But the total movie industry revenue was $87 billion. Where did the other $57 billion come from?

From sources that the studios at one time claimed would put them out of business: Pay-per view TV, cable and satellite channels, video rentals, DVD sales, online subscriptions and digital downloads.

The Movie Industry and Technology Progress
The music and movie business has been consistently wrong in its claims that new platforms and channels would be the end of its businesses. In each case, the new technology produced a new market far larger than the impact it had on the existing market.

• 1920’s – the record business complained about radio. The argument was because radio is free, you can’t compete with free. No one was ever going to buy music again.
• 1940’s – movie studios had to divest their distribution channel – they owned over 50% of the movie theaters in the U.S. “It’s all over,” complained the studios. In fact, the number of screens went from 17,000 in 1948 to 38,000 today.
• 1950’s – broadcast television was free; the threat was cable television. Studios argued that their free TV content couldn’t compete with paid.
• 1970’s – Video Cassette Recorders (VCR’s) were going to be the end of the movie business. The movie businesses and its lobbying arm MPAA fought it with “end of the world” hyperbole. The reality? After the VCR was introduced, studio revenues took off like a rocket.  With a new channel of distribution, home movie rentals surpassed movie theater tickets.
• 1998 – the MPAA got congress to pass the Digital Millennium Copyright Act (DMCA), making it illegal for you to make a digital copy of a DVD that you actually purchased.
• 2000 – Digital Video Recorders (DVR) like TiVo allowing consumer to skip commercials was going to be the end of the TV business. DVR’s reignite interest in TV.
• 2006 - broadcasters sued Cablevision (and lost) to prevent the launch of a cloud-based DVR to its customers.
• Today it’s the Internet that’s going to put the studios out of business. Sound familiar?

Technology Innovation
The movie industry was born with a single technical standard – 35mm film, and for decades had a single way to distribute its content – movie theaters (which until 1948 the studios owned.) It was 75 years until studios had to deal with technology changing their platform and distribution channel. And when it happened (cable, VCR’s, DVD’s, DVR’s, the Internet,) it was a relentless onslaught. The studios responded by trying to shut down the new technology and/or distribution channels through legislation and the courts.

Regulation/Legislation
But why does the movie business think their solution is in Washington and legislation?

History and success.

In the 1920’s individual states were beginning to censor movies and the federal government was threatening to do so as well. The studios set up their own self censorship and rating system keeping most sex and politics off the screen for 40 years. Never again wanting to be at the losing side of a political battle they created the movie industry’s lobbying arm, MPAA.

By the 1960’s, the MPPA achieved regulatory capture (where an industry co-opts the very people who are regulating it,) when they hired Jack Valenti, who ran the studios’ lobbying efforts for the next 38-years. Ironically, it was Valenti’s skill in hobbling competitive innovation that negated any need for studios to develop agility, vision and technology leadership.

Management of Innovation
The introduction of new technology is always disruptive to existing markets, particularly to content/copyright owners whose sell through well-established distribution channels. The incumbents tend to have short-sighted goals and often fail to recognize that more money can be made on new platforms and new distribution channels.

In an industry facing constant technology shifts the exec staff and boards of the studios have lawyers, MBAs and financial managers, but no management skill in dealing with disruption. So they rely on lobbying ($110 million a year,) lawsuits, campaign contributions (wonder why the President won’t be vetoing SOPA?) and Public Relations.

Ironically, the six major movie studios have a great technology lab in Silicon Valley with projects in streaming rights, Video On Demand, Ultraviolet, etc. But lacking the support from the studio CEOs or boards, the lab languishes in the backwaters of the studios’ strategy.  Instead of leading with new technology, the studios lead with litigation, legislation and lobbying. (Imagine if the $110 million/year spent on lobbying went to disruptive innovation.)

Piracy
One of the claims that studios make is that they need legislation to stop piracy. The fact is piracy is rampant in all forms of commerce. Video games and software have been targets since their inception. Grocery and retail stores euphemistically call it shrinkage. Credit card companies call it fraud.  But none use regulation as often as the movie studios to solve a business problem. And none are so willing to do collateral damage to other innovative industries (VCRs, DVRs, cloud storage and now the Internet itself.)

The studios don’t even pretend that this legislation benefits consumers. It’s all about protecting short-term profit.

SOPA
When lawyers, MBAs and financial managers run your industry and your lobbyists are ex-Senators, understanding technology and innovation is not one of your core capabilities.

The SOPA bill (and DNS blocking) is what happens when someone with the title of anti-piracy or copyright lawyer has greater clout than your head of new technology. SOPA gives corporations unprecedented power to censor almost any site on the Internet. It’s as if someone shoplifts in your store, SOPA allows the government to shut down your store.

History has shown that time and market forces provide equilibrium in balancing interests, whether the new technology is a video recorder, a personal computer, an MP3 player or now the Net. It’s prudent for courts and congress to exercise caution before restructuring liability theories for the purpose of addressing specific market abuses, despite their apparent present magnitude.

What the music and movie industry should be doing in Washington is promoting legislation to adapt copyright law to new technology — and then leading the transition to the new platforms.

The U.S. State Department has been championing the Internet Freedom initiative across the world. Secretary of State Clinton said, “…when ideas are blocked, information deleted, conversations stifled, and people constrained in their choices, the Internet is diminished for all of us.”

It’s too bad the head of the MPAA – an ex Senator - made a mockery of her words when he wondered “why our online censorship can’t be like China?”

We wonder, “Why can’t the film industry innovate like Silicon Valley?”

Lessons Learned

• Studios are run by financial managers who lack the skills to exploit disruptive innovation
• Studio anti-piracy/copyright lawyers trump their technologists
• Studios have no concern about collateral damage as long as it optimizes their revenue
• Studios $110M/year lobbying and political donations trump consumer objections
• Politicians votes will follow the money unless it will cost them an election

I was lucky enough to get interviewed by Rob Morris of American Entrepreneur Radio.

Ron Morris has a great “radio voice,” and actually seemed to understand what the heck I was talking about.  It made for a fun interview.

