7 Principles For Startup Decision-Making

There is no predictability when creating a new business with an idea.


23 Mar, 2018

7 Principles For Startup Decision-Making | BEAMSTART News

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Innovation is about creating new things. But how do you create new things that people are willing to use and/or pay for? While ambiguity and uncertainty are always associated with innovation, people have a tough time dealing with both. One reason that big corporations are not good at creating new things is that they are not structured to do unpredictable things - a hallmark of the startup environment. There is no predictability when creating a new business with an idea. 

Creating a successful startup depends on the interplay amongst idea (product or service), market, people, and capital. The outcome is unpredictable and it can change the world. For this article, startup means a newly formed business based on a novel idea with an ambition of exponential growth in its early years. There are other types of newly formed businesses. For example, you can start a consulting business with a friend or open a motel with the goal of making a decent living. These type of "lifestyle" businesses may not benefit from this article because they are inherently less risky and operate in the "Knowable" zone shown in the image below. Startups operate in the "Unknowable" zone. 

When you are forming a startup or developing something new, you have an idea, you may have access to technology or you may be developing a technology. You get capital, and you get people. You can learn about the market, and the history in the market category you are operating in. You can understand the buyer behavior and the competition. All these things are knowable. With all this knowledge, you form a hypothesis about how your idea/product will perform in the real world. However, there is no way of figuring out how your idea/product is going to perform in the market unless you are actually in the market. Like Yogi Berra said, "In theory there is no difference between theory and practice. In practice there is." The unknowable can only be learned by doing. Hence, startups are more about doing than planning. The world's biggest company (measured by revenue), Walmart, started with a mantra - Ready, Shoot, Aim!

I have been fortunate to have been a part of creating many new things and businesses (Wearable Devices, Public WiFi as a paid service, bringing benefits of mobile technologies to physical retail, accelerating the adoption of 3G/4G in the US at the expense of WiMAX, etc.). This experience coupled with Complex Systems learnings from Dr. Yaneer Bar-Yam has helped me to develop a few heuristics (experience-based techniques for problem-solving) that are useful for startups, innovators, and policymakers. Over the years, I have worked with scores of startups, venture capitalists, government bodies, incubators, and accelerators, and the feedback on these heuristics has been extremely positive. Here they are:

1. Business Plan is Useless

When you launch a startup, you go to an investor to get it funded. What is the first thing (s)he asks you? Usually, it is, "what is your business plan?" Think about the irony of this question. A startup goes through everything listed in the image above. Investors want to know what your revenue will be three to five years from now. How much market share will you have? How many monthly active users, what will the growth rate be, etc? There is no way of knowing this for something that has never existed before. All they want to see is exponential growth with precise numbers.

So, you know what the investors want to hear. You can't really tell them that business plan is useless. You have to understand that it is a game and play it to win. Make up stuff without spending much time on it. Entrepreneurs tend to value money much more than time because they have the time and they don't have the money. Time is as important in a startup as money.

What an entrepreneur needs is a learning plan, not a business plan. You have a hypothesis. There are things you know and things you don't know. You have to understand what you don't know in your hypothesis and what assumptions you are making and find a way to test the hypothesis with the least cost and the least risk possible. Generally, things won't work out as you imagine. What do you do then? You learned something by testing the hypothesis in the real-world and now you can apply that learning to tweak your idea/product. The number of times you can do this depends on your persistence, capital, and people.

Plan less, do more. Your business plan is useless. Create a learning plan.

2. Winner Takes All

Vilfredo Pareto has immensely simplified my life by his 80-20 principle. The principle originally came from observing land ownership in Italy. At the time, 20% of the richest people owned 80% of the land in Italy. This distribution is applicable very widely. 80% of complaints come from 20% of the customers, etc. etc.

