Category: Managing Startups

A Portuguese mother in labor and Throwback Innovation

The real voyage of discovery consists not in seeking new landscapes, but in having new eyes.

-Marcel Proust

One night when I was a medical student, I was doing my rotation through obstetrics at the Brigham and Women’s Hospital in Boston. It was about 8 pm at night, and I was exhausted from delivering several babies already.

Suddenly, a commotion erupted down the hall. An orderly and a nurse were wheeling in a pregnant woman. The patient was screaming incoherently, and writhing. She was obviously in tremendous pain.

We rushed to her and I set about taking her history, except… I quickly realized she sounded incoherent because she was speaking in a foreign language. She didn’t understand English.

My resident and I just stared at each other blankly, at a loss. We didn’t even know what language the woman was speaking. Then one of the delivery nurses told us the patient was speaking Portuguese.

Our nurses scattered throughout the hospital out to find a translator, and after quite a while, we located the one Brazilian nurse in the hospital who spoke Portuguese. It was a difficult delivery, and the mother was in quite a bit of distress, but fortunately the baby was healthy.

The next morning, I stood outside the room, and recited her history to the attending physician “26 year old Portuguese woman, G1P1A0 (Gravida 1, Para 1, Abortus 0, which means pregnant once, delivered one child, no abortions)…” At then end, I added, “and oh by the way, she only speaks Portuguese.”

But to our shock, when we entered the room, the new mother sat up, smiled brightly, and said “Good morning, doctors.” Surprised, and a little chagrined after I had just told my attending that she only spoke Portuguese, I said, “I thought you didn’t speak English!”

She looked puzzled, saying, “What do you mean? I was born in Portugal, but I moved to the States when I was three. I’ve forgotten all Portuguese. I only speak English.”

Indeed, she knew hardly a word of Portuguese, now that she was not in labor. But in the throes of labor, with the pain, she had forgotten all English and was tapping into Portuguese that she had learned as a child.

The point is this: in times of stress, we sometimes tap into abilities we didn’t even know we had. We are programmed to reach into our reserve and draw on talents we don’t — perhaps can’t — access under normal times. Portuguese was buried deep inside her, it had never disappeared.

History May Not Repeat, but it Rhymes

This has an important parallel in innovation.

We tend to think of great innovations as completely new inventions that have never existed before. And in some rare cases, that is true: steam engine, flight, polymerase chain reaction.

But many innovations, especially business innovations, come from reaching into the past and pulling forward into the present some innovation or business long forgotten. Just as the stress of labor allowed the re-emergence of Portuguese hidden deep into the recesses of this mother’s mind, many of the recent innovations emerged because internet allowed a previous suppressed product-market fit to re-manifest itself.

These are what I call Throwback Innovations. Like phoenixes, they are old ideas reborn. They include companies like Airbnb, Uber, Twitter, and eBay.

Let’s start with Airbnb. Almost all the people that Brian Chesky, one of the Airbnb Founders, talked to when he was starting his company thought the idea was crazy. No one thought people would want to rent out rooms in the their houses. Fewer still thought people would want to stay in other people’s houses.

The only exception was his grandfather, who said, “Of course that will work. That’s how we often used to travel when I was young – staying with people in their private houses.” (Indeed, for African Americans, sometimes the only way to travel was to stay in other people’s homes – hence the Green Book.)

Indeed, before modern hotels and motels, that’s how many people travelled – in other people’s houses. But with advent of hotel chains like Howard Johnson that offered consistent, reliable, and convenient service, the local home-stays couldn’t compete. People wanted to stay in hotels that they trusted. Mass market hotels took over. Until the advent of the Internet. Internet allowed Airbnb hosts to offer the same convenience and more importantly, trust, to travelers. It leveled the playing field and the lodging industry reverted back to the past.

One of the most important things for new tech startups is the product:market fit. They strive for, and often have difficulties with, finding a product that people want.

But, the markets are as old as the human race. Technologies change but people don’t. Airbnb didn’t discover a product market fit. It rediscovered it.

