When Customers Make You Smarter

We talk a lot about Customer Development, but there’s nothing like seeing it in action to understand its power. Here’s what happened when an extraordinary Digital Health team gained several critical insights about their business model. The first was reducing what they thought was a five-sided market to a simpler two-sided one.

But the big payoff came when their discussions with medical device customers revealed an entirely new way to think about pricing —potentially tripling their revenue.

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We’re into week 9 of teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) at UCSF teaching with a team of veteran venture capitalists. The class has talked to ~2,200 customers to date. (Our final – not to be missed – Lessons Learned presentations are coming up December 10th.)

Among the 28 startups in the Digital Health cohort is Tidepool. They began the class believing they were selling an open data and software platform for people with Type 1 Diabetes into a multi-sided market comprised of patients, providers, device makers, app builders and researchers.

tidepool website

The Tidepool team members are:

  • Aaron Neinstein MD  Assistant Professor of Clinical Medicine, Endocrinology and Assistant Director of Informatics at UCSF. He’s an expert in the intersection between technological innovations and system improvement in healthcare. His goal is to make health information easier to access and understand.
  • Howard Look, CEO of Tidepool, was VP of Software and User Experience at TiVo. He was also VP of Software at Pixar, developing Pixar’s film-making system, and at Amazon where he ran a cloud services project. At Linden Lab, delivered the open-sourced Second Life Viewer 2.0 project. His teenage daughter has Type 1 diabetes.
  • Brandon Arbiter was a VP at FreshDirect where he built the company’s data management and analytics practices. He was diagnosed at age 27 with Type 1 Diabetes. He developed a new generation diabetes app, “nutshell,” that gives patients the information they need to make the right decisions about their dosing strategies.
  • Kent Quirk was director of engineering at Playdom and director of engineering at Linden Labs.

A Five-sided Market
In Week 1 the Tidepool team diagramed its customer segment relationships like this:

Tidepool ecosystem

Using the business model canvas they started with their value proposition hypotheses, articulating the products and services they offered for each of the five customer segments. Then they summarized what they thought would be the gain creators and pain relievers for each of these segments.

Tide pool value prop week 1

Next, they then did the same for the Customer Segment portion of the canvas. They listed the Customer Jobs to be done and the Pains and Gains they believed their Value Proposition would solve for each of their five customer segments.

Tide pool cust week 1

It’s Much Simpler
Having a multisided market with five segments is a pretty complicated business model. In some industries such as medical devices its just a fact of life. But after talking to dozens of customers by week 3, Tidepool discovered that in fact they had a much simpler business model – it was a two-sided market.

tidepool simplification

They discovered that the only thing that mattered in the first year or two of their business was building the patient-device maker relationship. Everything else was secondary. This dramatically simplified their value proposition and customer segment canvas.

So they came up with a New Week 3 Value Proposition Canvas:

Tide pool value prop week 3

And that simplified their New Week 3 Customer Segment Canvas

Tide pool cust week 3

Cost-based Pricing versus Value-based Pricing
While simplifying their customer segments was a pretty big payoff for 3 weeks into the class, the best was yet to come.

As part of the revenue streams portion of the business model canvas, each team has to diagram the payment flows.

Tide pool market pricing

The Tidepool team originally believed they were going charge their device partners “market prices” for access to their platform. They estimated their Average Revenue per User (ARPU) would be about $36 per year.

Tide pool market pricing ARPU

But by week 6 they had spoken to over 70 patients and device makers. And what they found raised their average revenue per user from $36 to $90.

When talking to device makers they learned how the device makers get, keep and grow their customers.  And they discovered that:

  • device makers were spending $500-$800 in Customer Acquisition Cost (CAC) to acquire a customer
  • device makers own customers would stay their customers for 10 years (i.e. the Customer Life Time (CLT))
  • and the Life Time Value (LTV) of one customer over those 10 years to a device maker is $10,000

Tide pool market pricing device cac

These customer conversations led the Tidepool team to further refine their understanding of the device makers’ economics.  They found out that the device makers sales and marketing teams were both spending money to acquire customers.  ($500 per sales rep per device + $800 marketing discounts offered to competitors’ customers.)

Tide pool device economics

Once they understood their device customers’ economics, they realized they could help these device companies reduce their marketing spend by moving some of those dollars to Tidepool. And they realized that the use of the Tidepool software could reduce the device companies’ customer churn rate by at least 1%.

This meant that Tidepool could price their product based on the $1,800 they were going to save their medical device customers.  Read the previous sentence again. This is a really big idea.

Tide pool value pricing big idea

The Tidepool team went from cost-based pricing to value-based pricing. Raising their average revenue per user from $36 to $90.

Tide pool value pricing $90 ARPU

There is no possible way that any team, regardless of how smart they are could figure this out from inside their building.

If you want to understand how Customer Discovery works and what it can do in the hands of a smart team, watch the video below. The team ruthlessly dissects their learning and builds value-pricing from what they learned.

This short video is a classic in Customer Discovery.

If you can’t see the video click here.

Lessons Learned

  • Most startups begin by pricing their product based on cost or competition
  • Smart startups price their product based on value to the customer
  • You can’t guess how your product is valued by customers
  • Customer Development allows you to discover the economics needed for value pricing your product

Listen to the podcast here


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It’s Time to Play Moneyball: The Investment Readiness Level

Investors sitting through Incubator or Accelerator demo days have three metrics to judge fledgling startups – 1) great looking product demos, 2) compelling PowerPoint slides, and 3) a world-class team.

We think we can do better.

We now have the tools, technology and data to take incubators and accelerators to the next level. Teams can prove their competence and validate their ideas by showing investors evidence that there’s a repeatable and scalable business model. And we can offer investors metrics to play Moneyball – with the Investment Readiness Level.

Here’s how.

————–

We’ve spent the last 3 years building a methodology, classes, an accelerator and software tools and we’ve tested them on ~500 startups teams.

  • A Lean Startup methodology offers entrepreneurs a framework to focus on what’s important: Business Model Discovery. Teams use the Lean Startup toolkit: the Business Model Canvas + Customer Development process + Agile Engineering. These three tools allow startups to focus on the parts of an early stage venture that matter the most: the product, product/market fit, customer acquisition, revenue and cost model, channels and partners.

Lean moneyball

  • An Evidence-based Curriculum (currently taught in the Lean LaunchPad classes and NSF Innovation Corps accelerator). In it we emphasize that a) the data needed exists outside the building, b) teams use the scientific method of hypothesis testing c) teams keep a continual weekly cadence of:
    • Hypothesis – Here’s What We Thought
    • Experiments – Here’s What We Did
    • Data – Here’s What We Learned
    • Insights and Action – Here’s What We Are Going to Do Next

Evidence moneyball

  • LaunchPad Central software is used to track the business model canvas and customer discovery progress of each team. We can see each teams hypotheses, look at the experiments they’re running to test the hypotheses, see their customer interviews, analyze the data and watch as they iterate and pivot.

LPC

We focus on evidence and trajectory across the business model. Flashy demo days are great theater, but it’s not clear there’s a correlation between giving a great PowerPoint presentation and a two minute demo and building a successful business model. Rather than a product demo – we believe in a “Learning Demo”. We’ve found that “Lessons Learned” day showing what the teams learned along with the “metrics that matter” is a better fit than a Demo Day.

“Lessons Learned” day allows us to directly assess the ability of the team to learn, pivot and move forward. Based on the “lessons learned” we generate an Investment Readiness Level metric that we can use as part of our “go” or “no-go” decision for funding.

Some background.

NASA and the Technology Readiness Level (TRL)
In the 1970’s/80’s NASA needed a common way to describe the maturity and state of flight readiness of their technology projects.  They invented a 9-step description of how ready a technology project was.  They then mapped those 9-levels to a thermometer.NASA TRL

What’s important to note is that the TRL is imperfect. It’s subjective. It’s incomplete.  But it’s a major leap over what was being used before.  Before there was no common language to compare projects.

