In the Industrial Economy—where businesses are powered by factories, machines, railroads, and planes—sizing up investment potential can involve valuing a company’s hard assets. But the Digital Revolution has given rise to businesses that revolve around data sets and the insights gleaned from them. These internally produced intangible assets are not reported on balance sheets and prove much trickier to value.

That’s not the only stumbling block. Competition in the New Economy has heightened the stakes, with winners frequently dominating a given vertical. As valuation metrics and competitive dynamics evolve, how should investors adapt the techniques they use to uncover attractive investment potential?

“See” for Yourself

Though time consuming, the old research playbook remains fairly straightforward. When evaluating an industrial company, analysts make on-site visits to “kick the tires.” Observing an advanced manufacturing facility firsthand goes a long way toward solidifying your view of a company overall.

But the key competitive assets at Facebook, Amazon, Apple, Netflix, and Google, for example, are invisible. How do you get up close and personal with a database or an algorithm? How do you probe insights about which shows Game of Thrones fans might also like to watch?

What’s more, while the hard assets of industrial firms are often interchangeable (one lathe tends to be as valuable as another), the digital assets of new economy competitors differ from company to company. The proprietary insights generated from large, in-house data sets vary widely and, in some instances, confer an overwhelming competitive edge. Plus, lathes wear out over time—unlike insights about consumers, which only become more reliable as data sets grow.

When Success Breeds Success

In fact, that’s one of the ways Big Data business models up the ante: they tend to be self-reinforcing. What does that mean? Initial success expands the data set and allows for further refinement. The more successful a model becomes, the more users it attracts. This, in turn, makes it even more precise—and so on (Display).

Take Facebook. Predictive algorithms enable the social media giant to connect seemingly unrelated dots—like friends’ posts you “liked,” places you posted from while on vacation, and links your friends have opened—in order to serve you more relevant ads. Such targeting increases the likelihood that advertising will convert you from a browser to a purchaser. And higher success rates ensure that companies and advertising agencies will pay a premium for Facebook’s targeted ads compared to those broadcast to a general audience.

As these virtuous cycles take hold, companies with the first-mover advantage (or those that fortuitously generate the best insights about their customers) may develop such an overwhelming competitive edge that they can drive their competitors out of business. That’s harder to do when industrial companies face off with essentially the same machinery. The result? Many new economy companies operate in a “winner-takes-all” environment where the number two competitor may struggle to achieve or maintain a significant market position. That makes the second-tier player an unattractive investment—even at a seemingly compelling price.

Rewriting the Rules

Investors in new economy companies, therefore, face an intricate challenge:

  • how to put a value on assets you can’t see or touch
  • which the company has made no effort to value for you; and
  • which may need to be state-of-the-industry to have any value at all?

Many investors have been slow to evolve. For example, broad value indices are still built using traditional price/book measurements. At best, this seems archaic.

Other investors have shifted focus. For instance, while we at Bernstein have always focused on indicators like cash flows, these measures have become more central to how we evaluate companies today. We can’t see or touch digital assets, but we can measure the amount of cash they are generating. And, more of that cash can likely be spent on expansion and growth opportunities. In contrast, some portion of the cash available at industrial companies must be tapped to replace worn-out equipment. This difference—along with the self-reinforcing nature of digital world success—may justify higher cash flow multiples for digital companies.

The economy is changing as the importance of tangible assets declines and the importance of intangible assets rises. Inevitably, this means the weight of industrial companies in the equity market is declining, too (though many still look attractive on traditional valuation measures).

In response to these broader shifts, we’ve evolved the way we pick stocks and build portfolios. Today our strategies emphasize companies with attractive cash flows that have the potential to rise. This ensures exposure to new sources of wealth creation in our economy. The byproduct? We own far fewer large industrial companies trading at steep discounts based on price to book than when old economy rules applied.

An information edge can mean the difference between getting ahead—or being left behind. That’s why many of our entrepreneurial clients look to us as a source of intellectual capital. For more insights on disruption, check out the related blogs here.

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams.

Clients Only

The content you have selected is for clients only. If you are a client, please continue to log in. You will then be able to open and read this content.