In my post yesterday, It Takes $30mm To Train A VC, I commented:
Let’s debunk one notion immediately: being a successful entrepreneur (or even a failed entrepreneur) is absolutely not a criterion for being a good VC. The data is extremely clear on this – there is little correlation between the best VCs and past entrepreneurial experience. That is not to say that entrepreneurial experience is not an excellent segway into VC, it’s just not a required segway.
There was some follow up to this statement in the comment section which prompted me to further expand on this issue.
Irrespective of the data (which speaks for itself), the rationale behind this statement is also important. Being an investor is quite different from being an operator. There are definitely overlapping skills between the two professions, but they don’t map one to one. In reality, many professions impart some of the skills necessary to be an investor, some more than others, but none give you the full exposure to it all.
Equally important, there are simply different types of investors out there who bring different value to the table. Some bring operational expertise, some deep technical and product understanding, and some are killer deal people who will help you land a major hire, close a big BD deal or raise your next round. There is no one-size-fits-all box that we can fit all good investors into.
Jeff Bussgang once told me ‘it takes $30mm to train a VC’.
I’ve been thinking about this comment a lot over the past few days while following two very interesting blog posts from my friend and colleague, Jerry Neumann. As is often the case, Jerry cuts straight to the heart of an important issue, this time regarding the issue of training young VCs. In his posts (see here and here), Jerry postulates that the venture industry does a piss poor job of training new VCs, arguing:
One of the odd things about venture is the lack of seriousness about what we do. Venture is the only professional services business which does not think training its employees is a good idea. Witness Brad Feld’s comment—ironically, in the textbook that Kauffman asks its Fellows to read—“We don’t intend to hire associates and train them; [when we retire] we are just going to shut shop and go home. Done!” This après moi le déluge attitude means that our industry continues to be half-staffed by people who half know the job. I am constantly amazed at the crazy things other angels do, usually sins of omission, and VCs I know express the same sentiment about other VCs. In no other profession do they expect people to just show up and do the job well. In our profession many show up and do the job poorly. We all suffer. If we care about innovation—not just making money—we should be training people how to invest in and manage investments in startups.
Both Brad Feld and Fred Wilson said they did not have junior VCs because they did not want to burden entrepreneurs with inexperienced VCs. This makes a ton of sense. But, then, where should experienced VCs come from? Andy Weissman comments that perhaps VCs are best trained by being entrepreneurs.
And finally, Jerry concludes:
So if specialized knowledge is needed, how to generate it? Kauffman has their Fellows program to train VCs. Andy thinks being an entrepreneur is the best training. I disagree with both. I think only doing the job teaches the job. And since no one wants anyone doing the job who doesn’t know the job, this means a long apprenticeship. But the best VCs seem to not be interested in having apprentices. So, then what?
In my opinion, if we want better trained VCs, then either the culture has to change so VCs feel an obligation to train the next generation, even though it costs them money, or the LPs need to start looking out for their future returns in addition to their present ones and compel VCs to have a bench.
As a young VC learning the business from the inside, this issue is front and center in my life.
There are a number of important questions embedded in this discussion:
- What are the characteristics of a good VC?
- Can these characteristics be trained?
- If so, how should they be trained?
Before going further, I will broadly qualify that there are no right answers to these questions. If there is one thing I have learned over the past three years it is that there is rarely a right answer for anything in venture – the degrees of freedom in this business are too massive to isolate specific success variables in any meaningful way. There are simply many different ways of doing things, each with their own costs and benefits. And in case you don’t believe me, please tell me which of the following venture models is ‘right’?
- SV Angel: seed, small checks, broad basket portfolio approach
- First Round Capital: seed, hybrid check size, hybrid concentrated/broad basket portfolio approach
- Union Square Ventures: early stage, larger checks, concentrated portfolio
With the qualifier above noted, let’s debunk one notion immediately: being a successful entrepreneur (or even a failed entrepreneur) is absolutely not a criterion for being a good VC. The data is extremely clear on this – there is little correlation between the best VCs and past entrepreneurial experience. That is not to say that entrepreneurial experience is not an excellent segway into VC, it’s just not a required segway.
So getting back to our three questions: what are the characteristics of a good VC? Can these be trained? And if so, how should they be trained?
