Venture Cyclist

Bonuses at Startups

2013-05-11T17:21:00.001-04:00

Eric Paley of Founder Collective wrote a great blog post earlier this month: "Bonuses are toxic at startups” (which was later republished on CNN Money).

In my years working in VC (the first time I have used this phrase), I found myself in complex situations about bonuses with the leadership of several startups, but had not stepped back to think about the underlying patterns. I agree wholeheartedly with Eric’s analysis.

Back from the Dark Side

2013-04-30T07:45:00.001-04:00

As many of my friends know, I recently joined the team at Optum Labs as Chief Operating Officer, located in Cambridge MA, working for the newly appointed CEO, Dr. Paul Bleicher. Also as many of you know, I was fortunate enough to be a co-founder with Paul at Phase Forward. Having worked together before, I was particularly pleased when he asked me to consider this opportunity.

Years ago, when I first joined Sigma Partners venture capital, everyone (including me) talked wryly about me “going over to the dark side.” (This is an industry wide joke; look at Mark Suster’s “about me” box on his blog, and what Andrew Manoske wrote in his article “Joining the Dark Side: Why I left engineering to become a VC.”) Even if Mark Suster and Andrew Manoske are still on the dark side, I am back on the operating side of the world – by corollary, back working for the Jedi knights, and remembering how to build my own light sabre.

I have not until now written publicly about my recent efforts to raise a micro-VC fund, which I had called Big Data Boston Ventures (BDBV). That was because the SEC has not yet published new regulations (required by the JOBS Act) to allow for a more relaxed approach to marketing for VC funds. While I was raising a fund I couldn’t talk about it – now I have stopped that effort, I can.

Big Data Boston Ventures was conceived as a micro-VC fund that would invest in seed stage companies which fit into the big data theme. I have been writing about big data in this blog for a while, and the idea that I am bullish on this should surprise no-one.

Many of my friends in the entrepreneurial and investing community have said (at least to me) that my fund concept made lots of sense, that it was needed, that it was the right theme, that I would be a sought after investor/mentor (and hence get the opportunity to participate in great deals), and that, therefore, the fund would be successful. The LP community (those who invest in VC funds) are caught in a series of dynamics that mean they are just not interested in taking the kind of risks that such a fund might offer. Many GPs (VC general partners) with a better track record, and a more conventional (and in that way stronger) pitch story than mine have been finding it tough to raise new funds. This was all the more so for me as a solo GP going out with a first fund.

I had not actually given up on my fundraising when this new opportunity presented. I was making very slow progress, but progress nonetheless, and had certainly planned for another few months to try and get launched. However, when Paul called about Optum Labs, I was immediately intrigued, and quickly became very enthusiastic.

People know I am a very interested observer of healthcare and life sciences (HC/LS), and have made a point of staying current on trends in the industry and related IT. Ever since the inception of BDBV, people have suggested I focus on healthcare and life science (HC/LS) inside the big data theme, or even consider a pure HC/LS IT fund. My consistent response was that I believe that while there are great HC/LS startups that could fit into a fund with a broader big data theme, there just are not enough to justify a narrow industry-focused seed stage fund. This answer provides the background for my response when Paul called. Optum Labs provide the opportunity and challenge for me to work at the center of innovation in HC/LS. Optum Labs is a small startup inside a large, well respected organization partnered with leading players in the industry.

I plan to stay in touch with early stage startups in big data, and especially in healthcare and life sciences. I hope to continue to do some mentoring and be involved in other ways in the start-up community. Optum Labs is based in Kendall Square (One Main St) so I will still be close to the action.

Freudian slip? HP Moonshot: meh

2013-04-19T12:55:00.001-04:00

In an article on the website of Tools Journal, about the HP Moonshot line of servers, a typo has the name of the HP CEO written as Meh Whitman (meh defined here). I am jaded about HP, but am I that jaded? Here is the screen shot in case they fix it (they will!).

Spring has sprung

2013-04-14T21:28:00.001-04:00

It is spring, just about, in New England. There are daffodils blooming in our yard, and I have been riding each Sunday since the beginning of April. The last few weeks have seen some major professional changes (more on that in a future post), and I have found riding on Sundays to be a great antidote to any stress that might have been creeping in.

Since spring brings frogs in the wetlands, I thought I would share something sent to me by Dean Landsman. Call this one the first geek joke of spring.

