The “Startup Owner’s Manual” goes On Press Tuesday 2/14
Two years in the making and literally ten years in development, I’m proud to announce that my new book, The Startup Owners Manual, goes onto the printing press next Tuesday.  This 608-page work is, as its subtitle says, “the step-by-step guide for building a great company.”  It’s the result of a decade of me learning from 1,000′s of entrepreneurs, corporate partners, students and scientists the best practices of what wins in startups. I’ve spent the last two years cramming knowledge into this new book.

In brief, the The Startup Owners Manual is far more detailed and more readable than Four Steps to the Epiphany, (most of the sentences are even finished!).  In fact, you could say that all that remains from my last book are the four steps of Customer Development.  Briefly, the new book:

• Integrates Alexander Osterwalders “Business Model Canvas” as the front-end and “scorecard” for the customer discovery process.
• Provides separate paths and advice for web/mobile products versus physical products
• Offers a ton of detail and great tips on how to get, keep, and grow customers, recognizing that this happens very differently between web and physical channels.
• and finally it teaches a “new math” for startups: “metrics that matter.”

The Lean LaunchPad Online Class
My online Lean LaunchPad class has created a lot of buzz this week. As you may have heard, I was deep into the production of the lectures when I realized I was producing the wrong class.  The online class was originally based on my book The Four Steps to the Epiphany.

Only when I held the draft of my latest book, The Startup Owners Manual, in my hands, did it dawn on me that my online students deserved all the latest best practices of entrepreneurship and Customer Development. Not the stuff I taught a decade ago, but all that I’ve learned teaching the Lean LaunchPad in front of students at Stanford, Berkeley, Columbia and the National Science Foundation in the last year.  And I particularly wanted to incorporate everything I’ve spent two years integrating into The Startup Owners Manual into the class.

So apologies to all of you who were expecting the class this month.  I hope to get the updated version online in the next 60 days.  I’ll keep you updated on this blog as we record our lectures.

In the meantime, if you want to prepare for the class…or get a jump on your startup competition, you can start reading the “recommended text” for the online class right now by ordering my new book.  It is recommended—not required—reading for the free online course, and I believe it will be immensely helpful to the startup community at large.

Lessons Learned

• Startups search for business models, exisitng companies execute them
• There are tons of texts about execution, but a paucity of practical ones for founders on how to search
• The Startup Owners Manual is the definitive reference book for founders, investors and everyone interested in startups
• The Lean Launchpad on-line class will be based on the new book

The 21 NSF teams had been out of the classroom for just 15 hours as they filed back in with their business model canvas presentations.  Their assignment appeared (to them) to be deceptively simple:

• Write down their initial hypotheses for the 9 components of their company’s business model (who are the customers? what’s the product? what distribution channel? etc.)
• Come up with ways to test each of the 9 business model canvas hypotheses
  • Decide what constitutes a pass/fail signal for the test. At what point would you say that your hypotheses wasn’t even close to correct?
• Consider if their business worth pursuing? (Give us an estimate of market size)
• Start their team’s blog/wiki/journal to record their progress during for the class 

Teaching logistics
Each week every team presented a 5-minute summary of what they had done and what they learned that week. As each team presented, the teaching team would ask questions and give suggestions (at times direct, blunt and pointed) for things the students missed or might want to consider next week.

While the last sentence is short, it’s one of the key elements that made the class effective. Between the three of us on the teaching team there was 75 years of entrepreneurial experience. (The 2 VC’s between them probably have seen 1000′s of presentations.) While there’s no guarantee our comments were correct or we had any unique insight, we did have enough data for pattern recognition.

The instructors sat in the back of the room and used a shared Google spreadsheet for grading. We graded the teams on a scale of 1-10 and each of us left detailed comments the other teaching team members could share and comment on. Week after week it gave us a pretty detailed record of the progress and trajectory of each team.

(As great as the presentations may be, sitting through 21 of them in a row were exhausting. After this first cohort, the NSF will be putting 25 teams at a time in a class. We intend to break the group into three parallel presentation sections.)

All teams kept a blog – almost like a diary – to record everything they did outside the building. This let the teaching team keep tabs on their progress and offer advice in-between class sessions.

Getting the teams to blog required constant “encouragement,” but it was invaluable. First, as we had a window into each teams engagement with customers, it eliminated most of the surprises when they came into class to present. Second, the blog helped us see if they were gaining insight from their customer discovery. Insight is what enables entrepreneurs to iterate and pivot their business model. The goal wasn’t just to talk to lots of people – the goal was to learn from them. Finally, their blogs gave us and them a permanent record of who they talked to. Over time this contextual contact list will be turned into a shared contact database for all future NSF teams.

The 21 Teams Present
The first team up was Arka Lighting. We liked these guys, but for a while no one on the teaching team could figure out what their core technology was. We knew they wanted to make LED lights that had better performance because they would dissipate less heat.  Finally when we understood that their core technology was heat pipes, it wasn’t clear why that made them a better LED supplier.  Were they selling to end users? OEMs? Manufacturers? We suggested that perhaps they had jumped to too many assumptions.

If you can’t see the slide deck above, click here

Next up was SenSevere – solid-state hydrogen and hydrocarbon sensors for use in severe environments.  They were going to start with the $81M Chlorine market where they already had a partner. It seemed like a tiny business. Did they just want to become a licenser of technology? Were their other severe environments that their sensors fit into? Did customers just want the sensors or a more complete sensing solution?

If you can’t see the slide deck above, click here

Graphene Frontiers was next. Graphene is incredibly cool. It’s touted as the new “wonder material” and its inventors won the 2010 Nobel Prize in Physics. The team wanted to make wafer-scale Graphene films. And do it at ambient pressure. But their proposed products seemed like research lab selling other research labs low volume products. It seemed liked technology in search of a business. Reading the Graphene Frontiers blog for the first week, we realized that in a burst of enthusiasm they set up a Google AdWords campaign to drive traffic to their site!

If you can’t see the slide deck above, click here

Ground Flour Pharma was going to take Fluorine-18 and make a new generation of fluorodeoxyglucose (FDG) radiotracers for Positron emission tomography scanners. But it wasn’t clear who benefits enough to make this a business. If they need FDA trials is it worth the money needed for approval? Is this just a technology license or is it a company?

If you can’t see the slide deck above, click here

C6 Systems had a great set of photos with things on fire in the woods. It seemed like they were going to burn downed trees to do what? Make charcoal? It looked like fun but is this a hobby or a scalable business? Is their any patentable Intellectual Property? What was their Value Chain? Their blog showed a good head-start on talking to customers.

If you can’t see the slide deck above, click here

Photocatalyst made nanogrids that became miniaturized self-supported mats, similar to fishing nets, that float on water and rapidly decompose crude oil using sunlight. The result is that pollutants are turned into water, carbon dioxide and other biodegradable organics for environmental remediation. Their slides sounded like a technical presentation of nanocatalyst features but their blog showed that they had been actively talking to customers in the last two days.

If you can’t see the slide deck above, click here

After the teams presented it was the turn of the teaching team.  We presented our second lecture, this time on “Value Proposition.”

If you can’t see the slide deck above, click here

For tomorrow, the teams had 15-hours to get out of the building and talk to 10-15 customers and test their Value Proposition.

While most of the teams got on the phone or into their cars, a couple of others complained, “You didn’t tell us we were supposed to use our spare time to talk to customers. We thought this was just spare time.”

At first, I thought they were joking. Spare time? I don’t think you understand the key principle in a startup – there is no such thing as spare time. The clock is running and you’re burning cash.

Go!

They launched an incubator for the top scientists and engineers in the U.S.

This week we saw the results.

63 scientists and engineers in 21 teams made 2,000 customer calls in 8 weeks, turning laboratory ideas into formidable startups. 19 of the 21 teams are moving forward in commercializing their technology.

It was an extraordinary effort.

Your Country Needs You
In July I got a call from Errol Arkilic, a program manager at the National Science Foundation (NSF), the $6.8-billion U.S. government agency that supports research in all the non-medical fields of science and engineering.  “We’ve been reading your blog about your Lean Launchpad class.”  Wow, that’s nice, I thought, a call from a fan. No, the conversation was about to get more interesting.

“Our country needs you.” Say what? “Part of the NSF charter is to commercialize the best of the science and engineering research we fund. We want to make a bet that your Lean Launchpad class can apply the scientific method to market-opportunity identification. We think your class can train scientists to start companies better than how we’re doing it now.”  Uh oh, where’s this heading?  “We want to select the best of our researchers, pay them $50,000 to take your class and see if we can change the outcome of their careers and their research.”

“That’s great, maybe I can set up a class for you next year,” I replied.  The answer shot back, “We want the class to start in 90 days,”

I remember thinking, “Wow, whoever’s on the other end of phone sounds just like an entrepreneur, they were asking for the impossible.”  Just as I was computing whether this was possible, he added, “And we want to bring 25 new teams every quarter.”

So of course, I said yes.

While they’ll never admit it, the National Science Foundation was starting an incubator – the Innovation Corps – to take the most promising research projects in American university laboratories and turn them into startups.

The Innovation Corps – Using the Lean LaunchPad as an Incubator for Scientists and Engineers

The Innovation Corps Startup Team
These weren’t 22-year olds who wanted to build a social shopping web site. Each of the teams selected by the NSF had a Principal Investigator – a research scientist who was a University professor; an Entrepreneurial Lead – a graduate student working in the Investigator’s lab; and a mentor from their local area who had business and/or domain expertise. And they were hard at work at some real science.

The I-Corps Incubator Program
Unlike other incubators, our Lean LaunchPad Class had a specific curriculum. We taught them the business model / customer development / agile development solution stack. This methodology forces rapid hypothesis testing and Customer Development by getting out of the building while building the product. (The mentors in our program are there to support the methodology, but aren’t there to tell stories.)

The gamble was that we could train Professors doing hard-core science, who had never been near a startup or Silicon Valley, to get out of the building and talk to customers and Pivot as easily as someone at a web startup.

The Scientists, the NSF and the teaching team were all going to go where no one had before.

Given that Silicon Valley had started with scientists and engineers not MBA’s, I thought this was a bet worth making.

The Curriculum
Since the teams were in Universities scattered across the U.S., we couldn’t keep them in Silicon Valley for all 8 weeks, so we tried an experiment in teaching remotely.

First, we brought all 21 teams to Stanford for 3-days of 10 hour-a-day classes in business model design and customer development. After returning to their schools, they got out of their labs while they built their products. Once a week, via Webex,they presented their Customer Development progress on line to the teaching team and the other teams. Then it was our turn, and we lectured all the teams remotely. After 7 weeks they returned to Silicon Valley for their final presentations.

(The class syllabus is here. The class textbooks were “The Four Steps to the Epiphany and Business Model Generation.”)

Assembling the Teaching Team
We recruited two veteran Venture Capital partners to be part of the 10-week teaching team: Jon Feiber, at Mohr Davidow and John Burke of True Ventures. Alexander Osterwalder joined us for the opening day, and Oren Jacob, ex-CTO of Pixar joined us for a finale.

The First Class
As the first class settled into their seats at Stanford I wondered if we were going to be able to get them to act like startups. Most of the Principal Investigators were professors. Some had their own labs managing large groups of researchers. Their average age was in the mid-40’s. Their mentors were at least that old. Only the Entrepreneurial Leads (the PI’s assistants) were in their mid to late 20’s.

Looking at them  I wondered if: 1) hard-core science and engineering projects could rapidly pivot, 2) if the Principal Investigators would simply “assign” the work to their graduate students. I thought about the common wisdom that only 20-year olds doing Internet startups could be agile. Some incubators would have labeled this group too old to be entrepreneurs. I smiled as I realized that I was older than most (but not all) of them.

The Stanford Lectures
Our first lecture was about 1) how to organize their thinking of what it takes to build a startup – the business model canvas and 2) how to test their hypotheses – the Customer Development Process.

