Steve Blank's Blog, page 53

Risk and Culture in Silicon Valley

Om Malik runs Gigaom, probably the most interesting and accurate site on the blogosphere.

Om was kind enough to have me in for an interview. We covered a wide range of topics. This talk on Risk and Culture in Silicon Valley is a small  1 minute snippet of a longer interview on his blog.

Filed under: Family/Career, Teaching, Technology, Venture Capital

Entrepreneurs Are Artists

I wrote about entrepreneurs as artists in a previous post.

The FounderLy team interviewed me and got me to give a better explanation of what I was trying to say in this 2 minute video clip.

If you can't see the video click here.

Filed under: Big Companies versus Startups: Durant versus Sloan, Business Model versus Business Plan, Customer Development, Family/Career

Flowery Words – True Ventures Founders Camp

The team at True Ventures was kind enough to invite me to speak at their Founders Camp. They pull in the founders of all their startups for 24 hours of activities, speakers, and discussions. I was blown away by the raw talent of these teams.

They had someone translating my words into a diagram as I spoke. (Click on it for the full effect.)

Filed under: Venture Capital

One Hand Clapping – Entrepreneurship In Ann Arbor, Michigan

I spent a few days in March in Ann Arbor Michigan as a guest of Professor Thomas Zurbuchen, Associate Dean for Entrepreneurial Programs, and Doug Neal, Director of Center for Entrepreneurship in the Engineering School at the University of Michigan.

I gave a keynote on entrepreneurship to MPowered, the student Entrepreneurship Organization, spoke on a panel on Entrepreneurship and the Aerospace Industry, and gave another keynote at the Ann Arbor New Tech Meetup and A2Geeks, the regional startup network.

I got smarter about engineering and innovation in "flyover country", met some wonderful people and shared some thoughts about what it might take to spark an innovation cluster in Ann Arbor.

This post is a personal view of what I saw in Ann Arbor — in no way does it represent the views of the fine institutions I teach at. Read this with all the usual caveats: visiting a place for a few days doesn't make you an expert, I'm not an economist, and the odds are I misunderstood or misinterpreted what I saw or just didn't see enough.

One Hand Clapping - Creating an Innovation Cluster – The Ann Arbor Experiment

In my short time in Ann Arbor, I spent time meeting with:

Faculty; I met with the Dean of Engineering, held faculty lunches and roundtables in the Engineering School, and met one-on-one with several engineering and med school faculty who wanted to turn their research into a company.
Students; presented to entrepreneurship classes teaching technology-driven Scalable startups as well as students interested in Social Entrepreneurship. Held office hours and met lots of passionate students with great ideas.
Business School, met with the entrepreneurship center in the Business School,
Entrepreneurs; presented to MPowered the University of Michigan student Entrepreneurship Organization, the Ann Arbor New Tech Meetup and A2Geeks, the regional startup network (talk here.)
Venture Capital; met with the local hardware/software venture capital firm.
Incubators: toured the TechArb, the engineering student accelerator, and the Michigan Venture Center in the University's Tech Transfer Office

The good news:

Entrepreneurship and innovation has been embraced big time at U of M. The Engineering School has 5,600 undergrads and 3,000 graduate students. It' s probably no coincidence that the Dean of the Engineering School founded a company and gets what "startup" means first hand. The Center for Entrepreneurship in the Engineering School is akin to Stanford's STVP program. It offers 35 entrepreneurship courses.

Everyone I met in this program "gets" the principles of Agile, Lean and Customer Development big time. The TechArb is the engineering student accelerator/incubator (cofounded by the local VC) and also embraces these ideas. Finally, I was impressed to find a robust local entrepreneurial community centered around A2Geeks and the Tech Brewery (after I met Dug Song I understood why.)

(I didn't have enough time to connect with the entrepreneurial groups working on medical devices and life sciences, but they are another big component of the startup pool coming out of the University.)

What needs work:

It's been 33 years since I was last in Ann Arbor. (I call it the best school I was ever thrown out of.)  I was incredibly impressed with how far the University has inculcated innovation into the fabric of the Engineering School. However the challenges that still needed to be addressed were pretty apparent.

You Can't Start a Fire Without A Spark – A Lack of Venture Capital

For an Engineering School so focused on innovation and startups the lack of sufficient numbers of venture capitalists in the local community for Cleantech, hardware, Web/Mobile apps and aerospace was noticeable. Given the interesting things going on in the engineering labs I visited and the startups I met, one would have thought the school would have been crawling with VC's fighting over deals. Instead it seems that students who graduate simply pick up a plane ticket with their diploma. (Of course, some do stay. The spin-outs from Center of Entrepreneurship are impressive. Many of those companies are still Ann Arbor, but the ecosystem is a limiting factor.)