My hypothesis is that there are certain innate characteristics that are not only table stakes to play the game, but represent the intangible factors that distinguish the good from the great. These characteristics include:
- Honesty and integrity
- Intuition about people, markets and products (in that order)
- Intellect to problem solve and think critically about risk and opportunity
- Empathy for all stakeholders
- Personality to build enduring relationships
- Strategic mind
On the one hand, I don’t believe that it is possible to train these characteristics – you either have them or you don’t. Yet, on the other hand, I do believe that some of these – most specifically intuition, empathy and a strategic mind – can be refined and honed over time through life experience.
In addition to the innate characteristics, there is a second class of VC characteristics that are mostly acquired through traditional learning and on the job training. These include:
- Product expertise
- Domain and market expertise
- Deal making skills
- Network of relationships
- Financial savvy
There are many ways to acquire these characteristics – entrepreneurial experience, working in industry, learning on the job as a junior VC (although this won’t work for product), etc. It is tough to pinpoint a ‘best’ path, as each path teaches different and relevant skills. As Jerry notes:
The best—in fact almost all—VCs have historically come from one of five places: VC, banking, law, technology firm management, or journalism…Each of these paths teaches people some of the necessary skills to be a venture capitalist, but not all of them.
To be clear, while you can learn many of these acquired characteristics, I do not mean to imply that learning them will make you good or great at them. The degree to which you are good at something is generally a function of both your training and your natural born capacities. Different people have different natural strengths – some have natural product vision, others are killer deal people. No matter how much I train, I will never be as good at throwing a ball into a circular hoop as Michael Jordan. My point is not to diminish the importance of innate disposition, but rather to emphasize that these skills and characteristics more readily lend themselves to be improved through traditional learning methods in contrast to the uniquely innate characteristics described above.
Finally, I believe there are certain VC characteristics that are only acquired through direct life experience:
- Situational experience
- Cyclical market experience
In a blog post I wrote after meeting with Fred Wilson in November 2010, I commented:
While there are certain traits common to all successful investors - intellect, intuition and disposition - these are merely necessary, but insufficient, conditions to being great. Venture investing (like many investment professions) is heavily informed by pattern recognition, and for better or worse, pattern recognition is naturally derivative of experience.
The reality is that no amount of intellect, intuition or disposition can fully prepare a young VC to manage a dysfunctional board, bite the difficult bullet of a down round financing, push through painful but necessary management changes, or navigate macro economic cycles.
Given the framework laid out above, where does this all leave us with respect to the issue of training new VCs?
It is clear to me that there is a fundamental need to train young VCs by giving them access to the experiences necessary to grow into great venture investors. Part of that education can come through on the job training (both in and out of VC) and supplementary learning initiatives (e.g. individual learning, Kauffman Program, etc), but a massive part can only be acquired through the passage of time and living through various situations and scenarios. To me, the key to navigating learning through life experience is mentorship. As summarized in my Fred Wilson blog post:
In the absence of years of experience, there is one absolutely critical way to mitigate the risks of inexperience while young investors learn on the job - mentorship. As Fred has advocated time and again on his blog, the venture business is best learned through apprenticeship (at the very least this is true for those who are career VCs and not transplants from successful entrepreneurial careers). No training program in the world can prepare one to be a great VC precisely because experience is such a principal component. Having the opportunity to lean on and glean from the experience of those who have walked the walk is invaluable. It is not a ‘nice to have’, but rather a ‘need to have’.
While some firms have made the conscious decision not to train young VCs (I get it and respect the choice), many have thankfully chosen to mentor new entrants to our industry and provide them with the fertile learning ground upon which to grow into impactful venture investors.
Just last week, FRC announced that Phin Barnes and Kent Goldman had been promoted from Principal to Partner. Shortly prior, Mo Koyfman was promoted to Partner at Spark Capital. Eric Weisen of RRE was promoted from Principal to Partner two years ago. There are countless other strong young VCs out there that are making a huge positive impact – Adam Ludwin (RRE), Marissa Campise (Venrock), Christina Caciappo (USV), Andrew Parker (Spark), Matt Witheiler (Flybridge), Charlie O’Donell (Brooklyn Bridge Ventures), to name just a few that I am personally close with (and there are many many others not mentioned). These are a few examples of individuals who have grown and matured in the venture industry over the years. Only time will tell if they ultimately become great VCs, but early indications are promising that this crew (and others) represent a bright future for our industry.