Since the first part of the lecture was about Alexander Osterwalder’s Business Model Canvas, Osterwalder flew in from Switzerland to teach slides 20-76. And since the rest of the slides were about Customer Development, I taught those.

If you can’t see the slide deck above, click here.

The homework for the 21 teams in the next 24-hours? Come up with a business model canvas for their startup. And tell us how they will test each of their business model hypotheses.

As day one ended, I wondered what those canvases would look like.

Stay tuned for Part 2.

Over the last 40 years Technology investors have learned that the success of startups are not just about the technology but “it’s about the team.”

We spent a year screwing it up in our Lean LaunchPad classes until we figured out it was about having the right team.

Startup Team Lessons Learned
During the last 12 months we’ve taught 42 entrepreneurial teams with 147 students at Stanford, Berkeley, Columbia and the National Science Foundation. (As many teams as most startup incubators.)

Get into the Class
When I first started teaching hands-on, project/team entrepreneurship classes we’d take anyone who would apply. After awhile it became clear that by not providing an interview process we were doing these students a disservice. A good number of them just wanted an overview of what a startup was like – an entrepreneurial appreciation class (and we offer some great ones.) But some of our students hadn’t yet developed a passion for entrepreneurship and had no burning idea that they wanted to bring to market. Yet in class they’d be thrown into a “made-up in the first week” startup team and got dragged along as a spear-carrier for someone else’s vision.

Step One – Set a Bar
So as a first step we made students formally apply and  interview for the Lean LaunchPad class. We were looking for entrepreneurs who had great ideas and interest in making those ideas really happen. We’d hold mixers before the first class and the students would form their teams during week one of the class.

But we found we were wasting a week or more as the teams formed and their ideas gelled.

Step Two – Apply As A Team
So next time we taught, we had the students apply to the class as a team. We hold information sessions a month or more before the classes. Here students with preformed teams could come and have an interview with the teaching team and get admitted. Or those looking to find other students to join their team could mix and market their ideas or join others and then interview for a spot. This process moved the team logistics out of class time and provided us with more time for teaching.

But we had been selecting teams for admission on the basis of whether they had the best ideas. We should have known better.  In the classroom, as in startups, the best ideas in the hands of a B team is worse than a B idea in the hands of a world class team.

Here’s why.

Step Three – Hacker/Hardware, Hustler, Designer, Visionary
As we taught our Lean LaunchPad classes we painfully relearned the lesson that team composition matters as much or more than the product idea. And that teams matter as much in entrepreneurial classes as they do in startups.

In a perfect world you build your vision and your customers would run to buy your first product exactly as you spec’d and built it. We now know that this ‘build it and they will come” is a prayer rather than a business strategy.  In reality, a startup is a temporary organization designed to search for a repeatable and scalable business model. This means the brilliant idea you started with will change as you iterate and pivot your business model until you find product/market fit.

The above paragraph is worth reading a few times.

It basically says that a startup team needs to be capable of making sudden and rapid shifts – because it will be wrong a lot. Startups are inherently chaos. Conditions on the ground will change so rapidly that the original well-thought-out business plan becomes irrelevant.

And finding product/market fit in that chaos requires a team with a combination of skills.

What skills? Well it depends on the industry you’re in, but generally great technology skills (hacking/hardware/science) great hustling skills (to search for the business model, customers and market,) great user facing design (if you’re a web/mobile app,) and by having long term vision and product sense. Most people are good at one or maybe two of these, but it’s extremely rare to find someone who can wear all the hats.

It’s this combination of skills is why most startups are founded by a team, not just one person.

University Silos
While building these teams are hard in the real world, imagine how hard it is in a university with classes organized as silos. Business School classes were only open to business school students, Engineering School classes were only open to engineering school students, etc. No classes could be cross-listed. This meant that you couldn’t offer students an accurate simulation of what a startup team would look like. (In our business school classes we had students with great ideas but lacking the technical skills to implement it. And some of our engineering teams could have benefited from a role-model to follow as a hustler.)

So the next time we taught, we managed to ensure that the class was cross-listed and that the student teams had to have a mix of both business and engineering backgrounds.

I think we’ve finally got the team composition right – relearning all the lessons investors already knew.

But now on to the next goal – getting our mentor program correct.

Lessons Learned

• Finding product/market fit in startup chaos requires a team with a combination of skills
• Hacker/Hardware, Hustler, Designer, Visionary
• At times an A+ market (huge demand, unmet need) may trump all
• Getting the Mentors right is the next step

This is part 2 of 2 of what I found. Part 1 can be found here.

Toxic Business Press and Contradictory Government Incentives
Unique to Finland with its strong cultural emphasis on equality and the redistribution of wealth is a business press that doesn’t understand startups and is overtly hostile to their success. When MySQL was sold for $1B and the cleantech company the Switch got acquired for $250M, one would have expected the country to celebrate that they had built these world-class companies. Instead the business press dumped on the founders for “selling out.” In 2010 it got worse with an Act in parliament about the Monitoring of Foreigners’ Corporate Acquisitions. Many founders mentioned this as a reason not to incorporate or grow their companies in Finland.

While the government says they love startups, the first thing they did this year is raise the capital gains tax. While it might have been politically expedient, it was not a welcome sign for long-term investment. I suggested they consider an investment tax credit for pension funds that invest in Finnish based VC firms.

Nokia as “He Who Must Not Be Named”
I was in Finland three days before I realized that no one had mentioned the word “Nokia.”  After I brought it up in a meeting, you could have heard a pin drop.  Nokia was Finland’s symbol of national competence. Most Finns take their failure as a personal embarrassment. (Note to Finland – lighten up. Nokia was blind-sided in a classic disruptive innovation. 50% the fault of a Nokia management that didn’t see it coming, while 50% was due to brilliant Apple execution.) Ultimately, Nokia’s difficulties will turn out to be good news for Finnish entrepreneurs. They’ve stopped hiring the best talent, and startups are not looking so risky compared to large companies.

Nanny-Culture, Lack of Risk Taking, Not Sharing
What makes Finland such a wonderful place to live and raise a family may ultimately be what kills it as a startup hub. There’s a safety net in almost every part of one’s public and private life – health insurance, free college tuition, unions, collective bargaining, fixed work hours, etc. And what’s great for the mass of society – a government safety net verging on the ultimate nanny state – makes it impossible to fail. You find early stage employees expecting to work normal hours, to get paid a regular salary, and not asking or expecting equity. There isn’t much of a killer instinct among the masses.

It’s the rare region where risk equals experience. By nature Finns are not good at tolerating risk. This gets compounded by the cultural tendency not to share or talk in meetings, sometimes to the point of silence. This is a fundamental challenge in creating an entrepreneurial culture.  This extends to sharing among startups. The insular nature of the culture hasn’t yet created a “pay it forward” culture.

Summary
The young entrepreneurs I met are bringing impressive energy and intelligence to their goal of building one of Europe’s leading technology hubs in Helsinki. Finland itself has significant engineering talent, and is also attracting entrepreneurs from Russia and the former USSR. It will be fascinating to see if they can lead the cultural change and secure the political support (in a government run by an older generation) to support their vision.

Lessons Learned

• Finland is trying to engineer an entrepreneurial cluster as a National policy to drive economic growth through entrepreneurial ventures
• They’ve gotten off to a good start with a start around Aalto University with passionate students
• Startup incubators, business angels and VCs are starting to emerge
• The country needs to figure out a long term privatization strategy for Venture investing
• Finnish culture makes risk-taking and sharing hard

——

I was invited to Finland as part of Stanford’s Engineering Technology Venture Program partnership with Aalto University. (Thanks to Kristo Ovaska and team for the fabulous logistics!) I presented to 1,000’s of entrepreneurs, talked to 17 startups, gave 12 lectures, had 9 interviews, chatted with 8 VC’s, sat on 4 panels, talked policy with 2 government ministers, 2 members of parliament, 1 head of a public pension fund and was in 1 TV-documentary.

• a whole lot of smart, passionate entrepreneurs who want to build a startup hub in Helsinki
• a government that’s trying to help, but gets in the way
• a number of exciting startups, but most with a narrow, too-local view of the world
• and the sense that, before too long, they may well get it right!

While a week is not enough time to understand a country this post – the first of two – looks at the Finnish entrepreneurial ecosystem and its strengths and weaknesses.

The Helsinki Spring
Entrepreneurship and innovation are bubbling around Helsinki and Aalto University. There are thousands of excited students, and Aalto university is working hard to become an outward facing institution. Having a critical mass of people who think startups are cool in the same location is a key indicator of whether a cluster can catch fire. Finnish startup successes on a global stage include MySQL, F-Secure, Rovio, Habbo, Playfish, The Switch, Tectia, Trulia and Linux. While it’s not clear yet whether the numbers of startups in Helsinki are sufficient to ignite, it feels like it’s getting there, (and given the risk-averse and paternal nature of Finland that by itself is a miracle.)

The good news is that for a 5 million person country, there’s an emerging entrepreneurial ecosystem that looks like something this:

• Aalto University: Aalto Center for Entrepreneurship, Aalto Entrepreneurship Society
• Startup Accelerators: Startup Sauna and Vigo which includes Lifeline Ventures, KoppiCatch, and Veturi
• Startup Blog: Arctic Startup
• Business Angels: FiBAn, Sitra
• Venture Capital: FVCA, NextIt Ventures, Primus Ventures, Open Ocean Capital, Connor VC, and Inventure
• Government Funding: Tekes, Sitra, Finnvera, Finnish Investment Industry

9-to-5 Venture Capital
Ironically one of the things that’s holding back the Finnish cluster is Tekes, the government organization for financing research, development and innovation in Finland. It’s hard enough to pick which existing companies with known business models to aid. Yet Tekes does that and is trying to act like a government-run Venture Capital firm. At Tekes, government employees (and their hired consultants) – with no equity, no risk or reward, no startup or venture capital experience – try to pick startup winners and losers.

Tekes has ended up competing with and stifling the nascent VC industry, indiscriminately handing out checks to entrepreneurs like an entitlement. (To be fair this is an extension of the government’s role in almost all parts of Finnish life.)

In addition to Tekes, Vigo, the government’s attempt at funding private business accelerators, started with good intentions and got hijacked by government bureaucrats. The accelerators I met with (the ones the government pointed to as their success stories) said they were leaving the program.

Tekes lacks a long-term plan of what the Finnish government’s role should be in funding startups. I suggested that they might want to consider putting themselves out of the public funding business by using public capital to kick-start private venture capital firms, incubators and accelerators. And they should give themselves a 5-10 year plan to do so.  Instead they seem to be stuck in the twilight zone of not having a long-term vision of their role. (There has been tons of reports on what to do, all seemingly ignored by an entrenched bureaucracy.)

Lack of Business Experience
Direct government funding of startups has also delayed the maturation of business experience of local angels and VC’s. Finnish private investors don’t yet have enough time-in-grade to have developed good pattern recognition skills, and most lack operating backgrounds. I have no doubt they’ll get there by themselves, but in wouldn’t take much imagination to attempt to recruit some seasoned overseas investors to add to the mix.

Even a more serious challenge is the lack of global business competence. The number of serial entrepreneurs is very low and until recently most of the talented sales and marketing professionals choose to work for Nokia.

Part 2 with more observations about Finland and the Lessons Learned will follow shortly.

——-

We’re all in this together – The Chips are Down
in 1962 Walker’s Wagon Wheel Bar/Restaurant in Mountain View became the lunch hangout for employees at Fairchild Semiconductor. When the first spinouts began to leave Fairchild, they discovered that fabricating semiconductors reliably was a black art. At times you’d have the recipe and turn out chips, and the next week something would go wrong, and your fab couldn’t make anything that would work. Engineers in the very small world of silicon and semiconductors would meet at the Wagon Wheel and swap technical problems and solutions with co-workers and competitors.