An engineer was crossing a road one day, when a frog called out to him and said, "If you kiss me, I'll turn into a beautiful princess."
He bent over, picked up the frog and put it in his pocket.
The frog then cried out, "If you kiss me and turn me back into a princess, I'll stay with you for one week and do ANYTHING you want."
Again, the engineer took the frog out, smiled at it and put it back into his pocket.
Finally, the frog asked, "What is the matter? I've told you I'm a beautiful princess and that I'll stay with you for one week and do anything you want. Why won't you kiss me?"
The engineer said, "Look, I'm an engineer. I don't have time for a girlfriend, but a talking frog, now that's cool."

Big Data and the Internet of Things

2013-02-24T09:20:00.001-05:00

I recently wrote about the amazing amount of data being produced by people on the internet or mobile web. For example, every minute, YouTube gets 48 hours of video uploads, and nearly a quarter of a billion emails are sent… yes that’s what people do every minute.

However, that pales in comparison to the amount of data that will soon be generated by things – sensors, machines, monitors, switches and so on. Scroll down the infographic (from 2011) below, from CISCO, to see the immensity of big data that will soon be flowing from the Internet of Things.

As you can see, when farmers attach health monitors to cattle, each one sends 200MB of data per year. Apparently the total number of cattle in the US was 89.3 million. If every head of cattle had such a monitor that would result in over 16 petabytes of data collected annually.

A petabyte is about a billion megabytes. That’s big data.

Another example on the graphic, and written about last year, is that we could track every heartbeat of every person, using wearable heart monitors.

When we used to talk about “Data” (with a capital D) we might imagine research data from scientific endeavors, or corporate data tracking sales orders or factory output. Data was tracked because it was intrinsic to the activities that are central to our daily toil. Now data is extrinsic, coming from outside – whether generated by people (YouTube videos and emails) or machines (energy sensors, health sensors, traffic sensors).

The fact that we are interested in, and able to utilize, data coming to us from outside our immediate sphere of influence is what defines the age of big data.

Presenting to Win

2013-02-21T18:37:00.001-05:00

“Whether you are presenting to investors or to startup competition judges, you are faced with some amount of random behavior.”

A while ago I wrote a piece on “How to Score an Investment for your Startup”. Following that theme you can now read “Presenting to Win”, my latest article written for Scalable Startups project at UC Berkeley.

Lots of data, all the time

2013-02-17T15:45:00.001-05:00

This infographic is already, no doubt, out of date. It is from last June, but was probably out of date in July! People ask where big data comes from. This is a partial answer – as this is “just” data generated on the web and related web-facing activity. However, it starts to give you a feeling about where all this big data (data growing fast than Moore’s law) is coming from.

Infographic by Visual News

Big data doesn’t mean right answers

2013-02-12T12:36:00.001-05:00

My friend Judah Levine sent me a link to this great article in InfoWorld “Big data's pitfall: Answers that are clear, compelling, and wrong”.

This reminded me of an article which I really enjoyed from The Atlantic “The Data Vigilante” which is about small data as much as big, but clearly is relevant for the big data world.

All this is to say that big data amplifies the problems of garbage-in, garbage-out, but introduces other more complex problems too. Big data, almost by definition, requires statistical analysis (it’s too big to just look at). How many of us, however, really know enough statistics to know the right analysis to conduct. The chart below from the Psychology Department web page at Muhlenberg College shows some simple examples.

If you read about big data proving this, that, or the other result, can you get a feel for whether any of these problems might be obfuscating the truth?

15 minutes of fame … in Denmark

2013-01-25T11:56:00.001-05:00

A few months ago I was invited to be interviewed about big data by Anders Høeg Nissen of the Danish Broadcasting Corp when he was visiting Boston. Anders is the presenter of Harddisken, a weekly hour-long program about technology, which first started broadcasting in 1994.

Earlier today, his program on big data was broadcast, and I already received one email from someone who heard the show (I am duly flattered). This week’s web cover page is online here, in Danish, but if you have Chrome or another similar browser you should be able to get Google to translate the blurb for you.

The podcast of the broadcast is available in Danish, and the segment that includes some of the interview with me (speaking English, please!) runs from 12:50 – 19:27. There is more Danish than English, so feel free to skip that. In fact, as I now ponder that my 15 minutes of fame happened in Danish, I can wryly hope that about England’s “crush” on Danish TV might perhaps extend to radio. (See the recent article in the New Yorker - subscription needed for full article.)

Tak og farvel.

Will your startup be around for the long term?

2013-01-14T19:28:00.001-05:00

Who wants to know whether your startup will be around for the long term? Everyone.

“Investors want to invest in a company that will be around long enough to have a chance of making money. Customers don’t want to spend time and effort bringing on a new product or service that might go away. Employees (and their spouses) want to know the paycheck and benefits are at least somewhat stable (no matter how many stock options you give them).”

