   It’s perhaps obvious in retrospect, but one surprise to me was that VCs spend an awful lot of time raising money – you’d figure that as an early stage VC, you’d be the one investing the money but the reality is that, once you’ve made the initial investment, you find yourself involved in all sorts of fundraising processes for follow on rounds for your companies, so you end up hat in hand alongside your entrepreneur.   Another unanticipated aspect of the job is that VCs can really help with exits – particularly not-so-great ones.  It’s something that doesn’t make great press stories and that people don’t like to brag about, but behind the scenes, I have seen good VCs spend a lot of time engineering exits for companies that need to “find a home”.  That often makes the whole difference between a complete disaster and a “soft landing” or an acqui-hire that occasionally nets the founders some real money.   Of course, the VC is self-interested (optimizing for results and reputation) but in my opinion, just that is a real reason to take VC money.

NYC: A Natural Home for European Entrepreneurs

Last night I was invited to speak at the inaugural NYC European Tech Meetup.  There are tons of obvious reasons why the NYC and European tech ecosystems should work closely with one another, so a meetup on the topic was long overdue.  Congrats to Alban Denoyel and Anthony Marnell for starting it, and thanks for inviting me to speak, was a lot of fun.  Below are the slides I used – the presentation was meant to be a “State of the Union” of European tech in NYC, a high level overview fit for an inaugural meetup and get the conversation started.

 

Many thanks to David Rogg, our newest associate at FirstMark, for helping me with this.  I’m sure we missed some companies and people – if so, let us know in the comments, and we’ll update the presentation.

The French Startup Ecosystem: At a Tipping Point

I know, when thinking about hotbeds of startup innovation, France doesn’t exactly jump to mind. Sure, there are interesting things happening in European tech – in London, or Berlin (which I covered here). Or Finland. But France? Ask U.S investors and entrepreneurs, and you’ll hear more or less the same thing: high taxes. Impossible to fire people. Government intervention. Language barrier. Fear of failure. Strikes. The country of the the 35 hour law, where people are prohibited by law to answer email past 6pm.

Yet things have started to accelerate meaningfully in French early stage tech, particularly in the last two or three years. I was fortunate to be recently invited as part of a delegation of US VCs and media guests to spend a few days in Paris to meet with local entrepreneurs and VCs, as well as President Hollande and other senior members of the French government. As a Frenchman who has spent his entire professional career in the US, I’m perhaps more cynical than most about those matters, but I came back from my trip genuinely intrigued by the potential of the French tech scene.

For anyone who cares to look, the fairly obvious conclusion is that there’s a huge gap between perception and reality, when it comes to the French startup ecosystem. Very significant progress has been made on all fronts – more interesting startups, more funding, lots more talent rushing into the sector, improved legistation, etc. – yet the word has not caught on.

It is going to take a while to close that perception gap – if nothing else, because it takes a long time to overcome a negative reputation. But you can’t blame people outside France for being confused – France has been showing traits of schizophrenia in its approach to innovation and business success. For all its emerging crop of talented young tech entrepreneurs, most of France is still deeply ambivalent about business and individual wealth creation. French entrepreneurs are building great businesses, but often show a tendency for self-bashing and country-bashing. The current French government has been sending mixed signals (or has done a dramatic 180 degree turn, depending on how you look at it). Elected on a left wing platform, at first it showed signs of being anti business – including an ill fated attempt at raising capital gains tax, and a badly botched meddling into Yahoo’s attempt to acquire Dailymotion, a French competitor to YouTube. It now has launched a charm offensive towards the startup world both within and outside France, labeled “La French Tech” – first started by Fleur Pellerin, then Minister for the Digital Economy and now run by Axelle Lemaire, her successor since April 2014 – both talented and in sync with a younger generation of French entrepreneurs.  All of this is certainly encouraging; time will tell whether this is a long term change of mentalities.

Here some thoughts – not meant to be a comprehensive review of everything happening in France of course or mention every single noteworthy person or company – just my notes.

Talent is French Tech’s Biggest Asset. France has had excellent engineering schools and a deep bench of technical talent for generations.   The big development of the the last few years is that many graduates of those schools are increasingly choosing to go work for startups (or start one) instead of choosing a career at Bain, Goldman Sachs or Total.  Many of those schools have launched seemingly very active incubators.  And this new generation of graduates speaks English a lot better than its elders.