Similarly, Uber. is a reincarnation of jitneys. When cars were first invented, people would offer rides in their cars to strangers for a small fee. Often, they would race ahead of streetcars and pick up passengers waiting for the streetcars. Not surprisingly, the streetcar companies legislated the jitneys out of existence in most cities. (Although it hung on in a few cities, and in San Francisco, the birthplace of Uber an Lyft, it hung on until modern times).

Or, let’s consider Twitter. I must admit, it look me a while to understand Twitter. I didn’t understand why people used it.

Then, I realized what Twitter was: rumors.

I remembered that when I was a child growing up in pre-modern Korea, most of the important news didn’t come from newspapers or television. It came from rumors. Newspapers were censored and not reliable. And they only had 8 pages. Not much information could be crammed into a newspaper.

On the other hand, rumors were uncensored. Important news would fly on wings of rumors from one end of the country to the other in hours or minutes. People were plugged into rumor networks, and key information was transmitted from one trusted person to another like wildfire. Currency is going to be devalued. Price of heating coal is going to triple. A subway station is going to built on that block. It could make an enormous difference in lives. In times of war, it could mean life or death. The army is about to lose the city and we must flee. The bridge across the river has been destroyed.

Twitter reminds me of rumor networks – ultra-rapid, unverified (uncensored), decentralized information networks based on trusted sources. The way news was disseminated and consumed for hundreds of thousands of years. It’s a real throwback.

Similarly, eBay is a throwback to the era before packaged good era, to the times when the price of each item was separately negotiated between the shopper and the proprietor. And a throwback to the times when the reputation of each seller and buyer was known, because the communities were smaller. When reputation followed you throughout your life and therefore you guarded it with care.

And of course, Amazon did with internet and UPS what Sears did with mail order and railroads. Both became dominant because they could order broader inventory and lower prices than local merchants.


So what can we learn from this?

First, that as new technologies emerge, business models that made the most sense in a previous era can get toppled by old ideas reborn, not just by new ideas. And the forgotten old ideas may be the most potent ones–because those are the ones that are not immediately obvious to everyone.

Second, that as we search for a product:market fit, it may behoove us to look to the past to guide us. What was popular in the past, what worked in the past, may portend a new way of achieving the same.

Third, and most importantly, that history is important in innovation. History rhythms, even at the frontiers of technology. This is why when young aspiring entrepreneurs ask me what they should study if they want to do a startup, I tell them: first, study history.

Deciding to Innovate

One night many years ago, I was a second-year medical resident on duty in the emergency room. It was about 3 a.m. and things had finally slowed down after a very busy evening. Abruptly, I was jolted wide awake from an exhausted half-slumber. A nurse in the next room had shouted, “code”. That meant that a patient’s heart had stopped.

I rushed into the room, and as the first doctor on the scene, I started “running the code”: assessing the patient, calling for medicines, checking the chest compressions, and getting the paddles ready to shock. Nurses and other personnel were streaming in. In a code, the person running the code is in charge, and everyone follows his or her orders. There is no time for discussion.

I ordered the proper medicines to be administered. We shocked him. Once, twice, thrice. At 200 joules. At 300 joules. At 360 joules. His heart didn’t respond.

In a code, there is a very specific, defined protocol you follow. How much medicine to give, what kind of medicine, when to shock. We followed the algorithm exactly. He should have responded. He didn’t. There was something wrong.

We kept on shocking, and still no response. He was dying.

So, I did something not in the algorithm. He was going to die otherwise. I called for higher power on the paddles. I shocked him at a very high-power level. It was something that was not in my training. It was something that, had I consulted others, might have led to objections. But as the code leader, it was my call and others followed my lead.

And it worked. The young man regained his heartbeat. He survived.

Soon afterwards, his chest X-ray arrived. I put it up on the light-box and cocked my head. Something wasn’t right. Flipping the X-ray back and forth, I realized what was out of place. His heart was on the right side of his chest. He had dextrocardia. (1)

Consensus Decision-Making

So how does this relate to business?

In a code there is no time for debate. Only one person makes the decision. I don’t know if I could have convinced everyone that we should step outside the protocol and increase the power on the paddles. I don’t think I could have. That patient lived because we didn’t run the code with consensus decision-making.