At some point over the past two years I crossed some mythical chasm where I started receiving at least one or two emails each day that read something like this:
Dear Ben, I am a [student, developer, aspiring entrepreneur, agitated lawyer, recovering banker]. I recently came across your [blog, company website, long lost cousin] and would love to talk to you about [my new company, career trajectory, the supersonics]. Do you have any time in the next week to connect?
I am a softy when it comes to these types of meeting requests, particularly because I’ve written so many of these notes myself over the past decade through multiple job searches, career soul searching, business school, and simply seeking general mentorship and advice. I am a HUGE proponent of mentorship having been the fortunate recipient of incredible advice and guidance over the years, and I believe in karma points for giving of your time with no expectation of receiving anything in return.
Unfortunately, the physical laws of nature have become an insurmountable barrier to accommodating all of these requests. 24 hours in a day is not nearly enough time to get through all that needs to be done, neither personally nor professionally. I simply no longer have enough open capacity in my calendar to take all of the meetings. As a result, I’ve found myself writing responses that read like this:
Dear [X], thanks so much for your note. Unfortunately, my calendar is jam packed so I won’t be able to fit in this meeting. I wish I could be more helpful, but I just don’t have the bandwidth right now.
These notes SUCK and I feel like a humungous schmuck every time I click send.
Truth be told, I am incredibly flattered every time someone reaches out seeking my input (why someone would ask for my input remains one of the great mysteries of the world) and I most definitely do not mean any disrespect by denying a request for such a meeting. It is just that, like many many many other people who work hard and have a family, I am very busy.
I’ve been thinking about how to better handle these requests and have come up with the following action plan:
- Going forward I’ll try holding more regular office hours broken into 20 minute slots to accommodate more of these requests
- I’m going to integrate the ‘productivity hack’ of scheduling more standard 30 minute meetings instead of hour meetings
- I plan to include a link to this blog post every time I send a ‘rejection’ notice in hopes that people will understand that I don’t mean to be a huge schmuck but am just a busy guy
If you have other suggestions for how to better handle this I’d love to hear them in the comments.
————— Forwarded message —————
From: [XXXXXXX] <XXXX@XXXXX.com>
Date: Wed, Mar 7, 2012 at 5:04 PM
Subject: Early Stage Company Looking for Capital
To: Ben Siscovick <firstname.lastname@example.org>
Good afternoon Ben,
My name is [JANE DOE]. I am [MORON BANKER]’s Secretary. [MORON BANKER] is a Merger & Acquisition Specialist in California. He is working on behalf of an early stage business in the mobile industry looking for growth capital. He asked me to try to arrange a call with you to make an introduction and discuss this deal. Please find attached a profile with information related to our client. Please let me know if your schedule would permit a call at the end of this week or early next.
Executive Secretary to [MORON BANKER]
Merger and Acquisition Specialist
I am SO late to this party (47 MILLION views as of this posting), but this has got to be the best music video (music + visual) that I’ve seen in ages.
Discovered via @mauerbach804
Gotye - Somebody That I Used To Know
And if you want to really have your mind blown, watch this remake (32 MILLION views so far) by Walk Off The Earth.
I have the opportunity to see many companies doing fascinating things with data at my day job. One truism that needs to be recognized is that generating interesting data is not nearly enough, but rather entrepreneurs need to be laser focused on productizing data. I’ve seen many entrepreneurs miss this point, often times creating an interesting mousetrap for generating, collecting or aggregating data, but stopping there instead of going the distance by productizing the data.
So what does it mean to productize data?
Most generally, there are two types of data-related products:
- Data-driven product. A standalone product that is informed and enhanced by data (ex. Amazon’s recommendation engine)
- Data product. The product is data itself (ex. AP newsfeed)
Let’s look into each of these types of products more closely.