One particularly noteworthy addition to the French educational system: Ecole 42, a new and highly innovative computer science school funded by a $100 million gift from Xavier Niel, France’s most successful tech entrepreneur. As far as I know their model is entirely unique: anyone can be admitted regardless of previous educational background (high school diploma not required). Past an initial online logic test, applicants go through a month long selection process involving a grueling 15 hours a day, 7 days a week routine. Those who are admitted to the school go through a curriculum that involves entirely team based projects, and are assessed through peer review only.  Oh, and it’s free.  The quality of the first class is said to be truly outstanding.

Big Data and Connected Devices. France tends to produce fairly original startups and comparatively few “copycats” of successful U.S. companies – for example Vente Privee pioneered the concept of online flash sales that was then imported in the U.S.. There are plenty of startups large and small in areas such as eCommerce (ShowroomPrive), video (Dailymotion) and music (Deezer, eDJing). But considering my specific areas of interest, I’m excited to see French startups excelling in Big Data and or math/data driven areas (think Criteo, Talend, Scality, Qunb, PriceMatch, etc.). France is also particularly innovative in the connected devices and hardware space (Parrot, Withings, Netatmo, Sigfox, Sense, Aldebaran, etc.).

Startups Dreaming Bigger: A common complaint against France (and indeed, most of Europe) expressed by US investors has been the relative scarcity of startups with truly global ambitions. In an environment where financing has been limited, many startups have had to focus on reaching profitability quickly, as opposed to focusing on scale. Also, French startups have historically focused on the French market, at least initially. Not that this is not a viable strategy: the market is reasonably large (65 million inhabitants), and large tech businesses have been built with a domestic focus – not least of which Illiad, Xavier Niel’s $17 billion ISP and cell network business. But it’s typically not what US investors are looking for, as their economics are driven by their ability to find hypergrowth businesses with true potential for $1BN+ exits, which are typically generated by startups conquering quickly very large markets.

This, too, seems to be changing, as the new generation of French startups seems to be thinking globally much more systematically, and much earlier in their development. Of course, French startups have had big international successes before (Business Objects, ILOG, Kelkoo, etc.). But there just seems to be a lot more French startups that are showing a strong international inclination – Criteo (which IPO’ed on the NASDAQ last year) derives at least 80% of its revenues outside France; rapidly growing ride sharing startup BlaBla Car is already present in 12 countries. Anecdotal conversations I have with French entrepreneurs indicate a clear desire to go international very early.

More VC Financing Options: While there’s still long ways to go compared to the U.S., there seems to be more VC financing options than ever before available to French startups:
• Seed financing: compared to other European countries, there seems to be more funds than individual angels at the seed fun: Elaia, Alven and Isai are names that come back frequently in conversations
• Early stage financing: Partech, Idinvest and Iris seem to be the main players.
• Growth financing: there seems to be a gap there, filled in part by London based funds (mostly Accel and Index)
• BPI France is an important (a strange, by American standards) player in the ecosystem. The result of an amalgamation of various state entities in late 2012, it is a VC fund (with 5 different funds), a venture debt provider and a fund of fund (with 56 partner funds).

Improved Regulatory Environment. This would be worth a separate  blog post, but here are some of the highlights of what was discussed during my recent trip to France:
• A startup can fire employees completely at will during their first 8 months of employment
• Past that 8 month period, French labor laws were relaxed in 2008 to allow firing in a broader range of situations, including “economic” situations where requirements or qualifications change – not quite the US situations but in practice, not a major issue apparently
• The 35 hour work week law, passed in 2000, was essentially amended in 2004 to the point of being completely voided of substance
• The 6pm email ban never existed and was the result of bad transation (see The Economist here)

Celebrating the rise of the French-American startup: Whether you call it a brain drain or a global partnership in the making, it’s hard not to notice the recent influx of French tech entrepreneurs in the U.S. Sure, a handful of French nationals have been prominent in the US startup industry for a while: Bernard Liautaud (Business Objects), Jeff Clavier (SoftTech), Loic Le Meur (Le Web), Fabrice Grinda (OLX), Tariq Krim (Netvibes now JoliCloud), Hubert Tieblot (Curse) and, increasingly, Renaud Laplanche (Lending Club) are some of the more obvious names. But the pace of arrival of French entrepreneurs has now accelerated to an entirely different dimension.