The TRL solved a huge problem – it was a simple and visual way to share a common understanding of technology status.  The U.S. Air Force, then the Army and then the entire U.S. Department of Defense along with the European Space Agency (ESA) all have adopted the TRL to manage their complex projects. As simple as it is, the TRL is used to manage funding and go/no decisions for complex programs worldwide.

We propose we can do the same for new ventures – provide a simple and visual way to share a common understanding of startup readiness status. We call this the Investment Readiness Level . 

The Investment Readiness Level (IRL)
The collective wisdom of venture investors (including angel investors, and venture capitalists) over the past decades has been mostly subjective. Investment decisions made on the basis of “awesome presentation”, “the demo blew us away”, or “great team” is used to measure startups. These are 20th century relics of the lack of data available from each team and the lack of comparative data across a cohort and portfolio.

Those days are over.

Hypotheses testing and data collection
We’ve instrumented our startups in our Lean LaunchPad classes and the NSF I-Corps incubator using LaunchPad Central to collect a continuous stream of data across all the teams.  Over 10 weeks each team gets out and talks to 100 customers. And they are testing hypotheses across all 9 boxes in the business model canvas.

We collect this data into a Leaderboard (shown in the figure below) giving the incubator/accelerator manager a single dashboard to see the collective progress of the cohort. Metrics visible at a glance are number of customer interviews in the current week as well as aggregate interviews, hypotheses to test, invalidated hypotheses, mentor and instructor engagements. This data gives a feel for the evidence and trajectory of the cohort as a whole and a top-level of view of each teams progress.

leaderboard moneyball

Next, we have each team update their Business Model Canvas weekly based on the 10+ customer interviews they’ve completed.

canvas updates moneyball

The canvas updates are driven by the 10+ customer interviews a week each team is doing. Teams document each and every customer interaction in a Discovery Narrative. These interactions provide feedback and validate or invalidate each hypothesis.

disovery 10 moneyball

Underlying the canvas is an Activity Map which shows the hypotheses tested and which have been validated or invalidated.

activty updates moneyball

All this data is rolled into a Scorecard, essentially a Kanban board which allows the teams to visualize the work to do, the work in progress and the work done for all nine business model canvas components.

scorecard update moneyball

Finally the software rolls all the data into an Investment Readiness Level score.

IRL

MoneyBall
At first glance this process seems ludicrous. Startup success is all about the team. Or the founder, or the product, or the market – no metrics can measure those intangibles.

Baseball used to believe that as well. Until 2002 – when the Oakland A’s’ baseball team took advantage of analytical metrics of player performance to field a team that competed successfully against much richer competitors.

Statistical analysis demonstrated that on-base percentage and slugging percentage were better indicators of offensive success, and the A’s became convinced that these qualities were cheaper to obtain on the open market than more historically valued qualities such as speed and contact. These observations often flew in the face of conventional baseball wisdom and the beliefs of many baseball scouts and executives.

By re-evaluating the strategies that produce wins on the field, the 2002 Oakland A’s spent $41 million in salary, and were competitive with the New York Yankees, who spent $125 million.

Our contention is that the Lean Startup + Evidence based Entrepreneurship + LaunchPad Central Software now allows incubators and accelerators to have a robust and consistent data set across teams. While it doesn’t eliminate great investor judgement, pattern recognitions skills and mentoring – it does provide them the option to play Moneyball.

if you can’t see the video above click here

Last September Andy Sack, Jerry Engel and I taught our first stealth class for incubator/accelerator managers who wanted to learn how to play Moneyball.

We’re offering one again this January here.

Lessons Learned

  • It’s not clear there’s a correlation between a great PowerPoint presentation and two minute demo and building a successful business
  • We now have the tools and technology to take incubators and accelerators to the next step
  • We focus on evidence and trajectory across the business model
  • The data gathered can generate an Investment Readiness Level score for each team
  • the Lean Startup + Evidence based Entrepreneurship + LaunchPad Central Software now allows incubators and accelerators to play Moneyball

Listen to the podcast here


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Free Reprints of “Why the Lean Startup Changes Everything”

The Harvard Business Review is offering free reprints of  the May 2013 cover article, “Why the Lean Startup Changes Everything

Available here

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When Hell Froze Over – in the Harvard Business Review

Page 1 HBR with text

“I refuse to join any club that would have me as a member.”

Groucho Marx

In my 21 years as an entrepreneur, I would come up for air once a month to religiously read the Harvard Business Review. It was not only my secret weapon in thinking about new startup strategies, it also gave me a view of the management issues my customers were dealing with. Through HBR I discovered the work of Peter Drucker and first read about management by objective. I learned about Michael Porters’s five forces. But the eye opener for me was reading Clayton Christensen HBR article on disruption in the mid 1990’s and then reading the Innovators Dilemma. Each of these authors (along with others too numerous to mention) profoundly changed my view of management and strategy. All of this in one magazine, with no hype, just a continual stream of great ideas.

HBR Differences

For decades this revered business magazine described management techniques that were developed in and were for large corporations –  offering more efficient and creative ways to execute existing business models. As much as I loved the magazine, there was little in it for startups (or new divisions in established companies) searching for a business model. (The articles about innovation and entrepreneurship, while insightful felt like they were variants of the existing processes and techniques developed for running existing businesses.) There was nothing suggesting that startups and new ventures needed their own tools and techniques, different from those written about in HBR or taught in business schools.

To fill this gap I wrote The Four Steps to the Epiphany, a book about the Customer Development process and how it changes the way startups are built. The Four Steps drew the distinction that “startups are not smaller versions of large companies.” It defined a startup as a “temporary organization designed to search for a repeatable and scalable business model.” Today its concepts of  “minimum viable product,” “iterate and pivot”, “get out of the building,” and “no business plan survives first contact with customers,” have become part of the entrepreneurial lexicon. My new book, The Startup Owners Manual, outlined the steps of building a startup or new division inside a company in far greater detail.

HBR Cust DevIn the last decade it’s become clear that companies are facing continuous disruption from globalization, technology shifts, rapidly changing consumer tastes, etc. Business-as-usual management techniques focused on efficiency and execution are no longer a credible response. The techniques invented in what has become the Lean Startup movement are now more than ever applicable to reinventing the modern corporation. Large companies like GE, Intuit, Merck, Panasonic, and Qualcomm are leading the charge to adopt the lean approach to drive corporate innovation. And  the National Science Foundation and ARPA-E adopted it to accelerate commercialization of new science.

Today, we’ve come full circle as Lean goes mainstream. 250,0000 copies of the May issue of Harvard Business Review go in the mail to corporate and startup executives and investors worldwide. In this month’s issue, I was honored to write the cover story article, “Why the Lean Startup Changes Everything.”  The article describes Lean as the search for a repeatable and scalable business model – and business model design, customer development and agile engineering – as the way you implement it.

I’m  proud to be called the “father” of the Lean Startup Movement. But I hope at least two—if not fifty—other catalysts of the movement are every bit as proud today. Eric Ries, who took my first Customer Development class at Berkeley, had the insight that Customer Development should be paired with Agile Development. He called the combination “The Lean Startup” and wrote a great book with that name.

HBR CanvasAlexander Osterwalder‘s inspired approach to defining the business model in his book Business Model Generation provide a framework for the Customer Development and the search for facts behind the hypotheses that make up a new venture. Osterwalder’s business model canvas is the starting point for Customer Development, and the “scorecard” that monitors startups’ progress as they turn their hypotheses about what customers want into actionable facts—all before a startup or new division has spent all or most of its capital.

The Harvard Business Review is providing free access to the cover story article, “Why the Lean Startup Changes Everything.  Go read it.

Then go do it.