While one can't recreate all the happy accidents that made Silicon Valley, it doesn't take a rocket scientist to realize that it's the combination of technology entrepreneurs and risk capital that are two of the essential ingredients in any cluster.  (I list some of the others in the diagram below.)

Innovation Cluster - What's Missing in Ann Arbor

Therefore the lack of critical mass in Venture Investors in Ann Arbor was palpable – and incomprehensible. This place could support at least one or two seed funds like 500 Startups, and a couple of True Venture/Floodgate-type of VC's as well as more Cleantech investors. Getting them in Ann Arbor would solve the other missing piece; the lack of a startup culture.

A Lack of a Startup Culture in the Community

Visiting Silicon Valley you can't mistake that its primary business is innovation. In Ann Arbor and southeast Michigan entrepreneurship is a small part of a more diverse business culture. One of the characteristics of a cluster is that it isn't hard to find other like-minded individuals. In Ann Arbor, they're scattered in between the auto industry, biotech, hospital workers, etc. As a consequence Ann Arbor lacks the culture of risk-taking and respect for failure critical in an innovation cluster. You see it in the existing angel groups and VC's. They feel more like banks than risk capital. And that lack of tolerance for failure and comfort with the status quo gets fed back to the entrepreneurs. Getting a few experienced super-angels and/or VC's seeding 5-10 Lean Startup deals here a year, with a couple of Cleantech/energy deals as well, could kickstart the culture.

Not My Problem

The interesting thing is that no one seems to own the problem. The University of Michigan tech transfer office has an incubator but 1) mixes software, hardware, med devices and life sciences deals in the same program, and 2) takes no ownership of figuring out how to get a risk capital ecosystem in place. Surprisingly, the same with the entrepreneurship center in the Business School. I would have thought they'd be leading the charge.

The new governor of Michigan, Rick Snyder was a venture capitalist in Ann Arbor, so I'm surprised he hasn't jawboned some combination of Michigan alumni working in venture capital in Silicon Valley to return, and paired them with the old-school money from the Auto industry, that's hiding under mattresses. (If the old money doesn't get the new mobile/web app space, note that new money is pouring into Cleantech/energy VC funds in the Valley. Silver Lake Kraftwerk's Fund just raised $1.3 billion for a Cleantech/Energy growth fund. Bet Ann Arbor and the Detroit Metro area have a few startups in that space. Where are the investors?)

—-

The real test of a cluster "catching fire" is not when it provides local employment, but when people from outside the area start coming to work and invest there.

These guys are this close to making it happen. It would be a shame if it didn't.

Lessons Learned

U of M has a College of Engineering dean who "gets it"
He's turned the school into an outward facing school, fostering an entrepreneurial and innovation culture
The Center for Entrepreneurship is on board with passionate faculty, innovative curriculum and excited students
The area has almost no experienced Angel, super Angel or Venture Capital (as we know it in Silicon Valley) for web/mobile apps, hardware and software
The lack of experienced risk capital means a lack of experienced mentors, coaches, and infrastructure.

Filed under: Teaching, Venture Capital

The LeanLaunch Pad at Stanford – Class 4: Customer Hypotheses

The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. This post is part four. Part one is here, two is here and three is here. Syllabus is here.

Week 4 of the class.

Last week the teams were testing their hypotheses about their Value Proposition (their company's product or service.) This week they were testing who the customer, user, payer for the product will be (and discovering if they have a multi-sided business model, one with both buyers and sellers.) Many of them had heard the phrase "product/market fit" before, but now they were living it. And for some of the teams the halcyon days of "we're taking this class so we can just build our great product and get credit for it" had come to a screeching halt. The news from customers was not good.

Let the real learning begin.

The Nine Teams Present

This week, our first team up was PersonalLibraries (the team that had software to help researchers manage, share and reference the thousands of papers in their personal libraries.) Going into the first four weeks their business model hypotheses looked like this:Last week we told them team: 1) see if the market size was really large enough to support a business, and 2) to find that out they were going to have to 
talk to more customers
 outside of Stanford. So during the past week, the team got feedback from >60 researchers from 
cold calls, in-person interviews, and a web survey.  (We were impressed when we found that they did the in-person interviews by hiring usertesting.com for $39 to set up test scenarios, gave the users specific tasks to accomplish with their minimum viable product, videotaped the customer interactions and summarized customer likes and dislikes.) The good news was that customers said that their minimum viable product (easily organizing research papers) was correct. The bad news was that users would play with their product on-line for a while and leave and never return.  Politely it was described as "poor customer retention" but in reality it was because the product was really hard to use.

