Saul,
Thanks once again for a detailed and highly informative report. I know I am not alone in expressing deep appreciation for the fact that you so freely share your thoughts and wisdom gained from years of successful investing experience. I’ve followed this board nearly since its inception. I always look forward to and carefully read your posts and especially your monthly summaries (and occasional mid-month activity reports). I am not nearly as interested in your positions as I am in your lucid explanations of why you hold and why you trade.
I am sure you are aware that I do not post my portfolio and seldom state my trade activity. It is not that I am selfish or embarrassed or any of those kinds of reasons. It is primarily that I don’t feel that I have a lot of new information to add, especially with respect to financial analysis. My strengths and therefore my contributions are largely based on 30 years of experience in a very large IT shop where I closed my career in a position of high influence over the direction of the corporation with regard to data/information management (I wrote the approved definitions for my company that distinguished between data and information. In condensed form, if it is manipulated by a machine, it’s data. If it is perceptible to and consumable by a human, it’s information).
Even though my experience base with respect to the specific technologies is rapidly growing stale and I make little effort to KUTD as I was pretty well burnt out when I retired, I still have a pretty good understanding of the basic technologies and I feel a good deal of the historical perspective I gained is still relevant. I also feel that having been close to the internal decision making process in IT for most of my career my experience is relevant because even as the technology rapidly changes, I have reasonably high confidence that management decisions remain driven by the same factors that they were for virtually my entire career. The specific technologies play a role, but they are just another factor, certainly not the only one and often not even the deciding one.
I am also very familiar with the mindset of techies. Over my career I saw many people come and go. I was one of the “old guard” that remained in the company, though my role in IT went through many changes. IMO, irrespective of chronological age, techies share a lot of common characteristics. Even though they are not the decision makers, they play a significant role in the decisions that get made because they form the knowledge pool that must be taken into consideration when big decisions are made. So, my experience is the basis of my contributions to this board. It is far more relevant now than it was when we were investing in sneakers and home builders.
On to observations - - -
One thing I’ve been slow to pick up on is what you appear to mean with the words “when the story changes.” Most of the time, this applies to the specific company you are talking about, but I’ve discovered that not too infrequently it is the relative story rather than the specific story. What I mean by that is you have no income stream and hence no new money for investing. And, you like me, stay fully invested or nearly so most of the time. So when you wish to make a new purchase, the money has to come from somewhere. That means you’ve got to sell something. But, you already feel that you are invested in the best and smartest investment out there. That presents somewhat of a conundrum.
Along comes Zoom (I’m long), Datadog (I’m long), Coupa (no position) and you want to invest in these companies as you feel the opportunity is too good to pass up, but in order to do so, you are forced to take a hard critical look at all your current category crushers in order to decide what to sell in order to raise the cash for the new investment. Sometimes, the decision isn’t that hard as there was some new news during a recent conference call or from a competitor that makes the decision a bit easier. But sometimes you’re decision is not driven by news that directly reflects on the companies you end up selling (i.e., Alteryx). The decision is a relative one in which you compare your current portfolio positions with respect to the new opportunity. Maybe, as in the example just cited, it’s based on the dominance of one position. Maybe you’ve lost patience with a growth lull (i.e., Mongo, you even said you know this is not a valid reason to sell, but it was your reason).
Personally, I find pulling the trigger to sell a far more difficult decision (most the time) than the decision to buy. Buying (unless I’m adding to a position) always involves a new, unfamiliar relationship. Selling is shedding (in whole or in part) and established, familiar relationship. I’m hard wired to remain loyal to established relationships. It’s difficult for me to treat my investment relationships differently than the way I deal with life in general. I continue to learn from you, sometimes slowly.