The French-American startup seems to come in three flavors:
• Startups founded by French nationals in the U.S.: for example Lending Club (San Francisco), Wit.ai (Palo Alto), Datadog (NYC), Placemeter (NYC), etc. Those companies often have no specific connection to France other the nationality of their founders.
• Startups founded in France by French nationals, that move to the U.S. very early in their development, sometimes after going through a local incubator like Le Camping (and then going through a U.S. incubator like Techstars): Sketchfab, Infinit, Doctrackr are some examples. Dashlane (in which my firm, FirstMark, has been an early investor) is another prominent example. Those companies often have their development teams in France and at least half of their management team in the U.S.
• Startups founded in France by French nationals, that reach some scale domestically first, and then move in the U.S. for growth expansion, for example: Novapost, Synthesio, Criteo
While one should be careful to not immediately assimilate this trend to “the Israeli model” (lots of nuances there), this dual structure (R&D in France and commercial operations in the U.S.) seems to work quite well.

This new generation of cross-atlantic startups should be celebrated. Seen from a purely French and short term perspective, this may not feel ideal: many of those companies will “flip” (meaning, transform from a French legal entity to a Delaware one, effectively becoming U.S. companies), and some entrepreneurs will become rich but won’t pay taxes in France. Long term, however, the benefits are immense – the vast majority of those French entrepreneurs will eventually come back to France, bringing with them deep entrepreneurial expertise, international connections and the financial means to be active seed investors in French startups, which will in turn hire people in France.

The key is here is to think of French tech as a globally distributed ecosystem, as opposed to a French one – many of French tech’s biggest successes will occur in the U.S. and, increasingly Asia.

NYC is a logical second home for French tech: while the Silicon Valley is the undisputed center of the tech world, NYC offers obvious advantages to French entrepreneurs interested in building global businesses: shorter flight, less of a time difference, arguably less of a cultural difference, and a younger, hungrier tech ecosystem where it easier to make a name for oneself. From that perspective, it was somewhat of a surprise to me when speaking to French entrepreneurs in Paris that they were most often thinking about the Valley as opposed to New York.

New York has a strong emerging French tech community: Fabrice Sergent (Cellfish), Mathieu Nouzareth (Freshplanet), Morgan Hermand-Waiche (Adore Me), Olivier Pomel and Alexis Lê-Quôc (Datadog), Alexandre Douzet (The Ladders), Gaspard de Dreuzy (Kapitall, Pager), Christophe Garnier (MommyCoach) and many others.  Some prominent figures of the NYC tech community have deep ties or strong interest in France, including Kevin Ryan (Gilt, MongoDB, Business Insider, Zola) and Ed Zimmerman (Lowenstein Sandler). This community is starting to gel quite nicely. The French consulate in New York (led by the new-ish consult Bertrand Lortholary) is starting to actively promote the French entrepreneurial community. And just this week, a new conference (La French Touch conference) is being launched and could become an important focal point.

What needs to happen next? Building a tech ecosystem takes generations (of startups). Companies need to start, receive financing, grow and exit. Founders and early employees need to contribute back their expertise and money (through angel investing) into the next generation of startups.  Large exits also embolden the next generation of entrepreneurs and VCs.  So France, like other emerging tech hubs, needs more exits.  However, it does have an incredible secret (or not so secret) weapon in the form of Xavier Niel – who invested 200 million euors to convert a former railroad depot into an incubator for 1,000 startups. This could be just the final touch that Paris (in particular) needs to get to the tipping point – this by itself should give a serious reason to US VCs to make Paris a must-stop destination on their tours of tech hubs in Europe.

Special thanks to Jerome Lecat (Scality) and Marie Ekeland (formerly of Elaia) for organizing our Paris visit, and to Philippe Collombel (Partech) for walking me through the Sentier and the Paris VC world.

 

The State Of Big Data in 2014: a Chart

Note: This post appeared on VentureBeat, here.

It’s been almost two years since I took a first stab at charting the booming Big Data ecosystem, and it’s been a period of incredible activity in the space. An updated chart was long overdue, and here it is:

(click on the arrows at the bottom right of the screen to expand)

A few thoughts on this revised chart, and the Big Data market in general, largely from a VC perspective:

Getting crowded: Entrepreneurs have flocked to the space, VCs have poured money into promising startups, and as a result, the market is starting to get crowded. Certain categories like databases (whether NoSQL or NewSQL) or social media analytics feel ripe for consolidation or some sort of shakeout (which may have already started in social analytics with Twitter’s acquisitions of BlueFin and GNIP). While there will be always room for great new startups, it seems that a lot of the early bets in the broader infrastructure and analytics segments have been made at this stage, and the bar for success is getting higher – which doesn’t mean that VC money will stop pouring in. In terms of this specific industry chart, we’ve clearly reached the limit of how many companies we can fit one page. I’m sure there are a number of great companies we either missed or didn’t have enough space to include – apologies in advance to those, and I’d love to hear people’s thoughts and suggestions in the comments section about who else should be included.