But it was their market size survey that had the team (and us) even more concerned; last weeks "hot" market of biomed researchers looked like it was only $30m market, and the total available reference manager market was another $80M.The question was, even if they got the product right, were there enough customers to make it a business?

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

For next week, they decided to improve the product by adding more tutorials, do a 2nd Customer Survey and begin to create demand for their product with AdWords Value Prop Testing and Landing Page A/B Testing.

The feedback from the teaching team was that customer feedback seems to be saying that this product is a "nice to have" versus "got to have." Is the lack of excitement the MVP? Users?  Is this a hobby or a business?

Agora Cloud Services

The Agora team started the week wondering whether they were 1) a true marketplace for cloud computing, where they provide both matching and exchange capabilities for real-time trading. Or were they 2) an information exchange, providing matching services for cloud computing buyers and sellers, providing matching services.

They began with a set of questions:

What are our new hypothesized value propositions?
Which segments have we identified and which do we want to narrow in on?
Which value added services do public clouds want to attract customers for?
Is there a certain segment of buyers that continually makes purchasing decisions (as opposed to only once at the very beginning of a company).
How can we attract buyers to our channel before they make purchasing decisions?
Longer-term work/planning: what other experiments should we be constructing
Sales process: buyer/ user/ influencer etc.?  Demand generation?

The Agora team decided to formalize the customer discovery process by coming up with a set of Customer Discovery principles and questions that were as good as any I've seen.

They had 16 interviews with target customers (Zynga, Yahoo, VMware, Walmart,  Zeconder, etc.) as well as channel partners and cloud industry technology consultants.

Agora was in a classic two-sided market (having both buyers and sellers. The Business Model Canvas is a great way to diagram it out. Each side of a market has it's own Value Proposition, Customer Segment and Revenue Model.) They learned that one their core customer hypothesis about their buyers, "startups would want to buy computing capacity on a "spot market" was wrong. Startups were actually happy with Amazon Web Services. The Agora team was beginning to believe that perhaps their ideal buyers are the companies that have to handle variable and unpredictable workloads.

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

The Agora team left the week thinking that it was time for a Pivot: find cloud buyers and sellers who need to better predict demand.  Perhaps in market segment: medium-large companies that do 3D modeling and life sciences simulations

The feedback from the teaching team "great Pivot" and very clear Lessons Learned presentation. Keep at it.

(For the teaching team one of the most important ways to track the teams progress was through the weekly blogs we made each team keep. This of this as their on-line diary. They hated doing it, but for us it added a window into their thinking process, allowed us to monitor how much work they were doing, and more importantly let us course correct when needed.

BTW, If I was on the board of a startup with a first time CEO I might even consider asking for this in the first year as they went through Customer Discovery. Yes it takes time, but I bet it's less than time than you would spend having coffee with an advisor each week.)

D.C. Veritas, was the team building a low cost, residential wind turbine that average homeowners could afford. From a slow start of customer interaction they made major progress in getting out for the building. This week they refined their target market by building a map of potential customers in the U.S. by modeling wind speed, energy costs, homeownership density and green energy incentives. The result was a density map of target customers. They then did face-to-face interviews with 20 customers and got data from 36 more who fit their archetype.  They also interviewed two companies – Solar City and Awea in the adjacent market (residential photovoltaic's.)

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

The teaching team offered that unlike solar panels which work anywhere, they've narrowed down the geographic areas where their wind turbine was economical. We observed that their total available market was getting smaller daily. After the next week figuring out demand creation costs, they ought to see if the homeowners were still a viable target market for residential wind turbines.

Autonomow, the robot lawn mower, came in with a major Pivot. Instead of a robotic lawn mower, they were now going to focus on robotic weeding and drop mowing as a customer segment. (Once you use the Business Model Canvas to keep score of Customer Discovery a Pivot is easy to define. A Pivot is when you substantively change one or more of the Business Model Canvas boxes.)

Talking to customers convinced the team that the need for robotic weeding was high, there was a larger potential market (organic crop production is doubling every 4 years and accelerating,) and they could make organic produce more affordable (labor cost reduction of 100 to 1) – and could possibly change the organic farming industry!  And as engineers they believed weed versus crop recognition, while hard, was doable.