Check out my article on demonstrating some hope of longevity for the Scalable Startups project at UC Berkeley.

Your business in the Gartner Hype Cycle

2012-12-18T10:41:00.001-05:00

I was recently asked to contribute to a series of articles for the Scalable Startups project at UC Berkeley. The first of my articles is now up and available for reading.

“Most new businesses that are based on new technology of any kind are at the mercy of the Hype Cycle.”

The gist of the article is that knowing where you are in the hype cycle is an important part of startup self-awareness.

Comments welcome!

Incentives without pricing?

2012-12-13T08:44:00.001-05:00

When I get to refilling a prescription on the CVS website I am amused, and then sickened, by the announcement that “Price will vary based on insurance”. When I click on the link “Why can’t you tell me the price?” I get the response in the pop-up as shown in this screen-capture.

I could complain about the fact that they do have my insurance details on file and could at least tell me the the expected price assuming my insurance doesn’t change by the time I pick it up in two hours.

However, this is just the tip of the proverbial iceberg. Ask your doctor how much that blood test will be – he or she will likely not even know what the “list price” is, let alone what the negotiated rate for your insurer, or the status of your annual deductible. If you are referred to a specialist you can’t shop by price for the same reason.

This means that all this market based reform which is supposed to incent patients to use healthcare services “more wisely” is crippled from the beginning. If I can’t find out how much something costs ahead of time, how can I decide which is the cheapest. It goes without saying that I can consider various quality metrics to my thinking (some of which are possible to find ahead of time), but come on, be serious! Consumer oriented market based incentives without pricing information – it’s a fallacy.

Happy Chanukah

2012-12-10T20:34:00.001-05:00

My family, along with many others, is currently celebrating Chanukah, which is a minor Jewish festival made more significant only by its proximity to Christmas. I am blessed with family, friends and good health and am glad to celebrate even as the days get shorter and colder, and the bicycling season (in Boston, at least) draws to a close. The theme of light in dark times is universal, and Chanukah is a joyous reminder that darkness is driven out not by more darkness but by light.

As a Venture Cyclist this whimsical Chanukah Menorah is a particular treat, although I am looking for a recumbent version for future years!

Big data (very) geek humor

2012-11-14T20:55:00.001-05:00

Hat tip to Paul Bleicher, love this very geeky take – from 2009 – but just as relevant to today. (Cartoon by John Muellerleile.)

Should an Angel Investor also get Advisory/Board Equity?

2012-11-13T07:29:00.001-05:00

It’s demo day time of year in New England. Last month was the big MassChallenge finale. Last week was demo day for BetaSpring in Providence, RI, as well as for HealthBox Boston. This week it’s Techstars Boston Demo Day. One thing most of the presenting companies have in common is that they are raising seed investment funds from the angel, micro-VC and VC communities.

Over the last couple of years entrepreneurs have asked me a few times about cases where a potential angel investor, often someone who has been a mentor to the company in the program, says that they want to invest, but that they also want extra equity for being an advisor or board member, because they “bring more to the table than just money”.

Those people may be right. Some angels can indeed offer more than just money, but the decision about who should be an investor is different from who should get equity for advisory or board help. Equity is very precious, and so advisory or board equity should not be granted lightly.

Here is my advice.

If someone can be really helpful, the chemistry is good, you like them and you think they can bring great value as an advisor or board member then you should be willing to bring them on in this kind of role and grant them some equity, whether or not they invest.
If someone is your lead (or a major) investor and their terms are to require a board seat (plus equity) then you can decide whether or not to accept those terms, negotiate them or reject them.
If someone is joining an existing structure for a seed investment but insists on this extra role and equity you can politely say that you are keeping those elements separate, and they are welcome to invest but you are not linking the two at this time. This may mean turning down an investor. Obviously if you NEED them to make the round come together then you are back to #2.

Certainly you can approach this cautiously... including asking for references of other CEOs and startups where this angel is filling this kind of role, ideally from companies in similar industries where the extra “sweat” contribution is likely to be similar.

You should make sure the extra equity is common stock (not preferred), that it vests with a one year cliff, and that you have the right to terminate the relationship without cause at any time if you feel the person is not really adding the value that you hoped.

Startups: Dilemmas and Charters

2012-11-02T10:30:00.001-04:00

New startups are sometimes formed by teams that have known and worked with each other before, and some are formed by teams that just met each other at a founder dating website or event, and decide to work together after just a few weeks.

In either case, getting the team off to a good start where everyone is on the same page is really important.

Two great books that all founders should read are

When you get started with a good friend, an old friend, or a brand new one, these books show why getting explicit agreements, both formal and informal, on a wide variety of issues can be deeply important in the years ahead.

