You tell me!

There's no possible way I can get up to speed on what a founder knows about their industry, plan, goals, or team, in just a few hours or even days.  Hell, I could spend weeks on it and, hopefully, it wouldn't make a difference.  

You should know way more about this than I ever could.

That's why the consistent theme among the very worst pitches I take are the ones where the entrepreneur asks me what I think--about everything.  It feels as if the entrepreneur doesn't know for certain that the idea is good, and they want me to validate it.

That's not my job.

You're the one investing all your time into it.

You're going to put way more money--either directly or into opportunity cost--than I ever will.  You'll need to take on the responsibility of your employee's livelihoods.  It will be your reputation on the line much more than it will be mine.

So when you're asking me if an idea is good, my first thought is...

You tell me!

The most successful founders I've work with are in a position to know whether a plan is the right one.  Sure, there might be some blindspots in it--and that's where outside perspective can be helpful, but the general direction isn't for me to vet.

It's for you to tell me after you've told it to yourself convincingly--because you know you've done your homework and you're in a great position to be the judge.

Don't ask me if you're raising enough money.

Tell me you are.

Don't ask me what I think of the product.

Tell me what your customers do think or will think--and why.  

Don't ask me what the milestone should be.

You tell me what's really hard and what should convince a next round investor that you've accomplished amazingness after you reach it.

Most of the time, I'm pretty sure the entrepreneur pitching me lacks clarity and conviction, and they're not asking me to judge--they're asking me what they need to do to become sure.

The person they need to convince usually isn't me--it's a customer, and they probably haven't spent enough time with them, or never was one themselves.   

Turning the Phone Down the Street into the Feet in the Store: My Investment in Radius8

Amazon is opening up retail locations.

Think about that.  

The very behemoth that made bricks and mortar into dirty words thinks it's important to have a physical presence in a storefront.  

Makes you think about everyone trying to turn their digital presence into just another location, but in the cloud.  Competing with Amazon online is a loser's bet that smart retailers can't afford to make.  If you know what you're looking for, for most things, there's no better place to get a thing than Amazon.

If you need help, need to touch a item, see how it feels, talk to a human, try on, test, or hell, if you're just looking to walk around and pass the time with your friend, you want to go into a store.  Plus, as quickly as Amazon can deliver something, it isn't quicker than just walking in and walking out with something.

And now, Amazon's going after that, too.  

If I were a retailer, I'd be pretty scared if I didn't have a plan to fight.

And fighting means using all of my resources, together, in a united front--both digital and storefront--together.

That's where Radius8 comes in, the latest Brooklyn Bridge Ventures investment that I'm excited to announce.

 

 

They provide a technology that allows retailers to curate trending local store inventory online, in real time, to customers who are online and within the vicinity of a store.  Brands and retailers have traffic--lots of it.  You visit the sites and social of brands you love because they speak to you.  You have a relationship there.  They're your trusted and stylish friend.  

Amazon in your employee.  You tell it what to do, but you don't spend time there.  You're in and out.  

Brands need to turn that time and influence into in store dollars.  

Radius8 turns the phones down the street into the feet in the store by turning the local portion of their digital presence on it's head.  Instead of hitting local last--that clunky 1990's "Find a store" page (always the worst page on a site)--now you hit it first, at the top of the funnel.  You experience the digital presence of a store or brand locally, because you are local.

Retailers can offer individual items to online customers within a geofence of each location and connect you to the human who can tell you for sure that your pants are in stock and so is a nice pair of shoes to go with it.  It just makes sense--because if you're in a Starbucks next door to a Gap, the website should know that, as should their Facebook and so should their ads.  They should direct you to come on over, not shop online where the experience and delivery competes head to head with Amazon, and creates costly returns.  

Brands and retailers agree.  Before Radius8 came out of beta they signed a six figure deal with Guess and have several more in the works.  I led a million dollar pre-seed round for them and I continue to be impressed with their traction and product development.  

 

The Trouble with Venture Capital Data

There aren't many people who get the chance to analyze venture capital fund return data.  You'd have to work for a very limited number of fund performance tracking firms, like Thomson Reuters, Cambridge, etc., or be an institution big enough to see a ton of different funds over time.

So when someone gets access to a dataset, no matter how incomplete, it's no surprise they'll rush into making lots of declarative statements about how the asset class performs without even a reasonable gut check.