During the week the team drove the 160 miles round-trip to the Salinas Valley and had on-site interviews with two organic farms. They walked the fields with the farmers, hand-picked weeds with the laborers and got down into the details of the costs of brining in an organic crop.

They also talked by phone to organic farmers in Nebraska and the Santa Cruz mountains.

They acquired quantitative data by going through the 2008 Agricultural Census. Most importantly their model of the customer began to evolve.

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

Our feedback: could they really build a robot to recognize and weeds and if so how will they kill the weeds without killing the crops?  And are farmers willing to take a risk on untested and radical ideas like robots replacing hand weeding?

The Week 4 Lecture: Customer Relationships

Our lecture this week covered Customer Relationships (a fancy phrase for how will your company create end user demand by getting, keeping and growing customers.) We pointed out that get, keep and grow customers are different for physical versus virtual channels. Then different again for direct and indirect channels. We offered some examples of what a sales funnel looked like. And we described the difference between creating demand for products that solve a problem versus those that fulfill a need.

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

———

The biggest lesson for the students this week was the entire reason for the class – no business plan survives first contact with customers – as customers don't behave as per theory. As smart as you are, there's no way to predict that from inside your classroom, dorm room or cubicle. Some of the teams were coming to grips with it. Others would find reality crashing down harder a bit later.

Next week, each team tests its demand creation hypotheses. The web-based teams needed to have their site up and running and be driving demand to the site with real Search Engine Optimization and Marketing tests.

Filed under: Business Model versus Business Plan, Customer Development, Lean LaunchPad, Teaching

Entrepreneurship is an Art not a Job

Some men see things as they are and ask why.

Others dream things that never were and ask why not.

George Bernard Shaw

Over the last decade we assumed that once we found repeatable methodologies (Agile and Customer Development, Business Model Design) to build early stage ventures, entrepreneurship would become a "science," and anyone could do it.

I'm beginning to suspect this assumption may be wrong.

Where Did We Go Wrong?

It's not that the tools are wrong, I think the entrepreneurship management stack is correct and has made a major contribution to reducing startup failures. Where I think we have gone wrong is the belief that anyone can use these tools equally well.

Entrepreneurship is an Art not a Job

For the sake of this analogy, think of two types of artists: those who creators and performers (think music composer versus members of the orchestra, playwright versus actor etc.)

Founders fit the definition of a creator: they see something no one else does. And to help them create it from nothing, they surround themselves with world-class performers. This concept of creating something that few others see – and the reality distortion field necessary to recruit the team to build it – is at the heart of what startup founders do. It is a very different skill than science, engineering, or management.

Entrepreneurial employees are the talented performers who hear the siren song of a founder's vision. Joining a startup while it is still searching for a business model, they too see the promise of what can be and join the founder to bring the vision to life.

Founders then put in play every skill which makes them unique – tenacity, passion, agility, rapid pivots, curiosity, learning and discovery, improvisation, ability to bring order out of chaos, resilience, leadership, a reality distortion field, and a relentless focus on execution – to lead the relentless process of refining their vision and making it a reality.

Both founders and entrepreneurial employees prefer to build something from the ground up rather than join an existing company. Like jazz musicians or improv actors, they prefer to operate in a chaotic environment with multiple unknowns. They sense the general direction they're headed in, OK with uncertainty and surprises, using the tools at hand, along with their instinct to achieve their vision. These types of people are rare, unique and crazy. They're artists.

Tools Do Not Make The Artist

When page-layout programs came out with the Macintosh in 1984, everyone thought it was going to be the end of graphic artists and designers. "Now everyone can do design," was the mantra. Users quickly learned how hard it was do design well (yes. it is an art) and again hired professionals. The same thing happened with the first bit-mapped word processors. We didn't get more or better authors. Instead we ended up with poorly written documents that looked like ransom notes. Today's equivalent is Apple's "Garageband". Not everyone who uses composition tools can actually write music that anyone wants to listen to.

"Well If it's Not the Tools Then it Must Be…"

The argument goes, "Well if it's not tools then it must be…" But examples from teaching other creative arts are not promising. Music composition has been around since the dawn of civilization yet even today the argument of what "makes" a great composer is still unsettled. Is it the process (the compositional strategies used in the compositional process?) Is it the person (achievement, musical aptitude, informal musical experiences, formal musical experiences, music self-esteem, academic grades, IQ, and gender?)  Is it the environment (parents, teachers, friends, siblings, school, society, or cultural values?) Or is it constant practice (apprenticeship, 10,000 hours of practice?)