We’re all in this together – A Computer in every Home
In 1975 a local set of hobbyists with the then crazy idea of a computer in every home formed the Homebrew Computer Club and met in Menlo Park at the Peninsula School then later at the Stanford AI Lab. The goal of the club was: “Give to help others.” Each meeting would begin with people sharing information, getting advice and discussing the latest innovation (one of which was the first computer from Apple.) The club became the center of the emerging personal computer industry.

We’re all in this together – Helping Our Own
Until the 1980’s Chinese and Indian engineers ran into a glass ceiling in large technology companies held back by the belief that “they make great engineers but can’t be the CEO.”  Looking for a chance to run their own show, many of them left and founded startups. They also set up ethnic-centric networks like TIE (The Indus Entrepreneur) and the Chinese Software Professionals Association where they shared information about how the valley worked as well as job and investment opportunities. Over the next two decades, other groups — Russian, Israeli, etc. — followed with their own networks. (Anna Lee Saxenian has written extensively about this.)

We’re all in this together – Mentoring The Next Generation
While the idea of groups (chips, computers, ethnics) helping each other grew, something else happened. The first generation of executives who grew up getting help from others began to offer their advice to younger entrepreneurs. These experienced valley CEOs would take time out of their hectic schedule to have coffee or dinner with young entrepreneurs and asking for nothing in return.

They were the beginning of the Pay-It-Forward culture, the unspoken Valley culture that believes “I was helped when I started out and now it’s my turn to help others.”

By the early 1970’s, even the CEOs of the largest valley companies would take phone calls and meetings with interesting and passionate entrepreneurs. In 1975, a young unknown, wannabe entrepreneur called the Founder/CEO of Intel, Bob Noyce and asked for advice. Noyce liked the kid, and for the next few years, Noyce met with him and coached him as he founded his first company and went through the highs and lows of a startup that caught fire.

Steve Jobs and Robert Noyce

The entrepreneur was Steve Jobs.  “Bob Noyce took me under his wing, I was young, in my twenties. He was in his early fifties. He tried to give me the lay of the land, give me a perspective that I could only partially understand,” Jobs said, “You can’t really understand what is going on now unless you understand what came before.”

What Are You Waiting For?
Last week in Helsinki Finland at a dinner with a roomful of large company CEO’s, one of them asked, ”What can we do to help build an ecosystem that will foster entrepreneurship?” My guess is they were expecting me talk about investing in startups or corporate partnerships. Instead, I told the Noyce/Jobs story and noted that, as a group, they had a body of knowledge that entrepreneurs and business angels would pay anything to learn. The best investment they could make to help a startup culture in Finland would be to share what they know with the next generation. Even more, this culture could be created by a handful of CEO’s and board members who led by example. I suggested they ought to be the ones to do it.

We’ll see if they do.

——

Over the last half a century in Silicon Valley, the short life cycle of startups reinforced the idea that - the long term relationships that lasted was with a network of people - much larger than those in your current company. Today, in spite of the fact that the valley is crawling with IP lawyers, the tradition of helping and sharing continues. The restaurants and locations may have changed, moving from Rickey’s Garden Cafe, Chez Yvonne, Lion and Compass and Hsi-Nan to Bucks, Coupa Café and Café Borrone, but the notion of competitors getting together and helping each other and experienced business execs offering contacts and advice has continued for the last 50 years.

It’s the “Pay-It-Forward” culture.

Lessons Learned

• Entrepreneurs in successful clusters build support networks outside of existing companies
• These networks can be around any area of interest (technology, ethnic groups, etc.)
• These were mutually beneficial –  you learned and contributed to help others
• Over time experienced executives “pay-back” the help they got by mentoring others
• The Pay-It-Forward culture makes the ecosystem smarter

Not understanding and agreeing what “Entrepreneur” and “Startup” mean can sink an entire country’s entrepreneurial ecosystem.

———

I’m getting ready to go overseas to teach, and I’ve spent the last week reviewing several countries’ ambitious attempts to kick-start entrepreneurship.  After poring through stacks of reports, white papers and position papers, I’ve come to a couple of conclusions.

1) They sure killed a ton of trees

2) With one noticeable exception, governmental entrepreneurship policies and initiatives appear to be less than optimal, with capital deployed inefficiently (read “They would have done better throwing the money in the street.”) Why? Because they haven’t defined the basics:

What’s a startup?  Who’s an entrepreneur? How do the ecosystems differ for each one? What’s the role of public versus private funding?

Six Types of Startups – Pick One
There are six distinct organizational paths for entrepreneurs: lifestyle business, small business, scalable startup, buyable startup, large company, and social entrepreneur. All of the individuals who start these organizations are “entrepreneurs” yet not understanding their differences screws up public policy because the ecosystem in supporting each type is radically different.

For policy makers, the first order of business is to methodically think through which of these entrepreneurial paths they want to help and grow.

Lifestyle Startups: Work to Live their Passion
On the California coast where I live, we see lifestyle entrepreneurs like surfers and divers who own small surf or dive shop or teach surfing and diving lessons to pay the bills so they can surf and dive some more.  A lifestyle entrepreneur is living the life they love, works for no one but themselves, while pursuing their personal passion. In Silicon Valley the equivalent is the journeyman coder or web designer who loves the technology, and takes coding and U/I jobs because it’s a passion.

Small Business Startups: Work to Feed the Family
Today, the overwhelming number of entrepreneurs and startups in the United States are still small businesses. There are 5.7 million small businesses in the U.S. They make up 99.7% of all companies and employ 50% of all non-governmental workers.

Small businesses are grocery stores, hairdressers, consultants, travel agents, Internet commerce storefronts, carpenters, plumbers, electricians, etc. They are anyone who runs his/her own business.

They work as hard as any Silicon Valley entrepreneur. They hire local employees or family. Most are barely profitable. Small business entrepreneurship is not designed for scale, the owners want to own their own business and “feed the family.” The only capital available to them is their own savings, bank and small business loans and what they can borrow from relatives. Small business entrepreneurs don’t become billionaires and (not coincidentally) don’t make many appearances on magazine covers. But in sheer numbers, they are infinitely more representative of “entrepreneurship” than entrepreneurs in other categories—and their enterprises create local jobs.

Scalable Startups: Born to Be Big
Scalable startups are what Silicon Valley entrepreneurs and their venture investors aspire to build. Google, Skype, Facebook, Twitter are just the latest examples. From day one, the founders believe that their vision can change the world. Unlike small business entrepreneurs, their interest is not in earning a living but rather in creating equity in a company that eventually will become publicly traded or acquired, generating a multi-million-dollar payoff.

Scalable startups require risk capital to fund their search for a business model, and they attract investment from equally crazy financial investors – venture capitalists. They hire the best and the brightest. Their job is to search for a repeatable and scalable business model.  When they find it, their focus on scale requires even more venture capital to fuel rapid expansion.

Scalable startups tend to group together in innovation clusters (Silicon Valley, Shanghai, New York, Boston, Israel, etc.) They make up a small percentage of the six types of startups, but because of the outsize returns, attract all the risk capital (and press.)

Just in the last few years we’ve come to see that we had been building scalable startups inefficiently. Investors (and educators) treated startups as smaller versions of large companies. We now understand that’s just not true.  While large companies execute known business models, startups are temporary organizations designed to search for a scalable and repeatable business model.

This insight has begun to change how we teach entrepreneurship, incubate startups and fund them.

Buyable Startups: Born to Flip
In the last five years, web and mobile app startups that are founded to be sold to larger companies have become popular. The plummeting cost required to build a product, the radically reduced time to bring a product to market and the availability of angel capital willing to invest less than a traditional VCs– $100K – $1M versus $4M on up – has allowed these companies to proliferate – and their investors to make money. Their goal is not to build a billion dollar business, but to be sold to a larger company for $5-$50M.

Large Company Startups: Innovate or Evaporate
Large companies have finite life cycles. And over the last decade those cycles have grown shorter. Most grow through sustaining innovation, offering new products that are variants around their core products. Changes in customer tastes, new technologies, legislation, new competitors, etc. can create pressure for more disruptive innovation – requiring large companies to create entirely new products sold to new customers in new markets. (i.e. Google and Android.) Existing companies do this by either acquiring innovative companies (see Buyable Startups above) or attempting to build a disruptive product internally. Ironically, large company size and culture make disruptive innovation extremely difficult to execute.

Social Startups: Driven to Make a Difference
Social entrepreneurs are no less ambitious, passionate, or driven to make an impact than any other type of founder. But unlike scalable startups, their goal is to make the world a better place, not to take market share or to create to wealth for the founders. They may be organized as a nonprofit, a for-profit, or hybrid.

So What?
When I read policy papers by government organizations trying to replicate the lessons from the valley, I’m struck how they seem to miss some basic lessons.

• Each of these six very different startups requires very different ecosystems, unique educational tools, economic incentives (tax breaks, paperwork/regulation reduction, incentives), incubators and risk capital.
• Regions building a cluster around scalable startups fail to understand that a government agency simply giving money to entrepreneurs who want it is an exercise in failure. It is not a “jobs program” for the local populace. Any attempt to make it so dooms it to failure.
• A scalable startup ecosystems is the ultimate capitalist exercise. It is not an exercise in “fairness” or patronage. While it’s a meritocracy, it takes equal parts of risk, greed, vision and obscene financial returns. And those can only thrive in a regional or national culture that supports an equal mix of all those.
• Building an scalable startup innovation cluster requires an ecosystem of private not government-run incubators and venture capital firms, outward-facing universities, and a rigorous startup selection process.
• Any government that starts public financing entrepreneurship better have a plan to get out of it by building a private VC industry. If they’re still publically funding startups after five to ten years they’ve failed.

To date, Israel is only country that has engineered a successful entrepreneurship cluster from the ground up. It’s Yozma program kick-started a private venture capital industry with government funds, (emulating the U.S. lesson of using SBIC funds.), but then the government got out of the way.

In addition, the Israeli government originally funded 23 early stage incubators but turned them over to the VC’s to own and manage. They’re run by business professionals (not real-estate managers looking to rent out excess office space) and entry is not for life-style entrepreneurs, but is a bootcamp for VC funding.

Unless the people who actually make policy understand the difference between the types of startups and the ecosystem necessary to support their growth, the chance that any government policies will have a substantive effect on innovation, jobs or the gross domestic product is low.

The combination of Venture Capital and technology entrepreneurship is one of the great business inventions of the last 50 years. It provides private funds for untested and unproven technology and entrepreneurs. While most of these investments fail, the returns for the ones that win are so great they make up for the failures. The cultural tolerance for failure and experimentation, and a financial structure which balanced risk, return and obscene returns, allowed this system flourish in technology clusters in United States, particularly in Silicon Valley.

Yet this system isn’t perfect. From the point of view of scientists and engineers in a university lab, too often entrepreneurship in all its VC-driven glory – income statements, balance sheets, business plans, revenue models, 5-year forecasts, etc. – seems like another planet. There didn’t seem to be much in common between the Scientific Method and starting a company. And this has been a barrier to commercializing the best of our science research.

Until today.

Today, the National Science Foundation (NSF) – the $6.8-billion U.S. government agency that supports research in all the non-medical fields of science and engineering - is changing the startup landscape for scientists and engineers. The NSF has announced the Innovation Corps – a program to take the most promising research projects in American university laboratories and turn them into startups. It will train them with a process that embraces experimentation, learning, and discovery.

The NSF will fund 100 science and engineering research projects every year. Each team accepted into the program will receive $50,000.

To commercialize these university innovations NSF will be putting the Innovation Corps (I-Corps) teams through a class that teaches scientists and engineers to treat starting a company as another research project that can be solved by an iterative process of hypotheses testing and experimentation. The class will be a version of the Lean LaunchPad class we developed in the Stanford Technology Ventures Program, (the entrepreneurship center at Stanford’s School of Engineering).

—–

This is a big deal. Not just for scientists and engineers, not just for every science university in the U.S., but in the way we think about bringing discoveries ripe for innovation out of the university lab. If this program works it will change how we connect basic research to the business world. And it will lead to more startups and job creation.