Still early: Overall, we’re still in the early innings of this market. Over the last couple of years, some promising companies failed (for example: Drawn to Scale), a number saw early exits (for example: Precog, Prior Knowledge, Lucky Sort, Rapleaf, Nodeable, Karmasphere, etc.), and a handful saw more meaningful outcomes (for example: Infochimps, Causata, Streambase, ParAccel, Aspera, GNIP, BlueFin labs, BlueKai). Meanwhile, some companies seem to be reaching significant scale, and have raised spectacular amounts of money (for example, MongoDB has now raised over $230M, Palantir almost $900M and Cloudera $1B). But overall, we’re still early in the curve in terms of successful IPOs (Splunk or Tableau notwithstanding) and large exits, although the big companies are getting more acquisitive in the space (Oracle with BlueKai, IBM with Cloudant). In many segments, startups and large companies are jockeying for position and no obvious leader has emerged.

Hype, meet reality: A few years into a period of incredible hype, is Big Data still a thing? While less press worthy, the next couple of years are going to be hugely important for this market, as corporations start moving Big Data projects from experimentation to full production. While they will lead to rapidly increasing revenues for some Big Data vendors, those deployments will also test whether Big Data can truly deliver on its promise. Meanwhile, the fundamental need for Big Data technology keeps increasing, as the deluge of data keeps accelerating, powered in part by the rapidly emerging Internet of Things industry.

Infrastructure: Hadoop seems to have solidified its position as the cornerstone of the entire ecosystem, but there are still a number of competing distributions – this will probably need to evolve. Spark, another open source framework that builds on top of the Hadoop Distributed File System, is getting a lot of buzz right now because it promises to fill in the places where Hadoop has been weak, namely interactive speeds and good programming interfaces (and early signs seem to point to fulfilling that promise). Some themes (for example, in memory or real time) continue to be top of mind; others are appearing (for example, there’s a whole new generation of data transformation/munging/wrangling tools, including Trifacta, Paxata and DataTamer). Another key discussion is whether enterprise data will truly move to the cloud (public or private), and if so, how quickly. Many will argue that Fortune 500 companies will keep their data (and the software to process it) on premise for years to come; a generation of Hadoop-in-the-cloud startups (Qubole, Mortar, etc.) will argue that all data is moving to the cloud long term.

Analytics: This has been a particularly active segment of the Big Data ecosystem in terms of startup and VC activity. From spreadsheet type interfaces to timeline animations and 3D visualizations, startups offer all sorts of different analytical tools and interfaces, and the reality is that different customers will have different type of preferences, so there’s probably room for a number of vendors. Go to market strategies differ as well – some startups focus on selling tools to data scientists, a group that is still small but growing in numbers and budget. Others adopt the opposite approach and sell automated solutions targeting business users, bypassing data scientists altogether.

Applications: As predicted, the action has been slowly but surely moving to the application layer of Big Data. The chart highlights a number of exciting startups that are fundamentally powered by Big Data tools and techniques (certainly not an exhaustive list). Some offer horizontal applications – for example, Big Data powered marketing, CRM tools or fraud detection solutions. Others use Big Data in vertical specific applications. Finance and ad tech were always early leaders in adopting Big Data, years before it was even called Big Data. Gradually, the use of Big Data is spreading to more industries, such as healthcare and biotech (particularly in genomics) or education. This is only the beginning.

Many thanks for my FirstMark colleague Sutian Dong for doing a lot of the heavy lifting on this chart. My former colleague Shivon Zilis of Bloomberg Beta contributed immensely to prior versions of this chart.

 

Can the Bloomberg Terminal be “Toppled”?