The Founder’s Dilemmas, by Noam Wasserman, is really focused on tech (and similar) startups that take outside financing and are geared towards a liquidity event (a sale or IPO). The book goes into detail, with great examples, of the things that can (and do) go wrong with alarming regularity. It then examines the dilemmas which are created in deciding how to get ahead of these problems and ways to get through the dilemmas to agreements that are clear, fair and workable.

The Partnership Charter, by David Gage, is a more general look at working together (and not just in tech startups). However, it provides a way for partners to think about, and talk about, working styles, values, accountability and responsibilities, future changes in management and structure and many other key issues. There is some overlap with Wasserman’s book, but the approach is different, and worth the time to read as well.

Look at the reviews on Amazon (and elsewhere), buy the books, and read them!

Talk about re-“cycle”-ing

2012-10-31T09:09:00.001-04:00

With a hat tip to John Halamka who brought this to my attention, check out this cardboard bike.

Izhar Gafni’s amazing $20 cardboard bike

If you can’t see the video it is embedded in this write-up of the project as well.

Cycling barefoot, in the cold–or in stilletos

2012-10-30T07:31:00.001-04:00

Love these cycling shoe covers from Podium.

Xconomy: Future of Big Data

2012-10-29T10:44:00.001-04:00

I got to moderate the startup panel at the Xconomy "Future of Big Data" Conference in Boston last week.

The audience seemed to really like the discussion which I put down to the great panel members:

Greg Huang's writeup of the event mentioned several quotes from the panel, including my definition of big data ("growing faster than Moore's law") that also got picked up in Forbes.com.

Questions we covered included:

How is your company is using Big Data to disrupt the vertical you're in?
How much of your big data secret sauce is about the data (acquiring, curating, creating) vs the algorithms and architecture used to process the data?
What has "big data"enabled which was not possible for startups 5 years ago. Could your companies have existed 5 years ago?

Two great quotes from elsewhere in the event were:

Big data is bullshit (Brad Feld)

and

The database people have been asleep, and Oracle has been providing the narcotics (Andy Palmer)

Phase Forward: Remembering the Early Days

2012-08-29T17:40:00.001-04:00

I went to Newton City Hall today to run an errand and saw the Balsamo/Millenium walkway that the city created to celebrate the year 2000. I remembered that when Paul Bleicher and I heard about this walkway in 1999 we thought it would be fitting to mark the fact that Newton was the first home of Phase Forward, the company we had co-founded a couple of years before.

In early 1999 it wasn’t clear how successful Phase Forward would go on to be. However, we were proud enough, even then, to have started the company in Newton, where we also both lived (and still do) with our respective families. Starting in 1996 we spent many hours in a study room in the Newton Free Library working on a business plan. Once we received venture capital funding (from Atlas Ventures and North Bridge Venture Partners) we opened our first office at 51 Winchester St, Newton in 1997. It was a couple more years before the company moved out to Waltham. The later history of Phase Forward included an IPO and then a successful acquisition by Oracle Corporation in 2010.

I am very proud that I got to work with Paul on his ideas that became so successful at Phase Forward. We had fun, changed an industry, created a bunch of jobs, and got to see some success along with way.

Hopefully the Phase Forward name will remain clear on this pathway as a mark of our gratitude for starting out in Newton, even as the name fades from prominence now it is no longer an independent company.

Now this is venture cycling!

2012-08-14T21:37:00.001-04:00

Check out this wonderful three minute movie – watch to the end – and see how venture capital and cycling really come together.

The Invisible Bicycle Helmet | Fredrik Gertten from Focus Forward Films on Vimeo.

The link, in case everything else fails is: http://vimeo.com/43038579

A Better Definition of Big Data

2012-08-07T13:23:00.001-04:00

As I have noted, Big Data is called that because of the problems it causes – it’s too big for this or that kind of processing or usefulness (ever tried looking through a million rows of data for something interesting?) The conventional definition of big data is slightly tautological: data that is big (or “too big”) in volume, velocity or variety for the current generation of hands-on data tools.

The kinds of data driving this big data wave are, as I hinted previously, high granularity data from systems and sensors recording behavior of (and inside) environments, people, markets and machines. This is in contrast to previous generations of data processing, designed to record and analyze the results of behavior, such as events and transactions, but not the behavior itself. In this era of big data, we have reached a new limit – something never usually considered a limit at all. That limit is Moore’s law.

Moore's law is the observation that computer power (for a given price) doubles approximately every two years. For a long time, Moore’s law would ensure regular general-purpose computers would improve fast enough to keep the databases humming with no need for (more expensive) special purpose products.