Similarly, while there are many issues in business that require consensus decision-making, there are some challenges that can’t be addressed with it. Sometimes you need one decision maker, someone who will step forward and take a risk. Innovation is one such example. Innovation by committee is virtually impossible. (2)

At many large companies, decisions are made by consensus. Every person on the team, and there can be twenty or more people on a team, has to agree before the project can move forward. And, for each of them to agree, their functions (their bosses) have to agree.

This practice can reach extreme forms. For example, when Lou Gerstner arrived at IBM in 1993 to save the storied company from near-certain demise, he learned a new word: non-concurrence. If one person non-concurred at IBM, the entire project would grind to a halt. There was an entire formal system of non-concurrences, with non-concurrence coordinators, non-concurrence schedules, and non-concurrence resolution processes. You can imagine how that was affecting IBM’s competitive advantage.

The reason why consensus decision making doesn’t work in an innovation-based industry like pharmaceuticals is that when 90% to 95% of drugs fail, you must take calculated risks to be successful. If you rely on consensus decisions, you usually end up with the decision that the most conservative person on the team is comfortable with. This means that the decisions default to the lowest common denominator: the least risky decision.

I can’t tell you where on the spectrum of risk any given decision should sit, but what I can tell you is that in an innovation-driven industry, the least risky decision is almost never the right one. The only way to have no failures is to have no successes.

In addition, in a consensus decision-making system, the decision often ends up such that it’s a compromise between two functions. The functions often horse trade, so that the decision that is the least painful to every function is adopted, and pain of the decision is relatively equally distributed.

Once again, I can’t tell you where on the spectrum the right decision is, but what I can tell you is that the right decision is almost never at the halfway point between what two functions want. Usually, the right decision is beneficial to one function at the cost of another one. A claim for the drug, for example, may be so valuable from a commercial standpoint that the clinical group needs to conduct a difficult study. Or stability may be so fickle for a drug from a CMC standpoint that marketing needs to accept a painfully short shelf life.

In addition, because everyone is responsible for the decision, no one is. Sometimes, a decision never even gets made because no one is responsible for the “team” decision and you end up with decision paralysis. Our CSO calls this “passing the ball.” Everyone is passing the basketball and no one is taking the shot.

Vertical Consensus

And it gets worse.

In many large companies, not only do you need horizontal consensus across team members, but then you have to obtain vertical consensus. You have to go up through several layers of approval up the chain of command. And once again, I can’t tell you what the right decision is, but if six people up the chain of command all agree with the decision, it is almost never the right decision because only the least risky decision will pass muster.

If twenty people on a team agree horizontally and six people up the chain of command agree vertically that a decision is innovative, then in all likelihood the exact opposite is the case.

A Single Decision Maker

How do you avoid death by consensus? Let’s turn to the Genentech model. Genentech during the 2000’s had a run of successes. Its success rate in drug development was about 80%, which is more than an order of magnitude higher than the standard 5%-10%.

One of the keys to Genentech’s success was its decision-making process. While there were several components of the process, perhaps the most salient aspect of the decision-making process was the single decision maker model. (3)

Unlike many other companies, Genentech always had one final decision maker. Usually, but not always, the team leader had that responsibility. In some cases, the vote would be twenty to one, but if the one vote was from the decision maker, that single vote carried the day. The team leader had the authority and the responsibility to make the final decision, after listening to and weighing all arguments and data. The team members all had an opportunity to make their case. (4)

Making one person responsible for the decision accomplishes three things. First, it allows calculated risk taking. Second, it removes the burden from the other team members, removing the incentive for them to protect themselves from the consequences of the decision by being overly risk-averse. Third, it designates one person to shoot the basketball, and prevents decision paralysis.

Get Out of the Team’s Way

Does this mean that the decisions should always be made at the top?

No. The exact opposite.

I’ve tried to incorporate the Genentech decision-making philosophy wherever I go. In addition, I’ve extended the model to remove vertical consensus.