It may be we can increase the number of founders and entrepreneurial employees, with better tools, more money, and greater education. But it's more likely that until we truly understand how to teach creativity, their numbers are limited.

Lessons Learned

Founders fit the definition of an artist: they see – and create– something that no one else does
To help them move their vision to reality, they surround themselves with world-class performers
Founders and entrepreneurial employees prefer operating in a chaotic environment with multiple unknowns
These type of people are rare, unique and crazy
Not everyone is an artist

Filed under: Big Companies versus Startups: Durant versus Sloan, Customer Development, Family/Career

Napkin Entrepreneurs

Faith is taking the first step even when you don't see the whole staircase.

Martin Luther King, Jr.

The barriers for starting a company have come down. Today the total available markets for new applications are hundreds of millions if not billion of users, while new classes of investors are popping up all over (angels, superangels, archangels, and even seraphim and cherubim have been spotted.)

Entrepreneurship departments are now the cool thing to have in colleges and universities, and classes on how to start a company are being taught over a weekend, a month, six weeks, and via correspondence course.

If the opportunity is so large, and the barriers to starting up so low, why haven't the number of scalable startups exploded exponentially? What's holding us back?

It might be that it's easier than ever to draw an idea on the back of the napkin, it's still hard to quit your day job.

Napkin Entrepreneurs

One of the amazing consequences of the low cost of creating web and mobile apps is that you can get a lot of them up and running simultaneously and affordably. I call these app development projects "science experiments."

These web science experiments are the logical extension of the Customer Discovery step in the Customer Development process. They're a great way to brainstorm outside the building, getting real customer feedback as you think through your ideas about value proposition/customer/demand creation/revenue model.

They're the 21st century version of a product sketch on a back of napkin. But instead of just a piece of  paper, you end up with a site that users can visit, use and even pay for.

Ten of thousands of people who could never afford to start a company can now start several over their lunch break. And with any glimmer of customer interest they can decide whether they want to:

run it as a part-time business
commit full-time to build a "buyable startup" (~$5-$25 Million exit)
commit full-time and try to build a scalable startup

But it's important to note what these napkin projects/test are not. They are not a company, nor are they are a startup. Running them doesn't make you a founder. And while they are entrepreneurial experiments, until you actually commit to them by choosing one idea, quitting your day job and committing yourself 24/7 it's not clear that the word "founder or entrepreneur" even applies.

Lessons Learned

The web now allows you to turn your "back of the napkin" ideas into live experiments
Running lots of app experiments is a great idea
But these experiments are not a company and you're not a "founder". You're just a "napkin entrepreneur."
Founding a company is an act of complete commitment

Filed under: Big Companies versus Startups: Durant versus Sloan, Teaching

The LeanLaunch Pad at Stanford – Class 3: Value Proposition Hypotheses

The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. This post is part three. Part one is here, two is here. Syllabus is here.

Week 3 of the class and our teams in our Stanford Lean LaunchPad class were hard at work using Customer Development to get out of the classroom and test the first key hypotheses of their business model: The Value Proposition. (Value Proposition is a ten-dollar phrase describing a company's product or service. It's the "what are you building and selling?")

The Nine Teams Present

This week, our first team up was PersonalLibraries (the team that made software to help researchers manage, share and reference the thousands of papers in their personal libraries.) To test its Value Proposition, the team had face-to-face interviews with 10 current users and non-users from biomedical, neuroscience, psychology and legal fields.

What was cool was they recorded their interviews and posted them as YouTube videos. They did an online survey of 200 existing users (~5% response rate). In addition, they demoed to the paper management research group at the Stanford Intellectual Property Exchange project (a joint project between the Stanford Law School and Computer Science department to help computers understand copyright and create a marketplace for content). They met with their mentors, and refined their messaging pitch by attending a media training workshop one of our mentors held.

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

In interviewing biomed researchers, they found one unmet need: the ability to cite materials used in experiments. This is necessary so experiments can be accurately reproduced. This was such a pain point, one scientist left a lecture he was attending to find the team and hand them an example of what the citations looked like.

The team left the week excited and wondering – is there an opportunity here to create new value in a citation tool? What if we could help scientists also bulk order supplies for experiments? Could we help manufacturers, as well, to better predict demand for their products, or perhaps to more effectively connect with purchasers?

