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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

The most important principle of start up fund raising is:

Raise enough money to achieve a set of milestones that will attract a subsequent round of investment from new investors.

Last week, a founder of a seed stage company came to pitch. When I told him the opportunity wasn’t a fit for us, he asked me what milestones he would need to achieve to raise a Series A - as he was raising a seed round! He was calibrating how much he needed to raise for in his seed to make sure he could raise a Series A.

Brokers serve two key roles within ecosystems. First, they introduce buyers and sellers. Second, they lend their expertise to help buyers and sellers make the right decisions in the market.

The internet neutralizes the first value proposition of brokers by leveling the information asymmetry between buyers and sellers at a far greater scale with much better data than any broker ever could. And for products and services with relatively small price points, commodity goods or where the cost of failure is low, market places often nullify the value (and cost) of an advisor.

Once each month I met Peter at Café Habana in Nolita for huevos rancheros drenched in tomato sauce and a glass of fresh orange juice. Mopping up yolks with tortillas, Peter and I chatted about his business: the techniques of scalable customer acquisition, the priorities of the product and engineering team, the structure of sales quotas and the ebbing and flowing dynamics of the market place he and his team were building.

Each time I open Salesforce in my browser, I think of Stephen Hawking. It’s because of an aphorism an entrepreneur shared with me a few weeks ago. He said:

The cost to fix a data error at the time of entry is $1. The cost to fix it an hour after it’s been entered is $10. And the cost to fix it several months later is $100+.

Take for example a venture capitalist’s CRM tool. If I mistype an email address or the details of the last fund raise, it might cost me a minute or two to fix it at that very moment. A minute of time is worth about $1.

The valley and startup-land does not fetishize failure despite the increasing reports to the contrary. FailCon is not the Darwin Awards for startups. Founders do not start businesses with the express interest to fail.

Instead, the valley is infatuated with the post-mortem of failures and successes alike because within every venture are pearls of wisdom - a subtle but important difference. Extracting and applying these insights can be the difference between success and failure. This is why founders pursue knowledge relentlessly. Ultimately, iteration and learning speed is the hallmark of great startup teams

To be truly successful, I believe startups should determine which of the four core disciplines is their strength: product, engineering, marketing and sales - and focus, focus, focus on leveraging that advantage in the market.

Product driven startups - At their outset Twitter, Pinterest and Instagram were exploratory products driven by their respective creators, Jack Dorsey Ben Silbermann, and Kevin Systrom, who were each product managers building a product of their own vision. The key innovations were the creation of new social environments.

Four and a half years ago, I left my role at Google as a product manager to join the team at Redpoint. The transition became the biggest professional challenge of my career up to that point. Suddenly, I was working with a smaller team, managing massive ambiguity in job definition, time allocation and decision-making, and giving up the adrenaline of launch day.

But far and away my biggest challenge was effective communication. I simply couldn’t articulate my points in convincing ways. During the first few weeks, I felt like an ineffective babbling mess. What had worked at Google was failing at Redpoint.