At KindredBio, the project teams know that they don’t have to obtain vertical consensus. For example, I don’t have to agree with their decisions. I only have to understand it and be satisfied that it is thoughtful. If we’ve hired the right team, and provided the right corporate context for the decision, then in cases where the team and I don’t agree on a decision, they should be right most of the time. The team spends every day thinking about the program while I spend a few hours a month thinking about the program. If I can come to a higher quality decision than they can, there is something very wrong. (5)

Most of the time, when I have supported the team leader’s decision over my own, the team leader has been right, and the projects have been great successes. In fact, I have found that if the team and I always agree on decisions, it is usually a sign that we are not taking enough risk, and not innovating enough.

Fostering innovation requires enough managerial courage to support team decisions that the senior management thinks is wrong, and enough confidence in the team to trust that they’re producing better ideas than senior management can.



(1) Dextrocardia is rare. I’ve only seen two cases of it, including this patient. You sometimes see it in identical twins because sometimes they are mirror images of each other. One might have larger right eye and the other might have larger left eye, etc.

(2) Now, don’t get me wrong. Consensus is an excellent decision-making model for many situations. Social policy-setting. Decision-making in a low innovation business. Decision in a zero-risk tolerance business. Just not for innovation.

(3) Some of the other aspects include data-driven rather than opinion-driven decisions and a focus on good decisions rather than right decisions. I will write about these in future LinkedIn articles.

(4) And, once a decision was made, all the functions lined up behind the decision. (In a healthy corporate culture, this happens. In an unhealthy one, there is a lot of foot dragging and passive aggressive behavior after a decision is made. Sometimes this leads to consensus decision making solely to ensure that foot dragging is avoided.)

(5) To do this successfully, you have to be very transparent and push down information as well. The teams can’t make the right decisions if you are not providing them with the right information. I provide the context and the constraints, such as the budget, time envelope and success criteria, and then I push decision-making down.

How Hedge Funds Make Money on Warrants

I’ve been CEO of two public companies, and on the board of several other public companies. It’s always puzzled me a bit how hedge funds made money on warrants.

When a small biotech company raises money, it often has to offer warrants in order to raise capital. For example, it might sell 10 million shares of stock (usually at a discount to market, let’s say of 10%), and offer

Continue reading “How Hedge Funds Make Money on Warrants”

Branding and Corporate Culture

I’ve previously written about emergent phenomena as they relate to science. It’s the idea that reductionism can only take us so far, because when you put smaller units together, you often get properties that are impossible to describe without referring to the whole unit.

There is a similar phenomenon in business.

Continue reading “Branding and Corporate Culture”

Almost Impossible

Westley: “Ha! Your pig fiance is too late. A few more steps and we’ll be safe in the fire swamp.”

Buttercup:  “We’ll never survive.”

Westley: “Nonsense. You’re only saying that because no one ever has.”

– from: Princess Bride, via

If you took physics in high school, you learned that it was impossible to see anything smaller than half the wavelength of light, no matter how powerful the microscope. This limitation is a hard, fixed law of physics, not a matter of how good the microscope is. It’s just a law of nature, proven mathematically by Ernst Abbe in 1873.

Except Betzig and Hell figured out how to break this law, for which they won Continue reading “Almost Impossible”

Power of Failure

“All I wanted was the opportunity to fail” – Jack Goeken, Founder of MCI

You can’t have successes without risking failure

When medical students are taught about appendicitis, we are taught that 20% of the appendectomies should find that the appendix does not need to removed. In other words, we should have such a low threshold for surgery that in 20% of the cases, we should be wrong. If only 10% of the surgeries are wrong, we are killing patients because Continue reading “Power of Failure”

Decision Making

One mystery of drug productivity at large pharma is the persistent low productivity despite the fact that there are tremendously talented scientists at every large pharma company. Their expertise is often encyclopedic, and their creativity is often very evident. Despite this, productivity at large companies have been less than impressive. The productivity appears to be low in comparison to small biotechs, but even more shocking, Continue reading “Decision Making”

Backward Planning

I was recently talking to someone who used to work at Amazon. I was telling him we were trying to institute backwards planning – basically setting the target date and budget and having the teams work to fit their project into that.

He asked me how else one might do that and I told him that at most companies, the project manager asks everyone to Continue reading “Backward Planning”