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Nail the Customer Development Manifesto to the Wall

When Bob Dorf and I wrote the Startup Owners Manual we listed a series of Customer Development principles. I thought they might be worth enumerating here:

A Startup Is a Temporary Organization Designed to Search
for A
 Repeatable and Scalable Business Model

  1. There Are No Facts Inside Your Building, So Get Outside
  2. Pair Customer Development with Agile Development
  3. Failure is an Integral Part of the Search for the Business Model
  4. If You’re Afraid to Fail You’re Destined to Do So
  5. Iterations and Pivots are Driven by Insight
  6. Validate Your Hypotheses with Experiments
  7. Success Begins with Buy-In from Investors and Co-Founders
  8. No Business Plan Survives First Contact with Customers
  9. Not All Startups Are Alike
  10. Startup Metrics are Different from Existing Companies
  11. Agree on Market Type – It Changes Everything
  12. Fast, Fearless Decision-Making, Cycle Time, Speed and Tempo
  13. If it’s not About Passion, You’re Dead the Day You Opened your Doors
  14. Startup Titles and Functions Are Very Different from a Company’s
  15. Preserve Cash While Searching. After It’s Found, Spend
  16. Communicate and Share Learning
  17. Startups Demand Comfort with Chaos and Uncertainty
Quite a few people have asked for a way to remember these without having to dig through the book.  So by popular demand, here’s a poster of the Customer Development Manifesto.  You can order a copy here.
Nail it to your wall.

Nail the Manifesto to your Wall
Get your own Poster here: http://sblank.com/HpwmuN

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When It’s Darkest Men See the Stars

When It’s Darkest Men See the Stars
Ralph Waldo Emerson

This Thanksgiving it might seem that there’s a lot less to be thankful for. One out of ten of Americans is out of work. The common wisdom says that the chickens have all come home to roost from a disastrous series of economic decisions including outsourcing the manufacture of America’s physical goods. The United States is now a debtor nation to China and that the bill is about to come due. The pundits say the American dream is dead and this next decade will see the further decline and fall of the West and in particular of the United States.

It may be that all the doomsayers are right.

But I don’t think so.

Let me offer my prediction. There’s a chance that the common wisdom is very, very wrong. That the second decade of the 21st century may turn out to be the West’s and in particular the United States’ finest hour.

I believe that we will look back at this decade as the beginning of an economic revolution as important as the scientific revolution in the 16th century and the industrial revolution in the 18th century. We’re standing at the beginning of the entrepreneurial revolution. This doesn’t mean just more technology stuff, though we’ll get that. This is a revolution that will permanently reshape business as we know it and more importantly, change the quality of life across the entire planet for all who come after us.

There’s Something Happening Here, What It Is Ain’t Exactly Clear
The story to date is a familiar one. Over the last half a century, Silicon Valley has grown into the leading technology and innovation cluster for the United States and the world. Silicon Valley has amused us, connected (and separated us) as never before, made businesses more efficient and led to the wholesale transformation of entire industries (bookstores, video rentals, newspapers, etc.)

Wave after wave of hardware, software, biotech and cleantech products have emerged from what has become “ground zero” of entrepreneurial and startup culture. Silicon Valley emerged by the serendipitous intersection of:

  • Cold war research in microwaves and electronics at Stanford University,
  • a Stanford Dean of Engineering who encouraged startup culture over pure academic research,
  • Cold war military and intelligence funding driving microwave and military products for the defense industry in the 1950’s,
  • a single Bell Labs researcher deciding to start his semiconductor company next to Stanford in the 1950’s which led to
  • the wave of semiconductor startups in the 1960’s/70’s,
  • the emergence of venture capital as a professional industry,
  • the personal computer revolution in 1980’s,
  • the rise of the Internet in the 1990’s and finally
  • the wave of internet commerce applications in the first decade of the 21st century.

The pattern for the valley seemed to be clear. Each new wave of innovation was like punctuated equilibrium – just when you thought the wave had run its course into stasis, a sudden shift and radical change into a new family of technology emerged.

The Barriers to Entrepreneurship
While startups continued to innovate in each new wave of technology, the rate of innovation was constrained by limitations we only now can understand. Only in the last few years do we appreciate that startups in the past were constrained by:

  1. long technology development cycles (how long it takes from idea to product),
  2. the high cost of getting to first customers (how many dollars to build the product),
  3. the structure of the venture capital industry (a limited number of VC firms each needing to invest millions per startups),
  4. the expertise about how to build startups  (clustered in specific regions like Silicon Valley, Boston, New York, etc.),
  5. the failure rate of new ventures (startups had no formal rules and were a hit or miss proposition),
  6. the slow adoption rate of new technologies by the government and large companies.

The Democratization of Entrepreneurship
What’s happening is something more profound than a change in technology. What’s happening is that all the things that have been limits to startups and innovation are being removed.  At once.  Starting now.

Compressing the Product Development Cycle
In the past, the time to build a first product release was measured in months or even years as startups executed the founder’s vision of what customers wanted. This meant building every possible feature the founding team envisioned into a monolithic “release” of the product. Yet time after time, after the product shipped, startups would find that customers didn’t use or want most of the features.  The founders were simply wrong about their assumptions about customer needs. The effort that went into making all those unused features was wasted.

Today startups have begun to build products differently.  Instead of building the maximum number of features, they look to deliver a minimum feature set in the shortest period of time.  This lets them deliver a first version of the product to customers in a fraction on the time.

For products that are simply “bits” delivered over the web, a first product can be shipped in weeks rather than years.

Startups Built For Thousands Rather than Millions of Dollars
Startups traditionally required millions of dollars of funding just to get their first product to customers. A company developing software would have to buy computers and license software from other companies and hire the staff to run and maintain it. A hardware startup had to spend money building prototypes and equipping a factory to manufacture the product.

Today open source software has slashed the cost of software development from millions of dollars to thousands. For consumer hardware, no startup has to build their own factory as the costs are absorbed by offshore manufacturers.

The cost of getting the first product out the door for an Internet commerce startup has dropped by a factor of a ten or more in the last decade.

The New Structure of the Venture Capital industry
The plummeting cost of getting a first product to market (particularly for Internet startups) has shaken up the venture capital industry. Venture capital used to be a tight club clustered around formal firms located in Silicon Valley, Boston, and New York. While those firms are still there (and getting larger), the pool of money that invests risk capital in startups has expanded, and a new class of investors has emerged. New groups of VC’s, super angels, smaller than the traditional multi-hundred million dollar VC fund, can make small investments necessary to get a consumer internet startup launched. These angels make lots of early bets and double-down when early results appear. (And the results do appear years earlier then in a traditional startup.)

In addition to super angels, incubators like Y Combinator, TechStars and the 100+ plus others worldwide like them have begun to formalize seed-investing. They pay expenses in a formal 3-month program while a startup builds something impressive enough to raise money on a larger scale.

Finally, venture capital and angel investing is no longer a U.S. or Euro-centric phenomenon. Risk capital has emerged in China, India and other countries where risk taking, innovation and liquidity is encouraged, on a scale previously only seen in the U.S.

The emergence of incubators and super angels have dramatically expanded the sources of seed capital. The globalization of entrepreneurship means the worldwide pool of potential startups has increased at least ten fold since the turn of this century.

Entrepreneurship as Its Own Management Science
Over the last ten years, entrepreneurs began to understand that startups were not simply smaller versions of large companies. While companies execute business models, startups search for a business model. (Or more accurately, startups are a temporary organization designed to search for a scalable and repeatable businessmodel.)

Instead of adopting the management techniques of large companies, which too often stifle innovation in a young start up, entrepreneurs began to develop their own management tools. Using the business model / customer development / agile development solution stack, entrepreneurs first map their assumptions (their business model) and then test these hypotheses with customers outside in the field (customer development) and use an iterative and incremental development methodology (agile development) to build the product. When founders discover their assumptions are wrong, as they inevitably will, the result isn’t a crisis, it’s a learning event called a pivot — and an opportunity to change the business model.

The result, startups now have tools that speed up the search for customers, reduce time to market and slash the cost of development.