Click here to listen to the interview: Steve Blank American Entrepreneur Radio interview

The following week Ron Morris interviewed Regis McKenna, who for decades was the “gold standard” for high tech Public Relations in Silicon Valley. Click here to listen to the Regis interview.

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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

Steve Jobs

Watching an entrepreneur fail is sad, but watching them fail from a lack of nerve is tragic.

Excitement
At the beginning of this year Bob, one of my ex-students was in entrepreneurial heaven. He had an idea for a new class of enterprise software insight-as-a-service based on big data web analytics as a Cloud/SaaS (Software As a Service) application.

Bob had taken to heart the business model canvas and Customer Development lessons. After graduating he put together a prototype and had quickly marched through Customer Discovery, iterating his product with the help of CIOs and Fortune 1000 IT departments.

I had made one of the introductions to a Fortune 100 CIO’s so I got to hear his progress from both him and the CIO.

Takeoff
After 90 days, things seemed to be moving at startup speed. Bob had a backlog of users wanting to try his application, and the corporate IT people who were trying his early prototype said, “It’s crude, we hate the user interface, it’s missing lots of features – but we’ll kill you if you try to take it away from us.”

I pointed a VC who followed the space to the CIO who was testing the prototype. The VC told me the CIO wouldn’t get off the phone. He kept telling him he couldn’t remember when he had seen an enterprise software product with so much promise. The VC checked with other IT users and heard the same reaction. It was a “gotta use it, don’t take it away, we’ll have to buy it” product. After a demo and lunch, the VC (who normally did later stage deals) wrote my ex student a check for a seed round.

Life couldn’t be better.

I followed Bob progress in bits and pieces from updates from the CIO, the VC and his emails and blogs. He seemed to be on the fast track to startup success. But pretty soon a few worrying warning signs appeared.

The first thing that I noticed was that Bob couldn’t seem to find a co-founder. I wasn’t close enough to know if he wasn’t really looking for one, but given the early success he was having, it seemed a bit odd. But the next thing really got me concerned. Bob started hiring second rate developers. At best they were B- players.

Stall
A month went by, and the product stopped getting better. The U/I still sucked, and new features had stopped appearing. The next month, the same thing. I got a call from my CIO friend asking, “what was going on?” He said, “It was a great prototype, we would have loved to deploy it company-wide, and I hate to let it go, but it looks like Bob company just lost interest in developing it. I’m going to dump it and look for a substitute.” So I called Bob and suggested we grab a coffee.

I asked him how things were going and got the update on how the earlyvangelists were using the product. As I had heard, they were ecstatic. But Bob said he was worried he hadn’t found the right customer segment yet. “I’m not sure I can get all of these guys to pay me big bucks,” he said. “That’s why I stopped coding, and I’m spending all my time out in the field still talking to more customers.” “What does your VC’s say you ought to be doing?” I asked.  “Oh, he hasn’t had much time for me, his firm almost never does seed deals. It turns out I was an exception.”  Oh, oh.

The conversation was starting to make the hair on the back of my neck stand up. Bob had gotten to a place most founders never do – his product was a “gotta have it for people with big budgets.” He should have been back rapidly coding, iterating and finding out what feature set would get him to paying customers.

Instead he had produced barely 3 weeks of progress in the last 5 months. His prototype was rapidly wearing out its welcome.

A Lack of Nerve
When I pressed Bob on this he admitted, “No I guess my engineers aren’t very good. But I hired guys who were cheap because I wasn’t sure if my hypotheses were right. Didn’t you tell us to test our hypotheses first?” Now it was my time to be surprised. “Bob, you’ve validated your hypotheses better than any startup I’ve ever seen. You found that out in the first month. You got customers begging you to finish the product so they could buy it. You should have been hiring world-class talent and building something these CIO’s will pay for. It’s not too late. It’s time to grab them by the throat and go for it.”

I wasn’t ready for the answer, “Steve, I’ve been reading all about premature scaling and making sure everything is right before I go for it. I want to be sure I get all of this right. I’m afraid I’ll run out of money.”

I thought I’d make one more run at it. “Bob,” I said, “few entrepreneurs get the first time response you have from an early product. At your rate you’re going to burn through your cash trying to get it perfect. It’s a startup. You’ll never have perfect information. You’re sitting on a gold mine. Grab the opportunity!”

I got a blank stare.

We made some more small talk and shook hands as he left.

Bob was in the wrong business, not the wrong market. He wanted certainty, comfort and security.

I stared at my coffee for a long time.

Carpe Diem – make your lives extraordinary.

Lessons Learned

• Yes, premature scaling is a cause of startup death
• Yes, you need to get out of the building and test your hypotheses
• But, when an opportunity smacks you in the head for gosh sake grab it with both hands and don’t let go
• If you can’t, get out of the startup game

George Bernard Shaw

We’re in the middle of our National Science Foundation Innovation Corps class – taking the most promising research projects in American university laboratories and teaching these scientists the basics of entrepreneurship. Our goal is to accelerate the commercialization of their inventions. Our Lean LaunchPad class teaches scientists and engineers that starting a company is another research project that can be solved by an iterative process of hypotheses testing and experimentation built around the business model / customer development / agile development solution stack. It’s “the scientific method” applied to startups.

Although I typically don’t write about a class while it’s going on, I had to share this extraordinary reflection that Satish Kandlikar, one of the National Science Foundation principal investigators, posted to our Lean LaunchPad class blog.

Satish Kandlikar – The Spirit of Entrepreneurship
Satish Kandlikar has been a professor in the mechanical engineering department at the Rochester Institute of Technology for the past twenty-one years. His research is focused in the areas of flow boiling, critical heat flux, contact line heat transfer, and advanced cooling techniques

His team, Akara Lighting, wants to build a device for LED lights that gets rid of heat 50% better than anything on the market. This would result in LED’s having a higher performance at a reduced cost.

Here’s what he had to say about his experience in the Lean LaunchPad class ….