—–

Introducing the Innovation-Corps
The NSF Innovation-Corps program (I-Corps) is designed to help bridge the gap between the many scientists and engineers with innovative research and technologies, but little knowledge of the first steps to take in starting a company.

I-Corps will help scientists take the first steps from the research lab to commercialization.

Over a period of six months, each I-Corps team, guided by experienced mentors (entrepreneurs and VC’s) will build their product and get out of their labs (and comfort zone) to discover who are their potential customers, and how those customers might best use the new technology/invention. They’ll explore the best way to deliver the product to customers, the resources required, as well as competing technologies.  They will answer the question, “What value will this innovation add to the marketplace? And they’ll do this using the business model / customer development / agile development solution stack.

At the end of the program each team will understand what it will takes to turn their research into a commercial success. They may decide to license their intellectual property based on their research. Or they may decide to cross the Rubicon and try to get funded as a startup (with strategic partners, investors, or NSF programs for small businesses). At the end of the class there will be a Demo Day when investors get to see the best this country’s researchers have to offer.

What Took You So Long
A first reaction to the NSF I-Corps program might be, “You mean we haven’t already been doing this?”  But on reflection it’s clear why.  The common wisdom was that for scientists and engineers to succeed in the entrepreneurial world you’d have to teach them all about business. But it’s only now that we realize that’s wrong.  The insight the NSF had is that we just need to teach scientists and engineers to treat business models as another research project that can be solved with learning, discovery and experimentation.

And Stanford’s Lean LaunchPad class could do just that.

Join the I-Corps
Today at 2pm the National Science Foundation is publishing the application for admission (what they call the “solicitation for proposals”) to the program. See the NSF web page here.

The syllabus for NSF I-Corps version of the Lean LaunchPad class can be seen here.

Along with a great teaching team at Stanford, world-class VC’s who get it, and foundation partners, I’m proud to be a part of it.

This is a potential game changer for science and innovation in the United States.

Join us.

Apply now.

ESL, the first company I worked for in Silicon Valley, was founded by a PhD in Math and six other scientists and engineers. Since it was my first job, I just took for granted that scientists and engineers started and ran companies.  It took me a long time to realize that this was one of Silicon Valley’s best contributions to innovation.

Cold War Spin Outs
In the 1950’s the groundwork for a culture and environment of entrepreneurship were taking shape on the east and west coasts of the United States. Each region had two of the finest research universities in the United States, Stanford and MIT, which were building on the technology breakthroughs of World War II and graduating a generation of engineers into a consumer and cold war economy that seemed limitless. Each region already had the beginnings of a high-tech culture, Boston with Raytheon, Silicon Valley with Hewlett Packard.

However, the majority of engineers graduating from these schools went to work in existing companies.  But in the mid 1950’s the culture around these two universities began to change.

Stanford – 1950’s Innovation
At Stanford, Dean of Engineering/Provost Fred Terman wanted companies outside of the university to take Stanford’s prototype microwave tubes and electronic intelligence systems and build production volumes for the military. While existing companies took some of the business, often it was a graduate student or professor who started a new company. The motivation in the mid 1950’s for these new startups was a crisis – we were in the midst of the cold war, and the United States military and intelligence agencies were rearming as fast as they could.

Why It’s “Silicon” Valley
In 1956 entrepreneurship as we know it would change forever.  At the time it didn’t appear earthshaking or momentous. Shockley Semiconductor Laboratory, the first semiconductor company in the valley, set up shop in Mountain View. Fifteen months later eight of Shockley’s employees (three physicists, an electrical engineer, an industrial engineer, a mechanical engineer, a metallurgist and a physical chemist) founded Fairchild Semiconductor.  (Every chip company in Silicon Valley can trace their lineage from Fairchild.)

The history of Fairchild was one of applied experimentation. It wasn’t pure research, but rather a culture of taking sufficient risks to get to market. It was learning, discovery, iteration and execution.  The goal was commercial products, but as scientists and engineers the company’s founders realized that at times the cost of experimentation was failure. And just as they don’t punish failure in a research lab, they didn’t fire scientists whose experiments didn’t work. Instead the company built a culture where when you hit a wall, you backed up and tried a different path. (In 21^st century parlance we say that innovation in the early semiconductor business was all about “pivoting” while aiming for salable products.)

The Fairchild approach would shape Silicon Valley’s entrepreneurial ethos: In startups, failure was treated as experience (until you ran out of money.)

Scientists and Engineers as Founders
In the late 1950’s Silicon Valley’s first three IPO’s were companies that were founded and run by scientists and engineers: Varian (founded by Stanford engineering professors and graduate students,) Hewlett Packard (founded by two Stanford engineering graduate students) and Ampex (founded by a mechanical/electrical engineer.) While this signaled that investments in technology companies could be very lucrative, both Shockley and Fairchild could only be funded through corporate partners – there was no venture capital industry. But by the early 1960′s the tidal wave of semiconductor startup spinouts from Fairchild would find a valley with a growing number of U.S. government backed venture firms and limited partnerships.

A wave of innovation was about to meet a pile of risk capital.

For the next two decades venture capital invested in things that ran on electrons: hardware, software and silicon. Yet the companies were anomalies in the big picture in the U.S. – there were almost no MBA’s. In 1960’s and ‘70’s few MBA’s would give up a lucrative career in management, finance or Wall Street to join a bunch of technical lunatics. So the engineers taught themselves how to become marketers, sales people and CEO’s. And the venture capital community became comfortable in funding them.

Medical Researchers Get Entrepreneurial
In the 60’s and 70’s, while engineers were founding companies, medical researchers and academics were skeptical about the blurring of the lines between academia and commerce. This all changed in 1980 with the Genentech IPO.

In 1973, two scientists, Stanley Cohen at Stanford and Herbert Boyer at UCSF, discovered recombinant DNA, and Boyer went on to found Genentech. In 1980 Genentech became the first IPO of a venture funded biotech company. The fact that serious money could be made in companies investing in life sciences wasn’t lost on other researchers and the venture capital community.

Over the next decade, medical graduate students saw their professors start companies, other professors saw their peers and entrepreneurial colleagues start companies, and VC’s started calling on academics and researchers and speaking their language.

Scientists and Engineers = Innovation and Entrepreneurship
Yet when venture capital got involved they brought all the processes to administer existing companies they learned in business school – how to write a business plan, accounting, organizational behavior, managerial skills, marketing, operations, etc. This set up a conflict with the learning, discovery and experimentation style of the original valley founders.

Yet because of the Golden Rule, the VC’s got to set how startups were built and managed (those who have the gold set the rules.)

Fifty years later we now know the engineers were right. Business plans are fine for large companies where there is an existing market, product and customers, but in a startup all of these elements are unknown and the process of discovering them is filled with rapidly changing assumptions.

Startups are not smaller versions of large companies. Large companies execute known business models. In the real world a startup is about the search for a business model or more accurately, startups are a temporary organization designed to search for a scalable and repeatable business model.

Yet for the last 40 years, while technical founders knew that no business plan survived first contact with customers, they lacked a management tool set for learning, discovery and experimentation.

Earlier this year we developed a class in the Stanford Technology Ventures Program, (the entrepreneurship center at Stanford’s School of Engineering), to provide scientists and engineers just those tools – how to think about all the parts of building a business, not just the product. The Stanford class introduced the first management tools for entrepreneurs built around the business model / customer development / agile development solution stack. (You can read about the class here.)

So what?

Starting this Thursday, scientists and engineers across the United States will once again set the rules.

Stay tuned for the next post.

When The Boardroom is Bits
A revolution has taken hold as customer development and agile engineering reinvent the Startup process. It’s time to ask why startup board governance has failed to keep pace with innovation. Board meetings that guide startups haven’t changed since the early 1900’s.

It’s time for a change.

Reinventing the board meeting may allow venture-backed startups a more efficient, productive way to direct and measure their search for a profitable business model.

Reinventing the board meeting may offer angel-funded startups that don’t have formal boards or directors (because of geography or size of investment) to attract experienced advice and investment outside of technology clusters (i.e. Silicon Valley, New York).

Here’s how.

A Hypothesis – The Boardroom As Bits
Startups now understand what they should be doing in their early formative days is search for a business model. The process they use to guide their search is customer development. And to track their progress startups now have a scorecard to document their week-by-week changes – the business model canvas.

Yet even with all these tools, early stage startups still need to physically meet with advisors and investors. That’s great if you can get it.  But what if you can’t?

What’s missing is a way to communicate all this complex information and get feedback and guidance for startups who cannot get advice in a formal board meeting.

We propose that early stage startups communicate in a way that didn’t exist in the 20^th century – online – collaboratively through blogs.

We suggest that the founders/CEO invest 1 hour a week providing advisors and investors with “Continuous Information Access” by blogging and discussing their progress online in their startup’s search for a business model. They would:

• Blog their Customer Development progress as a narrative
• Keep score of the strategy changes with the Business Model Canvas
• Comment/Dialog with advisors and investors on a near-realtime basis

What Does this Change?
1) Structure. Founders operate in a chaotic regime. So it’s helpful to have a structure that helps “search”
 for a business model. The “boardroom as bits” uses Customer Development as the process for the search, and the business model canvas as the scorecard to keep track of the progress, while providing a common language for the discussion.

This approach offers VC’s and Angels a semi-formal framework for measuring progress and offering their guidance in the “search”
 for a business model. It turns ad hoc startups into strategy-driven startups.

2) Asynchronous Updates. Interaction with advisors and board members can now be decoupled from the – once every six weeks, “big event” – board meeting. Now, as soon as the founders post an update, everyone is notified. Comments, help, suggestions and conversation can happen 24/7. For startups with formal boards, it makes it easy to implement, track, and follow-up board meeting outcomes.

Monitoring and guiding a small angel investment no longer requires the calculus to decide whether the investment is worth a board commitment. It potentially encourages investors who would invest only if they had more visibility but where the small number of dollars doesn’t justify the time commitment.

A board as bits ends the repetition of multiple investor coffees. It’s highly time-efficient for investor and founder alike.

3) Coaching. This approach allows real-time monitoring of a startup’s progress and zero-lag for coaching and course-correction.  It’s not just a way to see how they’re doing. It also provides visibility for a deep look at their data over time and facilitates delivery of feedback and advice.

4) Geography. When the boardroom is bits, angel-funded startups can get experienced advice – independent of geography. An angel investor or VC can multiply their reach and/or depth. In the process it reduces some of the constraints of distance as a barrier to investment.

Imagine if a VC took $4 million (an average Series A investment) and instead spread it across 40 deals at $100K each in a city with a great outward-facing technology university outside of Silicon Valley. In the past they had no way to monitor and manage these investments. Now they can. The result – an instant technology cluster – with equity at a fraction of Silicon Valley prices.  It might be possible to create Virtual Valley Ventures.

We Ran the Experiment
At Stanford our Lean Launchpad class ran an experiment that showed when “the boardroom is bits” can make a radical difference in the outcome of an early stage startup.

Our students used Customer Development as the process to search for a business model. The used a blog to record their customer learning, and their progress and issues. The blog became a narrative of the search by posting customer interviews, surveys, videos, and prototypes. They used the Business Model Canvas as a scorekeeping device to chart their progress. The result invited comment from their “board” of the teaching team.

Here are some examples of how rich the interaction can become when a management team embraces the approach.

We were able to give them near real-time feedback as they posted their results. If we had been a board rather than a teaching team we would have added physical reality checks with Skype and/or face-to-face meetings.

Show Me the Money
While this worked in the classroom, would it work in the real world? I thought this idea was crazy enough to bounce off a five experienced Silicon Valley VC’s. I was surprised at the reaction – all of them want to experiment with it. Jon Feiber at MDV is going to try investing in startups emerging from Universities with great engineering schools outside of Silicon Valley that have entrepreneurship programs, but minimal venture capital infrastructure. (The University of Michigan is a possible first test.) Kathryn Gould of Foundation Capital and Ann Miura-Ko of Floodgate also want to try it.

