One important question when evaluating a new product or technology is “will people or companies adopt this?”. I’ve found the best way to answer this is with another question: “Is the next best alternative significantly worse or non-existent?”. If yes, then the product or technology has a good chance of adoption; if no, it’s likely to remain unadopted. This heuristic is particularly useful for navigating the startup idea maze.
In Clayton Christensen’s jobs to be done framework, people and companies hire products and technologies to solve problems, i.e. jobs. People hire Google to search for something or Amazon to buy something. But people were searching and buying before Google or Amazon—so why did each get adopted?
In each case, the next best alternative was significantly worse or non-existent: pre-Google search options were slower and less relevant (significantly worse), and in many cases the information had yet to be indexed (non-existent); pre-Amazon, buying a basket of items required visiting multiple stores and were likely more expensive (significantly worse), and niche items were not available from local stores (non-existent).
Significantly worse—as opposed to just worse—is a subjective and in some cases tricky distinction. Few people will switch from a marginally worse alternative. Whether it’s laziness, ignorance or the power of habit, an existing worse alternative will have a status quo bias that can be hard to overcome. Significantly worse alternatives, however, are usually associated with enough pain and dissatisfaction that people are happy to switch.
So how can you determine whether the next best alternative is significantly worse? Peter Thiel’s 10x better framework is useful: if a new product or technology is 10x better, it’s likely that the next best alternative is significantly worse; something that’s only 10% better is unlikely to be able to overcome the inertia of the existing choice and/or behavior. Another sign of significantly worse is, when asking someone about the product, they lead with a complaint, e.g. “it’s expensive” or “it’s slow”.
Cryptocurrency examples
Significantly worse or non-existent has been an effective way to evaluate what ideas will work in cryptocurrency. Bitcoin and public blockchains are true technology breakthroughs: until invented, the ability to transfer value in a trustless, decentralized, digital manner was non-existent. But just because something exists doesn’t mean it will be adopted.
For example, in the early 2010s, many thought Bitcoin would be widely adopted by e-commerce websites given Bitcoin was lower cost, global, instantly settled and lacked chargeback risk. But while Bitcoin satisfied significantly worse or non-existent from the e-commerce website perspective, it did not answer that question for consumers: they already had credit/debit cards, nearly every e-commerce website accepted cards, and rewards points and chargebacks were popular consumer features of cards. Further, Bitcoin was relatively hard to acquire and required gain/loss tax accounting for every transaction. Not surprisingly, Bitcoin payments were not very popular for mainstream e-commerce websites. (However, for e-commerce websites where payment service providers were non-existent, e.g. Silk Road (dark/grey market goods) and SatoshiDice (online gambling), Bitcoin was adopted.)
A similar story exists in DeFi. Traditionally, cryptocurrencies have traded on centralized exchanges, offering users liquidity, functionality and usability that was non-existent on blockchains, i.e. you could not trade Bitcoin for US dollars on-chain. However, centralized exchanges had some disadvantages: they were susceptible to hacks, subject to regulatory restrictions, and developers of new crypto tokens found it hard/slow to get their tokens listed. As Ethereum became more popular, 0x developed a decentralized exchange protocol addressing the disadvantages of centralized exchanges. But usage was only marginal: 0x suffered from low liquidity. A few years later, Uniswap solved the liquidity problem (via an automated market maker which natively incentivized liquidity providers), and trading volumes quickly grew to rival centralized exchanges.
The Bitcoin e-commerce and decentralized exchange examples illustrate an important point about significantly worse or non-existent: it’s not sufficient to solve problems if you create a new, more fundamental problem. For Bitcoin e-commerce, while Bitcoin solved problems for merchants, it created new problems for consumers. And in the case of early decentralized exchange protocols, despite solving the security and listing scarcity problems, the lack of liquidity was a more pressing problem that centralized exchanges had already solved.
In conclusion, entrepreneurs and investors should spend time understanding what problem a new product or technology is solving, are the alternatives significantly worse or non-existent, and does the new thing surface new problems that the worse alternative has already solved.