In the eye of some entrepreneurs and venture capitalists, the Bloomberg terminal is a bit of an anomaly, perhaps even an anachronism.  In the era of free information on the Internet and open source Big Data tools, here’s a business that makes billions every year charging its users to access data that it generally obtains from third parties, as well as the tools to analyze it.  You’ll hear the occasional jab at its interface as reminiscent of the 1980s.  And at a time of accelerating “unbundling” across many industries, including financial services, the Bloomberg terminal is the ultimate “bundling” play: one product, one price, which means that that the average user uses only a small percentage of the terminal’s 30,000+ functions.  Yet, 320,000 people around the world pay about $20,000 a year to use it.

If you think that this sounds like a perfect opportunity for disruption or “unbundling” at the hand of nimble, aggressive startups, you’re not alone.  I spent four years at Bloomberg Ventures, and this was a topic that I heard debated countless times before, during and after my tenure there. Most recent example: a well written article in Institutional Investor a few weeks ago declared the start of “The Race to Topple Bloomberg“, with a separate article highlighting my friends at Estimize and Kensho as startups that “Take Aim at Bloomberg“.

Yet, over the years, the terminal has seen its fair share of would be disruptors come and go. Every now and then, a new wave of financial data startups seems to be appearing, attempting to build businesses that, overtly or not, compete with some parts of the Bloomberg terminal.  Soon enough, however, those companies seem to disappear, through failure, pivot or acquisition.

What gives? And where are the opportunities for financial data startups?

Frontal assault: good luck

To start, Bloomberg is not exactly your run-of-the-mill, lazy incumbent. Perhaps I drank too much of the Kool-Aid while I was there, but I left the company very impressed.  Bloomberg, which was itself a startup not that long ago, comes armed with a powerful brand, deep pockets, a fiercely competitive culture, a product that results from billions of dollars of R&D investment over the years, and a technology platform that basically never goes down or even slows down, supported by generally excellent customer service.

But great incumbents have been disrupted before.  So there is perhaps another set of less immediately apparent reasons why the terminal has so far been very resilient to disruption by startups:

1.  It is protected by strong network effects.  One surprisingly misunderstood reason to the long term success of the Bloomberg terminal is that, beyond the data and analytics, it is fundamentally a network.  In fact, it was probably the first ever social network, long before the term was coined. Although some believe that its cachet as a status symbol is starting to erode, “the Bloomberg” (as it is often called) has been for decades the way you communicate with other finance professionals (for legitimate or not so legitimate reasons).  In its relevant target market, everyone is on it and uses it all day to communicate with colleagues, clients and partners. Web based services (Facebook, Dropbox, Gmail), often banned in financial services companies, haven’t made much of a dent in that, at least for desktop communication.

2.  It is an aggregation of niche products.  In the world of financial data, there is enough specificity to each asset class (and subsegment thereof) that you need to build a substantially different product for each, which requires deep expertise, as well as a huge amount of effort and money, to address a comparatively small user base (sometimes just a few tens of thousands of people around the world).  Bloomberg started with fixed income data and over many years, used its considerable cash flow to gradually conquer other classes (still a work in progress, to this day).  So disrupting the Bloomberg is not as “easy” as coming up with a great one-size-fits-all product.  It would take immense amounts of venture capital money to build a direct competitor across all those niches.

3.  It’s not “just” a technology play.  Providing financial data at scale is not a pure technology play, so it is not a matter of coming up with radically better technology to aggregate and display data, either.  At this stage at least, there is a whole web of human processes, relationships and contracts with underlying data providers that has been put on place over many years.

4.  It’s a mission critical product. This is a key point.  In the financial world, data is used to make gigantic bets, so total accuracy and reliability is an absolute must – which makes people cautious when experimenting with new products, particularly built by a startup.

The Bloomberg terminal business may face macro headwinds, as described in the Institutional Investor piece (dwindling of the number of relevant jobs on Wall Street and a global shift from desktop data to data feeds).  However, as a result of the above, I don’t see the Bloomberg terminal being entirely “toppled” by any one given startup anytime soon, and I think even competing directly with any of its key functionalities (unbundling) is a tall order for startups, even with access to large amount of VC money.  Not that it can’t be done – I just think there are lower hanging fruits out there and some real benefit to position away from the Bloomberg.

Where are the opportunities in financial data?

While I don’t see much opportunity for startups to build a Bloomberg terminal replacement (or a a replacement to Thomson Reuters or Factset, to be clear), I think there are fertile grounds “around” and “below” the terminal – meaning in areas where the company is unlikely to want to go.