The concept of productizing data is quite intuitive with respect to data-driven products. In these cases a feedback loop is created where some standalone product improves by collecting and effectively utilizing data. Zynga exemplifies the power of data-driven productization by capturing, storing and analyzing almost every interaction users have with their games, and then uses this data to improve game play and optimize monetization. As described in a recent WSJ piece:
To understand why Zynga Inc. is among the tech industry’s hottest companies, consider how it gets people to buy a bunch of things that don’t exist. Last year, Zynga product managers for a videogame called “FishVille” discovered something intriguing while sifting data that Zynga collects when people play its online games. Players bought a translucent anglerfish at six times the rate of other sea creatures, using an imaginary currency people get by playing the game. The “FishVille” managers had artists whip up a set of similar imaginary sea creatures with translucent fins and other distinctive features, says Roger Dickey, a former Zynga general manager who left the San Francisco company recently. This time, they charged real money for the virtual fish, and players snapped them up at $3 to $4 each, says Mr. Dickey.
’We’re an analytics company masquerading as a games company,’ said Ken Rudin, a Zynga vice president in charge of its data-analysis team.
Companies that are able to leverage data to improve products benefit from what we at IA describe as Data Economies of Scale. You can think of Data Economies of Scale as a virtuous spiral in which strong products attract users who generate invaluable data through their usage. Insight gleaned from user generated data is then fed back into product development which helps evolve and improve the product, thus enabling it to attract more users who contribute more data which then feeds into further product improvements, more users and more data, etc. etc. etc.
Data Economies of Scale is an extremely powerful competitive barrier enabling a product to move further and further ahead of new competitive entrants who have yet to achieve enough scale to benefit from a data-driven product feedback loop.
In contrast to data-driven products, it is somewhat less intuitive to understand the concept of productizing data for a product that is essentially, in and of itself, pure data.
Before diving into productization strategies, let’s spend a moment first clarifying the concept of a company whose product is essentially data. Using an example to demonstrate the concept, let’s look at the New York Stock Exchange (NYSE). As the exchange through which stock transactions occur, the NYSE generates an extremely valuable proprietary data asset - market tick data. NYSE then sells this market tick data to banks, hedge funds and media outlets that use it in a variety of productive and profitable ways. Thought of in this light, NYSE is most fundamentally a mousetrap for generating and capturing data and its core salable product is data itself.
Contrary to what you might think at first blush, selling raw data is rarely a ‘product’. The problem with raw data is that it is difficult for end users to consume and it requires users to start from scratch trying to figure out what to do with it. (That said, sometimes users - particularly those who are highly technical and quantitative - want the exploratory flexibility that comes with having the unfettered raw data; but this is the exception, not the rule.)
Instead, data almost always require some sort of ‘packaging’ to become a product. Though I am sure there are more, here are three types of effective packaging for productizing data:
- Structuring data for a particular use cases and ease of consumption, often in the form of an API. A great example of an API product company is The Echo Nest whose entire product suite is a set of highly structured developer APIs that provide powerful access to music data. Another good example of a structured data product is Yipit Data from our portfolio company Yipit. Yipit Data aggregates and structures all relevant daily deal data in an easily understandable and consumable manner specifically tailored for their primary target market of financial analysts.
- Visualizing data in the form of a highly interactive, dynamic and insightful dashboard. Great analytic dashboards allow users to both explore data and be pushed actionable insight. Our portfolio company Next Big Sound does a killer job of taking raw social, event and transactional music data and turning it into easily understandable graphs, charts and visualizations enabling sophisticated exploration of the data and highlighting important actionable insight.
- Creating an experience around data. Sometimes packaging is as straightforward as creating a nice interface and simple interaction tools. For example, Twitter’s product is most fundamentally data (tweets) wrapped in a clean interactive interface that allows users to create, consume and engage with the data. (Interestingly, Twitter initially allowed third parties to create competitive packaging but later strongly discouraged and eventually prevented third parties from creating their own experiences. This strategic move is very much in line with the spirit of the framework I have laid out here – Twitter recognized that a fundamental part of the Twitter ‘product’ is the packaged experience around the data, and as such, they felt it imperative not to outsource this critical element of productization.)
I had a chance to meet with an impressive entrepreneur last week who exemplifies the theme of productizing data. The entrepreneur’s fundamental asset is TV related social engagement data, but his products include 1) multiple well defined structured APIs, 2) an interactive analytics dashboard, and 3) stand-alone applications build on top of the data. It was awesome to see an entrepreneur with such strong product sensibility exemplifying the powerful offerings that emerge when you productize your data.