The Pareto principle goes two levels deeper:

i) 20% of 20% is 4% and 80% of 80% is 64% which means that 4% of people own 64% of land, etc. etc.

ii) 20% of 4% is 0.75% (~1%) and 80% of 64% is 50% which means that 1% owns 50% of land, etc. etc.

Digital technologies that do not see physical boundaries, the Internet, globally distributed supply chains, relatively freer movement of labor and capital have created a world where a startup can be very big, very fast.

What this boils down to is that it is possible now for one company to dominate the market (1% owns 50%) . Think about companies that have become the global phenomenon and part of everyday life for most people - Google, Facebook, WhatsApp, etc. Even if you don't become the next Google, the chances of you becoming the next millionaire are relatively higher because the successful startups get bigger by acquiring the smaller players. There are more startups, more exits, and more big successes these days compared to thirty years ago.

Think big. Start small. If you are not getting bigger, you may disappear.

3. Understand Causation

If you ask people how did the Arab Spring start? Why did it happen around early 2011? Usually the answers are: social media, smartphones, "people were fed up" etc. Food prices never come up as a possible cause. The graph above is the UN Food Price Index. The red vertical lines on the graph are the dates of the food-related riots and the number in the parenthesis next to the country name count deaths from these riots. The New England Complex Systems Institute did excellent work to prove this causation (NECSI). The blue line marks the date when NECSI submitted a report to the US government warning about the upcoming unrest. What do people do when they can't afford to eat? They go to the streets and protest.

What does Arab Spring have to do with startups? The Arab Spring example clearly shows that most people don't understand causation. Since a startup is an interplay amongst idea, market, people, and capital, it is tough to know why things are working or not working. If you don't understand causation then you will continue on the wrong path and you will run out of money and time. I see an interesting phenomenon in big companies all the time. You ask someone in sales (Business to Business) why customers are buying from the company. The answer usually is because they have great relationships. Now, ask the product teams in the company why customers are buying. The answer usually is because the products are so great that they can sell themselves despite the salespeople.

Not understanding causation causes another big problem in the tech industry. Companies make new versions of the product every year or so by adding new features. No one checks how many features in the previous version have been used and liked. Instead of making the features people use better, companies add new features. This goes on until a competitor emerges with a much simpler product!

A startup needs to get a clear understanding of why people are using the product and how to evolve the product. If a new product has two main features, let's say A and B, launch three different versions of the product - A, B, and A+B. This will help you understand which feature is valued more by the users. It gets more complex with hardware products and products with high numbers of features.

Get a crystal-clear understanding of why people are using your product.

4. Do not Confuse Risk with Probability

Hundreds of people die every year because they fall from ladders. You can look at the data from the last few decades and calculate the probability of the number of people dying from ladder falls this year. The chances of that number being in the millions is almost impossible. Now let's look at terrorist attacks. You can look at the data from the last century and it does not tell you anything about the probability of the number of people who may die from a terrorist attack. So, in this scenario, the risk of you dying from a terrorist attack is higher than the risk of you dying from falling from a ladder [thanks to Nassim Taleb for this example].

Innovation is a high-risk business. You cannot look at historical data and calculate the precise probability of success for your startup. What do you do in this situation? You create optionality. Don't get fixated on your idea. Create flexibility in your product/service architecture so you can test different options. Understand how your knowledge/learnings can be applied to different markets. Think of bundling with existing products. Figure out new distribution channels.

Don't fall in love with your idea. Test a lot of options.

5. TMI [Too Much Information] Increases Confidence and Not Accuracy

The chart shows how US GDP growth has changed Year-over-Year from 1950 to 2010. In 2004, the US Federal Reserve Bank (Fed) popularized the term: The Great Moderation. It meant that the era of wide swings in GDP growth is over since starting in the 1980s, the GDP growth rate stabilized [see the yellow section of the graph]. What happens a couple of years later? We almost went into a depression. If the Fed, with very smart people working for them, and the availability of vast data-sets, can make such a huge mistake, then people like us have to be extra-careful about large amounts of data increases our confidence.