Specifically, I believe there are going to be ongoing opportunities to apply some of the quintessential internet concepts and processes (networks, crowdsourcing, etc) as well as new-ish technology (Big Data)  to the world of financial data, including:

1.  Finance networks/communities.  Like the Bloomberg terminal did, some of the more interesting “adjacent” plays opportunities will marry data, tools and community.  Historically, capital markets haven’t seen much of a sharing culture (lots of nuances here, I know), which is in part due to the nature of finance investing itself – however, it’s going to be interesting to see how, at least in certain areas, that culture will evolve as digital natives rise in the ranks of their organizations.  Beyond early entrants Stocktwits and Covestor (which generally target a more casual audience), examples of such professional communities include SumZero, initially for Buy Side analysts but now wider, and more recently Quantopian, an algorithmic trading community where scientifically educated people and other quant types share strategies and algorithms.  Early stage startup ThinkNum thinks financial models should be shared and wants to the “Github” for financial models.  What else can be shared?

2.  App stores. The app store model is an interesting way of leveraging the expertise of a “crowd” of specialized third party developers (Bloomberg launched its own a couple of years ago). OpenFin, for example, provides infrastructure to enable the deployment of in-house app stores, addressing the necessary compliance, security and inter-operability requirements (having data flow from one tool to the other). A combination of an in-house app store infrastructure with some best of breed applications (say, a ChartIQ, which provides HTML5 financial charts, including technical analysis tools) is an interesting approach to target the portion of the market “below” the terminal, as  companies that cannot afford a full on terminal infrastructure could pick and choose the apps they need and have them work in their environment.

3.  Crowdsourced data.  From Estimize (which crowdsources analyst estimates) to Premise (which crowdsources macroeconomic data through an army of people around the world equipped with mobile phones), a whole new way of capturing financial data has emerged. Quandl, a financial data search engine, has aggregated over 8 million financial and economic datasets through both web crawling and crowdsourced, community contributions.  Once such a data platform has been built, could third party developers add analytic and visualization tools on top, essentially resulting in a crowdsourced “terminal” of sorts that would be reliable enough, at least for non mission critical, non real time use cases?

4.  Big Data “insights”: Extracting signal from data is obviously the end game here, and interesting startups are heavily focused on those opportunities, from Dataminr (social data analytics for Wall Street) to Kensho (which is working on “bringing the intelligent assistant revolution to finance”). In terms of market positioning, it is unclear to which extent those technologies compete with the Bloomberg terminal (which, for example, has been very active on the social data front), or potentially complete it.

The big question facing entrepreneurs and VCs alike is how to scale those businesses and turn them into billion dollar companies in a context where solidly entrenched platforms have a stronghold on arguably the juiciest part of the market. But overall I believe that we’re only going to see more startups going after financial data opportunities, with potential for some serious wins – I’m excited to see how it all evolves.

Recombine

The field of bioinformatics is having its “big bang” moment.   Of course, bioinformatics is not a new discipline and it has seen various waves of innovations since the 1970s and 1980s, with its fair share of both exciting moments and disappointments (particularly in terms of linking DNA analysis to clinical outcomes).  But there is something special happening to the industry right now, accelerated by several factors:

•      The cost of full genome sequencing has been dropping precipitously, in fact a lot faster than Moore’s law would have suggested.  Illumina just released brand new machines that make the $1,000 full genome sequencing a realistic possibility.  As a result, an extraordinary amount of data is going to become available at reasonable cost (5.5TB or 6.3 Billion bases… per patient).

•      Big Data technology has had its own, separate evolution, and there is now an arsenal of tools to process and analyze massive amounts of data, at a comparatively cheap cost.

•      Wet lab work has become a more standardized and increasingly automated process, considerably reducing the “friction” involved in collecting and processing physical samples. The cost of setting up biology labs, while still high, is starting to decrease, and molecular techniques are no longer the limiting step in genomic analysis.

As a result of the above, biology is rapidly evolving from being predominantly driven by traditional life sciences research to being largely driven by software and Big Data.  This evolution considerably reduces the capital required to build a successful venture in the space.  It also opens up the field to a new generation of startups run by inter-disciplinarian teams that have at least as much of a software and data science background as a biology background.  A whole new world of bio-hackers is also emerging, from synthetic biology to personalized medicine, the possibilities are immense and the impact on our lives potentially unparalleled.  It is entirely possible that the next generation of great entrepreneurs will be building “biology 2.0″ companies, rather than mobile apps.