“It is quite an eye-opening experience to transition from an academic “PI” (Principal Investigator) to someone who wants to run a technology start-up. The change in the mindset is perhaps the important factor on the path to success…

The teaching team is simply phenomenal in identifying the pitfalls in our path and guiding us in finding the solutions. They have shown us the other side of the equation from technology to market acceptability. We have been extremely fortunate in having this kind of guidance and support.

A key finding I would like to report is that we just had another “pivot” two days ago when our mentor brought to our attention that we can succeed as a heat pipe company providing thermal solutions to various LED products as well as other applications. I visited two companies, one providing data center cooling solutions, and other providing control panel cooling systems. Key alliances are expected to occur through these initial, very positive, contacts.

One fundamental change that I see in my approach going forward is that I am looking at the research in a totally different way. It is no longer, in my mind, a means to publishing papers and simply graduating students. It means now, to me, how the research can be applied to make products that are accepted in marketplace. Making students understand the entire process, to whatever extent I can influence them, and inspiring them to aspire for transferring their knowledge to products is becoming an important thrust in my classroom interactions.

Another eye-opener was on understanding communications. While making presentations in academic setting, it was more of a paper-based research with extension of knowledge, without too much understanding of its application. Knowing the audience was really not a factor. Now after making “cold-calls”, and seeing that there is a certain way to get them interested in just a few opening sentences, was simply amazing. Knowing what their needs are is a crucial step.

Now it is becoming clear what Steve meant when he said, “get out of the building”. It is clear that the building referred to our mindset more than the physical act of going out or simply contacting someone outside.

The purpose of this posting was to document my beginning of the transformation process from an academician to an entrepreneur. And I am definitely enjoying it.”

Scientists Unleashed
Over fifty years ago Silicon Valley was born in an era of applied experimentation driven by scientists and engineers. Fifty years from now, we’ll look back to this current decade as the beginning of another revolution, where scientific discoveries and technological breakthroughs were integrated into the fabric of society faster than they had ever been before, unleashing a new era for a new American economy built on entrepreneurship and innovation.

And scientists like Satish Kandlikar and the National Science Foundation will lead the way.

Mark Twain

Venture Capitalists who are serious about turning their firms into more than one-fund wonders may want to have their associates actually start and run a company for a year.  Running a company is distinctly different from simply having operating experience – (working in bus dev, sales or marketing.) None of that can compare with being the CEO of a startup facing a rapidly diminishing bank account, your best engineer quitting, working until 10pm and rushing to the airport and catching a redeye for a “Hail Mary” close of a customer, with your board demanding you do it faster.

Venture capital as a profession is less than half a century old.

Over time Venture firms realized that the partners in the firms needs a variety of skills:

• People skills (ability to recognize patterns of success in individuals and teams)
• People skills
• People skills
• Market/technology acuity (patterns of success, domain expertise)
• Rolodex/deal flow (deal sourcing/ability to make connections for the portfolio)
• Board skills (Startup coaching, mentoring, strategy, operational/growth)
• Fund raising skills

Some of these skills are learned in school (finance), some are innate aptitudes (people skills), some are learned pattern recognition skills (shadowing experienced partners, hard won success and failures of their own), and some are learned by having operating experience. But none of them are substitutes for having started and run a company.

How to Become a VC
Early-stage Venture Capital firms grow their partnerships in different ways, some hire:

• partners from other firms
• associates and put them on a long career path
• venture/operating partners to get them into new industries
• an executive who had startup “operating experience”
• rarely a startup founder/CEO

In surveying my VC friends, I was surprised about the strong and diverse opinions. The feedback varied from:

• “.. because culture is such an important part of who we are, we will probably never hire a partner from another firm. The idea of bolting on someone from another firm is somewhat antithetical to who we are. We think that our venture partner role is the most likely path to general partner.”
• ..we have a partner-track associates program.  We want to find someone who has a lot of consumer internet product experience as either product manager, founder, VP Product, etc. with 3-7 years of experience.”
• “…we do not even try to train new partners. We bring people into our firm who have learned how to be VCs at the partner level somewhere else and have demonstrated their talent in boardrooms alongside of us. We completely and totally punt on the idea of “training a VC.”  It’s an ugly and painful process and I don’t want to be part of it.”
• “…if they don’t have operating experience  the odds of them knowing what they’re talking about in a board meeting for the first five years is low..”

Carrying the Cat By The Tail
When I finally became a CEO it was after I had spent my career working my way up the ladder in marketing in startups. I did every low-level job there was, at times sleeping under my desk (engineering was doing the same.) By the time I was running a company, having some junior employee tell me why they couldn’t do something because of “how hard it was” didn’t get much sympathy from me. I knew how hard it was because I had done it myself. Startups are hard.

What running a company would do is give early-stage VC’s a benchmark for reality, something most newly-minted partners sorely lack. They would learn how a founding CEO turns their money into a company which becomes a learning, execution and delivery engine. They would learn that a CEO does it through the people – the day-to-day of who is going to do what, how you hold people accountable, how teams communicate, and more importantly, who you hire, how you motivate and get people to accomplish the seemingly impossible. Further, they’d experience first hand how, in a startup, the devil is in the details of execution and deliverables.

My hypotheses is simple:  what most VC’s lack is not brains or rolodex or people skills – but hands-on experience as a startup CEO – knowing what it’s like trying to make a payroll while finding sufficient customers while you’re building the product.  Sure, a year as a CEO won’t make them an expert, but it will change them quicker than 10 years in the boardroom.

Does it Matter?
There’s a school of thought that says the skill set of a great early-stage VC – awesome people skills, curiosity, likable, etc. – versus the attributes of a great entrepreneur – pattern recognition, tenacity, etc. may not have much overlap. Early stage investing is not a spreadheet, quantitative driven exercise, nor is it about technology – it is a deal business and people drive the deals. And while having experience as a startup CEO may make you a better board member, it may not substantively contribute to your career as an early stage investor – which depend on many more important skills.