Consumer Internet Driving Innovation
In the 1950’s and ‘60’s U.S. Defense and Intelligence organizations drove the pace of innovation in Silicon Valley by providing research and development dollars to universities, and purchased weapons systems that used the valley’s first microwave and semiconductor components. In the 1970’s, 80’s and 90’s, momentum shifted to the enterprise as large businesses supported innovation in PC’s, communications hardware and enterprise software. Government and the enterprise are now followers rather than leaders. Today, it’s the consumer – specifically consumer Internet companies – that are the drivers of innovation. When the product and channel are bits, adoption by 10’s and 100’s of millions users can happen in years versus decades.

The Entrepreneurial Singularity
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. For example, Internet commerce startups the time needed to get the first product to market has been cut by a factor of ten, the dollars needed to get the first product to market cut by a factor of ten, the number of sources of initial capital for entrepreneurs has increased by a factor of ten, etc.

And while innovation is moving at Internet speed, this won’t be limited to just internet commerce startups. It will spread to the enterprise and ultimately every other business segment.

When It’s Darkest Men See the Stars
The economic downturn in the United States has had an unexpected consequence for startups – it has created more of them. Young and old, innovators who are unemployed or underemployed now face less risk in starting a company.  They have a lot less to lose and a lot more to gain.

If we are at the cusp of a revolution as important as the scientific and industrial revolutions what does it mean? Revolutions are not obvious when they happen. When James Watt started the industrial revolution with the steam engine in 1775 no one said, “This is the day everything changes.”  When Karl Benz drove around Mannheim in 1885, no one said, “There will be 500 million of these driving around in a century.” And certainly in 1958 when Noyce and Kilby invented the integrated circuit, the idea of a quintillion (10 to the 18th) transistors being produced each year seemed ludicrous.

Yet it’s possible 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.

One that our children will look back on and marvel that when it was the darkest, we saw the stars.

Happy Thanksgiving.
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Crisis Management by Firing Executives – There’s A Better Way

Insanity is doing the same thing over and over again and expecting different results.
Albert Einstein

For decades startups were managed by pretending the company would follow a predictable path (revenue plan, scale, etc.) and being continually surprised when it didn’t.

That’s the definition of insanity. Luckily most startups now realize there is a better way.

Startups Are Not Small Versions of Large Companies
As we described in previous posts, startups fail on the day they’re founded if they are organized and managed like they are a small version of a large company. In an existing company with existing customers you 1) understand the customers problem and 2) since you do, you can specify the entire feature set on day one. But startups aren’t large companies, but for decades VC’s insisted that startups organize and plan like they were.

These false assumptions – that you know the customer problem and product features – led startups to organize their product introduction process like the diagram below – essentially identical to the product management process of a large company. In fact, for decades if you drew this diagram on day one of a startup VC’s would nod sagely and everyone would get to work heading to first customer ship.


The Revenue Plan – The Third Fatal Assumption
Notice that the traditional product introduction model leads to a product launch and the execution of a revenue plan. The revenue numbers and revenue model came from a startups original Business Plan. A business plan has a set of assumptions (who’s the customer, what’s the price, what’s the channel, what are the product features that matter, etc.) that make up a business model. All of these initial assumptions must be right for the revenue plan to be correct. Yet by first customer ship most of the business model hasn’t been validated or tested. Yet startups following the traditional product introduction model are organized to execute the business plan as if it were fact.

Unless you were incredibly lucky most of your assumptions are wrong. What happens next is painful, predictable, avoidable, yet built into to every startup business plan.

Ritualized Crises
Trying to execute a startup revenue plan is why crises unfold in a stylized, predicable ritual after first customer ship.

You can almost set your watch to six months or so after first customer ship, when Sales starts missing its “numbers,” the board gets concerned and Marketing tries to “make up a better story.” The web site and/or product presentation slides start changing and Marketing and Sales try different customers, different channels, new pricing, etc. Having failed to deliver the promised revenue, the VP of Sales in a startup who does not make the “numbers” becomes an ex-VP of Sales. (The half-life of the first VP of sales of a startup is ~18 months.)

Now the company is in crisis mode because the rest of the organization (product development, marketing, etc.) has based its headcount and expenses on the business plan, expecting Sales to make its numbers. Without the revenue to match its expenses, the company is in now danger of running out of money.

Pivots By Firing Executives
A new VP of Sales (then VP of Marketing, then CEO) looks at their predecessors’ strategy, and if they are smart, they do something different (they implement a different pricing model, pick a new sales channel, target different customers and/or partners, reformulate the product features, etc.)

Surprisingly we have never explicitly articulated or understood that what’s really happening when we hire a new VP or CEO in a startup is that the newly hired executive is implicitly pivoting (radically changing) some portion of the business model.  We were changing the business model when we changed executives.

Startups were pivoting by crisis and firing executives.  Yikes.

Business Model Design and Customer Development Stack
The alternative to the traditional product introduction process is the Business Model Design and Customer Development Stack. It assumes the purpose of a startup is the search for a business model (not execution.) This approach has a startup drawing their initial business model hypotheses on the Business Model Canvas.

Each of the 9 business model building blocks has a set of hypotheses that need to be tested. The Customer Development process is then used to test each of the 9 building blocks of the business model. Each block in the business model canvas maps to hypotheses in the Customer Discovery and Validation steps of Customer Development.

Simultaneously the engineering team is using an Agile Development methodology to iteratively and incrementally build the Minimum Feature Set to test the product or service that make up the Value Proposition.

Pivots Versus Crises
If we accept that startups are engaged in the search for a business model, we recognize that radical shifts in a startups business model are the norm, rather than the exception.

This means that instead of firing an executive every time we discover a faulty hypothesis, we expect it as a normal course of business.

Why it’s not a crisis is that the Customer Development process says, “do not staff and hire like you are executing. Instead keep the burn rate low during Customer Discovery and Validation while you are searching for a business model.”  This low burn rate allows you to take several swings at the bat (or shots on the goal, depending on your country.) Each pivot gets you smarter but doesn’t put you out of business. And when you finally find a scalable and repeatable model, you exit Customer Validation, pour on the cash and scale the company.

Lessons Learned

  • “I know the Customer problem” and “I know the features to build” are rarely true on day one in a startup
  • These hypotheses lead to a revenue plan that is untested, yet becomes the plan of record.
  • Revenue shortfalls are the norm in a startup yet they create a crisis. 
  • The traditional solution to a startup crisis is to remove executives. Their replacements implicitly iterate the business model.
  • The alternative to firing and crises is the Business Model/Customer Development process.
  • It says faulty hypotheses are a normal part of a startup
  • We keep the burn rate low while we search and pivot allowing for multiple iterations of the business model.
  • No one gets fired.

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Entrepreneurship as a Science – The Business Model/Customer Development Stack

Over the last 50 years engineers have moved from building computers out of individual transistors to building with prepackaged logic gates. Then they adopted standard microprocessors (e.g. x86, ARM.) At the same time every computer company was writing its own operating system.  Soon standard operating systems (e.g. Windows, Linux) emerged. In the last decade open source software (e.g LAMP) emerged for building web servers.

Each time a standard solution emerged, innovation didn’t stop. It just allowed new innovation to begin at a higher level.

In this post I want offer a solution stack for Entrepreneurship. It’s the combination of Business Model Design and Customer Development.

Business Model Design
Today every business organization from startup to large company uses the words “business model.”  Some use it with certainty like they know what it means. Others use it with an implied question mark realizing they don’t have a clue to its components.

Alexander Osterwalder and Yves Pigneur defined a business model as how an organization creates, delivers, and captures value. More importantly they showed how any company’s business model could be defined in 9 boxes. It’s an amazing and powerful tool.  It instantly creates a shared visual language while defining a business.  Their book “Business Model Generation,” is the definitive text on the subject.  (And their forthcoming Business Model Toolbox is a killer iPad app for business strategy.)