This opportunity has not been lost on entrepreneurs and the last 3 years or so have seen a rapid acceleration of startup creation, in a wide range of area from diagnostics (Counsyl) to cloud platforms (DNANexus) to lab automation (Benchling, Transcriptic).  Interestingly but not surprisingly considering the above, most of those startups are funded by technology, rather than life sciences, venture capital firms.

Today I’m excited to announce that FirstMark is partnering with Recombine, a New York based startup that very much operates at this intersection between software, Big Data and biology, as its lead Series A investor. Recombine’s CEO, Alex Bisignano, symbolizes this new generation of entrepreneurs who have deep knowledge in multiple technical fields.  He has built around him a great, multi-disciplinarian team, and benefits from the deep industry knowledge and expertise of co-founder Dr. Santiago Munne, the owner of Reprogenetics and pioneer in pre-implantation genetic diagnosis.

Recombine’s core focus is the field of fertility and reproductive genetics, and it has had a spectacular early start with CarrierMap, its first product, generating a profitable multi-million dollar business with a comparatively small seed investment. The CarrierMap test is the most comprehensive, cost-effective, carrier screen on the market, and has already helped thousands of couples to identify and mitigate the risk of passing on serious illnesses to their children.  CarrierMap is sold exclusively through doctors and clinics, it is not a Direct to Consumer product (and therefore falls in a different category than 23andMe).

Beyond this initial focus, Recombine has ambitious plans to fully leverage Big Data technology to help decode the myriad aspects of our genome that are still not well understood. They have already obtained Institutional Review Board (IRB) approval for their first large-scale study, and the company is currently assembling a crack team of data scientists in New York City.  If you have deep expertise in data science field, this is an opportunity to help bring about a revolution in personalized medicine. Come join us!

 

Introduction to the Internet of Things (Video)

Here’s the video from SIIA’s “IIS: Breakthrough” conference that corresponds to the slides in the previous post.  Not necessarily the crispest delivery on this one, but here you go.

Introduction to the Internet of Things (Slides)

I’m doing a talk on the Internet of Things tomorrow at the SIIA’s “IIS: Breakthrough” conference tomorrow, and here are the slides I’ll use.  It’s meant to be a high level introduction to the topic, for a broad audience of “information industry” professionals.  Also used an earlier version of those slides at the WIN Global Innovator last week, which was fun. Feedback welcome.

10 Quick Takeaways from CES 2014

1.  Big brand curved TVs and mega booths are cool, but to me this year’s show was all about the rise of the crowdfunded hardware startup.

 

 2.  It’s official, there are now more wearable wristband vendors than there are human wrists on the planet.

 

3.  The wearables category is still waiting for its disruptive “iPhone moment”.  New releases show nice progress, but mostly incremental.  Smart watches have a long way to go.

 

4.  Accelerating trends on display, still early: family tech and senior tech.

 

5.  The lines between the tech and non-tech worlds keep blurring.  Pizza Hut and Ford both had a very noticeable presence and were pitching their tech innovation.

 

6.  Hardware innovation is truly global.  Some of the most interesting startups I met were from Manchester (UK), Ukraine and Lebanon.  France continues to be very active in the space (Parrot, Withings, Netatmo, Sen.se, etc.). [UPDATE: See below some great 3D visualizations of the latest Withings and Sen.se products, produced by SketchFab]

 

7.  China was left, front and center.  Not just as the “workshop of the world” but, more strikingly, as as a producer/innovator in their own right. The rise of the juggernaut only seems to be accelerating.

 

8.  In home automation, entrepreneurs were talking a lot about AllJoyn, Qualcomm’s open source platform and language, and the AllSeen alliance that is going to promote an open standard for the Internet of Things.

 

9.  In 3D printing, Makerbot is killing it, with its three gorgeous new printers.  Toys still seem to be the killer app for consumer 3D printing, although the new Chefjet chocolate 3D printer by 3D systems was pretty awesome. Consolidation in the consumer 3D printer space seems likely, in the not-too-distant future.

 

10.  Yves Behar and Bre Pettis are incredible creative and entrepreneurial minds, who deserve all the hype they get.  I got to witness this firsthand as a judge on the finals of the first TechCrunch Hardware Battlefield (with Jen McCabe, also very sharp), as they turned the judging into a real time mentoring session, providing  insights that were worth way more than the top $50,000 prize.  Exciting and inspiring.

Mother (click to view in 3D)

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Mother

Withings Aura (click to view in 3D)

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Withings Aura

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