Steel in their eyes

Ten years ago starting a company required millions of dollars and first customer ship took years. Now it’s possible to build a company, ship product and get tens of thousands of customers in a year with less than $500K. For venture firms who want to groom/grow associates or operating execs into partners (rather than hiring proven partners), here’s my suggestion:

1. Have them start as an analyst (search for deal flow and people, due diligence)
2. Then take a year as a product manager in a startup in the firm’s portfolio
3. Then come back as an associate for a year – shadowing board and partner meetings
4. Then take a year and $250-500K to start and run a mobile/web/cloud company. See what it’s really like on the other side of that boardroom table
5. Then return as a partner

This process will create a new generation of venture capital partners, ones who have been battle tested in the trenches of a startup, hardened by hiring and firing, tempered by making a payroll and losing orders, and will never forget it’s all about the people.

These VC’s would return to their firms with steel in their eyes. They’d be relentless about accountability from board meeting to board meeting with laser like focus on the one or two issues that matter. They would understand the CEO-VC-board dynamic in a way that few who hadn’t lived it could. They’d be ruthless in their choice of people and teams, looking for those few who have natural curiosity, a passion to win, and who won’t take no for answer.

Lessons Learned

• Venture Capital is still a “craft business”
• Early stage VC’s should have startup CEO experience
• It can now be gained cheaply and quickly
• It will give them perspective and edge that would take a decade to learn 

By the early 1920’s General Motors realized that Ford, which was now selling the Model T for $290, had an unbeatable monopoly on low-cost automobile manufacturing. Other manufacturers had experimented with selling cars based on an image and brand. (The most notable was an ad by the Jordan Car company.) But General Motors was about to take consumer marketing of cars to an entirely new level.

Market Segmentation General Motors had turned the independent car companies acquired by its founder Billy Durant into product divisions. But in a stroke of genius GM transformed these divisions into a weapon that Ford couldn’t match. With the rallying cry “a car for every purse and purpose,” GM positioned its car divisions (Chevrolet, Pontiac, Oldsmobile, Buick and Cadillac) so they would cover five price segments – from low-price to luxury. It targeted each of its brands (and models inside those brands) to a distinct economic segment of the population. Chevy was directly aimed at Ford – the volume car for the working masses. Pontiac came next, then Oldsmobile, then Buick. The top-of- the-line Cadillac offered luxury and prestige announcing you had finally arrived at the top of the conspicuous consumption heap. Consumers could announce their status and lives had improved by upgrading their brands.

GM had one more trick to make this happen. Within each brand, the top of the line was just a bit less expensive than the lowest priced model of the next expensive brand. The goal was to convince the consumer to spend a little more to trade up to a more prestigious brand.

Market segmentation by price was something no other automotive manufacturer had ever done. While other car companies could compete with one of GM’s divisions, few had GM’s capital and resources to compete simultaneously with the onslaught of car models from all five divisions.

Planned Obsolescence While market segmentation allowed GM to use its divisions to reach a wider market than Ford or Chrysler, this didn’t solve the problem of market saturation. By the late 1920’s, most everyone in the U.S. had a car. And cars lasted 6 to 8 years. Even worse, the market was now filled with used cars that provided even lower cost basic transportation. Sloan, the General Motors CEO, faced two seemingly unsolvable challenges:

• How do you get consumers to abandon their perfectly fine cars and buy a new one?
• How do you turn a product that competed on price and features into a need?

In another stroke of genius, GM invented the annual model change. Sloan borrowed this idea from fashion where styles changed every year and applied it to automobiles starting in the 1920s. General Motors would change the external appearance of cars every year. Sloan preferred to call it “dynamic obsolescence.”

Styling and design became an integral part of GM’s strategy. Sloan hired Harley Earl to set up GM’s in-house styling staff. Earl would run it from 1927 to 1958.

Before Earl, cars were designed by in-house body-engineers who focused on practical issues like function, costs, features, etc. Each exterior component was designed separately to be functional – radiator, bumpers, hood, passenger compartment, etc. Some companies used 3^rd party bodymakers to set the style , but GM was the first to take car design away from the engineers and give it to the stylists.

The concept of yearly “improvements”, whether styling or incremental technology improvements, every model year gave GM an unbeatable edge in the market. (Henry Ford hated the idea. He had built Ford on economies of scale – the Ford Model T lasted for 19 years.) Smaller car makers could not afford the constant engineering and styling changes they had to make to keep competitive. GM would shut down all their manufacturing plants for a few months and literally rip out the tooling, jigs and dies in every plant and replace them with the equipment needed to make the next year’s model.

GM had figured out how to take a product which solved a problem – cheap transportation – and transform it into a need. It was marketing magic that wasn’t to be equaled until the next century.

By the mid-1950′s every other car company was struggling to keep up.

Mass Marketing Starting in the 1920’s and continuing for the next half century, automobile advertising hit its stride. Ads emphasized brand identification and appealed to consumers’ hunger for prestige and status. Advertising agencies created catchy slogans and jingles, and celebrities endorsed their favorite brands. General Motors turned market segmentation and the annual model year changeovers into national events. As the press speculated about new features, the company’s added to the mystique by guarding the new designs with military secrecy. Consumers counted the days until the new models were “unveiled” at their dealers.

Results
For fifty years, until the Japanese imports of the 1970’s, Americans talked about the brand and model year of your car – was it a ’58 Chevy, ’65 Mustang, or 58 Eldorado?  Each had its particular cachet, status and admirers. People had heated arguments about who made the best brand.

The car had become part of your personal identity while it became a symbol of 20^th Century America.

After Sloan took over General Motors its share of U.S cars sold skyrocketed from 12 per cent in 1920, until it passed Ford in 1930, and when Sloan retired as GM’s CEO in 1956 half the cars sold in the U.S. were made by GM. It would keep that 50% share for another 10 years. (Today GM’s share of cars total sold in the U.S. has declined to 19%.)

How the iPhone Got Tail Fins
Over the last five years Apple has adopted the GM playbook from the 1920′s – take a product, which originally solved a problem – cheap communication – and turn it into a need.

