There’s a Pattern Here

After my eighth and likely final startup, E.piphany, sitting in a ski cabin, it became clear that there is a better a way to manage startups. Joseph Campbell’s insight of the repeatable patterns in mythology is equally applicable to building a successful startup. All startups (whether a new division inside a larger corporation or in the canonical garage) follow similar patterns—a series of steps which, when followed, can eliminate a lot of the early wandering in the dark. Looking back on startups that have thrived reflect this pattern again and again and again.

So what is it that makes some startups successful and leaves others selling off their furniture? Simply this: startups are not small versions of large companies.  Yet the processes that early-stage companies were using were identical to that of large corporations. In hindsight it appeared clear that startups that survive the first few tough years do not follow the traditional product-centric launch model espoused by product managers or the venture capital community. Through trial and error, hiring and firing, successful startups all invented a parallel process to product development. In particular, the winners invent and live by a process of customer learning and discovery. It’s a process that doesn’t exist in large companies with existing customers and markets.  But it is life and death for a new venture.

I call this process “Customer Development,” a sibling to “Product Development,” and each and every startup that succeeds recapitulates it, knowingly or not.

The “Customer Development” model is a paradox because it is followed by successful startups, yet articulated by no one.  Its basic propositions are the antithesis of common wisdom yet they are followed by those who succeed.

It is the path that is hidden in plain sight.

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Out of the Ashes – Something Isn’t Quite Right

“Customer Development” was born four years earlier and 200 miles away on Sandhill Road.  I was between my 7th and 8th and final startup; licking my wounds from Rocket Science, the company I had cratered as my first and last attempt as a startup CEO. I was consulting for the two venture capital firms who between them put $12 million into my last failed startup. (My mother kept asking if they were going to make me pay the money back. When I told her they not only didn’t want it back, but were trying to see if they could give me more for my next company, she paused for a long while and then said in a very Russian accent, “Only in America are the streets paved with gold.”  It was a long way from Ellis Island.) Both venture firms sought my advice for their portfolio companies. Surprisingly, I enjoyed seeing other startups from an outsider’s perspective. To everyone’s delight (and my surprise,) I usually could quickly see what needed to be fixed. At about the same time, two newer companies asked me to join their boards.  Between the board work and the consulting, I enjoyed my first-ever corporate “out-of-body experience.”

No longer personally involved, I became a dispassionate observer. From this new vantage point I began to detect something deeper than I had ever seen before: there seemed to be a pattern in the midst of the chaos. Arguments that I had heard at my own startups seem to be repeated at others. The same issues arose time and again: big company management styles versus entrepreneurs wanting to shoot from the hip, founders versus professional managers, engineering versus marketing, marketing versus sales, missed schedule issues, sales missing the plan, running out of money, raising new money. I began to gain an appreciation of how world-class venture capitalists develop pattern recognition for these common types of problems. “Oh yes, company X, they’re having problem 343. Here are the six likely ways that it will resolve, with these probabilities.” No one was actually quite that good, but some VCs had “golden guts” for these kinds of operating issues.

Yet something in the back of my mind bothered me. If great venture capitalists could recognize and sometimes predict the types of problems that were occurring, didn’t that mean that the problems were structural rather than endemic? Wasn’t something fundamentally wrong with the way everyone organizes and manages startups? Wasn’t it possible that the problems in every startup were somehow self-inflicted and could be ameliorated with a different structure? Yet when I talked to my venture capital friends, they said, “Well, that’s just how startups work. We’ve managed startups like this forever; there is no other way to manage them.”

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The Product Development Model

I realized that traditional ways to think about startups – have an idea, raise some money, do product development, go through an alpha test, beta test and first customer ship was the canonical model of how entrepreneurs thought about early stage ventures.


This product development diagram had become part of the DNA of Silicon Valley.  So much so that after I started teaching I’d ask, “Can anybody recognize this model of startups?”  And when everyone raised their hands I used to joke, “Even the waiters in San Francisco could draw this model.”  But in 2002 a student with a pained look on his face raised his hand and said, “Well, we’re now waiters in San Francisco because we used to be CEO’s of dot-com companies.”  So I no longer make that joke.

When I looked at the diagram in that ski cabin I realized there was a fundamental question I couldn’t answer: if all startups follow that model, why is it that some companies are opening bottles of champagne at their IPO and others who almost followed the same rules are selling off their furniture?  What was the difference here?  Were all startups the same? Were startups failing because of product failures or was there some other failure mode?  Is there any way to predict success or failure?  And even more importantly, was there any way to reduce risk in early stage ventures?

That day, alone in the cabin I knew I had to find the answer.

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Retirement and Redemption

In 1999 I retired and began to reflect about my career and what had happened in the previous 21 years and eight startups in Silicon Valley.  Alone in a ski cabin with the snow coming down outside, and my wife and daughters out on the slopes all day, I started collecting my thoughts by writing a series of “lessons learned” stories that I had hoped would become my memoirs.

Eighty some pages later I realized that a) I had some great war stories as a good marketeer and failed CEO, b) I’d have to pay my wife and kids to read them, c) the three of them were probably the entire total available market, and d) when I looked at what I had done and what other entrepreneurs had done at their startups, that there was a pattern.

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