Business Model Canvas

Yet as powerful as the Business Model Canvas (a template with the nine blocks of a business model) is, at the end of the day it was a tool for brainstorming hypotheses without a formal way of testing them.

Business Model Design Gets Dynamic, Customer Development Gets Strategic
One of the key tenets of Customer Development is that your business model is nothing more than a set of untested hypotheses.  Yet Customer Development has no structured and systematic way of describing a business model.

In the last year I found that the Osterwalder Business Model canvas could be used for something much more than a static planning tool.  I realized that it was the launch-pad for setting up the hypotheses to test, and a scorecard for visually tracking iterations and Pivots during Customer Discovery and Validation.

Meanwhile on the other side of the world Alexander Osterwalder was coming to the same conclusion: tying the two processes together would create a “strategy stack for entrepreneurship.”  We got together this weekend (along with our partners Alan Smith and Bob Dorf and my student Max Marmer) to try to integrate the two.

Business Model Design Meets Customer Development
In its simplest form the way to think about the intersection of the two processes is that you start by designing your business model.  Next, each one of the 9 business model canvas boxes then directly translates into a set of Customer Discovery hypotheses that are described in Customer Development and the Four Steps to the Epiphany.

Business Model Design meets Customer Development

Pivots and Iterations
Many entrepreneurs assume that the assumptions in their original business model (or business plan if they wrote one) will be correct.  Confronting the reality that one of these hypotheses is wrong (finding out you have the wrong sales channel, revenue model, target market or customer) creates a crisis.

Pivots are Business Model Insights

Tying Osterwalder’s Business Model Canvas with the Customer Development process turns these potential crises into learning opportunities called the Pivot. Customer Development forces you to get out of the building and discover and validate each one of the assumptions behind the business model. A Pivot is when reality leads you to change one or more business model hypotheses.  The result is an updated business model not a fired VP of Sales.

The Pivot turns a failed business model hypotheses into insight.

The Business Model/Customer Development Stack
We’ll have more to say about combing these two methodologies in future posts.

Lessons Learned

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The Phantom Sales Forecast – Failing at Customer Validation

Startup CEO’s can’t delegate sales and expect it to happen. Customer Validation needs to have the CEO actively involved.

Here’s an example in a direct sales channel.

Customer Development Diagnostics over Lunch
A VC asked me to have lunch with the CEO of  a startup building cloud-based enterprise software. (Boy did I feel like Rip Van Winkle.) The board was getting nervous as the company was missing its revenue plan.

These lunches always start with the CEO looking like they had much better things to do. Before lunch even came the CEO ticked off the names of forty or so customers he talked to during the company’s first nine months and gave me a great dissertation on the day-in-the-life of his target customers and what their problems were. He went through his product feature by feature and matched them to the customer problems. He talked about how his business model would make money and how the prospects he talked to seem to agree with his assumptions.

It certainly sounded like he had done a great job of Customer Discovery.

Sales Process
Next, he took me through his sales process. They had five salespeople supported by two in marketing. (They had beta customers, using but not paying for the product.)

Over lunch the CEO told me he had stopped talking to customers since he had been tied up helping get the product out the door and his VP of Sales (a successful sales executive from a large company) had managed the sales process for the last six months. In fact, the few times he had asked to go out in the field the VP of Sales said, “Not yet, I don’t want to waste your time.”

Too Good to Be True
For the first time I started squirming in my seat. He said, “I insist on getting weekly status reports with forecasted deal size and probability of close. We have a great sales pipeline.” When I asked how close any of the deals on the forecast were to getting closed, he assured me the company’s two beta customers—well-known companies that would be marquee accounts if they closed—were imminent orders.

“How do you know this?” I asked. “Have you heard it personally from the customers?”

Now it was his turn to squirm a bit. “No, not exactly,” he replied, “but our VP of Sales assures me we will have a purchase order in the next few weeks or so.”

I put my fork down. Very few large companies write big checks to unknown startups without at least meeting the CEO. When I asked if he could draw the sales road map for these two accounts that were about to close, he admitted he didn’t know any of the details, given it was all in the VP of Sales’ head. Since we were running out of time, I said, “Your sales pipeline sounds great. In fact, it sounds too good to be true. If you really do close any of these accounts, my hat is off to you and your sales team. If, as I suspect they don’t close, do me a favor.”

“What’s that?” He asked, looking irritated.

“You need to pick up the phone and call the top five accounts on your sales pipeline. Ask them this question: if you gave them your product today for free, are they prepared to install and use it across their department and company? If the answer is no, you have absolutely no customers on your forecast who will be prepared to buy from you in the next six months.”

He smiled and stuck me with the tab for lunch. I didn’t expect to hear from him ever again.

What If the Price Were Zero?
Less than two weeks later, I got a call and was surprised to hear the agitated voice of the CEO. “Steve, our brand-name account, the one we have been working on for the last eight months, told us they weren’t going to buy the product this year. They just didn’t see the urgency.” Listening, I got the rest of the story.

“When my VP of Sales told me that,” he said, “I got on the phone and spoke to the account personally. I asked them your question—would they deploy the product in their department or company if the price were zero? I’m still stunned by the answer. They said the product wasn’t mission critical enough for their company to justify the disruption.”

“Wow, that’s not good,” I said, trying to sound sympathetic.

“It only gets worse,” he said. “Since I was hearing this from one of the accounts my VP of Sales thought was going to close, I insisted we jointly call our other ‘imminent’ account. It’s the same story as the first. Then I called the next three down the list and got essentially the same story. They all think our product is ‘interesting,’ but no one is ready to put serious money down now. I’m beginning to suspect our entire forecast is not real. What am I going to tell my board?”

My not-so-difficult advice was that he was going to have to tell his board exactly what was going on. But before he did, he needed to understand the sales situation in its entirety, and then come up with a plan for fixing it. Then he was going to present both the problem and suggested fix to his board. (You never want a board to have to tell you how to run your company. When that happens, it’s time to update your resume.)

The Phantom Sales Forecast
The implications of a phantom sales forecast meant something fundamental was broken. In talking to each of his salespeople, he discovered the sales team had no standardized sales process. Each was calling on different levels of an account and trying whatever seemed to work best. This was just a symptom of something deeper –  while they thought they understood the target customer their initial hypotheses from Customer Discovery were wrong. But no one had told the CEO.

He realized the company was going to have to start from scratch, Pivot back to Customer Discovery and find out how to develop a sales road map. He presented his plan to the board, fired the VP of Sales and kept his best salesperson and the marketing VP. Then he went home, kissed his family goodbye, and went out to the field to discover what would make a customer buy. His board wished him luck and started the clock ticking on his remaining tenure. He had six months to get and close customers.

Customer Validation
The CEO had discovered what happens when you do a good job on Customer Discovery but get too “busy” for to personally get involved in Customer Validation. It wasn’t that he didn’t need a VP of Sales, but he had entirely outsourced the Validation step to him. Until a scalable and repeatable business model is found the CEO needs to be intimately involved in the sales process.

Lessons Learned

  • Ownership of Customer Validation belongs to the CEO.
  • A VP of Sales can assist but the CEO needs to answer:
  • Do I understand the sales process in detail?
  • Is the sales process repeatable?
  • Can I prove it’s repeatable? (Proof are multiple full-price orders in sufficient quantity.)
  • Can we get these orders with the current product and release spec?
  • Do we have a workable sales and distribution channel?
  • Am I confident we can scale a profitable business?

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No One Wins In Business Plan Competitions

Last week one of the schools I teach at invited me to judge a business plan contest. I suggested that they first might want to read my post on why business plans are a poor planning and execution tool for startups. They called back laughing and the invitation disappeared.

At best I think business plan competitions are a waste of time. But until now I haven’t been able to articulate a framework of why or had a concrete suggestion of what to replace them with.

Now I do.