Mattermark just posted a short report full of such statements and the former 21 year old institutional LP analyst in me (the job I got my VC start in over 15 years ago) flipped his shit upon close review.

Here's everything wrong with this dataset:

1) Sounds big, but really isn't.  

First, the author says the dataset is "a dataset compiled by Bloomberg, covering 3,300 individual funds and 1,600 general partners".  Sounds like a huge amount, but only later does he say that only "476 funds which had known Net IRR values, the overwhelming majority of which were from vintage 2002, or more recently."   

VC funds raise money, on average, between every 3-4 years--and many more often than that.  Conservatively, though, this data set of mostly 2002 or later funds would cover about 4 funds from each firm given that timeframe.  That means if you have 476 funds, you're looking at about 119 managers.  Now, not every manager sticks around through four funds, but even if you're generous it's probably no more than 200 managers.  If it's much more than that, you're probably looking at a bunch of newbie funds on their first or second fund and their performance is too new to judge.

So what percent of the market is that?  Well, CB insights lists somewhere in the neighborhood of 500 active VC firms as of 2013--meaning firms that did 4 or more deals that year.  The NVCA has pegs the number of firms in this period as 900, but either way, it's multiples larger than whatever dataset Bloomberg has.  Because returns are so positively and unevenly skewed, it's really hard to say you know a ton about the asset class.  

2) Saying "long term returns" when you only have vintage 2002 and after data is a joke.

Companies take a long time to exit--often 5-9 years.  If funds put their money to work over 3-4 years, how long before you really know that much about a VC fund.  

The midway point of this dataset is 2009.

The average company of a 2009 fund was funded in 2011, just five years ago, and half the companies in that fund are less than five years old.

That means that half of the deals in half of the funds in this dataset are younger than Munchery, Duolingo, FiftyThree, and Codecademy.  

Seems a little presumptuous to know exactly how that younger half is actually going to turn out when you look at it that way, doesn't it?

You know what a long term dataset is?  Try one that starts with Accel I or Battery I back in the early 80's.  That's some long term, multiple cycle kind of data.  That's what we had at the General Motors pension fund when I was there.  I mean, even forget the 80's for a moment.  Analyzing venture returns without even looking at the 90's?

What is this?  The baseball steroid era?  Did we just forget that decade even happened?  That's a lot of data to ignore.  

Plus, if you were analyzing data from funds, you wouldn't necessarily compare absolute sizes.  Fund sizes on average have grown every year as the asset class has changed.  Companies are staying private longer than they did and so the growth rounds being raised are unique to this era.  If you really want to compare big versus small, you'd try to normalize the size data across time.

3) You can't eat IRRs for breakfast.

You know what the IRRs of Quirky and Fab were before they went to zero?  Really really big.

Looking at interim IRRs of young funds, especially during boom periods in venture isn't predictive of outcomes.  Sometimes you've got a Google and other times it's a Pets.com.  

The only really way to know?

Cash in the bank.  Cash on cash returns, which take a long time to get, if you get them at all, are really the only true judge of VC returns.

Making investment decisions based on the private company markup of the last idiot who put money into something to get a preferred share that comes out first if shit hits the fan... well, good luck with all that.

4) Gut check.

Sometimes, you have to pull back from the data and just think rationally.  If you don't think that it's harder to put more money to work in venture than less, in a world where companies do more with less, and great deals are scarce, than I don't know what color the sky is in your world.  

If you have a $500 million fund, and you invest in two unicorns, and somehow maintain your pro rata, owning 20% of the fund, you still haven't even returned capital to your LPs.

In my dinky little sub-$25mm seed fund, a billion dollar outcome returns the whole fund three times over--just one, let alone what all the other deals do.

Venture doesn't scale--and if the data doesn't point that out, then I think you have to start questioning your data, or deciding that the data you have isn't venture.  When Uber raises billions in a single round, seems weird to put that in the same asset class as the $350k I just gave to two people and some duct tape.  

Don't believe everything you read.  

Know Thyself, Venture Capitalist: Thoughts on feeling open or closed.

It's very easy to think that there is a clear cut difference between the really great ideas and the really bad ones.  You believe that no matter when you get pitched, you'll usually do a good job of telling the difference between the two.

Sure, most of the really low chance of success stuff--things in unworkably small markets, unprepared founders, or ideas that lack a clear user value proposition--falls away pretty quickly.

But there's *a lot* that "could be".  I think, if I'm not careful, my own personal feelings of being open or closed to new deals could impact my willingness to invest.

