“I'm no genius. I'm smart in spots and I stay around those spots.”
- Tom Watson
Most of us are probably familiar with the above famous quote from IBM’s founder Tom Watson. Even Warren Buffett (Trades, Portfolio) used Watson quotes frequently in various interviews. This one is closely tied to the concept of circle of competency.
As with other great sayings in investing, the most important thing is not to recite them, but to proactively practice in a way that’s consistent with the timeless wisdom. In this case, what I recommend to everyone is the following: figuring out both your smart spots and weak spots.
I’ll walk through my own approach in figuring out my smart spots and weak spots. The first thing I do is compile a list of most of my investment decisions and find my notes on why I’ve made those investments. It can take a while to gather all the information. Luckily, I’ve written about a good amount of my investment decisions on GuruFocus.
The next thing is to rank the performance of the past holdings in terms of realized returns. I also have a list of current holdings ranked by unrealized gains or losses. This is my raw data set.
The third step, which is critical, is to come up with a way to categorize all the investments. I basically need two Venn Diagrams (one for winners and one for losers), which demonstrate the overlaps among different sets of investments. I used four sets here: sectors, Peter Lynch’s buckets with a little tweak, tailwinds or headwinds, and levels of uncertainty. Each investment will be assigned to four different sets. For instance, Nestle (NSRGY, Financial) would be assigned to the sets of Consumer Staples, Steady Compounders, Tailwind and Low Uncertainty. And IBM would be assigned to Technology, Slow Growers, Headwinds mixed with Tailwinds, and Medium Uncertainty. Zai Lab (ZLAB, Financial) would be assigned to Biotech, Fast Growers, Tailwinds and High Uncertainty.
All of the above steps are time-consuming and tedious. But once I’ve done all of that, the fun really starts to kick in – figuring out the overlaps of my winners and losers group. Of course, we need to also be aware of the role luck and randomness played in each of our decisions but for now, we’ll focus on the cold facts first. I’ll share a few interesting findings.
Let’s talk about two examples of losers first.
The data clearly suggests that I should be extremely cautious with energy stocks, especially oil- and gas-related energy stocks. I’ve written about my fiasco with EXCO Resources (XCOOQ, Financial) a few years ago. Let me just say that EXCO is not alone in that category. PHI Inc. (PHIIK, Financial), although less disastrous than EXCO, was also dissatisfactory.
The data also suggests that I should probably avoid highly uncertain, fast-growing, early-stage health care companies, even with strong tailwinds behind them (I know it sounds obvious). The list includes Interpace Diagnostic (IDXG, Financial), Evolent Health (EVH, Financial) and NantHealth (NH, Financial). There are different reasons why these investment have not worked out well. In most of the cases, I’ve not only visited the companies and met with the management teams, but also talked to competitors and customers. This is very humbling because I’ve been spending a considerable amount of time building a competency in the health care sector.
Another weak spot of mine seems to be medium-uncertainty, decent companies facing industry headwinds. Discovery Communication (DISCK, Financial), DaVita (DVA) and Colfax (CFX, Financial) are examples of this category. I’ve written about all three of them in the past.
Now comes examples of winners.
My batting average is very high when it comes to low-uncertainty, steady compounders with tailwinds across sectors such as Nestle (NSRGY, Financial) and Markel (MKL).
Low-uncertainty, consumer-steady compounders also seem to be my sweet spot. My past investments in Nestle, Dollar General (DG), Dollar Tree (DLTR), Kweichow Maotai (SZSE:600519) and Wuliangye Yibin (SZSE:000858) have all done very well for me.
Another very surprising finding is that my batting average is very high when it comes to banks. My investments in a group of Chinese Banks, Bank of America (BAC), US Bancorp (USB), JPMorgan (JPM) and Wells Fargo (WFC) have all produced very satisfactory returns.
Conclusion:
From reflecting upon my own mistakes and talking to many other investors, I’ve observed that few investors really know what their strike zone is. But all of us have sweet spots and weak spots, and it’s extremely important to figure what they are so we can stay around our smart spots and stay away from our weak spots. By going through a similar exercise that I outlined in this article, we can all be more like Tom Watson.