Shawn Carolan of Menlo Ventures not only thought the idea had merit but seed-funded the LeanLaunchLab, a startup building software to automate and structure this process. (More than 700 startups signed up for the LeanLaunchLab software the day it was first demo’d.) Other entrepreneurs think this is an idea whose time has come and are also building software to manage this process including Alexander Osterwalder, Groupiter, and Angelsoft. Citrix thought this was such a good idea that their Startup Accelerator has offered to provide GoToMeeting and GoToMeeting HD Faces free to participating VC’s and startups. Contact them here.

Summary
For startups with traditional boards, I am not suggesting replacing the board meeting – just augmenting it with a more formal, interactive and responsive structure to help guide the search for the business model. There’s immense value in face-to-face interaction. You can’t replace body language.

But for Angel-funded companies I am proposing that a “board meeting in bits” can dramatically change the odds of success. Not only does this approach provide a way for founders to “show your work” to potential and current investors and advisors, but also it helps expand opportunities to attract investors from outside the local area.

Lessons Learned

• Startups are a search for a business model
• Startups can share their progress/get feedback in the search
• Weekly blog of the customer development narrative
• Weekly summary of the business model canvas
• Interactive comments and questions
• Skype and face-to-face when needed
• This may be a way to augment traditional board meetings
• This might be a way to rethink our notion of geography as a barrier to investments

Or watch the video here.

What’s Wrong With Today’s Board Meetings
As customer and agile development reinvent the Startup, it’s time to ask why startup board governance has not kept up with the pace of innovation. Board meetings that guide startups haven’t changed since the early 1900’s.

It’s time.

Reinventing the board meeting may offer venture-backed startups a more efficient, productive way to direct and measure their search for a profitable business model.

Reinventing the board meeting may offer angel-funded startups – which because of geography or size of investment typically don’t have formal boards or directors – to attract experienced advice and investment outside of technology clusters (i.e. Silicon Valley, New York).

Here’s how.

Because We’ve Always Done It This Way
The combination of Venture Capital and technology startups is only about 50 years old. Rather than invent a new form of corporate governance, venture investors adopted the traditional board meeting structure from large corporations. Yet boards of large companies exist to monitor efficient strategy and execution of a known business model. While startups eventually get into execution mode, their initial stages are devoted to a non-linear, chaotic search for a business model: finding product/market fit to identify a product or service people will buy in droves at a sustainable, profitable pace.

In the last few years, our understanding that startups are not smaller versions of large companies, made us recognize that startups need their own tools, different from those used in existing companies: Customer Development – the process to search for a Business Model, the Business Model Canvas – the scorecard to measure progress in the search, and Agile Engineering – the tools to physically construct the product.

Yet while we’ve reinvented how startups build their companies, startup investors are still having board meetings like it’s the 19^th century.

Why Have a Board Meeting?
From a VC’s point of view there are two reasons for board meetings.

1) It’s their fiduciary responsibility. Once a startup gets going, it has asymmetric information. Investors get board seats to assure themselves and their limited partners that they are duly informed about their investment.

2) Investors believe that their experience and guidance can maximize their return. Here it’s the board that has asymmetric knowledge. A veteran board can bring 50-100x more experience into a board meeting than a first time founder. (VC’s sit on 6 – 12 boards at a time. Assume an average tenure of 4 years per board. Assume two veteran VC’s per board.
=
50-100x more experience.)

From a founder’s point of view there are three reasons for board meetings.

1) It’s an obligation that came with the check.

2) Founders who have a great board do recognize the uncanny pattern recognition skills that good VC’s bring.

3) An experienced board brings an extensive network of customers, partners, help in recruiting, follow-on financing, etc.

What’s Wrong With a Board Meeting?
The Wrong Metrics. Traditional startup board meetings spend an insane amount of wasted time using Fortune 100 company metrics like income statements, cash flow, balance sheet, waterfall charts. The only numbers in those documents that are important in the first year of a startup’s life are burn rate and cash balance. Most board meetings never get past big company metrics to focus on the crucial startup numbers. That’s simply a failure of a startup board’s fiduciary responsibility.

The Wrong Discussions. The most important advice/guidance that should come from investors in a board meeting is about a startup’s search for a business model: What are the business model hypotheses? What are the most important hypotheses to test now? How are we progressing validating each hypothesis? What do those numbers/metrics look like? What are the iterations and Pivots – and why?

Not Real-time.  Startup board meetings occur every 4-6 weeks. While that’s great when you showed up in your horse and buggy, the strategy-to-tactic-to implementation lag is painful at Internet speeds. And unless there’s rigor in the process, because there is no formal structure for follow up, tracking what happened as a result of meeting recommendations and action items gets lost in the daily demands of everyone’s work. (Of course great VC’s mix in coffees, phone calls, coaching and other non-board meeting interactions but it’s ad hoc and not always done.)

Wastes Founders Time. For the founders, “the get ready for the board meeting” drill is often a performance rather than a snapshot. Powerpoints, spreadsheets and rehearsals consume time for materials that are used once and discarded. There are no standards for what each side (board versus management) does. What is the entrepreneur supposed to be doing? What are the board members supposed to be contributing?

The Wrong Structure. If you read advice on how to run a board meeting you’ll get advice that would have felt comfortable to Andrew Carnegie or John D. Rockefeller.

In the age of the Internet why do we need to get together in one room on a fixed schedule? Why do we need to wait a month to six weeks to see progress? Why don’t we have standards for what metrics VC’s want to see from their early stage startup teams?

Angels In America
For angel-funded startups, life is even tougher. Data from the Startup Genome project shows that startups that have helpful mentors, listen to customers, and learn from startup thought leaders raise 7x more money and have 3.5x better user growth. If you’re in a technology cluster like Silicon Valley you may be able to attract ad hoc advice from experienced investors. But very little of it is formal, and almost none of it approaches the 50-100x experience level of professional investors.

As there’s no formal board, most of these angel/investors meetings are over coffees. And lacking a board meeting there’s no formal mechanism to get investor advice. Angel investments in mobile and web apps today are approaching the “throw it against the wall and see if it sticks” strategy.

And for startups outside of technology clusters, there’s almost no chance of attracting Silicon Valley VC’s or angels. Geography is a barrier to investment.

So given all this, the million dollar question is: Why in the age of the Internet haven’t we adopted the tools we build/sell to solve these problems?

In the next post – Reinventing the Board Meeting.

Lessons Learned

• Early stage board meetings are often clones of large company board meetings
• That’s very, very wrong
• Angel-funded startups have no formal mechanism for experienced advice
• There’s a better way

Ok, I get a lot of these. Is this some grad student or post doc who wanted to do some independent study?

The email continued,  ”The problem I’m working on is that many founders are either making uninformed decisions or inefficiently learning the new skills they need. The solution I’m exploring is a just in time learning methodology that accelerates founders’ learning curve by aggregating relevant content, peers and mentors.”

Hmm, now I’m getting intrigued. This sounded like one heck of an interesting guy and it’s a subject I care about. I wondered where he got his MBA from?

The email closed by saying, “The project is a hybrid between academic and entrepreneurial circles and I’d really love to begin a dialogue with people in the academic world also interested in solving this problem. Your name has come up a lot in that regard. Let me know if this interests you and if you have any time to speak.”

It was signed Max Marmer.

I set up a meeting and at Cafe Borrone some kid who looked 18-years old came up to me and introduced himself as Max. “How old are you? I asked. “18,” he replied.

Holy sx!t.

When I asked Max why he was interested in solving entrepreneurial education problems he replied, “I was always interested in big picture trends for where the world is headed. I spent time with organizations like the Institute for the Future and Singularity University. My conjecture became that the world’s biggest problem isn’t poverty or disease or any oft-stated major problem, but that we don’t have enough people engaged in trying to solve these problems. A big piece of the solution lies in the scalable impact of entrepreneurship and an increase of successful entrepreneurs. But potential impact consistently fails to be realized because of self-destruction.”

I don’t think I touched my sandwich. I tried to remember what I was doing at 18 and whatever it was I wasn’t this. Max continued, “That’s why I’m really interested in ways of optimizing the entrepreneurship ecosystem to allow more entrepreneurs to go from idea to reality. To do this requires: a methodology, tools and systematically reducing friction.”

Tune In, Turn On, Drop Out
Max entered Stanford in the fall of 2010 as a freshman, took as many of the engineering entrepreneurship classes as he could and independent study with me. (He was part of the Sandbox network - a group of incredibly smart under 30 year olds.)

Max dropped out of Stanford after his first quarter.

But he left to work on what he told me he came to do - crack the innovation code of Silicon Valley and share it with the rest of the world. He set up Blackbox.vc, a seed accelerator for technology startups (and one of the tour stops for entrepreneurs from around the world.) They went to work gathering deep knowledege of what makes successful Internet startups.

Max and his partners interviewed and analyzed over 650 early-stage Internet startups. Today they released the first Startup Genome Report— a 67 page in-depth analysis on what makes early-stage Internet startups successful.

Startup Genome Report
Some of their key findings:

1. Founders that learn are more successful: Startups that have helpful mentors, track metrics effectively, and learn from startup thought leaders raise 7x more money and have 3.5x better user growth.

2. Startups that pivot once or twice times raise 2.5x more money, have 3.6x better user growth, and are 52% less likely to scale prematurely than startups that pivot more than 2 times or not at all.

3. Many investors invest 2-3x more capital than necessary in startups that haven’t reached problem solution fit yet. They also over-invest in solo founders and founding teams without technical cofounders despite indicators that show that these teams have a much lower probability of success.

4. Investors who provide hands-on help have little or no effect on the company’s operational performance. But the right mentors significantly influence a company’s performance and ability to raise money. (However, this does not mean that investors don’t have a significant effect on valuations and M&A)

5. Solo founders take 3.6x longer to reach scale stage compared to a founding team of 2 and they are 2.3x less likely to pivot.

6. Business-heavy founding teams are 6.2x more likely to successfully scale with sales driven startups than with product centric startups.

7. Technical-heavy founding teams are 3.3x more likely to successfully scale with product-centric startups with no network effects than with product-centric startups that have network effects.

8. Balanced teams with one technical founder and one business founder raise 30% more money, have 2.9x more user growth and are 19% less likely to scale prematurely than technical or business-heavy founding teams.

9. Most successful founders are driven by impact rather than experience or money.

10. Founders overestimate the value of IP before product market fit by 255%. 

11. Startups need 2-3 times longer to validate their market than most founders expect. This underestimation creates the pressure to scale prematurely.

12. Startups that haven’t raised money over-estimate their market size by 100x and often misinterpret their market as new.

13. Premature scaling is the most common reason for startups to perform worse. They tend to lose the battle early on by getting ahead of themselves.

14. B2C vs. B2B is not a meaningful segmentation of Internet startups anymore because the Internet has changed the rules of business. We found 4 different major groups of startups that all have very different behavior regarding customer acquisition, time, product, market and team.

———

I’m not sure I believe every one of the report conclusions – it just covers very early stage web startups, and the methodology is still shaky – but this is a landmark study. I think these guys have gone a long way to turn hypotheses about early-stage Internet startups into facts. And they’re just getting started.

Congratulations.  A+

Download the full Startup Genome report here.

——-

I can’t wait to see what Max does by the time he’s 21.

He had me in for an interview. We covered a wide range of topics.

0:22 – the Entrepreneurial explosion
1:45 – Are we in a Bubble?
3:20  - The Last Bubble
6:30 – Rules for the New Bubble
8:05 – Metrics for Success
10:10 – Total Available Market in the Billions
11:45 – Is this a Really a Bubble – the greater fool theory
13:00 – VC’s – The Pact With the Devil
14:10 – What to Use VC’s $’s for?
15:36 – How to Get Customer Centric – an unnatural act
17:00 – The Secrets to Social Networks – Bowling Alone
17:45 – Who Are the Best Entrepreneurs?
18:45 – Entrepreneurs are Artists
21:39 – What Makes Silicon Valley Special?
22:50 – Risk and Culture in Silicon Valley

I am honored to be with you as we gather to celebrate your graduation from Philadelphia University.