The feedback from the teaching team was a reminder to see if the users they were talking to constitute a large enough market and had budgets to pay for the software.

Agora Cloud Services

The Agora team (offering a cloud computing "unit" that Agora will buy from multiple cloud vendors and create a marketplace for trading) had 7 face-to-face interviews with target customers, and spoke to a potential channel partner as well as two cloud industry technology consultants.

They learned that their hypothesis that large companies would want to lower IT costs by selling their excess computing capacity on a "spot market" didn't work in the financial services market because of security concerns.  However sellers in the Telecom industries were interested if there was some type of revenue split from selling their own excess capacity.

On the buyers' side, their hypothesis that there were buyers who were interested in reduced cloud compute infrastructure cost turned out not to be a high priority for most companies. Finally, their assumption that increased procurement flexibility for buying cloud compute cycles would be important turned out to be just a "nice to have," not a real pain. Most companies were buying Amazon Web Services and were looking for value-added services that simplified their cloud activities.

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

The Agora team left the week thinking that the questions going forward were:

žHow do we get past Amazon as the default cloud computing service provider?
How viable is the telecom market as a potential seller of computing cycles?
We need to further validate buyer & seller value propositions
How do we access the buyers and sellers? What sort of sales structure and salesforce does it require?
Who is the main buyer(s) and what are their motivations?
Is a buying guide/matching service a superior value proposition to marketplace?

The feedback from the teaching team was a reminder that at times you may have a product in search of a solution.

D.C. VeritasD.C. Veritas, the team that was going to build a low cost, residential wind turbine that average homeowners could afford, wanted to provide a renewable source of energy at affordable price.  They started to work out what features a minimum viable product their value proposition would have and began to cost out the first version. The Wind Turbine Minimum Viable Product would have a: Functioning turbine, Internet feedback system, energy monitoring system and have easy customer installation.

The initial Bill of Material (BOM) of the Wind Turbine Hardware Costs looked like: Inverter (1000W): $500 (plug and play), Generator (1000W): $50-100, Turbine: ~$200, Output Measurement: ~$25, Wiring: $20 = Total Material Cost: ~$800-$850

The team also went to the whiteboard and attempted a first pass at who the archetypical customer(s) might be.

To get customer feedback the team posted its first energy survey here and received 27 responses. In their first attempt at face-to-face customer interviews to test their value proposition and problem hypothesis (would people be interested in a residential wind turbine), they interviewed 13 people at the local Farmer's Market.

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

The teaching team offered that out of 13 people they interviewed only 3 were potential customers. Therefore the amount of hard customer data they had collected was quite low and they were making decisions on a very sparse data set. We suggested (with a (2×4) that were really going to have to step up the customer interactions with a greater sense of urgency.The teaching team offered that out of 13 people they interviewed only 3 were potential customers. Therefore the amount of hard customer data they had collected was quite low and they were making decisions on a very sparse data set. We suggested (with a 2×4) that were really going to have to step up the customer interactions with a greater sense of urgency.

Autonomow

The last team up was Autonomow, the robot lawn mower. They were in the middle of trying to answer the question of  "what problem are they solving?" They were no longer sure whether they were an autonomous mowing company or an agricultural weeding company.

They spoke to 6 people with large mowing needs (golf course, Stanford grounds keeper, etc.) They traveled to the Salinas Valley and Bakersfield and interviewed 6 farmers about weeding crops. What they found is that weeding is a huge problem in organic farming. It was incredibly labor intensive and some fields had to be hand-weeded multiple times per year.

They left the week realizing they had a decision to make – were they a  "Mowing or Weeding" company?

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

Our feedback: could they really build a robot to recognize and kill weeds in the field?

The Week 3 Lecture: Customers

Our lecture this week covered Customers – what/who are they?  We pointed out the difference between a user, influencer, recommender, decision maker, economic buyer and saboteur. We also described the differences between customers in Business-to-business sales versus business-to-consumer sales.  We talked about multi-sided markets and offered that not only are there multiple customers, but each customer segment has their own value proposition and revenue model.

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

Getting Out of the Building

Five other teams presented after these four. All of them had figured out the game was outside the building, with some were coming up to speed faster than others. A few of the teams ideas still looked pretty shaky as businesses. But the teaching team held our opinions to ourselves, as we've learned that you can't write off any idea too early. Usually the interesting Pivots happens later. The finish line was a ways off. Time would tell where they would all end up.

———

Next week each team test their Customer Segment hypotheses (who are their customers/users/decision makers, etc.) and report the results of face-to-face customer discovery. That will be really interesting.

