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Net Giants

Why Big Cap Tech is So Big

Imagine that this lion is a giant tech company. Their scale is often good for we puppies.  (Image Shutterstock, by Eric Isselee)

There’s a lot of talk these days that certain companies are too big, particularly in tech. And in the political sphere we’re constantly inundated with questions around fairness and income distribution. We hear suggestions to alter the tax system, regulate, or even break-up companies. But what angry activists and government officials don’t take into account is one inconvenient truth.

Uneven outcomes, for companies and people, are inescapable. And uneven outcomes often lead to gigantic companies. Such results are the product of statistical laws. You can’t fight such laws. It’s a losing proposition. And while the results might often feel unfair, you don’t want them to change.

Here’s why: Uneven outcomes frequently lead to the best solutions for consumers, and the benefits businesses get from scale allow them to continuously improve their services and experiences. However, when the incentives of companies, no matter their size, are no longer aligned with that of its users, there is overwhelming incentive for others to unseat bad actors, particularly when profit margins are outsized relative to peers.

But in the meantime, there are advantages to companies being so big. Think about it this way… Are consumers better or worse off from having concentrated power in the hands of the few?

Are you better off with more users on Facebook or less? If Amazon has more selection and logistical prowess, or less? If you can have a greater variety of iOS experiences on your iPhone, or less? Do you want more content on Netflix, or less? Is it better to have more information on Google, or less?

You’ve likely heard of the 80/20 rule. It’s become a way to explain many phenomena in life and business. For example, in wealth distribution, roughly 80% of the wealth is controlled by 20% of the people. In business, 80% of the sales are typically generated by 20% of the team. And in software, 80% of errors are caused by 20% of the bugs. We see this phenomenon in our everyday use of technology, as disproportionate power and data is held by the largest tech companies.

So is it fair for companies to get so big and wealth to be distributed accordingly? Formally, the 80/20 rule is known as the Pareto principle, after the Italian economist Vilfredo Pareto. In 1896 he noticed that 80% of the land in Italy was owned by approximately 20% of the people.  Researching other countries, he found that the same general rule applied. Fast forward to today, if you substitute the word ‘data’ for ‘land,’ you can better understand the power of big cap tech.

Here’s an exercise which helps illustrate the inescapable truth about uneven outcomes. Imagine a coin flipping game at a casino. The dealer tells you that each time you get heads, you win a 50% positive return on your wealth. And each time you get tails, you lose 40% of it. With a 50/50 shot, you would seem to be offered a positive expected return, so the odds appear stacked in your favor.  But if everyone played this game flipping the coin every minute for an hour, the math shows that over 30% of the players would be bankrupt, with the majority of the wealth accumulating to only a select few at the top. Interestingly, however, the overall wealth across all players actually increases.

What few appreciate today is that bigger businesses are usually better for consumers, if the business incentives are appropriately aligned with users. There are many solutions that are ‘good enough’ for any specific problem, but generally there is only one great one. When a company finds a solution that consumers ascribe value to, that creates a self-reinforcing positive cycle that attracts more users, and in turn, more value for owners and investors.

The difficulty in gauging what’s too big is that the internet has changed the way company size affects the consumer.  In the past, the most important aspect of a large company’s power was the strength of its distribution, its infrastructure, or its manufacturing prowess. Today’s most important assets are instead generally a function of one thing: data.

The question should not be if a company is too big. Instead, the question should be how much data is too much and in what ways is it ok to use that data. On the one hand, more data leads to better personalization, services, and efficiencies for consumers. On the other hand, the consumer is in exchange giving up control over their personal information.

If the FAANGs were smaller, that would not only diminish consumer experiences, but the companies would not have the ability to continue to drive efficiency in our daily lives. In our view, the most essential purpose of technology is its ability to offer customers time savings. And the best way for that to happen is if users and engagement concentrate around a few companies or services.

Every decision consumers make about which platforms to engage with must take into account the tradeoff between time savings and privacy. For regulators, too, understanding that tradeoff should determine which platforms they scrutinize.

How can we tell when service quality is not good enough, considering how much data is being collected? The answer depends on the company’s intent. So long as personal information is being utilized for the consumer’s benefit, companies should be able to continue to accrue it. When things go astray (read: Facebook and Google), then uneven outcomes, benefitting the company, create societal incentives that are likely to disrupt these businesses, either through market competition or government action, or both.

Don’t forget that this has happened time and again during every innovation cycle. Just because you can’t see what the disruptive forces will be doesn’t mean they are not already emerging.  Jeff Bezos said as much himself recently when he admitted “one day, Amazon will fail.” But without uneven outcomes, there wouldn’t be incentive to unseat the underperforming players, and the evolutionary cycle of innovation would grind to a halt.

What’s important to acknowledge is that uneven outcomes are essential for evolution. Facebook right now is on shaky ground in terms of the tradeoff between utility and data control, and it also operates with incredibly attractive margins. So there’s a lot of incentive for others to try to unseat it with a better solution.

When forecasting the future of big tech, analysts and regulators need to remember that nothing happens in a vacuum. The world is dynamic, not static. As a consumer, you don’t want just an adequate solution. This is precisely why Google trumped Yahoo, Netflix trumped the media giants, and start-ups like Glossier are a thorn in the side of big cosmetics companies.

We want the best solutions to get better, and scale enables that. This is true whether we want the best software, the best jeans, the best makeup, or even the best scooter. As a result, we need uneven outcomes, to help propagate the best solutions.

James Cakmak was a Wall Street security analyst for over 10 years covering the Internet sector. He is also co-founder of Snailz, a digital beauty booking marketplace in New York. Follow him on Twitter: @JamesCakmak. Ryan Guttridge is Adjunct Professor at Smith School of Business, University of Maryland. They write regularly about tech and markets for Techonomy.

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