A common human misjudgment tendency is to confuse correlation with causation. With vast amounts of data available, it is easy to observe correlation among various variables and come to the conclusion that you want to achieve.

TMI has another impact in our world. Noise rises much faster than your signal (message).

So, how does a startup leverage this insight? Don't let a lot of data make you overconfident. Understand correlation amongst the variables in your business: Hardware, Software, Cloud, User-Experience, Cost, Distribution, Competition, Customers, Packaging, Capital, Time, etc. Understand opportunity cost; that is, if you chose to do x, that means you are doing it at the expense of everything else.

Positioning and communication are increasingly important for startups because there is so much more noise around. One simple trick is to think in big numbers. For example, when Mary Meeker talks about Wearable Devices, she talks about the cumulative number of steps that have been taken with these devices. This number is in the Trillions and it gets attention. In reality, a few million fitness devices have been sold and if you just say that, it won't get any attention. The Internet of Things is another example. People cite that it is multi-Trillion dollar market and that gets attention. Think about how you can position your startup so that it gets attention.

Understand correlation amongst variables in your business. Position the startup to be noticed.

6. Replication with Variation and Selection with Competition

The best way to understand how Silicon Valley works today is by understanding evolution which operates with the principle of Replication with Variation and Selection with Competition. Genes get replicated from one generation to the next and each copy is a little bit different than the original. Then the copies compete with each other and the best ones get to reproduce and so on.

Silicon Valley has an environment that enables Replication with Variation and Selection with Competition. Think of a gene as an idea that gets "hot". A lot of people jump on that idea and create startups. Since the culture is open, people talk to each other, they pitch their ideas all the time. Each startup adjusts and creates a variance from other startups. Venture Capitalists like investing in what's hot, so many variations of the same idea get funded. There were at least thirty search engine startups around when Google started. These startups compete with each other and eventually one of them succeeds in becoming the dominant player or in getting acquired by a big corporation. The fate of the other startups is not as bad as the genes. A lot of them get acquired by the startup that is getting bigger or becoming the most successful. Even if your startup does not get acquired, the chances of you getting a job with the successful startup are high because you have experience in the new domain. So, if you are in the right category, the risk of doing a startup is not that high.

Pick a positioning category where the money is going and create unique value.

7. Competition and Cooperation Work Together

The example shown in the graph explains how competition and cooperation work together in sports. At the sport level, the sport, let's say football, is competing with all the other sports and other forms of entertainment to get your time and money. This causes teams to collaborate, form leagues, spend money on advertising to get people to watch football. If you go one level down, the teams compete with each other in the sport. That is the idea of a sport. This competition makes the team players collaborate with each other. Now, go one level down and you see players competing with each other for money, sponsorship deals, exposure, etc.

This heuristic is more applicable to policymakers. They have to create the environment and incentives that enable competition and collaboration to work together. A region competes with other regions to get investors and entrepreneurs. New York, Austin, and Denver are competing with Silicon Valley. All venture capitalists compete with each other to invest in new promising startups. However, when they invest, it is usually in syndication with other venture capital firms. Competing startups cooperate to fight against policy changes like net neutrality. And, they cooperate to form industry organizations to agree on standards.

Choose the right environment which is open and gives you access to capital, connections, and competence.

Applying these seven heuristics may tremendously increase your chances of success. Let's look at them again:

1. Plan less, do more. Your business plan is useless. Create a learning plan

2. Think big. Start small. If you are not getting bigger, you may disappear

3. Get a crystal-clear understanding of why people are using your product

4. Don't fall in love with your idea. Test a lot of options

5. Understand correlation amongst variables in your business. Position the startup to be noticed

6. Pick a positioning category where the money is going and create unique value

7. Choose the right environment which is open and gives you access to capital, connections, and competence.


Good luck!

Author Info:
This article was first published by Chander Chawla on Forbes

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