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In HBR this month, two British researchers reported on their study of the impact of competition on startups. In a study of over 2M companies spanning 10 years, the researchers determined that if a startup faced competition in its first year, it was more likely to fail. But if the startup survived its first year, it’s survival rate jumped nearly 30%.

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This data screams survivorship bias. Of course the startups who navigate hostile waters deftly in their first year will have a higher likelihood of success. These startups' management teams have already proven they can develop marketing and sales competencies while bringing a product to market.

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Successful startups are money machines: they ingest a dollar of investment and produce more than a dollar in revenue.

There are three steps to build a money machine:

1. Find or create a product many people will use.
2. Convince customers to buy the product.
3. Mechanize the two processes above, reducing costs and increasing profitability to finance growth.

Startups repeat these three steps many times during their lifespans. In a team of seven people, there may be five engineers building the product, one product manager marketing the product and one salesperson. But to grow to be a big company, all those teams and functions must be continuously reinvented, tuned and refined.

For sales people, social proof is one of the most powerful forms of influence, as Robert Ciadini proved in his seminal book on the topic. It’s no secret that the best leads are referrals. Second best is the friend who is a customer in common: “Oh, Peter chose Salesforce for his CRM. Maybe I should consider them too.” Social proof confers the trust of a relationship to the salesperson improving close rates.

On a Saturday morning in August of 2006, Sergey Brin and a team of Googlers flew to Los Angeles to meet Tom Anderson and his MySpace team. By the next afternoon, the two founders shook hands on a three year $900M contract. About twelve months later, I found myself as the product manager for the team in Marrakesh, Google’s executive board room, reporting the state of affairs to Eric, Larry and Sergey.

If you’re a Netflix subscriber, in all likelihood you’re a big fan of “House of Cards.” Netflix designed it that way.

With the release of “House of Cards” Netflix began the Moneyball-era of content production. The majority of Netflix subscribers watch Kevin Spacey, political thrillers and David Fincher’s movies. Guess what? “House of Cards” has all three.

In baseball, on-base percentage is the best predictive metric for team success. In content production, the best predictor is user viewership behavior.

When interviewing product managers at Google, we ranked candidates on four metrics: technical ability, communication skills, intellect and Googliness. A Googley person embodies the values of the company - a willingness to help others, an upbeat attitude, a passion for the company, and the most important, humility.

In the past week, I asked two heads of engineering to identify the most important characteristic in new hires. Both responded, “humility”. For one startup ascertaining humility is so important, it is the first filter in the interview process.

Kenny Van Zant is a marketing wizard. Before his current role at Asana, Kenny managed products and marketing for Solarwinds, a publicly traded company that sells networking equipment to the mid-market. Solarwinds pioneered the low-friction, high-velocity sales model in their segment to great success.

SolarWinds offered free products to their customers to gain usage data that informs their sales and marketing efforts. As one might expect, inside sales reps would call upon the most likely customers to up-sell them to paid. And of course, SolarWinds employed the enterprise sales team to win the business of the largest customers. Plain vanilla freemium, right?

David Brooks has a great op-ed this morning on the Philosophy of Data. He argues that data offers one major advantage and one major drawback. Data enables humans to discover patterns otherwise unobservable by our senses/intuition or patterns that violate human intuition. But the religion of data engenders a fallacy: that everything can and should be measured; and with this data, the best answer will emerge.

Belief in the power of data has become a sort of religious debate which has manifested itself in product design (data driven vs intuitive design), in politics, in baseball, in climate change debates and many others. At some level, it’s an extension of the religion/ science debate: what I feel/believe vs what my instruments indicate. Which is better?

With a litany of articles in recent months highlighting the number of companies with valuations greater than $1B, I’ve started to wonder about the valuation trends for the highest profile venture backed companies.

Venture capitalists are increasing market prices in Series A and Series B rounds aggressively in effort to reap disproportionate returns. And the variances in the prices of different startups in these early rounds is enormous, indicating a relatively inelastic market. Investors are chasing fast-growth startups irrespective of the price.

Even the greatest minds fear missing out. Nobel laureate Richard Feynman who assisted in the development of the atomic bomb, contributed substantial advances to quantum mechanics and particle physics, discovered the cause of the Challenger Shuttle disaster and popularized science as a witty and successful author, faced this fear when confronted with a menu.

How many different dishes should he order from a menu before settling upon a favorite? Feynman used probability theory to solve the problem. Below is the formula he developed with Ralph Leighton