In doing so Apple did to Nokia and RIM what General Motors did to Ford. In both cases, innovation in marketing completely negated these firms’ strengths in reducing costs. The iPhone transformed the cell phone  from a device for cheap communication into a touchstone about the user’s image. Just like cars in the 20th century, the iPhone connected with its customers emotionally and viscerally as it became a symbol of who you are.

—-

The desire to line up to buy the newest iPhone when your old one works just fine was just one more part of Steve Jobs’ genius – it’s how the iPhone got tail fins.

It’s one more reason why Steve Jobs will be remembered as the 21st century version of Alfred P. Sloan.

They opened retail outlets across the country and figured out how to convince consumers to flock to buy the newest “gotta have it” version and abandon the perfectly functional last year’s model.

No, it’s not Apple and the iPhone.

It was General Motors and the auto industry.

In the Beginning
At the beginning of the 20^th century the auto industry was still a small hand-crafted manufacturing business. Cars were assembled from outsourced components by crews of skilled mechanics and unskilled helpers. They were sold at high prices and profits through nonexclusive distributors for cash on delivery. But by 1901, Ransom Olds invented the basic concept of the assembly line and in the next decade was quickly followed by other innovators who opened large scale manufacturing plants in Detroit – Henry Packard, Henry Leland’s Cadillac, and Henry Ford with the Model A.

The Detroit area quickly became the place to be if you were making cars, parts for cars, or were a skilled machinist. By 1913 Ford’s first conveyor belt-driven moving assembly line and standardized interchangeable parts forever cemented Detroit as the home of 20^th century auto manufacturing.

Feature Wars
The automobile industry was founded and run by technologists: Henry Ford, James Packard, Charles Kettering, Henry Leland, the Dodge Brothers, Ransom Olds. The first twenty-five years of the century were a blur of technology innovation – moving assembly line, steel bodies, quick dry paint, electric starters, etc. These men built a product that solved a problem – private transportation first for the elite, and then (Ford’s inspiration) – transportation for the masses.

Market Saturation
Ford tried to escape the never-ending technology feature wars by becoming the low cost manufacturer. Fords River Rouge manufacturing complex – 93 buildings in a 1 by 1.5 mile manufacturing complex, with 100,000 workers – vertically integrated and optimized mass production.

By 1923, through a series of continuous process improvements, Ford had used the cost advantages of economies of scale to drive down the price of the Model T automobile to $290.

When the 1920’s began there were close to a 100 car manufacturers, but the relentless drive for low cost production forced most of them out of business as they lacked capital to scale. For a brief moment, half the cars in the world were now Fords. To make matters worse, the long service life of Ford and GM cars (8 years for Fords Model T, 6 years for everyone else) retarded sales of new cars. In 20 years, U.S. car ownership had risen from 0 to 80% of American families – the market was approaching saturation.

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.

But for the rest of us mortals whose eyes glaze over at the buzzwords, the questions are, “How do I get my great idea on the web? What are the steps in building a web site?”  And the most important question is, “How do I use the business model canvas and Customer Development to test whether this is a real business?”

My first attempt at helping students answer these questions was by putting together the Startup Tools Page - a compilation of available web development tools. While it was a handy reference, it still didn’t help the novice.

So today, I offer my next attempt.

How To Build a Web Startup – The Lean LaunchPad Edition

Here’s the step-by-step process we suggest our students use in our Lean LaunchPad classes.

1. Set up the logistics to manage your team
2. Craft company hypotheses
3. Write a value proposition statement that other people understand
4. Set up the Website Logistics
5. Build a “low-fidelity” web site
6. Get customers to the site
7. Add the backend code to make the site work
8. Test the “problem” with customer data
9. Test the “solution” by building the “high-fidelity” website
10. Ask for money

(Use the Startup Tools Page as the resource for tool choices)

Step 1: Set Up Team Logistics

• Read Business Model Generation pages 1-72, and The Four Steps to the Epiphany Chapter 3
• Set up the Lean LaunchLab or a WordPress blog to document your Customer Development progress
• Use Skype or Google+ Hangouts for team conversations

Step 2. Craft Your Company Hypotheses (use the Lean LaunchLab)

• Write down your 9-business model canvas hypothesis
• List key features/Minimal Viable product plan
• Size the market opportunity. Use Google Trends, Google Insights, and Facebook ads to evaluate the market growth potential. Use Crunchbase to look at competitors.
• Calculate Total Available Market, and customer value.
• Pick market type (existing, new, resegmented)
• Prepare weekly 7-minute class progress summary: business model canvas update + weekly Customer Development summary (described after Step 10.)

• If you can’t easily explain why you exist, none of the subsequent steps matter.  A good format is “We help X do Y by doing Z”.
• Once you have a statement in that format, find a few other people (doesn’t matter if they’re your target market) and ask them if it makes sense.
• If not, give them a longer explanation and ask them to summarize that back to you.  Other people are often better than you at crafting an understandable value proposition.

Step 4: Website Logistics

• Get a domain name for your company. To find an available domain quickly, try Domize or Domainr
• Then use godaddy or namecheap to register the name. (RetailMeNot usually has ~ $8/year discount coupons for Godaddy You may want to register many different domains (different possible brand names, or different misspellings and variations of a brand name.)
• Once you have a domain, set up Google Apps on that domain (for free!) to host your company name, email, calendar, etc

 For coders: set up a web host

• Use virtual private servers (VPS) like Slicehost or Linode (cheapest plans ~$20/month, and you can run multiple apps and websites)
• You can install Apache or Nginx with virtual hosting, and run several sites plus other various tools of your choice (assuming you have the technical skills of course) like a MySQL database
• If you are actually coding a real app, (rather than for class) use a “Platform As A Service” (PAAS) like Heroku, DotCloud or Amazon Web Services if your app development stack fits their offerings
• BTW: You can see the hosting choices of YCombinator startups here

Customer Discovery for the Web

Step 5: Build a Low-Fidelity Web Site

• Depending on your product, this may be as simple as a splash page with: your value proposition, benefits summary, and a call-to-action to learn more, answer a short survey, or pre-order.)
• For surveys and pre-order forms, Wufoo and Google Forms can easily be embedded within your site with minimal coding.