Like my good friend elsiguy, I’ve fallen in love with Spotify. Over the weekend I decided to take my relationship with it to the next level by upgrading to the premium service for $10/month. For the uninitiated, Spotify’s basic service is free, on-demand desktop music streaming supported by advertising. There are two premium offerings:
- $5/month removes all ads
- $10/month removes all ads, offers mobile access to the entire music library, and allows users to sync songs and playlists to devices for offline listening
Spotify is not the first music service to offer a vast music library, on-demand streaming and mobile access. So why has Spotify emerged as the leader of the pack in on-demand streaming when others (Rhapsody, Napster, etc.) have failed to gain serious market traction.
I believe the answer is rooted in Spotify’s implementation of the freemium business model.
Let’s step back for a moment. A freemium model is one in which some basic product or service is given away for free and premium features are offered at a price.
Freemium models need to satisfy two conditions to be viable:
- the basic free service needs to be strong enough to attract lots of users
- the premium offering needs to be compelling enough to incentivize some meaningful subsection of users to pay
Spotify nails freemium. Let’s take a closer look at some of the specific factors that make it so compelling.
Free basic service
Spotify’s free service is an awesome standalone offering. Some factors that contribute to its awesomeness:
- Library. Spotify’s music library is vast with licensing deals with all major record labels. You won’t find everything (Metallica, The Beatles, Pink Floyd, Led Zeppelin - absent do to asinine and shortsighted thinking), but you’ll find almost everything.
- On-demand. On-demand means the user has the flexibility to listen to any song at any time and in any order (and until recently, only music owned/locally stored afforded users this flexibility). Historically, free online music offerings have been constrained by the economics of music licensing and have been unable to combine ‘free’ with ‘on-demand’ (on-demand royalty payments are much higher than those for ‘radio’/non-on-demand streaming). And while the the jury is still out with respect to the economic viability of the Spotify model, the fact that there is a framework that allows free on-demand music streaming is HUGE. Together with mobile access and offline syncing, on-demand streaming is fundamental to move to a more attractive cloud-based streaming universe where there is no need to ever own and locally store music.
- Social. A fundamental part of Spotify’s experience is the innate social integration. For most people the Facebok integration is not only a wonderful tool for music discovery, but also serves to create massive stickiness on the platform. The fact that I can share and benefit from shared playlists creates a strong incentive to be on the same platform as friends. In effect, Spotify is leveraging Facebook to bootstrap the creation of it’s own ‘music social graph’ and will benefit immensely from powerful network effects that emerge from owning it. (Note: Spotify is not the first to integrate social with music listening, but they do it relatively well and make it core to the fabric of the experience. I have a full blog post brewing on this topic…stay tuned.)
- Ad supported. The fact that the free service is ad supported is important, but not all that interesting in and of itself. However, what is important and interesting is Spotify’s specific and unique implementation of ads within the service. First, Spotify does a great job walking the tight rope of making ads intrusive and annoying enough to incentivize users to seriously consider upgrading, but not so much so that it completely interferes with usage of the basic offering. Spotify uses some interesting tricks to walk this line, the most interesting to me is that they constantly rotate the ad unit interface - sometimes vertical, sometimes horizontal, sometimes audio, and sometimes there are no ads at all. Some find this annoying. I find that it actually makes the ads more effective (i.e. I notice them a lot more) and I’m satisfied knowing the ad will shortly move. Second, the quality of Spotify’s audio ad unit is quite impressive. Despite the fact that audio ads cut into the listening experience, Spotify seems to intelligently serve units that are contextually relevant to the user and their listening tastes - making the ads more bearable and less obnoxious. It also serves these ads in a relatively well integrated manner so the audio experience is not jarring to the ear.
The premium offering is sufficiently differentiated from the free service and offers clear and demonstrable value - a compelling mouse trap to attract users to upgrade and pay.
- Mobile. A massive amount of music is consumed outside the home and on the go, and as noted above, offering mobile access is a key condition to evolve away from owned/locally stored music to cloud streaming. Having on-demand access to the entire Spotify music library at my fingertips at all times makes my local music collection seem puny and pathetic.
- Offline. The world is moving towards ubiquitous connectivity, but until we get there offline sync is necessary to replace the owned music paradigm. With offline sync, I have unfettered offline access to all songs, albums and playlists that I have selected to sync locally to my devices. In fact, I’m benefiting from offline sync at this very moment listening to Bon Iver 30,000 feet above the ground while writing this blog post.