Business Plan Versus Business Models
Where did the idea that startups write business plans come from?  A business plan is the execution document that large companies write when planning product-line extensions where customer, market and product features are known. The plan describes the execution strategy for addressing these “knowns.”  In the early days of venture capital, investors and entrepreneurs were familiar with the format of business plans from large company and adopted it for startups. Without much thought it has been used ever since.

It turns out that’s a mistake.  A startup is not executing a series of knowns. Most startups are facing unknown customer needs, an unknown product feature set and is an organization formed to search for a repeatable and scalable business model.  That means that writing a static business plan adds no value to starting a company, as the plan does not represent the iterative nature of the search for the model. A simple way to think about it is that in a startup no business plan survives first contact with customers.

Instead of business plans I have suggested that startups use business models.

Business models are dynamic and reflect the iterative reality that startups face. Business models allow agile and opportunistic founders to keep score of the Pivots in their search for a repeatable business model.

Business Plan Competitions are Great for Schools and Bad For Students
Almost every university, region and car wash now has a business plan competition; the rules, who can participate, how large the prizes and who are the judges vary by school.

Business plan competitions perpetuate everything that is wrong about trying to make plans that were designed to be used in large companies fit startups. (One of my favorites: “Judging will include such factors as: Market opportunity, reward to risk, strategy, implementation plan, financing plan, etc.”) All of which may be true in large companies. But little of it is relevant to the chaos and uncertainty in the life of a startup.

Yet an ever increasing number of schools keep holding Business Plan competitions.  Why?

  • They’re a match for the “How to write a business plan” classes that are offered.
  • It makes the school appear relevant to their constituencies; students, donors, faculty, VC’s.
  • Business plans are easy to grade, score and judge.
  • Schools can get Venture Firms to fund prizes for the best business plan.
  • Venture Firms use the contests as another source of deal flow and talent.
  • There is no alternative.

The irony is that business plan competitions ought to be held for plans from large companies not for startups.

The Alternative – Business Model Competitions
I’ll offer that to be useful for startups Business Plan competitions need to turn into Business Model competitions. A Business Model competition has a radically different goal than writing a business plan.  The Business Model competition measures how well students learn how to Pivot by getting outside the building (not by writing a plan inside one.)

Each team would be judged by their business model presentation on these five steps.

  1. What did you initially think your initial business model was? (initial business model hypotheses)
  2. What did you build/do? (built first product, talked to users, etc.)
  3. What did you learn outside the building? (parts of our feature set/business model were wrong)
  4. Then what did you do? (iterated product, changed business model, etc.)
  5. Repeat steps 1-4

The business model would be scored and judged based on steps 3 and 4.  And extra credit for multiple times through the loop.

For the first time we’d have a competition that closely resembled the reality that founders face, rather than a creative writing exercise.

There are now examples of business model presentations on the web. They were also at the heart of the Startup Lessons Learned conference.

——–

I’ll be happy to hand out the prizes at the first competition.  Lets call it the “Pivot Award for Excellence.”

Lessons Learned

  • Business plans are the wrong tool to search for a startup business model
  • They are best suited for large companies
  • Yet we have startup business plan contests
  • Experienced entrepreneurs know that business model iteration and validation occurs outside the building
  • Some school will be first to hold a contest that rewards what matters

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Why Accountants Don’t Run Startups

This week I’m at the California Coastal Commission hearing in Ventura California wearing my other hat as a public official for the State of California.  After the hearing I drove up to Santa Barbara to give a talk to a Lean Startup Meetup.

The talk, “Why Accountants Don’t Run Startups” summarized my current thinking about startups, how and why they’re different than large companies and for good measure threw in a few thoughts about entrepreneurial education.

It was a dry run of a talk I’ll be giving at Eric Ries’ Startup Lessons Learned conference April 23 2010 in San Francisco (streaming and simulcast across the world.)  I’m a small part of what’s shaping up to be a spectacular conference and an all-star cast.

The talk is below.

Update: I’ve updated the slides to the latest version of the talk. The original can still be found here.

Why Startups are Agile and Opportunistic – Pivoting the Business Model

Startups are the search to find order in chaos.
Steve Blank

At a board meeting last week I watched as the young startup CEO delivered bad news. “Our current plan isn’t working. We can’t scale the company. Each sale requires us to handhold the customer and takes way too long to close.  But I think I know how to fix it.” He took a deep breath, looked around the boardroom table and then proceeded to outline a radical reconfiguration of the product line (repackaging the products rather than reengineering them) and a change in sales strategy, focusing on a different customer segment. Some of the junior investors blew a gasket. “We invested in the plan you sold us on.” A few investors suggested he add new product features, others suggested firing the VP of Sales. I noticed that through all of this, the lead VC just sat back and listened.

Finally, when everyone else had their turn, the grey-haired VC turned to the founder and said, “If you do what we tell you to do and fail, we’ll fire you. And if you do what you think is right and you fail, we may also fire you. But at least you’d be executing your plan not ours. Go with your gut and do what you think the market is telling you.  That’s why we invested in you.”  He turned to the other VC’s and added, “That’s why we write the checks and entrepreneurs run the company.”

The Search for the Business Model
A startup is an organization formed to search for a repeatable and scalable business model.

Investors bet on a startup CEO to find the repeatable and scalable business model.

Unlike the stories in the popular press, entrepreneurs who build successful companies don’t get it right the first time. (That only happens after the fact when they tell the story.) The real world is much, much messier.  And a lot more interesting. Here’s what really happens.

Observe, Orient, Decide and Act
Whether they’re using a formal process to search for a business model like Customer Development or just trial and error, startup founders are intuitively goal-seeking to optimize their business model. They may draw their business model formally or they may keep the pieces in their head. In either case founders who succeed observe that something isn’t working in their current business model, orient themselves to the new facts, decide what part of their business model needs to change and then act decisively.

(A U.S. Air Force strategist, Colonel John Boyd, first described this iterative Observe, Orient, Decide and Act (OODA) loop. The Customer Development model that I write and teach about is the entrepreneur’s version of Boyds’ OODA loop.)

Pivoting the Business Model
What happens when the startup’s leader recognizes that the original business model model is not working as planned? In traditional startups this is when the VP of Sales or Marketing gets fired and the finger-pointing starts. In contrast, in a startup following the Customer Development process, this is when the founders realize that something is wrong with the business model (because revenue is not scaling.) They decide what to change and then take action to reconfigure some part(s) of their model.

The Customer Development process assumed that many of the initial assumptions about your business model would probably be wrong, so it built in a iteration loop to fix them. Eric Ries coined this business model iteration loop – the Pivot.

(One of the Pivot’s positive consequences for the startup team is realizing that a lack of scalable revenue is not the fault of Sales or Marketing or Engineering departments – and the solution is not to fire executives – it’s recognizing that there’s a problem with the assumptions in the initial business model.)

Types of Pivots
“Pivoting” is when you change a fundamental part of the business model. It can be as simple as recognizing that your product was priced incorrectly. It can be more complex if you find the your target customer or users need to change or the feature set is wrong or you need to “repackage” a monolithic product into a family of products or you chose the wrong sales channel or your customer acquisition programs were ineffective.

If you draw your business model, figuring out how to Pivot is simpler as you can diagram the options of what to change. There are lots of books to help you figure out how to get to “Plan B,” but great entrepreneurs (and their boards) recognize that this process needs to occur rapidly and continuously.

Operating in Chaos + Speed + Pivots = Success
Unlike a large profitable company, startups are constrained by their available cash. If a startup does not find a profitable and scalable business model, it will go out of business (or worse end up in the “land of the living dead” eking out breakeven revenue.)  This means CEO’s of startups are continually looking to see if they need to make a Pivot to find a better model. If they believe one is necessary, they do not hesitate to make the change. The search for a profitable and scalable business model might require a startup is make multiple pivots – some small adjustments and others major changes.