Filed under: Business Model versus Business Plan, Customer Development, Lean LaunchPad, Teaching

The Democratization of Entrepreneurship

I gave a talk at the Stanford Graduate School of Business as part of Entrepreneurship Week on the Democratization of Entrepreneurship. The first 11 minutes or so of the talk covers the post I wrote called "When It's Darkest, Men See the Stars."

In it I observed that the barriers to entrepreneurship are not just being removed. In each case they're being replaced by innovations that are speeding up each step, some by a factor of ten.

My hypotheses is that we'll look back to this decade as the beginning of our own revolution. We may remember this as the time when scientific discoveries and technological breakthroughs were integrated into the fabric of society faster than they had ever been before. When the speed of how businesses operated changed forever. As the time when we reinvented the American economy and our Gross Domestic Product began to take off and the U.S. and the world reached a level of wealth never seen before.  It may be the dawn of a new era for a new American economy built on entrepreneurship and innovation.

If you can't see the video above, click here.)

If you've seen my other talks, after the first 11 minutes you can skip to ~1:04 with the Sloan versus Durant story and some interesting student Q&A. You can follow the talk along with the slides I used, below.

(If you can't see the slide presentation above, click here.)

Filed under: Big Companies versus Startups: Durant versus Sloan, Customer Development

New Rules for the New Internet Bubble

Carpe Diem

We're now in the second Internet bubble. The signals are loud and clear: seed and late stage valuations are getting frothy and wacky, and hiring talent in Silicon Valley is the toughest it has been since the dot.com bubble. The rules for making money are different in a bubble than in normal times. What are they, how do they differ and what can startup do to take advantage of them?

First, to understand where we're going, it's important to know where we've been.

Paths to Liquidity: a quick history of the four waves of startup investing.

The Golden Age (1970 – 1995): Build a growing business with a consistently profitable track record (after at least 5 quarters,) and go public when it's time.
Dot.com Bubble (1995-2000): "Anything goes" as public markets clamor for ideas, vague promises of future growth, and IPOs happen absent regard for history or profitability.
Lean Startups/Back to Basics (2000-2010): No IPO's, limited VC cash, lack of confidence and funding fuels "lean startup" era with limited M&A and even less IPO activity.
The New Bubble: (2011 – 2014): Here we go again….

(If you can't see the slide presentation above, click here.)

If you "saw the movie" or know your startup history, and want to skip ahead click here.

1970 – 1995: The Golden Age

VC's worked with entrepreneurs to build profitable and scalable businesses, with increasing revenue and consistent profitability – quarter after quarter. They taught you about customers, markets and profits. The reward for doing so was a liquidity event via an Initial Public Offering.

Startups needed millions of dollars of funding just to get their first product out the door to customers. Software companies had to buy specialized computers and license expensive software. A hardware startup had to equip a factory to manufacture the product. Startups built every possible feature the founding team envisioned (using "Waterfall development,") into a monolithic "release" of the product taking months or years to build a first product release.

The Business Plan (Concept-Alpha-Beta-FCS) became the playbook for startups. There was no repeatable methodology, startups and their VC's still operated like startups were simply a smaller version of a large company.

The world of building profitable startups ended in 1995.

August 1995 – March 2000: The Dot.Com Bubble

With Netscape's IPO, there was suddenly a public market for companies with limited revenue and no profit. Underwriters realized that as long as the public was happy snapping up shares, they could make huge profits from the inflated valuations. Thus began the 5-year dot-com bubble. For VC's and entrepreneurs the gold rush to liquidity was on. The old rules of sustainable revenue and consistent profitability went out the window. VC's engineered financial transactions, working with entrepreneurs to brand, hype and take public unprofitable companies with grand promises of the future. The goals were "first mover advantage," "grab market share" and "get big fast." Like all bubbles, this was a game of musical chairs, where the last one standing looked dumb and everyone else got absurdly rich.

Startups still required millions of dollars of funding. But the bubble mantra of get "big fast" and "first mover advantage" demanded tens of millions more to create a "brand." The goal was to get your firm public as soon as possible using whatever it took including hype, spin, expand, and grab market share – because the sooner you got your billion dollar market cap, the sooner the VC firm could sell their shares and distribute their profits.

Just like the previous 25 years, startups still built every possible feature the founding team envisioned into a monolithic "release" of the product using "Waterfall development." But in the bubble, startups got creative and shortened the time needed to get a product to the customer by releasing "beta's" (buggy products still needing testing) and having the customers act as their Quality Assurance group.

