Let’s start with the first point: the hyper-growth phase. This is growth in excess of the rate of expansion of nominal GDP; a key consideration when valuing tech companies. In principle, it is not difficult to build a valuation model to incorporate the different growth phases – high, medium and low. The difficulty lies in deciding how long each phase will last.
Closely linked is the second point: hyper-growth rates are intimately bound with the effectiveness of the barriers preventing a competitor snatching away its business.
Take Google. Many people thought it was over-valued when it floated. To start with, it was not obvious what barriers to entry, if any, would protect Google’s market position. But that was to assume the traditional notion of what constitutes a barrier to entry: perhaps an exclusive piece of intellectual property, or a state-granted monopoly.
As it turned out, the Google name itself became the most effective barrier to competition.
This gives rise to questioning the value of intangibles. How much is a name or brand worth? How long does the name act as a barrier to entry? A reasonably straightforward but far from exhaustive method is to compare the valuations of brand-name companies and firms without household names.
Our third point examines multiples – traditionally used to turn an accounting line item into a market value. Earnings per share, for instance, is commonly used to calculate multiples. We look at comparative valuations to spot mis-valuations. For example, a bank trading on a lower multiple than all the other banks may be doing so because of a corporate governance issue that is on the cusp of being resolved. This can make shares attractive.
With tech companies, however, the challenge is to decide which accounting item is most meaningful. Ideally, we should use an accurate measure of value and a figure that is hard for management to manipulate. Another question is whether a multiple is the right valuation method at all. In the tech sector, perhaps clicks, user numbers or engagement figures would be better metrics on which to base market valuations.
Currently, such indicators are quite hard to collect and process. It is likely to become easier as data analytics improve. Data will show not just numbers of users but the stickiness of those users. Firms that make good use of this data will make good returns.
Success or failure in the conversion of first-mover advantage into lasting market power, our fourth point, matters in the tech world. It is the difference between global champion and also-ran. Some may have said that Google’s success was obvious from the start. But they may also have said the same about other first movers, such as AOL or Yahoo!, if they had proved as successful as Google. It is about converting first-mover advantage into lasting competitive advantage.
So what is the special ingredient? Well, in part, the Googles and Facebooks of this world have market edge because people believe they do. There is an element of self-fulfilling prophecy.
Beyond that, however, we can ask what characterises the management of first movers who claimed market status and those who did not? Look at the management team: skill-set, compensation, governance.
Using soft indicators, as opposed to the hard financial numbers, it is possible to spot early signs, both good and bad. The diversity of the management team is often a good soft indicator. A diverse team shows a willingness at top management to listen to dissenting views. A lack of diversity suggests senior executives like to be surrounded by yes-people.
Another good example of a soft indicator is the way managers communicate with investors. A management team willing to articulate its strategy is a good sign. A management team that fails to offer rationale and calls its strategy obvious is clearly a bad sign. Failing to dignify a question around strategy with an answer is proof by intimidation.
Increasingly, we are moving towards textual analysis. Investors have always listened to what management has had to say and the way they have said it. Did they sound positive or negative? How do they usually sound? But this is very subjective. Textual analysis is better as it is a way to judge a company’s sentiment. For example, by asking how many times a firm used the words profit, debt or competition.
Our final point relates to governance issues, specifically the absence of shareholder voting rights. Increasingly, tech companies come to market with shares that have low or zero voting rights. How much value should we attach to votes and to the decision rights of shareholders?
Traditionally, there are voting rights in newly-floated shares, although top management retains most of the voting power. It is clearly a bad signal when investors are offered no voting rights. Why? Because companies can give themselves controlling voting rights and still remain in charge. By offering no voting rights whatsoever, they are effectively saying: “I’m not interested in listening to you.”
The challenges of valuing tech firms and non-traditional businesses can be met with a flexible toolbox. You just need to know which one to use. A carpenter uses a hammer on nails and a screwdriver on screws but would quickly run into problems trying to screw nails. The best way to value ultramodern firms is to build flexibility into our valuation models – and ask smart people to use the right tool at just the right time.