- Ad free. Nuff said.
Spotify is not the only music streaming service making waves right now - Rdio has a very compelling differentiated service as well (similar to Spotify in many ways and even better in some). The emerging model for these new and hopefully viable music services is to create a killer freemium offering that attracts masses of free users while offering enough premium value to incentivize users to upgrade to the paid subscription. As a die-hard music fan, I’m rooting hard for these guys to make it work.
I recently had a fundraising discussion with the head of BD at company looking to raise capital. He is a good guy and the company is doing cool stuff. But a word to the wise - fundraising is not business development and your BD lead should not run your fundraising process. Fundraising is fundamentally the responsibility of the CEO and cannot be delegated to other members of the team.
I get the rationale for having the head of BD run the fundraising process; business development professionals are deal people - they are articulate, know how to sell and are skilled negotiators. Their job is to ‘do the deal.’
And this is where some companies get tripped up. Despite the fact that it looks like a duck, walks luck a duck and talks like a duck, your discussion with a VC is *not* a ‘deal’ in the traditional BD sense. It is not a temporal alignment of strategic interests.
Your engagement with a VC is a marriage. It is a fundamental, nearly irrevocable, company-life-long partnership.
From the investor’s perspective, the single most important determinant of whether or not to enter into the partnership is the people. Don’t get me wrong, everyone on the team is important, but there is no avoiding the reality that the CEO is the one driving the ship - the overall strategy, the product vision, the key sales initiatives, the hiring of lieutenants, and so much more. The CEO is the final decision maker and ultimately bears responsibility for the success of failure of the company. The buck stops at the CEO.
When the CEO is not leading the fundraising discussion, rightly or wrongly, that in and of itself sends a strong negative signal - is he incapable of describing the vision? Does he have a problem inspiring others to believe in the opportunity? Is he unable to sell? Will he be steam-rolled in a negotiation?
Conversely, having the CEO run the process puts the CEO’s capacities as a leader, visionary and salesperson on display to inspire investor confidence. Furthermore, it enables the irreplaceable opportunity for the CEO to develop a relationship the investor. Remember, a venture investment is more akin to a marriage than a ‘deal’, and it only works if there is a strong relationship built upon mutual trust and respect. The CEO is the primary point of contact between the company and the investor, and it is the CEO who needs to play point building that relationship on behalf of the company.
To be clear - the CEO is not the only important team member and is often times not even the smartest or most capable (the best CEOs hire people who are smarter and more capable than themselves!). All the team members are important. But for the reasons described above, fundraising is fundamentally a CEO-level responsibility and should not be delegated.
Amongst the many buzzy internet themes popular these days, one that particularly intrigues me is the theme of consumerization of enterprise. Broadly speaking consumerization of enterprise refers to the evolution of enterprise software. As anyone who has worked in a big corporation can attest, enterprise software is generally stogy, complex, bland and antiquated. In stark contrast, successful modern consumer applications are clean, simple, engaging and fresh.
Over the past year, my colleagues at IA Ventures and I have developed a simple framework for thinking about this theme. To us, consumerization of enterprise means three things:
- UI/UX. Incorporating design and interaction best practices refined over the past decade in the consumer web for clean, simple and engaging user experience and user interface.
- Social. Building social into the foundational fabric of the application either by enabling social interaction and connectivity through the application and/or leveraging graph data (social, interest, professional or other) to optimize the experience and performance of the software.
- Mobile. Building applications with a mobile-centric design philosophy. In other words, building applications from the ground up optimized for usage on mobile phones and tablet devices.
We have made two investments at IA specifically around this theme - Banksimple and Coursekit. Both companies exist to disrupt massive incumbents (Banksimple :: online banking portals from traditional brick and mortar banks / Coursekit :: Blackboard learning management system) and both specifically replace antiquated enterprise offerings with applications designed from the ground up with UI/UX, Social and Mobile best practices incorporated.
The exciting thing is that the world of enterprise software is ginormous and industries across the board are ripe for disruption. The application of consumer web best practices will be one of the defining drivers of innovation and evolution in the world of enterprise software and we are just now beginning to see the promise of consumerization of enterprise become reality.