Why Scaling a Tech Company Is Different

Scaling Strategy by The Family

By Nicolas Colin (Co-Founder & Director) | The Family

This story is part of a The Family series exploring business strategy in the 21st century. Sign up for my weekly newsletter to make sure you’re up-to-date on how businesses thrive in the digital age.

Tech companies present several major differences with traditional ones when it comes to the challenge of scaling up and coping with the relative weight of risks at various stages.

The first difference concerns how low the technological risk is at the earlier stage. The whole phase of developing the technological resources necessary to create a new product is covered by commoditized technological resources such as the Internet, open source technology, and cloud computing platforms. As a result, the process of launching a new venture skips large parts of the product development phase in the traditional economy: founding a company starts at a point where technology is already available and thus the level of technological risk is already very low (even if a bit of technological innovation is still needed).

A second difference is the fact that product-market fit happens much earlier than in traditional companies. This is because tech Entrepreneurs have turned customer development into a science: growth hacking and sometimes crowdfunding are powerful tools that can hasten product-market fit. Instead of conquering the market with mass marketing (delayed product-market fit), it suffices to find early adopters (early product-market fit) and expand from there (= crossing the chasm).

Tech companies also reach a dominant position earlier for a very simple reason: winner takes all. In the digital economy, all it takes to be perceived as the dominant player is to have faster growth. And that’s when increasing returns kick in. There are at least four reasons why digital companies tend to grow exponentially.

Supply-side economies of scale — As centuries of business have taught us, the bigger you are, the lower your marginal cost — and lowering unit costs is what supply-side economies of scale are all about. (Yet those economies of scale reaches their limit soon enough. As commodities get scarcer, factories reach their peak capacity, distribution routes get longer, and prospective customers become more difficult to convert, scale ceases to be an advantage and turns into a liability. This is why most companies fail to grow beyond a certain market share). Amazon’s falling cost of sales (see graphic above) illustrates supply-side economies of scale at work in a traditional industry such as retail.

Network effects — Most technology-driven businesses connect their users with one another, enabling communication between them either directly (sharing content with our Facebook friends) or indirectly (reading another user’s review on an Amazon’s product page). Such connections turn users into nodes and trigger powerful network effects. When these are at work, the value created for each user increases exponentially as the number of users goes higher. The more a business grows, the easier and cheaper it is to acquire new users. Additionally, the more users an application has, the easier it is to retain current users. The result is more lock-in and a higher added value.

Data — The more a business grows, the more data it can collect from its various stakeholders, especially from its customers. This data can be put back into the company supply chain to train algorithms that constantly grow in terms of accuracy and processing speed. In other words, the bigger you are, the more data you collect, and the more you fine-tune your operations through ever-improving machine learning. Machine learning has thus become a central feature of the scalability at the core of tech companies’ business models.

Virality — As Sangeet Paul Choudary wrote in a useful reminder, virality is not the same thing as network effects. Network effects exist when additional users increase the value of the product, thus helping to attract even more users. Virality is more about users taking charge of marketing and selling the product. There are network effects in the Dropbox business model, but their main scalability feature is the virality that comes with existing users obtaining extra storage when inviting new users to use the product.

Increasing returns considerably lower the risks of marketing and distribution since you don’t need to finance marginal growth like in the traditional economy. Increasing returns spare companies part of the marketing effort, but they ignite two new kinds of technological risks: the infrastructure has to bear up under a rapidly scaling business, and some technology has to be developed to nurture increasing returns, especially machine-learning algorithms. Hence while technology is not so much of a challenge at the earlier stage, the digital economy features a much higher level of technological risk at later stages than in the traditional economy.

Corporate executives should ponder these three questions:

• Are you making the most of available technology at a project’s early stage? If not, you should, because it’s the only way to master the technological risk and reach the market faster.
• Is your project ready to generate the increasing returns at scale that will make it easier to reach a dominant position?
• Once in a dominant position, are you ready to tackle difficult technological challenges instead of taking things for granted?

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