A Man + Machine Process for Identifying Businesses with Moats

This article is authored by MOI Global instructor Luis Sanchez, Managing Partner of Overlook Rock Asset Management. Luis is an instructor at Wide-Moat Investing Summit 2018.

“The most important thing to me is figuring out how big a moat there is around the business. What I love, of course, is a big castle and a big moat with piranhas and crocodiles.” –Warren Buffett

A core strategy at Overlook Rock is investing in high quality businesses that may not trade at statistically cheap valuations but have the ability to compound at an above market rate for several years due to the existence of competitive advantages. Companies with sustainable competitive advantages are said to have a moat protecting their business from competition or other market forces, which can deliver significant value to shareholders over the long run.

Our research strongly convinced us that we could identify quality companies through a carefully reasoned and tested quantitative approach, enhanced with human oversight. As Michael Mauboussin noted, moats can be measured even if they cannot be simply explained.^[1]

Overlook Rock’s “High Quality Company” investment strategy involves leveraging quantitative techniques to measure the “quality” of businesses. We also perform bottom-up analysis to understand why moats exist in the businesses we invest in.  Finally, we constantly monitor our portfolio companies for the persistence of their “quality” and react accordingly if moats deteriorate over time.

There are many potential sources of a business moat. Competitive advantages can include a strong brand, superior economies of scale, or exclusive legal rights, just to name a few. Regardless of the source of competitive advantage, the existence of a moat can be evidenced by strong financial results that persist over extended periods of time.

As a starting point in identifying moats, it is important to define operating metrics that matter. Business operating metrics can include anything from annual revenue growth to monthly active users. We have identified several key metrics that indicate effective use of resources to produce real profits and value for equity holders. These metrics draw upon a deep understanding of business fundamentals and are backed up by careful and rigorous historical analysis to prove the theory out.

In addition to maintaining healthy operating metrics, the consistency and persistence of those metrics is a positive indicator of quality. It is one thing for a company to post a strong year after a weak year. However, if a company consistently posts strong financial performance year after year and over an extended period of time, there are likely competitive advantages or favorable industry dynamics at play. Not every high quality company needs to show good results every year, but as a general rule of thumb the more consistent and persistent, the better.

Improving trends can be indicative of moat strengthening. If a company not only generates strong metrics but consistently shows improvement in the underlying metrics, it is a sign that a company may be widening the gap between itself and its competitors.

While any individual measurement described above may identify a potentially moaty business, a combination of multiple positive data points provides a more reliable indicator that a moat likely exists. Thus, using a robust multi-factor quantitative process can be more powerful in identifying potential investments than a simple screening tool.

Quantitative techniques can merely identify the existence of a moat but human analysts are needed to explain why the moat exists. A core belief at Overlook Rock is that models are imperfect. Quantitative techniques sometimes produce false positives due to certain factors that may be more easily understood by humans. Supporting quantitative methods with bottom-up research complements and strengthens our investment process.

A false positive could include a situation where the historical source of a moat is no longer present. For example, when drug patents expire at a pharmaceutical company, generic competitors enter markets and radically change the earnings power of legacy products. The understanding that a company is highly dependent on a few contractual rights that may expire is more easily attainable for a human analyst reading a 10K and speaking to a management team than an algorithm purely focused on financial figures.

A false positive could also include a situation where historical operating metrics require a reinterpretation. “Reinterpreting the past” can be tricky and requires walking a fine line, but in this context we focus on what non-quantifiable issues can fool a model. For example, are there accounting issues that over- or under-state key operating metrics? In the case of companies with complex capital structures, it can often be confusing to determine how much earnings are attributable to minority owners or even how much capital is being employed in an enterprise without a careful reading of the accounting footnotes. Even premier databases such as Compustat often get the numbers wrong in complex or obscure situations. Also, GAAP accounting rules can sometimes obscure the economic reality of a business.

In the context of Overlook Rock’s research process, our default stance is to invest in the recommendations generated by our High Quality Company model (among others). However, if the human analyst has found a potential pitfall in the High Quality model’s application to real world situations, we may avoid investing in a specific recommendation. We let our model do the heavy lifting by systematically identifying high quality businesses, while avoiding the few exceptions that may trick our model. This is akin to what Howard Marks refers to as the “negative art” of investing.^[2]

^[1] Michael Mauboussin, “Measuring the Moat”, 2013.
^[2] Howard Marks, “The Most Important Thing”, 2011.