 For non-coders:

• Make a quick prototype in PowerPoint, or
• Use Unbounce, Google Sites, Weebly, Godaddy, WordPress or Yola
• For surveys and pre-order forms, Wufoo and Google Forms can easily be embedded within your site with minimal coding.
• Even non-coders should understand the coding buzzwords see here

For coders: build the User Interface

• Pick a website wireframe prototyping tool, (i.e. JustinMind, Balsamiq)
• 99 Designs is great to get “good enough” graphic design and web design work for very cheap using a contest format. Themeforest has great designs
• Create wireframes and simulate your “Low Fidelity” website
• Create a fake sign up/order form to test customer commitment.  Alternatively, create a “viral” landing page, with LaunchRock  or KickoffLabs
• Embed a slideshow on your site with Slideshare or embed a video/tour using Youtube or Vimeo
• Do user interface testing with Usertesting or Userfy

Step 6: Customer Engagement (drive traffic to your preliminary website)

• Start showing the site to potential customers, testing customer segment and value proposition
• Use Ads, textlinks or Google AdWords, Facebook ads and natural search to drive people to your Minimally Viable web site
• Use your network to find target customers – ask your contacts, “Do you know someone with problem X? If so, can you forward this message on to them?” and provide a 2-3 sentence description
• For B2B products, Twitter, Quora, and industry mailing lists are a good place to find target customers. Don’t spam these areas, but if you’re already an active participant you can sprinkle in some references to your site or you can ask a contact who is already an active participant to do outreach for you.
• Use Mailchimp, Postmark or Google Groups to send out emails and create groups
• Create online surveys with Wufoo or Zoomerang
• Get feedback on your Minimum Viable Product (MVP) features and User Interface

Step 7: Build a more complete solution (Connect the User Interface to code)

• Connect the UI to a web application framework (for example, Node.js, Rubyon Rails, Django, SproutCore, jQuery, Symfony, Sencha, etc.)

Step 8: Test the “Customer Problem” by collecting Customer Data

• Use Web Analytics to track hits, time on site, source.  For your initial site, Google Analytics provides adequate information with the fastest setup.  Once you’ve moved beyond your initial MVP, you’ll want to consider a more advanced analytic platform (Kissmetrics, Mixpanel, Kontagent, etc)
• Create an account to measure user satisfaction (GetSatisfaction, UserVoice, etc.) from your product and get feedback and suggestions on new features
• Specific questions, such as “Is there anything preventing you from signing up?” or “What else would you need to know to consider this solution?” tend to yield richer customer feedback than generic feedback requests.
• If possible, collect email addresses so that you have a way to contact individuals for more in-depth conversations.

• Update the Website with information learned in Step 5-8
• Remember that “High Fidelity” still does not mean “complete product”. You need to look professional and credible, while building the smallest possible product in order to continue to validate.
• Keep collecting customer analytics
• Hearing “This is great, but when are you going to add X?” is your goal!

Step 10: Ask for money

• Put a “pre-order” form in place (collecting billing information) even before you’re ready to collect money or have a full product.
• When you’re ready to start charging – which is probably earlier than you think – find a billing provider such as Recurly, Chargify, or PayPal to collect fees and subscriptions.

For all Steps: Monitor and record changes week by week using the Lean LaunchLab

For Class: Use the Lean LaunchLab to produce a 7-minute weekly progress presentation

• Start by putting up your business model canvas
• Changes from the prior week should be highlighted in red
• Lessons Learned.  This informs the group of what you learned and changed week by week – Slides should describe:

1. Here’s what we thought (going into the week)
2. Here’s what we found (Customer Discovery during the week)
3. Here’s what we’re going to do (for next week)
4. Emphasis should be on the discovery done for that weeks assigned canvas component (channel, customer, revenue model) but include other things you learned about the business model.

———

If you’re Building a Company Rather Than a Class Project

• Go through the legal steps of setting up a company. U.S. version here.
• Search the US Patent Office (for free) for similar trademarks to yours
• When you confirmed your product and identity, and obtained a good domain name, and a trademark you think you can own, register your company on Twitter, Facebook, LinkedIn, CrunchBase, and AngelList pages
•  Incorporate the company

———

Thanks for the comments, suggestions, corrections, and additions. Updates added.

——-

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.

Three months ago I wrote about my ex-student Max Marmer and the Startup Genome Project. They’ve been attempting to quantify the art. They believe that they can crack the code of innovation and turn entrepreneurship into a science if they had hard data rather than speculation of why startups succeed or fail. Max and his partners had interviewed and analyzed over 650 early-stage Internet startups. In May they released the first Startup Genome Report— an in-depth analysis on what makes early-stage Internet startups successful.

Now 90 days later Max and his team have gathered data on 3200 startups and they believe they’ve discovered the most common reason startups fail.

Today you’re invited to benchmark your own internet startup and see how you compare to the winners.

———

Benchmarking Your Startup
I hadn’t heard from Max for awhile so I thought he took the summer off. I should have known better, it turned out he was hard at work.

Max and his team built a website called the Startup Genome Compass (their benchmarking web site) that allows an Internet startup to evaluate their business performance. The Startup Genome Compass uses a hybrid “Stage and Type” model that describes how startups progress through their business development lifecycle.

The benchmark takes 20 or so minutes to go through as series of questions, and in the end it spits out an analysis of how you are doing.

The benchmark is not perfect, it may even be flawed, but it is head and shoulders above what we have now – which is nothing – for giving Internet startups founders specific advice on best practices.  If you have a few world-class VC’s on your board you’re probably getting this advice in person. If you’re like thousands of other startups struggling to get started, it’s worth a look.

It’s Not How Big It Is – It’s How Well It Performs
If you’re interested (and you should be) in how you compare to other early stage ventures, they summarized their results in a report “Startup Genome Report Extra: Premature Scaling.”