While I teach at Stanford and Berkeley, to be honest… this is the closest I’ve ever gotten to a college graduation.

I realize that my 15 minutes up here is all that’s between you and the rest or your life, so if I can keep you awake, I’m going to share 4 short stories from my life.

My first story is about finding your passion.
My parents were immigrants…  Neither of them had been to college—my mother graduated from high school but my father left school after the 7th grade.  Still, like many immigrants, they dreamed that someday their children would go to college…  Unfortunately that was their dream—but it wasn’t mine.

I ended up at Michigan State because I got a scholarship…Once I got there, I was lost…unfocused…and had no idea of who I was and why I was in school. I hated school.

One day my girlfriend said, “You know some of us are working hard to stay here. But you don’t seem to care.Why don’t you find out what you really want to do?”

That was the moment I realized I, …not anyone else…was in charge of my life.

I took her advice. I dropped out of Michigan State University after the first semester.

In the middle of a Michigan winter, I stuck out my thumb and hitchhiked to Miami, the warmest place I could think of.

I had no idea what would be at the end of the highway. But that day I began a pattern that I still follow—stick out your thumb and see where the road takes you.

I managed to find a job at the Miami International Airport loading racehorses onto cargo planes. I didn’t like the horses, but the airplanes caught my interest.

Airplanes were the most complicated things I had ever seen. Unlike other kids who were fans of the pilots, I was in awe of the electronics technicians in charge of the planes’ instruments. I would hang around the repair shop just helping out wherever I could. I didn’t know anything, so I didn’t get paid…

But soon some technician took me under his wing and gave me my first tutorial on electronics, radar and navigation. I was hooked. I started taking home all the equipment manuals and would read them late into the night.

For the first time in my life, I found something I was passionate about.

And the irony is that if I hadn’t dropped out, I would never have found this passion…the one that began my career. If I hadn’t discovered something I truly loved to do, I might be driving a cab at the Miami airport.

My life continued to follow this same pattern…I’d pursue my curiosity, volunteer to help, and show up a lot. Again and again, the same thing would happen… people would notice that I cared…and I’d get a chance to learn something new.

Now that you paid for your degree…I’m going to let you in on a secret. It’s your curiosity and enthusiasm that will get you noticed and make your life interesting—not your grade point average.

But at the time…as excited as I was…I couldn’t see how my passion for airplanes and avionics could ever get me anywhere.  Without money, or a formal education, how could I learn about them?

The answer turned out to be a war.

My second story is about Volunteering and Showing Up.
In the early 1970’s, as some of you might remember, our country was in the middle of the Vietnam War—-and the Air Force was happy to have me.

I enlisted to learn how to repair electronics. The Air Force sent me to a year of military electronics school. While college had been someone else’s dream, learning electronics had become mine.

After electronics school, when most everyone else was being sent overseas to a war-zone, I was assigned to one of the cushiest bases in the Air Force, right outside of Miami.

My first week on the base… our shop chief announced: “We’re looking for some volunteers to go to Thailand.” I still remember the laughter and comments from my fellow airmen. “You got to be kidding… leave Miami for a war in Southeast Asia?”

Others wisely remembered the first rule in the military: never volunteer for anything. Listening to them, I realized they were right. Not volunteering was the sane path of safety, certainty and comfort.

So I stepped forward, raised my hand—and I said, “I’ll go.”

Once again, I was going to see where the road would take me. Volunteering for the unknown…which meant leaving the security of what I knew…would continually change my life.

Two weeks later I was lugging heavy boxes across the runway under the broiling Thailand sun. My job was to replace failed electronic warfare equipment in fighter planes as they returned from bombing missions over North Vietnam.

As I faced yet another 110-degree day, I did consider that perhaps my decision to leave Miami might have been a bit hasty. Yet every day I would ask, “Where does our equipment come from… and how do we know it’s protecting our airplanes?”

The answer I got was, “Don’t you know there’s a war on? Shut up and keep doing what you’re told.”

Still I was forever curious. At times continually asking questions got me in trouble…

once it almost sent me to jail…

but mostly it made me smarter.

I wanted to know more.  I had found something I loved to do.. …and I wanted to get better at it.

When my shift on the flightline was over, my friends would go downtown drinking. Instead, I’d often head into the shop and volunteer to help repair broken jammers and receivers. Eventually, the shop chief who ran this 150-person shop approached me and asked, “You’re really interested in this stuff, aren’t you?” He listened to me babble for a while, and then walked me to a stack of broken electronic equipment and challenged me troubleshoot and fix them.

Hours later when I was finished, he looked at my work and told me, “We need another pair of hands repairing this equipment. As of tomorrow you no longer work on the flightline.” He had just given me a small part of the electronic warfare shop to run.

People talk about getting lucky breaks in their careers. I’m living proof that the “lucky breaks” theory is simply wrong. You get to make your own luck. 80% of success in your career will come from just showing up. The world is run by those who show up…not those who wait to be asked.

Eighteen months after arriving in Thailand, I was managing a group of 15 electronics technicians.

I had just turned 20 years old.

My third story is about Failure and Redemption
After I left the military, I ended up in Palo Alto, a town south of San Francisco. Years later this area would become known as Silicon Valley.

For a guy who loved technology, I was certainly in the right place. Endlessly curious, I went from startups in military intelligence to microprocessors to supercomputers to video games.

I was always learning. There were times I worried that my boss might find out how much I loved my job…and if he did, he might make me pay to work there. To be honest, I would have gladly done so.  While I earned a good salary, I got up and went to work every day not because of the pay, but because I loved what I did.

As time went on, I was a co-founder or member of the starting team for six high-tech startups…

With every startup came increasing responsibility. I reached what I then thought was the pinnacle of my career when I raised tens of millions of dollars and became CEO of my seventh startup… a hot new video game company. My picture was in all the business magazines, and made it onto the cover of Wired magazine. Life was perfect.

And then one day it wasn’t.

It all came tumbling down. We had believed our own press, inhaled our own fumes and built lousy games. Customers voted with their wallets and didn’t buy our products. The company went out of business. Given the press we had garnered, it was a pretty public failure.

We let our customers, our investors, and our employees down. While it was easy to blame it on others…and trust me at first I tried… in the end it was mostly a result of my own hubris—the evil twin of entrepreneurial passion and drive.

I thought my career and my life were over. But I learned that in Silicon Valley, honest failure is a badge of experience.

In fact, unlike in the movies, most startups actually fail. For every Facebook and Zynga that make the press, thousands just never make it at all.

All of you will fail at some time in your career…or in love, or in life.

No one ever sets out to fail. But being afraid to fail means you’ll be afraid to try.  Playing it safe will get you nowhere.

As it turned out, rather than run me out of town on a rail, the two venture capital firms that had lost $12 million in my failed startup actually asked me to work with them.

During the next couple years…and much humbler… I raised more money and started another company, one that was lucky enough to go public in the dot.com bubble.

In 1999… with the company’s revenue north of $100 million…I handed the keys to a new CEO and left. I had married a wonderful woman and together we had two young daughters.

I decided that after 20 years of working 24/7 in eight startups, I wanted to go home and watch my kids grow up.

Which brings me to my last story—There’s a Pattern Here.
When I retired I found myself with lots of time to think.

I began to reflect about my career and what had happened in my 21 years with startups in Silicon Valley.

I was all alone in a ski cabin with the snow falling outside…with my wife and daughters out on the slopes all day… I started to collect my thoughts by writing what I had hoped would become my memoirs.

Eighty pages later, I realized that I had some great stories as an entrepreneur and a failed CEO. But while writing them was a great catharsis, it was quickly becoming clear that I’d even have to pay my wife and kids to read the stories.

But the more I thought about what I had done, and what other entrepreneurs had tried, I realized something absurdly simple was staring at me.  I saw a repeatable pattern that no else had ever noticed.

Business schools and investors were treating new companies like they were just small versions of large companies. But it struck me that startups were actually something totally different. Startups were actually like explorers—searching for a new world, where everything—customers, markets, prices—were unknown and new.

These startups needed to be inventive as they explore, trying new and different things daily. In contrast, existing companies, the Wal-Mart’s and McDonalds, already had road maps, guide books and playbooks—they already know their customers, markets, and prices. To succeed they just need to do the same thing every day.

Now it would have been easy to say, “Nah, this can’t be right—every smart professor at Harvard and Wharton and Stanford believes something different.”

In fact, in your lives this will happen to you.

You will have a new idea, and people will tell you, “That can’t be right because we’ve always done it this way.”

Ignore them…..  Be persistent… Never give up. Innovation comes from those who see things that other don’t.

As a retired CEO, I had a lot of free time.  So I was often invited to be a guest lecturer at the business school at Berkeley. They thought I could tell stories about what it was like to start a company. I was generous with my time…and I showed up a lot.

But I began to nag the head of the department about this new idea I had…one that basically said that everything you learn about starting new companies in business schools was wrong. I thought that there was a better a way to teach and manage startups than the conventional wisdom of the last 40 years. And to their credit…Berkeley’s Business School and then Stanford’s Engineering School let me write and teach a new course based on my ideas.

Now…a decade later… that course called Customer Development… is the basis of an entirely new way to start companies.

If you’re in a technology company or build a web or mobile application, it’s probably the only way to start a company.

How did this happen?  By showing up a lot and questioning the status quo.

These days I write a weekly blog about entrepreneurship.  At the end of each post, I conclude with lessons learned—a kind of Cliff Notes of my key takeaways.  So in case you haven’t been listening, that’s how I’ll finish up today.

–

Be forever curious.
Volunteer for everything.
Show up a lot.
Treat failure as a learning experience.

Live life with no regrets.
Remembering…There is no undo button.

Congratulations again to you all…and thank you very much.

This is the End
Class lectures were over last week, but most teams kept up the mad rush to talk to even more customers and further refine their products. Now they were standing in front of us to give their final presentations. They had all worked hard. Teams spent an average of 50 to 100 hours a week on their companies, interviewed 50+ customers and surveyed hundreds (in some cases thousands) more.

While the slide presentations of each team are interesting to look at, that’s actually the sideshow. What really matters are the business model canvas diagrams in the body and appendix of each presentation. These diagrams are the visual representation of the how and the what a team learned in the class – how they tested their hypotheses by getting out of the building using the Customer Development process and what they learned about each part of their business model.

By comparing the changes the teams made week-to-week-week in their business model canvas diagrams, you’ll see the dynamics of entrepreneurship, as they iterate and Pivot over time. We believe these are the first visual representations of learning over time.

Team Agora

If you can’t see the Agora slides above, click here.

Team Autonomow

If you can’t see the Autonomow slides above, click here.
(p.s. they’re going to make a company out of this class project, and they’re hiring engineers.)

Team Blink Traffic

If you can’t see the Blink traffic slides above, click here.

Team D.C. Veritas

If you can’t see the D.C. Veritas slides above, click here.

Team Mammoptics

If you can’t see the Mammoptics slides above, click here.

Team OurCrave

If you can’t see the OurCrave slides above, click here.

Team PersonalLibraries

If you can’t see the PersonalLibraries slides above, click here.

Team PowerBlocks

If you can’t see the PowerBlocks slides above, click here.

Team Voci.us

If you can’t see the Voci.us slides above, click here.

———

Why Did We Teach This Class?
Many entrepreneurship courses focus on teaching students “how to write a business plan.” Others emphasize how to build a product. We believe the former is simply wrong and the later insufficient.

Business plans are fine for large companies where there is an existing market, existing product and existing customers, but in a startup all of these elements are unknown and the process of discovering them is filled with rapidly changing assumptions. Experienced entrepreneurs realize that no business plan survives first contact with customers. So our goal was to teach something actually useful in the lives of founders.

