Our AI & Big Data Watch List

We maintain Watch Lists for many of our major investment themes, such as 5G, Media & Entertainment or Autonomous & Electro Mobility. AI & Big Data is our largest Watch List. It is also the largest thematic exposure in our portfolio.

Our Watch Lists are not algorithmic. There’s a fair amount of subjectivity built into them. All our Watch Lists contain companies that, we believe, have compelling stories. Either they are 1) Global Dominators or 2) have exponential growth trajectories. Some companies have both attributes. Some even have a third attribute: they show up on our other Watch Lists as well, meaning they have multiple tailwinds behind them.

Our Watch Lists have one purpose above all – they inform us if there’s anything reasonably priced in a particular theme. What is “reasonably priced”? We have a simple metric for reasonableness: we back-solve into what revenue growth we’d need to believe to buy the stock. This is an unusual way to screen investment ideas. But we think it’s the most logical, and it’s closest to our investment methodology. The name of the process is Expectations Investing – as coined by Michael Mauboussin. But we’ve adapted his teachings and combined it with our experience in Value Investing.

Here a snapshot of our full AI & Big Data Watch List:

We deliberately left out Social Media companies like Facebook from this list. We have a separate Media & Entertainment Watch List. But, yes, you could argue that they are efficient wielders of Big Data, using AI. In this article, we’ll focus on more boring but arguably more important companies.

The last column in the Watch List is the most important one – “Revenue Growth we need to Believe”. We’ve explained our methodology in detail here. But the gist is this: We back-solve into revenue growth rate based on some fixed assumptions:

1. We never pay more than 20X Expected Free Cash Flow for a business.
2. We assume current Gross Margins will remain the same in the future.
3. We assume current Fixed Operating Costs will remain the same in the future.
4. We always look for a 30% Margin of Safety – difference between current stock price and purchase price.

“Revenue growth we’d need to believe in order to buy the stock” is a cumulative number, not an annual growth rate. This is important. Now, you may ask, “cumulative for how long?”. We’d say, “an average of 5 years”. We expect some companies to achieve this cumulative growth in 2 years while some will achieve it in 7. We can’t be precise about it, but it really does vary from company to company.

These other assumptions are somewhat crude. But for a first cut, this methodology is the most logical and effective way to screen investment candidates. It relieves us from the futile task of making precise forecasts. It gives us a quick way to spend our time wisely.

To really make educated assumptions about the trajectory of gross margins or fixed operating costs, we would need to dig into the story – 1) a firm’s competitive advantage, 2) the durability of that competitive advantage and 3) the management team’s strategy and investment plan. This analysis is usually done on a short list of highly promising candidates. That’s what this article is about.

We’ll start by splitting the AI & Big Data Watch List into sub-themes and then narrow down our list using some other metrics.