One of the biggest surprises is that success isn’t about size – of team or funding. It turns out Premature Scaling is the leading cause of hemorrhaging cash in a startup – and death. In fact:

• The team size of startups that scale prematurely is 3 times bigger than the consistent startups at the same stage
• 74% of high growth Internet startups fail due to premature scaling
• Startups that scale properly grow about 20 times faster than startups that scale prematurely
• 93% of startups that scale prematurely never break the $100k revenue per month threshold

The last time I wrote about Max I said, “I can’t wait to see what Max does by the time he’s 21.” Turns out his birthday is in a week, September 7th.

Happy birthday Max.

I had them leave with a pie chart.

There must be something in the air. In the last week I had four separate groups through the ranch all wanting to talk either about hiring a senior exec or a senior exec looking for a new job. Having sat through these job discussions as an entrepreneur, board member, and now an interested observer, here’s what I concluded:

1. Decide whether you’re hiring someone to help search for the business model or to help execute a business model you’ve already found (same is true is you’re looking for a job – are you going to be searching or executing?) Are you looking for a visionary or an operating executive?
2. The job spec’s for the same title differ wildly depending on whether the job requires search versus execution skills. Founders search, operating executives execute.

If you’re hiring an operating executive (CEO, VP, Executive Director, etc.)

• Don’t start with the candidate (board member x has a great VP of sales he knows, founder y wants this CEO he met at a conference, etc.)
• Don’t even start with the job spec

Since I’ve always been a visual guy, job specs with their long lists of job requirements always left me cold. My eyes would glaze over at these recruiter/board wish lists. I wished there was a way to see them at a glance. (Just to be clear this isn’t the entire hiring process, just a way to visually begin the discussion.) So here’s my suggestion: Start with a Pie Chart.

1. Draw a pie chart.
2. List all the job specs as slices
3. Adjust the width of the pie segments by importance. (Extra credit if you get the current CEO or internal candidate to help you write/draw the slices and weight their importance. Everyone involved in the hire gets to have an opinion on the slices and weights, but the person/group making the hiring decision gets to decide which ones to include.)
4. Now that you have this spec, evaluate each candidate by showing his/her competence in each slice by length
   
5. Compare candidates
   
6. Easy as pie!

Lessons Learned

• Are you hiring for search or execution skills?
• Show the job requirements visually as a pie chart
• Prioritize each requirement by the width of the pie
• Show your assessment of each candidate’s competencies by the length of the slices
• Now with the data in front of you, the conversation about hiring can start

Thanks to Denis Dovgopoliy for making the Russian version happen.

It joins the French version: Les quatre étapes vers l’épiphanie

and the Japanese version アントレプレナーの教科書 [単行本（ソフトカバー）

Now in Japanese

Pay It Forward
What’s pretty remarkable is these translations are not from a commercial publisher, but rather a labor of entrepreneurial love. All these translations have been crowd-sourced.

Entrepreneurs from Japan, France and now Russia believed they could help startups in their country if the Four Steps to the Epiphany was available in their native tongue. They translated it at their own expense. These are the first three translations and more are underway.

These individuals are “paying it forward” for their communities and country’s. Thousands of entrepreneurs are better for their efforts.

Blame it On Eric
We can blame it all on Eric Ries. When Eric was my student in one of the first Berkeley Customer Development classes, he suggested that I take my class notes, which until then had been printed at Cafepress.com, and offer it widely on Amazon. He said, “I bet there are a few people outside the class who might like to read it.” I photoshopped a cover for my notes, called it the Four Steps to the Epiphany, and bet him he was wrong.  He won the bet.

What A Long Strange Trip It’s Been
I was going to end this post here, but it’s late at night at the ranch and the coyotes are howling in the distance and somewhere closer, out in the redwoods, there’s a barn owl hooting in the trees.

Seeing this book in Russian for me is more than just another translation.

As a child, my mother fled the Soviet Union smuggled out in a hay cart in the middle of Russian Civil war. Until she died, she reminded me that on the way to Ellis Island, her first view of the United States was the Statue of Liberty in New York harbor - and she never looked back. (As kids we memorized the poem inside the statue.)

When I was growing up the odds were pretty low that the Cold War war would end with a whimper rather than a bang. Both the U.S. and the Soviet Union trained daily to kill hundreds of millions of people. Entrepreneurship was a crime in the Soviet Union. In the 1970′s the Soviet military was on the ascendency and wasn’t at all clear that the 20th century would end as the American century (or with 15,000 targeted nuclear warheads, anyones century.)

I spent my late teens here and my early 20′s here next to the sharp end of the spear, and this was no videogame. (There’s equal part irony and satisfaction that Silicon Valley and semiconductor fabs had a role in the demise of the Soviet Union.)

When the Cold War ended I waited for the victory parade down Main Street.

We never did have a parade, but as a consolation prize there’s now a McDonalds in Red Square, entrepreneurship is trying to blossom in a place that had 60 U.S. nuclear weapons aimed at it, my book (a revolutionary manual for capitalism,) is in Russian, and I’ve been asked to give my Secret History of Silicon Valley talk when I visit Moscow for the first time in September.

Good enough.

One of the key distinctions between an entrepreneur and an operating executive is an entrepreneur’s almost seamless agility in the face of changing circumstances versus an operating executive’s intense execution focus on a plan. World-class entrepreneurs learn how to combine both.

WTF?
Driving home over the mountains from a Coastal Commission hearing, I had time to ponder an email I received from a city official as the road wound through the Redwood trees. The Coastal Commission had found that a zoning change his city requested didn’t conform to the Coastal Act, and we denied it. I felt sorry for him because he had put together a project that depended upon the property owner, developer, unions, hotel operator, local neighbors, city council, weather, wind speed, phase of the moon and astrological sign all aligning just to get the project in front of us. It was like herding cats and pushing water uphill. Reading his email I was sympathetic realizing that if you substituted customers, channel, product development, hiring, board of directors, and fund raising, he was describing a typical day at a startup. I felt real kinship until I got to his last sentence:

“Now we’re screwed because we had no Plan B.”