Building a product is a critical part of a startup, but just implementing build, measure, learn without a framework to understand customers, channel, pricing, etc. is just another engineering process, not building a business. In the real world a startup is about the search for a business model or more accurately, startups are a temporary organization designed to search for a scalable and repeatable business model. Therefore we developed a class to teach students how to think about all the parts of building a business, not just the product.

There was no single class to teach aspiring entrepreneurs all the skills involved in searching for a business model (business model design, customer and agile development, design thinking, etc.) in one quarter. The Lean LaunchPad was designed to fill that void.

What’s Different About the Class?
The Lean LaunchPad class was built around the business model / customer development / agile development solution stack. Students started by mapping their assumptions (their business model) and then each week they tested these hypotheses with customers and partners outside in the field (customer development) and used an iterative and incremental development methodology (agile development) to build the product.

The students were challenged to get users, orders, customers, etc. (and if a web-based product, a minimum feature set) all delivered in 8 weeks. Our goal was to get students out of the building to test each of the nine parts of their business model, understand which of their assumptions were wrong, make adjustments and continue to iterate based on what they learned.  They learned first-hand that faulty assumptions were not a crisis, but a learning event called a pivot —an opportunity to change the business model.

What Surprised Us?

1. The combination of the Business Model Canvas and the Customer Development process was an extremely efficient template for the students to follow – even more than we expected.
2. It drove a hyper-accelerated learning process which led the students to a “information dense” set of conclusions. (Translation: they learned a lot more, in a shorter period of time than in any other entrepreneurship course we’ve ever taught or seen.)
3. The process worked for all types of startups – not just web software but from a diverse set of industries – wind turbines, autonomous vehicles and medical devices.
4. Insisting that the students keep a weekly blog of their customer development activities gave us insight into their progress in powerful and unexpected ways. (Much more on this in subsequent blog posts.)

What Would We Change?

1. In this first offering of the Lean Launchpad class we let students sign up without being part of a team. In hindsight this wasted at least a week of class time. Next year we’ll have the teams form before class starts. We’ll hold a mixer before the semester starts so students can meet each other and form teams. Then we’ll interview teams for admission to the class.
2. Make Market Size estimates (TAM, SAM, addressable) part of Week 2 hypotheses
3. Show examples of a multi-sided market (a la Google) in Week 3 or 4 lectures.
4. Be more explicit about final deliverables; if you’re a physical product you must show us a costed bill of materials and a prototype. If you’re a web product you need to build it and have customers using it.
5. Teach the channel lecture (currently week 5) before the demand creation lecture (currently week 4.)
6. Have teams draw the diagram of “customer flow” in week 3 and payment flows in week 6.
7. Have teams draw the diagram of a finance and operations timeline in week 9.
8. Find a way to grade team dynamics – so we can really tell who works well together and who doesn’t.
9. Video final presentations and post to the web. (We couldn’t get someone in time this year)

It Takes a Village
While I authored these blog posts, the class was truly a team project. Jon Feiber of Mohr Davidow Ventures and Ann Miura-Ko of Floodgate co-taught the class with me (with Alexander Osterwalder as a guest lecturer.) Thomas Haymore was our great teaching assistant. We were lucky to get a team of 25 mentors (VC’s and entrepreneurs) who selflessly volunteered their time to help coach the teams. Of course, a huge thanks to the 39 Stanford students who suffered through the 1.0 version of the class. And finally special thanks to the Stanford Technology Ventures Program; Tom Byers, Kathy Eisenhardt, Tina Selig for giving us the opportunity to experiment in course design.

E245, the Lean LaunchPad will be offered again next Winter.  See you there!

While this is the last lecture, the teams still have one more week to work on their companies, and then they have their final presentations – for 30% of their grade.  All the teams have crossed the Rubicon. 

Week 8 of the class.
Last week the teams tested their Revenue Models hypotheses: what are customers willing to pay for? This week they were testing their hypotheses about Partners. Partners are the external companies whose product or service combines with your Value Proposition to create a complete customer solution or “whole product” to satisfy customers. For example, Apple needed music from their record label partners to make the original iPod and iTunes experience complete. (The concept of Partners, took some explanation as some teams confused partners with the Distribution Channel.)

The Nine Teams Present
PersonalLibraries was now an on-line “social shopping system.” After a week of hectic customer discovery, the team further refined their new business model. Their minimum viable product would be “Trusted Advice on products tailored to your needs by people and groups relevant to you.” Their initial customer segment were upwardly mobile professionals with $2-10K discretionary purchases/year (excluding travel,) and their revenue model was affiliate program fees.

With the clock ticking down to the end of the class the team appeared to give up sleep for the remainder of the quarter. They contacted a dozen admissions consulting firms, ran three Usertesting.com video interviews on a social shopping tool, surveyed 40 Stanford students on their on-line shopping habits, and then did another survey of 700 Stanford MBA students (!) to find out what books they’d recommend for prospective students. They used that data as their first “trusted advice” for the new website they built in a week. http://insidely.com/books/

Within the week they were #6 in Google search results for “Stanford Admission Books.”

Amazingly it looked like the PersonalLibraries team had restarted the company and found a segment where customers wanted their product. They had another week to go until their final presentations. This looks like a race to the wire.

If you can’t see the slides above, click here.

Autonomow, the robotic farm weeder, spent part of the week investigating Partners that could help them build a more complete offering for farmers. The team talked to an agricultural sensor expert at U.C. Davis, a German applied Laser research group, a California organic farmer who wanted to be an Earlyvangelist, four service partners and three weed/pest management consultants.

On the technology front, last week they tested whether their Carrotbot (their research platform they built to gather data for machine vision/machine learning) could tell the difference between a carrot and a weed in a farm field versus the lab. This week the team started investigating whether the spectral reflectance curves of healthy green plants are different from weeds, and if so could an infrared Hyperspectral imaging camera be better suited than their current visible light camera for weed/plant recognition.

But what got our attention was when they told us they were investigating what it takes to kill a weed in the field. Their answer? With a laser. Way cool.

They spent the week sorting through some basic laser technical questions. How much energy does it take to kill a weed? Answer: About 5 Joules of energy. Next question: How much energy will the laser require? Answer: If the robotic weeder is traveling at 1.5 mph, the laser needs to kill the weed in about 10 milliseconds; therefore the laser needs to put out no more than 500 watts of energy. What wavelength of laser? Answer: The most cost effective wavelength is 800-900nm ~ $20/watt. But water (the main ingredient in a weed) best absorbs light at higher frequencies – think microwaves. Final question: Is the improved absorption efficiency worth the extra cost? Testing for all of these is required.

If you can’t see the slides above, click here.

The next team was D.C. Veritas, building a low cost wind turbine for cities. Last week the team did mass interviews of city officials across the United States to understand the project approval process inside a city. This week they broadened the discussion with interviews with the city planner in Mariposa, Texas and the city engineer from Rapid City, South Dakota.

They worked on understanding their partners. D.C. Veritas needs three types of partners: installers (to reduce their overhead,) certification authorities (who would provide credibility) and government and research labs (for testing facilities).

Of real interest was their evolving view of their revenue model. Instead of selling a city the wind turbine hardware, their revenue model moved to a Wind Power Purchase Agreement, a long term contract with a city to buy the electricity generated by the D.C. Veritas turbines.

If you can’t see the slides above, click here.

The Agora Cloud Services team was now making a tool set for managing Amazon Web Services cloud compute usage. They believed their tools could save customers 30% of their Amazon bill. Their value proposition was to provide service matching, capacity planning and usage monitoring & control.  They had another 3 interviews, this time with potential partners and integrators.

If you can’t see the slides above, click here.

The Week 8 Lecture: Q&A and Summing Up
Our lecture covered Key Resources and Cost Structure. The textbooks for this class were Alexander Osterwalder’s Business Model Generation (along with the Four Steps to the Epiphany). So who better to have as a surprise guest lecturer for our last class than Alexander Osterwalder himself.

His lecture covered: What resources do you need to build your business?  How many people? What kind? Any hardware or software you need to buy? Any IP you need to license?  How much money do you need to raise?  When?  Why? Importance of cash flows? When do you get paid vs. when do you pay others?

Our assignment for the teams during their final week: What’s your expense model? What are the key financials metrics for costs in your business model?  Costs vs. ramp vs. product iteration? Access to resources. Where is the best place for your business? Where is your cash flow break-even point? Assemble a resources assumptions spreadsheet.  Include people, hardware, software, prototypes, financing, etc.  When will you need these resources?  Roll up all the costs from partners, resources and activities in a spreadsheet by time.

The last part of their assignment is their final presentation – a “Lessons Learned” summary of their work over the entire quarter – which will count for 30% of their grade. To help them get ready for their final, one of our mentors plans to hold a mandatory “story-telling” workshop, to assist them in assembling their final presentation.

If you can’t see the slides above, click here.

———

Over the last few weeks as our students presented, we had a growing feeling that we were seeing something extraordinary. Our teaching objective was to take engineers (with a smattering of MBA’s) and give them an immersive hands-on experience of how an idea becomes a profitable business. We taught them theory, methodology, and practice using Customer Development and business model design.

Watching them we realized that we had found a way to increase the information density a student team could acquire in eight short weeks. But what was truly awe-inspiring was the breathtaking speed and tempo of the teams’ Pivots.

All teams had all accomplished something remarkable, but it won’t be clear what a singular achievement this was until we see their final presentations.

Stay tuned for the last post – the Final Presentations and Lessons Learned.

With a week to go the teams are starting to look like opening night before the big play. Teams are iterating and pivoting right and left, one team threw their entire business model out the window and did a complete restart, and another team was having a meltdown over personalities.

Week 7 of the class.
Last week the teams were testing their hypotheses about their Channel (how a company delivers its value proposition (i.e. its product or service) to its customers. This week they were testing their hypotheses about Revenue Models: what are customers really willing to pay for? How? Are you generating transactional or recurring revenues? Is it a multi-sided market, and if so who’s the user versus who’s the payer.

The Nine Teams Present
The first team up was PersonalLibraries the team making a reference management system for discovering, organizing and citing researchers’ readings. Oops.  No more.  The team looked at the potential revenue and concluded that the outlook for this business with this customer segment was dismal. They decided to do something more dramatic than just a Pivot. They did a restart. They moved from “Reference Libraries” to “Product Libraries”— an on-line social shopping system. (If this had been a real startup rather than a class we would have had the team test many more variants on customer segment, revenue models, channels, etc before such an extreme move.)

They quickly came up with a new business model canvas, value proposition and customer segment.

The team hasn’t been getting much sleep as they have a week and a half to make meaningful progress. Lets see what they can pull off.

If you can’t see the slides above, click here.

Autonomow, the robotic farm weeder had a busy week. In talking to their sales channel (farm equipment dealers) and customers (organic farmers) they realize they have an opportunity to come up with a unique revenue stream. Instead of selling or leasing the equipment they are going to charge for leasing according to weed density in the farm fields. The denser the weeds the higher the rental price per day. Customers and dealers agree that it’s a fair deal.  Wow.

.

On the way to the WorldAg Expo their Carrotbot (their research platform they built to gather data for machine vision/machine learning) hit the farm fields near Avenal, California.

The videos of the robot in the field were priceless.

At the World Ag Expo in Tulare the team encounters its first potential competitor –  “Robocrop.” (No kidding, I couldn’t make this up.) The Robocrop Precision Guidance System for row crop cultivators uses a camera to shift a hitch so cultivators can cut very close to the plant rows and the Robocrop InRow is a robotic weeder.

If you can’t see the slides above, click here.

The next team was D.C. Veritas, the team building a low cost residential wind turbine wind turbine for cities and utilities.Last week the team pivoted and their wind turbine is now embedded into street and highway light poles.