Then something happened. IT departments in large corporations started experiencing problems that outstripped the general improvements in computer power being delivered by Moore’s law. New technologies became commercial successes because these IT departments started to spend money on solving such problems. In 1996 TimesTen spun out of HP with a new approach to solve one relational database performance problem and became very successful in its particular corner of the market. Just as TimesTen was becoming successful, Boston-based Netezza launched its own very successful product that was, effectively, a special purpose computer for another key part of the relational database market.

In retrospect, these commercial successes heralded the start of the big data era. They illustrated, with the power of the market (including a great IPO for Netezza, and later acquisitions of both), that data growth was outstripping Moore’s law and new approaches were in demand. Both these companies relied on new arrangements of hardware (with proprietary software) to achieve new levels of performance. However, the big data wave quickly swung round to clever new software designs and algorithms, and clever new ways to parcel out problems to lots of regular computers working in parallel. Along with new hardware, new software approaches are just as powerful in coping with the big data that is outstripping Moore’s law. These include column stores (e.g., Vertica), Google’s famous map reduce algorithm (e.g., Hadoop) and now many more.

All this leads to my definition of big data:

data with velocity, volume and/or variety growing faster than Moore’s law

As a footnote, the recent announcements I covered in May, headlined by Intel’s massive grant to MIT related to big data research, brings this full circle. Gordon Moore coined Moore’s law just a few years before co-founding Intel.

Fundraising for Hazon

2012-07-25T13:00:00.001-04:00

Although I am not riding this year, I am fundraising for the 2012 Hazon NY Jewish Environmental Bike ride ... You all (should) know that Hazon is near and dear to my heart in many ways. You can read more about it by clicking through to my fundraising page. If you are able to support this wonderful organization please go ahead and do so!

Click Here to Donate

The $1,000 Genome is old news

2012-06-22T07:47:00.001-04:00

I have written a few times about the coming of the $1,000 genome, and what that really means.

I recently read an excellent Forbes article by Jim Golden that argues this is already rather old news. We are apparently close, if we haven’t already arrived, at the mechanical capability for sequencing a whole genome for that price in a few hours. However, to sort through the data we generated for $1,000 and get reasoned clinical knowledge for a patient still costs $25,000-$100,000.

In cancer labs (a hotbed of genetic research), the article notes that whole genome sequencing of tumor tissue will need to be repeated multiple times for at least thousands of patients (there are over 1.4 million new cancer cases each year in the US). Repeating the genetic analysis enables tracking the mutations as a patient undergoes treatment and the tumor changes and responds. The next frontier of genomic-based clinical research is not perfect personalized medicine – that is still way off in the future. The next frontier is about having the opportunity to get insight into the patterns of disease progression, treatment and response. Only after we leverage this lower cost of genome sequencing to amass statistically significant amounts of data for all very many different kinds and sub-types of cancer will personalized treatment become a mainstay of clinical practice.

Golden concludes:

It’s not about the $1000 genome. It’s about big data generation and analytics for insight creation over the clinical course of a patient’s journey through cancer.

The Four Horsemen of …

2012-06-13T11:39:00.001-04:00

A long time ago, around the time of the dot-com bubble, four companies emerged as the tech powerhouses of their time. Sun, Oracle, EMC, Cisco were known as the four horsemen of the new economy. Sun built the computing hardware, Oracle developed the database systems, EMC provided the storage infrastructure and Cisco powered the networks. Sales boomed, stock prices soared, and fortunes were made. After the bubble burst the term “four horsemen” seemed even more appropriate (the original horsemen were harbingers of the apocalypse). Sun never recovered and is now owned by Oracle which continues to thrive. EMC reinvented itself by adding sophisticated document management, security and virtualization technology. Cisco is most closely still like itself. Still, despite the gloomy associations, it appears that people like this four horsemen metaphor.

A year ago Eric Schmidt identified the four horsemen of the internet as Google, Apple, Facebook, and Amazon (also known as the four horsemen of the consumer apocalypse). Recently Michael Boland named Apple, Ebay, Facebook and Yahoo as the four horsemen of digital media (even though it is unclear whether Yahoo can strike fear into anyone’s heart anymore).

According to this post, the four horsemen of cloud computing are Amazon, Microsoft, Google and VMware.

I can’t seem to find anyone else’s view for four horsemen of big data, so here are my picks: IBM (Watson won Jeopardy after all), Google (organizing the world’s information), Apache Hadoop (big data’s favorite open source project right now), and Twitter (400 million tweets per day represents the global rush of random data about everything).

What are your picks for the four horsemen of big data, and why? You have to choose a list of four – more or less is cheating! Answers in the comments please.