Say what?

I had to read his email a few times to let this sink in. I kept thinking, “What do you mean there’s no plan B?” When I shared it with the other commissioners who were public officials, all of them could see that there could have been tons of alternate plans to get a project approved, and there were still several options going forward.  But the mayor just had been so intently focussed on executing a complex Plan A he never considered that he might need a Plan B.

By the time the mountain road unwound into rolling pastures and then flattened into the farmland just south of Silicon Valley, I realized that this was a real-world example of the difference between an entrepreneur and an operating executive.

There’s Always a Plan B
My formal definition of a startup is a temporary organization in search of a scalable and repeatable business model. Yet if you’ve founded a company you know that regardless of any formal definition, startups are inherently pure chaos. As a founder, keeping your company alive requires you to think creatively and independently because more often than not, conditions on the ground will change so rapidly that any original well-thought-out plan quickly becomes irrelevant. (It’s equally true for startups, war, love and life.)

The reality is that to survive requires a mindset which can quickly separate the crucial from the irrelevant, synthesize the output, and use this intelligence to create islands of order in the all-out chaos of a startup.  

To do this you are instinctually creating and testing multiple hypotheses which are creating an infinite number of possible future plans. And when the inevitable happens and some or all your assumptions were wrong, you pivot your model into the next plan and continue forward.  You do this until you find a scalable and repeatable business model or you die by running out of money.

Great entrepreneurs don’t just have a Plan B, they have Plans B through ∞

Lessons Learned

• A startup is initially about the search for a repeatable and scalable business model
• Most of the time your hypotheses about Plan A, B and C are wrong
• Searching requires agility, tenacity, resilience, curiosity, opportunism and pattern recognition
• Execution requires a different set of skills. At times it means bringing an operating executive
• Operating executives excel at focussed execution
• World-class technology CEO’s learned how to combine Searching and Execution (Gates, Jobs, Ellison, Bezos, Page, et al)

With 37 mllion people it’s remarkable that California has one of the most pristine and unspoiled coastline in the United States. One man and the organization he’s built is responsible for protecting it.

———–

California Dreaming
California Highway 1, (the Pacific Coast Highway) is a two-lane road that hugs the coast from Mexico to the town of Leggett in Northern California. It’s carved out of the edge of the California almost designed to connect you to the Pacific Ocean in a way that no other road in the country does. In some stretches It’s breathtaking and hair-raising and in others it’s the most tranquil drive you’ll ever take.

It goes through quintessential California beach towns right out of the 1950′s. It has hair-pin turns that have you’re convinced you’re about to fall into the ocean. It has open farm fields and hundreds of miles of unspoiled and undeveloped land. It’s the kind of road you see in car ads and movies, one that looks like it was built to be driven in a Porsche with the top down.  The almost 400 mile coast drive from Los Angeles to San Francisco is one the road trips you need to do before you die.

15 air miles away, the road parallels Silicon Valley (and the 7 million people in the San Francisco Bay Area.) In that 45 mile stretch – from Half Moon Bay to Santa Cruz – there’s not a single stoplight and less than 5,000 people.

The Peoples Coast
Yet there’s no rational reason most of the 1,100 miles of the California coast should look like this. 33 million Californians live less than an hour from the coast. It’s some of the most expensive land in the country. As our economy is organized to extract the maximum revenue and profits from any asset, you wonder why there aren’t condos, hotels, houses, shopping centers and freeways, wall-to-wall for most of it’s length (except in parts of Southern California where there already is.)

The explanation is that almost 40 years ago the people of California passed Proposition 20 – the Coastal Initiative – and in 1976 the state legislature followed it up by passing the Coastal Act, which created the California Coastal Commission. Essentially the Coastal Commission acts as California’s planning commission for all 1,100 miles of the California coast. It has a staff of ~120 who recommend actions to the 12 commissioners (all political appointees) who make the final decisions.

Among other things the legislature said the goals of the Coastal Commission was to: 1) maximize public access to the coast and maximize public recreational opportunities in the coastal zone consistent with sound resources conservation principles and constitutionally protected rights of private property owners. And 2) assure priority for coastal-dependent and coastal-related development over other development on the coast.

You Can Make a Difference
This week I had my public servant hat on in my role as a California Coastal Commissioner.

I don’t write about the commission because I want to avoid any conflict in my role as a public official.  But today is different. The single individual responsible for running the Commission staff for the last 26 years, it’s executive director Peter Douglas, just announced his retirement.

Unlike Robert Moses who built modern New York City’s or Baron Haussmann who built 19^th century Paris in concrete and steel, the legacy and achievements of Peter Douglas are all the things you don’t see in the 1,100 miles of the California coast; wetlands that haven’t been filled, public access that hasn’t been lost, highly scenic areas that haven’t been spoiled and destroyed.

There’s an old political science rule of thumb that says regulatory agencies become captured by the industries that they regulate within seven years. Yet for the 26 years of Peter’s tenure he’s managed to keep the commission independent despite of enormous pressure.

The Commission has been able to stave off the tragedy of the commons for the California coast. Upholding the Coastal Act had it taking unpopular positions upsetting developers who have fought with the agency over seaside projects, homeowners who strongly feel that private property rights unconditionally trump public access and local governments who believe they should have the final say in what’s right for their community.

Peter opened the commission up to public participation and promoted citizen activism. He built a world-class staff who understand what public service truly means.

Over the last 40 years the winners have been 37 million Californians and the people who drive down the coast and can’t imagine why its looks like it does. In spite of opposition the commission has carried out the public trust.

The coast is never saved, it is always being saved.  The work is never finished. The pressure to develop it is relentless, and it can be paved over with a thousand small decisions. I hope our children don’t look back at pictures of the California coast and wistfully say, “look what our parents lost.”

As commissioners it’s our job to choose Peter’s replacement. Hopefully we’ll have the wisdom in finding a worthy successor. The people of California and their children deserve as much.

Godspeed Peter Douglas.

Update
Great interview with Peter Douglas on his retirement.