The IPO offering document became the playbook for startups. With the bubble mantra of "get big fast," the repeatable methodology became "brand, hype, flip or IPO".

2001 – 2010: Back to Basics: The Lean Startup

After the dot.com bubble collapsed, venture investors spent the next three years doing triage, sorting through the rubble to find companies that weren't bleeding cash and could actually be turned into businesses. Tech IPOs were a receding memory, and mergers and acquisitions became the only path to liquidity for startups. VC's went back to basics, to focus on building companies while their founders worked on building customers.

Over time, open source software the rise of the next wave of web startups and the embrace of Agile Engineering meant that startups no longer needed millions of dollars to buy specialized computers and license expensive software – they could start a company on their credit cards. Customer Development, Agile Engineering and the Lean methodology enforced a process of incremental and iterative development. Startups could now get a first version of a product out to customers in weeks/months rather than months/years. This next wave of web startups; Social Networks and Mobile Applications, now reached 100's of millions of customers.

Startups began to recognize that they weren't merely a smaller version of a large company. Rather they understood that a startup is a temporary organization designed to search for a repeatable and scalable business model. This meant that startups needed their own tools, techniques and methodologies distinct from those used in large companies. The concepts of Minimum Viable Product and the Pivot entered the lexicon along with Customer Discovery and Validation.

The playbook for startups became the Agile + Customer Development methodology with The Four Steps to the Epiphany and Agile engineering textbooks.

Rules For the New Bubble: 2011 -2014

The signs of a new bubble have been appearing over the last year – seed and late stage valuations are rapidly inflating, hiring talent in Silicon Valley is the toughest since the last bubble and investors are starting to openly wonder how this one will end.

Breathtaking Scale

The bubble is being driven by market forces on a scale never seen in the history of commerce. For the first time, startups can today think about a Total Available Market in the billions of users (smart phones, tablets, PC's, etc.) and aim for hundreds of millions of customers. And those customers may be using their devices/apps continuously. The revenue, profits and speed of scale of the winning companies can be breathtaking.

The New Exits

Rules for building a company in 2011 are different than they were in 2008 or 1998. Startup exits in the next three years will include IPO's as well as acquisitions. And unlike the last bubble, this bubble's first wave of IPO's will be companies showing "real" revenue, profits and customers in massive numbers. (Think Facebook, Zynga, Twitter, LinkedIn, Groupon, etc.)  But like all bubbles, these initial IPO's will attract companies with less stellar financials, the quality IPO pipeline will diminish rapidly, and the bubble will pop. At the same time, acquisition opportunities will expand as large existing companies, unable to keep up with the pace of innovation in these emerging Internet markets, will "innovate" by buying startups. Finally, new forms of liquidity are emerging such as private-market stock exchanges for buying and selling illiquid assets (i.e. SecondMarket, SharesPost, etc.)

Tools in the New Bubble

Today's startups have all the tools needed for a short development cycle and rapid customer adoption – Agile and Customer Development plus Business Model Design.

The Four Steps to the Epiphany, Business Model Generation and the Lean Startup movement have become the playbook for startups. The payoff: in this bubble, a startup can actively "engineer for an acquisition." Here's how:

Order of Battle

Each market has a finite number of acquirers, and a finite number of deal makers, each looking to fill specific product/market holes. So determining who specifically to target and talk to is not an incalculable problem. For a specific startup this list is probably a few hundred names.

Wide Adoption

Startups that win in the bubble will be those that get wide adoption (using freemium, viral growth, low costs, etc) and massive distribution (i.e. Facebook, Android/Apple App store.) They will focus on getting massive user bases first, and let the revenue follow later.

Visibility

During the the Lean Startup era, the advice was clear; focus on building the company and avoid hype. Now that advice has changed. Like every bubble this is a game of musical chairs. While you still need irrational focus on customers for your product, you and your company now need to be everywhere and look larger than life. Show and talk at conferences, be on lots of blogs, use social networks and build a brand. In the new bubble PR may be your new best friend, so invest in it.

Lessons Learned

We're in a new wave of startup investing – it's the beginning of another bubble
Rules for liquidity for startups and investors are different in bubbles
Pay attenton to what those rules are and how to play by them
Unlike the last bubble this one is not about selling "vision" or concepts.
You have to deliver. That requires building a company using Agile and Customer Development
Startups that master speed, tempo and Pivot cycle time will win

Filed under: Technology, Venture Capital