This week the D.C. Veritas team put it into overdrive and did mass interviews of city officials across the United States. In Palo Alto they talked to the financial and utilities mangers. In Williamstown, West Virginia they spoke to the city planner and a member of the budget committee. In Oklahoma City, Oklahoma it was the city engineer and director of public works. In Amarillo, Texas they had interviews with the head of the bidding process, the Street light manager, Director of Public Works and the utilities engineer.

They quickly got a good handle on the canonical project approval process inside a city.

They combined their understanding of the city approval process with the data they gleaned from customer interviews and developed preliminary archetypes. These represented the different customers in the approval cycle inside a city.

If you can’t see the slides above, click here.

Agora Cloud Services

The Agora team, a marketplace for cloud computing, (a relative island of calm in a turbulent sea of other teams) now believed their business was žproviding a tool set for managing Amazon Web Services cloud compute usage. They believed they could build tools that would save customers 30% of their Amazon bill by provide service matching, capacity planning and usage monitoring & control.  The team was a paragon of steady and relentless progress. They had another 4 interviews with potential customers and consultants.

If you can’t see the slides above, click here.

The Week 7 Lecture: Partners

Our lecture this week covered Partners. Which partners and suppliers leverage your model? Who do you need to rely on?

Our assignment for the teams for next week: What partners will you need? Why do you need them and what are risks? Why will they partner with you? What’s the cost of the partnership?  What are the benefits for an exclusive partnership? What are the incentives and impediments for the partners?

If you can’t see the slides above, click here.

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The pressure was on. The other five teams were also furiously iterating and pivoting. The JointBuy team (the one that sent out 16,000 emails last week) realized that their low-fidelity website they used to test key concepts needed to get real to attract buyers and sellers in volume. The team pulled a week of all nighters and turned the wireframe prototype into a fully functioning site.

In almost every entrepreneurship class with a team project there’s a team that can’t figure out how to work together. These are the same problems one sees in real startups (disagreements over who controls the vision, team members not pulling their weight, disillusionment with the team direction, individuals uncomfortable in rapid decision making with less than perfect data, etc.) We give the students an escalation path if they’re having interpersonal problems (mentors – to Teaching Assistant – to Professors) to see if they can first worth through the issues without our intervention. While these are always painful we try to teach that they are part of the learning process. Better you encounter the problems in a classroom than after you raised a venture round.

At this point in the class almost all the teams are in a full sprint to the finish line. Next week, the last lecture. Then the final presentations.

While we’ve been pushing hard on the teams, this week the teaching team was about to get its socks blown off. All the teams were showing us what agile looked like, but this week several would remind us what focused and relentless really meant.

Week 6 of the class.
Last week the teams tested their hypotheses about Customer Relationships (how do they get, keep and grow customers.) This week they were testing their hypotheses about the sales “Channel” – how a company delivers its value proposition (i.e. its product or service) to its customers. There are two major channels: physical channels and virtual (web/mobile) channels. Physical channels include Direct Sales, Rep Firms, Systems Integrators, Value-added Resellers, Distributors, Dealers, Mass Merchandisers, and Original Equipment Manufacturers. Virtual channels include Dedicated e-commerce, Two-step e-distribution and Aggregators.

The Nine Teams Present
The first team up was Autonomow, the robotic mower farm weeder. They believed tthey would sell their robotic weeder to farm equipment dealers and distributors so they interviewed 9 more of them this week. They found that sales to this channel would require a demonstration, and that dealers would have to demo the robotic weeders to the customers. They learned that farmers expect personal and timely service/support. Relationships and trust are important.

Their week 6 business model now looked like this: 

All that we expected. But what they showed us next astonished all of us.

Last week we challenged the team that unless they developed hardware which could tell the difference between a weed and a plant, their business model would be just another set of PowerPoint slides. We expected that at best in the final 3 weeks of class they might build prototype hardware on a lab bench. Instead they built the prototype of an entire weeding robot – in one week. They called it the CarrotBot.

CarrotBot was their research platform to gather data for machine vision/machine learning. They wanted to test: can a machine tell the difference between a weed and a plant in the field? What about under different lighting and soil conditions? Could they train a machine to do this automatically?

The CarrotBot had a high-speed machine vision camera and a high-resolution camera for visual data as well as a panning LIDAR system for sub-millimeter depth measurement. Encoders on the drive motors and RTK-GPS measured precision position and velocity. After they validated the weed detection system, the next step was to arm the CarrotBot with a weed kill system (clove oil, high pressure steam/water, or lasers).

The Autonomow team worked 20-hour days, Wednesday – Monday. (On Wednesday night they got the idea to build a robot. On Thursday they ordered the parts, received them Friday, then built the robot over the next three days. (They got help from another student researcher in robotics and machine learning in the Stanford Artificial Intelligence Lab.)

Their goal is to deploy CarrotBot this week in the farm fields in Avenal, California, on the way to the World Ag Expo.

I’m sure the teaching team gave them some advice, but we were so busy trying to hide our jaws hitting the floor I can’t remember what it was..

If you can’t see the slides above, click here.

Next was D.C. Veritas, the team building a low cost residential wind turbine. This week the team got religion and decided that a major pivot was in order. They ditched the residential market as they realized that a more accessible and profitable customer segment(s) were cities, lighting companies and utilities.

In talking to customers, the team found that cities are actively trying to reduce street lighting costs (retrofitting with LEDs, turning off lights, and charging streetlight fees.) If they redesigned their the wind turbine,  it could be embedded into street and highway light poles. Not only could the turbine power the street lights, but it would make excess energy that could be sold back into the grid. Their value proposition had now changed from a wind turbine supplier to homes, to a distributed power supplier to cities and utilities.

Their channel was still direct sales, but now selling to cities allowed them to sell multiple turbines with a larger order size.

D.C. Veritas estimated that their new total available market was 13 million city street lights in the U.S., plus an unknown number of highway lights.

The feedback from the teaching team was that with a new customer segment identified the team was now in a race against time to provide a meaningful business model before the class ended.

If you can’t see the slides above, click here.

PersonalLibraries was focused on creating a reference management system for discovering, organizing and citing researchers’ readings. Last week the teaching team had suggested that they ought to “run away from the academic researcher market as fast as possible.” Yet like passionate entrepreneurs,  the team ignored our advice and pressed on. (To be fair, one of their team members had built the software and worked on it for awhile.)

This team spoke with 10 more customers and potential channel partners. They heard: “the academic market is terribly small, charging $1 a user for a high volume academic site license is unrealistic, the cost of reaching lab managers is prohibitive, despite poor economics there are many niche competitors, and academic software is a “dinosaur” business with lots of competitors in the space because they started there years ago and aren’t able to pivot out.”  Ouch!

With the evidence piling up, the team is now starting to think about pivoting to other customer segments and/or other pricing models. Should they create a freemium version of their current product?  Should they look at the Document Management market?

Time is running out for the PersonalLibraries team. Two more weeks of the class to go.  Take a look at their presentations and you decide – what should they do?

If you can’t see the slides above, click here.

The Agora Cloud Services team, (a marketplace for cloud computing) spent the week testing their channel hypotheses and further refined their business model canvas. They believed they were going to have inside sales reps, third party cloud computing consultants and their own web channel sales.

The team interviewed another 9 customers and industry experts and attended the Amazon Web Services meetup in San Francisco.

If you can’t see the slides above, click here.

The Week 6 Lecture: Revenue Model

This week’s lecture covered the Revenue Model including questions like these: How does your company make money? What are your customers going to pay for? What types of revenue streams are there? How does the web differ from other channels?

Our assignment for the teams for next week: What are the key financials metrics for your business model? If you have more than one product, how will you package it into various offerings?  How will you price the offerings? What is the customer lifetime value?  How are your competitors pricing? Each team has to test their pricing in front of 100 customers on the web or 10-15 customers non-web. And they had to assemble an income statement for the their business model.

If you can’t see the slide above, click here.

———

Most of the teams were doing great. A few were doing spectacularly well. One other team in the class, Jointbuy (an online platform allowing buyers to purchase products in bulk) turned in an equally extraordinary effort. When testing demand creation in their multi-sided business model, they couldn’t get enough sellers to their site. So they sent out mass emails to create demand. They certainly got noticed – as they had hijacked the Stanford email system to send 16,000 emails before they got shut down.

Much like startups in the real world, team performance in entrepreneurship classes seems to follow a Pareto distribution.

Two weeks to go. Let’s see how tenacity, sleepless nights, customer feedback and agile iteration change the final outcome.

Lots of entrepreneurs believe they want a mentor. In fact, they’re actually asking for a teacher or a coach. A mentor relationship is a two-way street. To make it work, you have to bring something to the party.

A Question from the Audience
Recently when I was at a conference taking questions from the audience, I got a question that I had never heard before. Someone asked, “How do I get you, or someone like you to become my mentor?” It made me pause (actually cringe.) As I gathered my thoughts, I realized that I’ve never thought much about the mentors I had, how I got them, and the difference between mentors, coaches and teachers.

Teachers
What I do today is teach. At Stanford and Berkeley, I have students, with classes and office hours. For the brief time in the quarter I have students in my class, at worst I impart knowledge to them. At best, I try to help my students to discover and acquire the knowledge themselves. I try to engage them to see the startup world as part of a larger pattern; the lifecycle of how companies are born, grow and die. I attempt to offer them both theory, as well as a methodology, about building early stage ventures. And finally, I have them experience all of this first hand by teaching them theory side-by-side with immersive hands-on using Customer Development to find a business model.

At times, the coffees, lunches and phone calls I have with current and past students are also a form of teaching. Most of the time students come with, “Here’s the problem I have. Can you help me?” Usually, I’ll give a direct answer, but sometimes my answer is a question.

In both cases, inside or outside the classroom, I consider those activities as teaching. At least for me, mentorship is something quite different.

Mentors
As an entrepreneur in my 20’s and 30’s, I was lucky to have four extraordinary mentors, each brilliant in his own field and each a decade or two older than me. Ben Wegbreit taught me how to think, Gordon Bell taught me what to think about, Rob Van Naarden taught me how to think about customers and Allen Michels showed me how to turn thinking into direct, immediate and outrageous action.

At this time in my life, I was the world’s biggest pain in the rear, lessons needed to be communicated by baseball bat, yet each one of these people not only put up with me, but also engaged me in a dialog of continual learning. Unlike coaching, there was no specific agenda or goal, but they saw I was competent and open to learning and they cared about me and my long-term development. I’m not sure it was a conscious effort on their part, (I know it wasn’t on mine,) but it continued for years, and in some cases (with my partner Ben Wegbreit) for decades. What is interesting in hindsight is that although the relationship continued for a long time, neither of us explicitly acknowledged it.

Now I realize that what made these relationships a mentorship is this: I was giving as good as I was getting. While I was learning from them – and their years of experience and expertise – what I was giving back to them was equally important. I was bringing fresh insights to their data. It wasn’t that I was just more up to date on the current technology, markets or trends, it was that I was able to recognize patterns and bring new perspectives to what these very smart people already knew. In hindsight, mentorship is a synergistic relationship.

Like every good student/teacher and mentor/mentee relationship, over time the student became the teacher, and this phase of relationship ends.

How Do I Find A Mentor
All this was running through my head as I tried to think of how to answer the question from the audience.

Finally I replied, “At least for me, becoming someone’s mentor means a two-way relationship. A mentorship is a back and forth dialog – it’s as much about giving as it is about getting. It’s a much higher-level conversation than just teaching. Think about what can we learn together?  How much are you going to bring to the relationship?”

If it’s not much, than what you really want/need is a teacher, not a mentor. If it’s a specific goal or skill you want to achieve, hire a coach, but if you’re prepared to give as good as you get, then look for a mentor.

But never ask. Offer to give.

Lessons Learned

• Teachers, coaches and mentors are each something different.
• If you want to learn a specific subject find a teacher.
• If you want to hone specific skills or reach an exact goal hire a coach.
• If you want to get smarter and better over your career find someone who cares about you enough to be a mentor.