As a founder, you need to prepare yourself to think creatively and independently because more often than not, conditions on the ground will change so rapidly that your original well-thought-out business model will quickly become irrelevant.

Summary
Startups are inherently chaotic. The rapid shifts in the business model is what differentiates a startup from an established company. Pivots are the essence of entrepreneurship and the key to startup success. If you can’t pivot or pivot quickly, chances are you will fail.

Pivot.

Lessons Learned

  • A startup is an organization formed to search for a repeatable and scalable business model.
  • Most startup business models are initially wrong.
  • The process of iteration in search of the successful business model is called the Pivot.
  • Pivots need to happen quickly, rapidly and often.
  • At the seed stage, microcap funds/ superangels understand that companies are still searching for a business model – they get Pivots.
  • Most of the time when startups go out for Series A or B round, the VC assumption is that a scalable business model has already been found.
  • Pivots are why startups must be agile and opportunistic and why their cultures are different from large companies.

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No Plan Survives First Contact With Customers – Business Plans versus Business Models

No campaign plan survives first contact with the enemy
Field Marshall Helmuth Graf von Moltke

I was catching up with an ex-graduate student at Café Borrone, my favorite coffee place in Menlo Park. This was the second of three “office hours” I was holding that morning for ex students. He and his co-founder were both PhD’s in applied math who believe they can make some serious inroads on next generation search. Over coffee he said, “I need some cheering up.  I think my startup is going to fail even before I get funded.” Now he had my attention. I thought his technology was was potentially a killer app. I put down my coffee and listened.

He said, “After we graduated we took our great idea, holed up in my apartment and spent months researching and writing a business plan. We even entered it in the business plan competition. When were done we followed your advice and got out of the building and started talking to potential users and customers.” Ok, I said, “What’s the problem?” He replied, “Well the customers are not acting like we predicted in our plan!  There must be something really wrong with our business. We thought we’d take our plan and go raise seed money. We can’t raise money knowing our plan is wrong.”

I said, “Congratulations, you’re not failing, you just took a three and a half month detour.”

Here’s why.

No Plan Survives First Contact With Customers
These guys had spent 4 months writing a 60-page plan with 12 pages of spreadsheets. They collected information that justified their assumptions about the problem, opportunity, market size, their solution and competitors and their team, They rolled up a 5-year sales forecast with assumptions about their revenue model, pricing, sales, marketing, customer acquisition cost, etc. Then they had a five-year P&L statement, balance sheet, cash flow and cap table. It was an exquisitely crafted plan. Finally, they took the plan and boiled it down to 15 of the prettiest slides you ever saw.

The problem was that two weeks after they got out of the building talking to potential customers and users, they realized that at least 1/2 of their key assumptions in their wonderfully well crafted plan were wrong.

Why a business plan is different than a business model
As I listened, I thought about the other startup I had met an hour earlier. They also had been hard at work for the last 3½ months. But they spent their time differently. Instead of writing a full-fledged business plan, they had focused on building and testing a business model.

A business model describes how your company creates, delivers and captures value. It’s best understood as a diagram that shows all the flows between the different parts of your company. This includes how the product gets distributed to your customers and how money flows back into your company. And it shows your company’s cost structures, how each department interacts with the others and where your company can work with other companies or partners to implement your business.

This team had spent their first two weeks laying out their hypotheses about sales, marketing, pricing, solution, competitors, etc. and put in their first-pass financial assumptions. It took just five PowerPoint slides to capture their assumptions and top line financials.

This team didn’t spend a lot of time justifying their assumptions because they knew facts would change their assumptions. Instead of writing a formal business plan they took their business model and got out of the building to gather feedback on their critical hypotheses (revenue model, pricing, sales, marketing, customer acquisition cost, etc.) They even mocked up their application and tested landing pages, keywords, customer acquisition cost and other critical assumptions. After three months they felt they had enough preliminary customer and user data to go back and write a PowerPoint presentation that summarized their findings.

This team had wanted to have coffee to chat about which of the four seed round offers they had received they should accept.

A plan is static, a model is dynamic
Entrepreneurs treat a business plan, once written as a final collection of facts. Once completed you don’t often hear about people rewriting their plan. Instead it is treated as the culmination of everything they know and believe.  It’s static.

In contrast, a business model is designed to be rapidly changed to reflect what you find outside the building in talking to customers.  It’s dynamic.

“So do you mean I should never have written a business plan?” asked the founder who had spent the time crafting the perfect plan. “On the contrary,” I said. “Business plans are quite useful. The writing exercise forces you to think through all parts of your business. Putting together the financial model forces you to think about how to build a profitable business. But you just discovered that as smart as you and your team are, there were no facts inside your apartment. Unless you have tested the assumptions in your business model first, outside the building, your business plan is just creative writing.

(Next post: Iterating the Business Model – The Pivot.)

Lessons Learned

  • A startup is an organization formed to search for a repeatable and scalable business model.
  • There are no facts inside your building, so get outside and get some.
  • Draw and test the Business Model first, the Business Plan then follows.
  • Few if any investors read your business plan to see if they’re interested in your business
  • They’re a lot more interested in what you learned

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Teaching Entrepreneurship – The “Survey” Class

The Fundamentals of Technology Entrepreneurship course at Stanford taught undergraduates how to take a technical idea and turn it into a profitable and scalable company. By getting out of the building on a team project, the class helped students viscerally understand that a startup is a search for a profitable business model. Students formed teams, came up with a business idea then talked to customers, vendors and sales channel partners to validate their business model. (And learned how to pivot their model as reality intruded.)

For undergraduates taking multiple classes finding the time to do it well was tough. But for those with full time jobs this class was a disaster.

Too Much
The first time I taught the Fundamentals of Technology Entrepreneurship class, a quarter of the class were foreign students in a special engineering-entrepreneurship program where they took one entrepreneurship class each quarter at Stanford while working full time in technology startups in Silicon Valley. The Fundamentals of Technology Entrepreneurship was intended to be their introduction to entrepreneurship. However, working full time while simultaneously attempting to participate in a team based project and Customer Discovery outside the classroom just didn’t work. The foreign students felt overwhelmed and the full time Stanford students thought they weren’t carrying their weight (when in fact they were carrying much, much more.)

We quickly realized we needed a different class to introduce entrepreneurship to students who were already knee deep in working in a startup 24/7.

Design a New Class Around Entrepreneurial Guest Speakers
Brainstorming with Tina Seelig we came up with the idea of a survey course – an introduction to entrepreneurship built around Stanford’s Entreprenuerial Thought Leaders speakers series which brings technology speakers to campus every week. In this survey course, the students would listen to the speakers and then attend twice-weekly classes which focused on the basic concepts of a startup (demand creation, sales, partnerships, team building, financing, etc.) We’d use the lectures and guest speakers to help students new to the field understand that a startup is simply a temporary organization to search for a repeatable and profitable business model.  Then we’d have the students interact directly with entrepreneurs and industry leaders in the classroom.

The Spirit of Entrepreneurship – An Interactive Survey Class
We christened the class The Spirit of Entrepreneurship. Open to all students at Stanford it was taught as two, one-hour sessions, one held the day before the guest speaker and one immediately after each guest speaker. To prepare for each speaker, we asked students to analyze the speakers company over the weekend. (For the students who were working full-time this schedule gave them the time they needed to complete their analysis.)

This new class also appealed to a wide variety of non-engineering Stanford students. In addition to the overseas work/study students I found myself teaching history majors, English majors, education majors, et al who were interested in getting their toes wet but weren’t sure they wanted to commit to the hardcore Fundamentals of Technology Entrepreneurship course.

Each week the students had to submit a two-page analysis of the presenting company’s business model, distribution channels, demand creation activities, and engineering. As some of the companies were already large, the students had to find out how the founders discovered their business model, built their team and got funded.

Since I did not select the guest speakers, the course turned into a continual improv session as I tried to match my lectures to the unpredictable variety of industries (biotech, enterprise software, video games, media, web 2.0, etc.) and different life cycle stages of the guest speakers’ companies (startup to 20+billion.)

