I grew up in a family of technologists in New Jersey, home of Edison’s Labs and the birthplace of the transistor.1 Where most families fought about politics or sports at the dinner table, we debated technology.
We received computers before we were 6 and our first programming lessons started in elementary school. When our teenage friends were out one winter day, my sister and I were critiquing my father’s practice presentation on using combinatorial techniques in software testing (in truth, we barely understood anything).
Over the years, our debates grew due to the different perspectives through which we approached technology: my father as a statistician at Bell Labs and later Bellcore, my mother in telecommunications programming at AT&T, and eventually, myself with startup product management and engineering in Silicon Valley.2
We put together a few reflections on the tech industry from these debates, based on the common misconceptions we saw:3
Exponential Growth and Wild Ideas
The heartbeat of the technology industry is Moore’s Law, which lets unexpected — often, magical — things happen in astonishingly short periods of time. Most industries have linear changes: products slowly get cheaper, quality consistently improves. The computing industry is defined by exponential changes.
The Law — as we refer to it — was first an observation that transistor density doubles every year. Today, it means that computing performance doubles every 18 months. The Law’s exponential spirit applies in every part of technology, including network bandwidth, computer storage, and even telecom network effects.
Compare the change in the price of a widget with that of a computer chip over a decade. Our widget might fall in price by 5% a year and be 40% cheaper after 10 years4. By comparison, a computing chip is 128 (12,700%) times more powerful and cheaper over that same 10-year period. A tiny 2000s cell phone motherboard is 1300X (129,000%) more powerful and several magnitudes cheaper than the ENIAC, a gigantic defense computer created sixty years earlier
Few people can think in exponential terms, even seasoned technology executives. This is partly because linear growth looks nearly the same as the exponential growth of Moore’s Law in a single year. It’s only over years where the change becomes especially apparent:
In the 1980s, Steve Jobs argued forcefully at Apple for workgroup printers even when detractors within Apple pointed out their sky-high prices — arguing that the price would go down dramatically and quickly (he made a similar observation when first releasing the Mac). In 2007, Steve Ballmer, the former CEO of Microsoft laughed at the iPhone’s starting price5, not realizing how quickly the price of the underlying technology would go down.6
Such an industry rewards people who are opportunistic and entrepreneurial and often plain crazy. After all, a lot of rational people think about the world through linear terms.
The Tradeoffs of Youth
Youths — teens to early 30s — take a leading role in the tech industry. This encourages risk-taking and new perspectives, while also leading to age discrimination and bad investment choices.
In most fields, age means more experience, knowledge, and a larger network. In many professions, people automatically make more money and get promoted as they get older. This has value where the past is a guide to the future and where long relationships are important. To make an impact in some fields, an entrepreneur often needs to have understood the industry or problem space over years.
But when the world changes significantly, the experience (and relationships) of old can be counterproductive. A seasoned bank executive or bank programmer’s knowledge doesn’t really map over to a new technology like blockchains/cryptocurrencies, even if both industries have to do with finance.
Younger people have lower opportunity costs and often a higher tolerance7 for risk. Consumer technology — like social networks or gaming — often begins among certain young segments before the rest of the population uses it. Younger leaders understand these communities in a way an outsider might not.
These debates of old vs young often miss where youth can be an asset and a curse. Enterprise products often benefit deeply from seasoned hands and networked people who can make critical sales. By comparison, a very specific subset of consumer products can benefit from founders who can empathize with their (sometimes young) users 8. (This is one business reason, among many others, why having less female tech entrepreneurs is such an issue for our society)
Both views on youth have tradeoffs. A substantial number of industries devalue the early years of their worker’s lives when over-weighting the importance of experience (especially when measured in years of experience rather than richness of experience). In fact, this may just be a simple rationing criteria to dole out favored positions to people who have done the requisite time.
But the Valley is much more susceptible to ageism — even when age (and its relevant experience/network) have substantial benefits to the problem at hand.
Execution over ideas
Would be entrepreneurs think that the quality of the idea and its uniqueness decides whether something will succeed. In reality, execution is critical to the success of any business. This is why so many aspiring entrepreneurs do well to dismiss the “X is already doing that” argument.
This bias for novelty is all around. Journalists, when deciding what startups to cover, prefer novel startups because this is more interesting to their readers (and therefore more profitable). Renowned scientists become successful from being the first to discover new things, not from slightly modifying existing ideas.
By contrast, many tech (and business) success stories start from derivative ideas. Execution is far more important than a brand new idea or strategy. Or rather, new ideas and strategy are just a jumping off point to make true impact.
