Gautam BakshiA few years ago, I was feeling really confident when I started my own startup. I had a lot of experience leading teams and had overseen large projects with big budgets. I thought it would be a piece of cake compared to what I had already done.
I was careful to make sure I had the best people around me and I listened to anyone who seemed to know what they were talking about.
What could go wrong?
Almost everything.
What is a startup?
A startup is a company designed to grow quickly.
It does not have to be a technology company, take venture funding, or have an "exit" to be considered a startup; the only essential factor is growth. All other aspects of startups are a result of the growth.
The big key is growth; the average growth of all companies in their respective economy is the country's GDP. This is the US GDP year-over-year growth since the 1960s:
As you can see, some of the best years have had a growth rate close to 8%, but mostly it's half that. With an economy as large as the USA, it's still highly impressive, as it's easier to grow from $100 to $108 than from $100 trillion to $108 trillion. This means at a company level there are firms that are growing at much less than that(think companies struggling or big slow companies where growth is harder) and there are companies doing much much better.
China has been able to sustain much larger growth and is now the second largest economy in absolute terms.
Wheras Japan has really stalled in terms of their growth:
Growth is very hard.
Some of the biggest companies, Apple and Amazon, have ~20% year-over-year growth. That is very impressive given the size of their firms, but eventually that growth will slow down as, if they keep growing in absolute terms, they will become larger than the economies they operate within. For finance geeks, this is why setting your terminal growth rate in your models is one of the most critical assumptions you can make, as, if your terminal value is larger than your discount rate, your model fails.
Distribution vs Product
The smart people combined these two, but they are very different. Most people who work at a big company will understand. There are sales and marketing teams and operations teams (the teams that manage existing customers, build new features, monitor progress, etc.), and then everyone else (those not directly related to the product, think HR, accounting, etc.).
Every part is critical, but the two parts that drive a company are sales/marketing and operations. We can call sales/marketing "distribution" and product/operations "product".
As many people know, if you build it, they will not come. You can have the best product in the world, but if you do not have distribution, you will not succeed. You either fail fast, die slow, or survive with highly engaged users that you cannot grow.
The key to growth for a startup is distribution. You need to get customers fast and cheaply. If your product is good, then you may not need to sell it as much, so a strong product is important, but distribution is still something that cannot be ignored.
If your onboarding process is months (at enterprises, I have gone through this pain) or your product doesn't solve a real need, then customer acquisition and closing deals will be a nightmare, so solving distribution problems often does involve adjusting the product.
This is one of the struggles we face at my startup. Some sprints, we provide amazing analytics that our existing users rave about, but other sprints we have to prioritize simplifying the user experience or making onboarding smoother. I'm sure I drive my product team crazy, but these two growth levers are constantly battling for our time.
What does this have to do with startups?
When you get advice from people, even those who have worked at a top-performing large company may have only seen and contributed to single or double-digit growth, which is not enough to be helpful to a startup, which needs massive growth upfront because that growth won't continue.
I was a senior executive at many of the largest financial firms in the world, and I did not have access to distribution teams. Often someone from operations who had a conversation with a product person (who in turn had spoken to a sales middle person) would relay some message that would be passed around. I remember how annoyed people would get with me when I would ask "why are we doing this? Who is specifically getting value and how does this help our business or our clients?". It was something that got pushback and it was clear the folks in charge didn't understand it either.
In the early days of most companies, it is not uncommon for them to double or triple their revenue every year. This is because they are starting from a small base, so going from $100 to $300 in monthly recurring revenue (MRR) is big, but in absolute terms, you need much, much larger growth; think 100x-1000x returns. This is also why venture capitalists (VCs) and experienced angels will fund ideas if they have a clear potential path to 1000x.
Does the person have experience with 100x growth?
This is where it gets challenging. You can speak with a CEO of a company and although they may give you great advice, if they are giving you advice that only provides a twofold return, then it might be limited in value.
I'm not saying ignore it, I'm saying that you have to either figure out how to convert it to one hundredfold or find advice that provides a greater return. By nature of this level of success, sometimes the person you think is successful at a big company may not be the best person to give you advice.
Sometimes the person who started a smaller business but went from zero to one and then scaled it is better to get advice from.
It sucks but you have to see and understand where you are at and what they succeed in.
Is scale the first thing that matters?
This may seem counterintuitive, but at first, scale is not important. What I mean by this is that although your business plan and model should be designed to grow very quickly, in order to understand the dynamics and factors, you need to optimize for learning.
This is why it is even harder to get advice from people, as most people do not know your specific situation, even if their industries are somewhat aligned. To optimize for learning, you need to set up micro-experiences with various growth metrics. Remember, growth is a lagging indicator of something you did upfront. Therefore, you need to put together a series of experiments. For example, if you are trying to optimize for users who convert to paying on your system, then you can give them nudges in the form of emails, SMS, or in-app notifications for certain behaviors that encourage them to try features that have been seen to convert.
When you start thinking in terms of experiments, two amazing things happen: you adopt a student mindset and stay humble, and you can detect bullshit from others quickly. When someone tells you "This will grow your business," you can simply figure out the micro-experiment and test it. If it works, then scale it, and if it doesn't, then you haven't lost much.
Why are startups so hard?
Startups are hard because when you think in terms of experiments and tests, you realize that the speed of experiments matters most. It becomes a marathon rather than a race, because you consistently have to think of experiments and test them in the smallest possible way.
Most people in big companies aren't designed for this. I know myself; I would oversee several programs over a year (perhaps up to four) with each having many projects under it. Even if my organization completed thirty projects a year, that would be the equivalent of three weeks in the life of a startup.
We aim to do at least ten experiments a week. This could be from testing new onboarding flows, to new content, to partnership contracts, etc. The implementation and testing become tough and when something succeeds to productionalize it becomes even more work.
So who make the best advisors?
This is still a difficult question for me to answer. On the surface, anyone who has gone from 0 to 1, i.e. started something from 0 and gained growth quickly, is an ideal advisor. On the other hand, sometimes there are folks who are trapped in big companies but are fast learners, so they can figure things out quickly.
What we found works best is to trust your gut but use KPIs. For product-level advisors, we want to see a certain percentage movement in our KPIs, and for strategy advisors, we want to also measure them against KPIs. The longer the duration of the indicator (strategy), the easier it is to go in the wrong direction. Part of the role of the startup team is to figure out how to compress these KPIs into a shorter feedback loop.
For example, if a person is working on an enterprise sales strategy, it may be a long sales cycle, but there need to be weekly KPIs that are rolled into monthly and then quarterly KPIs, so you can monitor them. The same applies to advisors: measure them and share the results, let them know how they are doing, and see if they are learning from the feedback loop.
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