Guest Speakers
The students saw the guests speak before a live-audience of several hundred of their fellow Stanford students.  (The videos of these speakers are edited, indexed and available as 1600 free videos and podcasts as part of Stanford’s E-Corner, on-line here.)

The heart of the class and its improvisational nature came when every speaker agreed to walk over to our classroom and sit and chat with our class one-on-one for an hour. I would interview them for the first 20 minutes or so and then turn the questioning over to the class. This personal first-hand interaction with entrepreneurs created lots of opportunity for insights. For example, hearing David Heinemeir Hannson of 37Signals talk about why his company will never get “big” and then have Steve Case of AOL/TimeWarner talk the next week about why his did helped students understand that there is no “right answer”. Similarly having the students question Trip Adler from Scribd one week about why posting documents on-line is the future and hearing from Rashmi Sinha and Jonathan Boutelle of Slideshare the next week remind us that it’s all about PowerPoints, vividly demonstrated that entrepreneurs can interpret the same market in very different ways.

Dinners
I spent quite a few dinners with my students in this class. The Stanford students were curious whether startups were for them and we talked about whether entreprenuers are born or can be made (the nature versus nurture debate.) The overseas students were trying to make sense of Silicon Valley, its work ethic and how its entrepreneurial culture would fit back home. In Silicon Valley we take for granted that someone who failed in their previous company is considered an “experienced entrepreneur.”  I was reminded that in other cultures and countries the consequences of failure are much less benign.

Lessons Learned

  • Entrepreneurship is an art not a science.
  • Entrepreneurship is driven by people as well as business models.
  • Entrepreneurship only thrives in a culture that does not penalize risk-taking or failure.
  • There is no “right path” to success

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Teaching Entrepreneurship – Logistics

Back from a family humanitarian trip/vacation to one of the last bastions of Communism where “marketing” isn’t even a profession and entrepreneurship is a crime.  The irony is that the “Revolutionary Square” in all these Communist countries will be the the first place the McDonald’s go when the system collapses.

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In my last post I described my approach to one of the three classes I teach at Stanford in the engineering school: Fundamentals of Technology Entrepreneurship.  The key things I want students to take from the class are:

  • Understand that a startup is a temporary organization designed to search for a profitable business model
  • Learn how to put together a business model, not a business plan
  • Understand that a business model is only a series of hypotheses that need to be validated outside the building

Class Logistics
As described in the previous post, this is a hands-on class. The 55 students formed 11 teams, and each team had to come up with an original idea, size the opportunity, propose a Business Model, get out of the building and test their hypotheses and analyze and explain each of the parts of their model.

The class wouldn’t have been possible without lots of hands other than mine.

Teaching Team
Having a teaching partner makes life a lot easier and the class improves. A partner allows me the flexibility to miss a session or two (my job as a California Coastal Commissioner meets three days every month up and down the coast of California.)  But the best benefit is bringing a second set of eyeballs to the curriculum which always makes it better.

This was the year I finally got the “business model versus business plan” concept nailed down. In previous classes I had experimented with moving away from the traditional focus on writing a business plan to a hands-on approach to building a business model.

But it wasn’t until Ann Miura-Ko joined me as a teaching partner that this “teach the model not the plan” idea jelled. Ann who had been my Teaching Assistant while she had finished her PhD at Stanford felt the same frustration about teaching entrepreneurs to assemble a business plan that we knew in the real world wouldn’t survive first contact with customers. After Stanford, Ann joined Mike Maples’ Venture Capital firm Floodgate as a partner. Over the summer we had both been impressed with Alexander Osterwalder’s Business Model Template work. At first we thought of adopting his template for the class, but found that an even more simplified version of a canonical business model that Ann developed worked better.

Teaching Assistants
Teaching at both Stanford and Berkeley I get to see the difference between the resources in a private university and those of a state university. (For the first 5 years at Berkeley, I taught 60 students by myself with no teaching partner or teaching assistant.) As the Stanford entrepreneurship program for the engineering school sits in the Management Science and Engineering Department, most of our TA’s are students in the MS&E PhD program. For this class Daisy Chung and David Hutton were our Teaching Assistants (TA’s.) TA’s make managing 60 students working on cases and team projects manageable.

They set up and keep the class web site updated.  They provide logistical support for guest speakers. They answer enumerable emails about logistics as well as substantive questions about class content. In addition to Ann and my office hours, Daisy and David held their own office hours to provide student support.

Most importantly, while Ann I reviewed all the grades, the TA’s managed the logistics of grading: grading the homework (in this class the case study summaries) and the business model written summary, keeping track of class participation and rolling up all the grades from the formal presentation. And they gave us feedback after each class session letting us know if we were particularly incoherent and kept us abreast of the usual student and team dynamics/crisis.

Finally our TA’s managed the mentors we had supporting the students.

Mentors
One part of Silicon Valley culture that doesn’t get enough credit is the generosity of entrepreneurs and VC’s who are willing to share their time with students. Ann and I recruited VC’s and entrepreneurs to be mentors for each team. (We’ve never had a problem in getting help for these classes.) Typically we have a mix of new mentors and those who have volunteered their time before.)  I wrote a handbook for the mentors to explain their roles (here.)

Essentially mentors support and coach each team. They typically met once or twice in person with the team, help them network outside the building, answer emails, provide critiques, etc. On average, mentors spent about 6 to 8 hours of time over the quarter with students. Some even came into to class to cheer on their team for their final business model presentations.

Guest Speakers
Two important things I learned early on in teaching are: 1) regardless of how good you are, students get sick of hearing you drone on week after week, and 2) hearing a guest make a point you’ve been trying to get across often makes it stick.  So we tried to break up our lectures with guest speakers.

Ideally we attempt to match the guests with the case or class session subject. For example, when we taught the value of getting out of the building and agile development, we had Eric Ries talk about the Lean Startup. When we covered partnerships with the WebTV case, we had Spencer Tall who negotiated the deal with Sony for WebTV come in and explain to the class what really happened. (Ann also kept me in the 21st century by making sure we had several woman entrepreneurs as guest speakers.)

Results
In the last decade, entrepreneurship has become faddish, particularly in college. It’s now “cool” to be an entrepreneur, and every school wants some type of entrepreneurship course. While that’s gratifying, the fact is that most people are ill suited to survive in the wild as founders or early employees.

I taught this introductory undergraduate class without many compromises. If you want to know what being an entrepreneur is going to be like you didn’t get to sit in a classroom listening to lectures for a quarter and then write a business plan. (I also teach a less intense introduction class for engineers called the Spirit of Entrepreneurship and the Customer Development Class at Berkeley which I’ll describe in a future post.) I actually hoped that some students who were curious about entrepreneurship would discover that it is definitely not for them. Better to find it out in a classroom than as a career choice.

While that did happen to a few (some are still in shock that I “cold-call” in class, others can’t handle the team dynamics or complain that there is no “right” answer, or were disoriented that the mentors, professors and customers all had different answers) the class seems to have had the opposite effect on an interesting segment.

Sometimes you get emails like this at the end of class:

“Just want to say thank you for the “big ideas” you brought to us. Thanks to your class, I have been thinking thoroughly about my future career and have decided that I would become an entrepreneur rather than anything else. Actually I made up my mind just on my plane to my final round of interview with the Boston Consulting Group. I flew there and told the partner that I would become an entrepreneur instead.”

Oh, oh.

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Coming Soon
In the fall Ann and I are going to develop a new graduate-level class for Stanford that will take this one to the next level. Students will not only have to assemble a team, come up with the idea and leave the classroom to test the business model – they’ll need to come back with real customer orders.  (And if it’s a web-based product, they’ll have to build it.)

I wonder if we can fill the class.

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A few more of the final class presentations are here (click on the thumbnails to enlarge):

One last presentation here:


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