A social network user’s experience benefits from others. Whoever can come up with an innovative way to acquire users quickly — such as, starting on a college campus like Facebook did — win, regardless of whether their product is truly differentiated from existing social networks. This understanding dictates why second time entrepreneurs think so deeply about distribution, rather than product differentiation:
The starting idea is often just the beginning of a journey to learn more about a space, leading to deeper insights in the future — and perhaps wholly different ideas. Microsoft began with a BASIC compiler, only realizing later that IBM needed an operating system.9 A bad idea can create the activation energy for a successful startup journey.10
Closet entrepreneurs can often be deterred by the fact that “someone is already doing X”. The question should be what they could see themselves doing, how strong of an executor are they, and what changes are coming in the market.
Why Crazy Valuations With No Profit or Revenue Makes Sense
Among technology commentators, outrage grows when a company’s valuation outstrips comparable companies and fundamental business metrics.
But many parts of technology is winner take all, with profits lagging by years. Amazon took 14 years to become profitable. Uber is still not profitable. Some companies with little revenue are critical to the success of deep pocketed companies. Network effects and exponential growth are hard to surmount. All these factors justify high valuations.
Facebook raised investor capital with a $10 billion valuation in the midst of a worldwide financial crisis in 2009. The company was unprofitable, and the valuation was far above what most pundits expected. At elite business schools and in journalism circles and even amongst famous VCs, there was a consensus: the business was widely overvalued.
One canny investor, DST’s Yuri Milner, assessed the potential growth based on other more networked countries (like Japan, South Korea). He invested, feeling that even this lofty Facebook valuation widely underweighted their potential, given what his team had seen elsewhere. (The $1 Billion Instagram acquisition by Facebook was similarly pilloried, as Instagram had little revenue, even though now it is considered a steal)
Of course, there’s countless examples of overvalued failures as well. But for investors, a single winning bet also makes up for tens of failed bets. They’ll often get it wrong, but the one time they get it right will make up for many failures.
Toys (and dumb apps) do change the world
A consistent criticism of the tech industry is that it sells the idea of transforming our lives for the better, but in reality creates prosaic inventions: rather than solving cancer, the tech industry focuses on yet another food or dating app.
For an entrepreneur facing nearly impossible odds, a sense of purpose — changing the world — is a motivating reason that makes up for the challenges they will face.
Often, these visions are nothing more than a “false mission” that lets entrepreneurs recruit employees who have a number of other opportunities, increases the likelihood of funding, and is a canny strategy for what the tech media likes to cover.
And yet, many revolutions start with dumb (but often ingenious) ideas discovered after much pain. They then have substantial impact when given time to grow — especially when led by the entrepreneurial, innovative people who founded the company. Consumer products especially seem like dumb ideas. But world changing companies started with laughable ideas like a social network for college students or a taxi cab for the elites or renting out air mattresses.
“Dumb businesses” are also the training ground for great entrepreneurs. Early business attempts like Elon Musk’s Zip2 or the Jobs/Wozniak Blue Boxes were the practice for the companies they would later build.
For entrepreneurs, using a filter of “how world changing is this idea” to decide what idea to pursue is a very dangerous thing. It adds crucial impediments to an already challenging journey. It also ensures many world changing ideas won’t ever be pursued, because their progenitors are not imaginative enough to see where the journey will eventually lead.
After all, if the original inventors of the transistor — the building block of all modern electronics — were alive today, they’d likely be amazed at the world their research led to.
Siddhartha Dalal is a professor at Columbia University’s School of Professional Studies and Department of Statistics. He previously was the Chief Data Scientist at AIG and the Chief Technology Officer at the RAND Corporation. He started his career at Bell Labs and Bellcore. He has an MBA and PhD in Statistics from the University of Rochester.
Alka Dalal was a staff manager at AT&T. She received her master’s degree from Rutgers, and bachelor’s and master’s degrees from New York University. She passed away in 2016.
Nemil Dalal is a product manager and software engineer.
Preeyel Dalal is a Product Manager at Amazon.
- My father started as a statistician at Bell Labs in the 1970s, my mother wrote C and Cobol in the 80s, and I would find my way to Silicon Valley for college. ↩
- My sister chose her own path outside of the tech industry in nonprofit fundraising, though even now she manages teams that handle critical technology systems. ↩
- I’ll focus on Silicon Valley and startups as it’s a world I know, though most observations apply to much of the worldwide computing industry. ↩
- US GDP per capita (the average American’s wealth) might rise by 3% a year over the same period, and be ~34% greater over 10 years. ↩
- While the price of the iPhone has gone up, the cost of a typical smart phone has gone down. ↩
- Incumbents often misjudge because they extrapolate linearly, especially when led by execution-focused management. ↩
- Also, a reason why top VC firms like immigrants. ↩
- Even with the latter, investors often draw spurious lines, such as arguing that consumer internet entrepreneurs are under 25. ↩
- My Stanford Business School professor remarked that if he had shown Microsoft to his students with a different name, they would likely have ripped it apart. After all, what was the market and monetization opportunity from Microsoft’s original idea, a BASIC compiler? ↩
- Thanks to Shvet Jain for first phrasing this to me. ↩