But it is these relative decisions that set us apart. Let me explain. During my career I watched two database products dominate the industry. First, the IBM product, IMS DB/TP (that translates to Information Management System Database/Teleprocessing). IMS was not the only database product, but it was by far the dominant one. So far as I know, it only ran on IBM equipment, or near end of life IBM OS compatible equipment made by IBM competitors (we had a couple of red boxes in our predominantly blue shop. I have no idea if IMS was hosted on them). At the time I was pretty young but I was a spec writer and tester. I didn’t write code and I wasn’t a DBA. What I observed was folks around my age or younger come into the shop fresh out of college. They’d gather 12 - 18 months training at the company’s expense and work on usually only one development project and then market their newly gained, high demand skills to another company (virtually never a competitor), getting a significant salary boost in the process. It was not all that unusual to see the same face return 12 - 18 months later at an even greater salary. The knowledge pool that got built up around IMS (as well as the fact that it was an IBM product - “no manager ever got fired for buying Blue” was a common saying) helped cement it as the dominant database product. I doubt that all the competition combined matched IMS sales figures (that’s pretty much a WAG, but an “educated” WAG). But, IMS had a fatal flaw. It was modeled the same way business organizations are built. It was hierarchical. I won’t digress into an explanation of why this is bad, trust me, it has the potential of creating a lot of data integrity problems. And that potential often became a reality. GIGO - garbage in, garbage out. When you’ve got different outputs, some of which are supposed to share the same values but it doesn’t, which one are you going to trust?
But data integrity problems alone did not lead to the demise of IMS. There were lots of other organizational reasons (sometimes called “data silos”) that created these problems. Faulty database design was not really the main culprit. The biggest flaw for IMS was that it only ran on big metal. A new paradigm in computing began to take hold. It was smaller, geographically distributed boxes linked together via a network and the UNIX operating system that eventually killed IMS. As I mentioned. IMS was designed to run in the data center on “big metal”. Oracle (and numerous competitive products) was designed to run under UNIX. It was years before Oracle came out with a relational DBMS that could be hosted on IBM mainframes.
Even though the relational model was created by an IBM mathematician, IBM was slow to develop a relational DBMS. They were caught in the common dilemma of slaughtering a cash cow in order to keep up with innovation. However, the argument for distributed computing under UNIX took hold more rapidly than most observers initially thought possible. It was technically up to the challenge of supporting the computing needs of mainline, mission critical business processes, and the ability to incrementally scale capacity while (more or less) avoiding hardware vendor lock-in due to the common OS was just too financially compelling. Incidentally, I was the manager in charge of the group that established internal standards for applications (written in C, a computer code that one of my gurus referred to as a write only language) and database design (with Oracle as the DBMS) when the company I worked at transitioned to distributed UNIX architecture.
Why did Oracle, in the face of a lot of competition quickly become the undisputed winner? Well, partly is was the technology. UNIX is not vanilla. We had a standard of “POSIX compliant”, but virtually every vendor claimed POSIX compliance - - - with extensions. In other words, every vendor’s flavor of UNIX was in some ways different. Ellison offered several flavors of Oracle so it ran on machines from the most dominant vendors: IBM, HP, Sun and I thing two or three others. And then there was Larry Ellison. He was a charismatic tech leader who had the ability to smile and tell convincing lies through his teeth. Oracle rapidly issued new upgrades (which were upsells) with the claims of all sorts of new, highly desired functionality that was often too buggy to use. But, with a fair degree of reliability, bugs from the previous version were generally repaired. So with each upgrade you were really buying the reliable functionality of the previous version and maybe some new, usable features. As you might imagine, this kept my database standards group very busy.
Why am I relating all this history? In a word, Mongo. I’ve seen this movie twice before. First with IMS which didn’t offer a separate investment thesis and then again with Oracle which did offer a fantastic investment thesis, but I just wasn’t into investing at the time. But the latest sequel to this movie is Mongo. You might have your doubts as to whether or not it’s the clear winner, but having watched the movie close up before, I haven’t any. Especially since the release of Atlas that runs under AWS, GCP and Asure. It will take a colossal management screw up (always possible) to unseat and inhibit the long term growth of Mongo (which is a stupid name IMO, oh well).
What I’m saying in a rather long winded manner is we can see what makes horse races. Saul gives Mongo 4.5 stars out of six. I’d give it 7 stars out of 6. Of course, Saul and I are both getting on in years. He has a few years on me and neither of us may live to see this whole movie. So maybe impatience with the here and now is warranted. Each passing quarter of “I could’ve done better if I were more impatient with X and more aggressive with Y” is a quarter we won’t see again.
Is the race between quarter horses or milers? It makes a difference.