That's a very dangerous thing for an investor--to have a major factor in decisionmaking be completely unrelated to a driver of success.  

It happens, though.  It's undeniable.

Sometimes, you feel like things are slow, and while you're not obligated to make a certain amount of investments per year, it's difficult not to "look for something".  On the other hand, good opportunities sometimes come in bunches.  You can feel a bit overwhelmed with your time and less open to writing new checks.  

If the amount of time an investor spent with a company was a major factor in its eventual success, it would make a lot of sense not to make investments when you don't have much time.  As much as any of us think we make an impact, factors like the team, the market, and the idea are going to dwarf anything we can do.  You'd rather be a time-crunched investor in Uber than be able to spend a lot of time on a mediocre idea. 

How an investor feels about their current portfolio can also have an impact.  Maybe things in their fund have taken a turn for the worse and they get conservative.  That might be the worst thing you can do when that fund-returning potential company shows up and requires an extra bit of guts to invest in.  

Similarly, fund timing has unintended consequences on investor mindset.  Some investors come out of the gate a little too fast when they raise a new fund, feeling like they have all the money in the world.  Others slow down after trying to finish out a previous fund that will do whatever it is doing to do, regardless of what the last two deals are--or so they think.  

It's a bit like relationships.  Undoubtedly, you look back on some perfectly great people that you've met over the course of your life and you wonder why things didn't work out.  The best explanation is usually that you just weren't open to it at the time.  Understanding why is the best way to be more open to a great person in the future--or at least to be conscious about the hesitations that close you off.

Staying self-aware is one of the best things I can do to eliminate my own tendencies towards openness or closedness.  Those aren't factors that should be impacting my decisionmaking.  I'll also try and compare what I was thinking or feeling at different times over the last few years versus what deals I did to help figure out where my center should be.  

You'll never eliminate all of your emotions in the process, nor should you.  You have to get excited about the potential of an idea to back it and empathetic to the customers as well as the founders if you're going to be a helpful investor.  You just want to be conscious of which emotions are present when you're making a decision and how they're impacting your mindset.  

Water and Data Make Plants Grow: Excited to Lead Agrilyst's Seed Round #tcdisrupt

I'm excited to announce that Brooklyn Bridge Ventures has led a $1 million round into Agrilyst

Food is a big market.

There are a lot of humans and those humans eat a lot.

Unfortunately, growing all this food is getting harder.  Climate change makes the weather unpredictable.  Frost, drought, and flooding make the prospects for outdoor growing more and more difficult.  On top of that, farmers are trying to figure out how to do more with less--and the answer to improving yields lay partially in being able to optimize and control more factors in the growing process.  On top of that, we're actively trying to cut the distance between where food is created and where it is consumed in order to make it more sustainable.  

That's why indoor farming has, no pun intended, gone through the roof.  It's not a simple solution, however.  Indoor farms consume a lot of energy--cutting into the sustainability gains around transportation decreases.  Farmers are now looking to technology to help solve those problems and make indoor growing more efficient--because climate change is making it look more and more like a necessity.  That's where data comes into play.  Knowing exactly what factors produce what kinds of outputs is critical to the indoor farming infrastructure.  

Over a year ago, Allison Kopf came to me to share her view on the tools that indoor growers needed to operate efficiently.  She had great experience and insights from her time at Brightfarms, which finances, designs, builds and operates greenhouse farms at or near supermarkets.  

How early was she in her planning?  Well, let's just say the idea was called "Gardeneuron" at the time.  :)  Glad she's rethought that brand direction over time.  

It was one of the first conversations she ever had about the idea--and she was about 9 months away from raising funding.  At Brooklyn Bridge Ventures, there's no such thing as too early to have a conversation.

Various hardware systems used sensors to track indoor environments, but none of them spoke to each other or had good interfaces.  It wasn't much different than the original pitch that I got for Datadog:  "See metrics from all of your apps, tools & services in one place."  Datadog is now a hugely successful startup monitoring all the systems of many of the apps you use everyday--enabling ops teams to make smart decisions around optimizing their infrastructure.  

I was seriously impressed with her insight and she convinced me about the market opportunity.  She went on to crush it at Techcrunch Disrupt in SF, winning the event, and we put together a seed round.  

I'm excited to back her and her co-founder, Jason Camp, and to have helped them connect to their new VP of Engineering Aaron Quint, who joined the company after a successful tour at Paperless Post.