My investment thesis on the market hasn’t changed in the past month, and I’m still more than 50% confident that we’ll see a medium to substantial drop in valuations as the Republicans’ overly business friendly policies are replaced by a Democrat government focused on long-term recovery from the Coronaconomy. With that in mind, I’m happy to remain broadly 20% cash for the moment.
Even though I very rarely trade (avoiding investment churn is one of the key success factors in building long-term growth), I maintain a watchlist of investment ideas, and generally review this fairly frequently to validate whether the investment thesis remains intact. I’ve already weeded-out most of the things I don’t want to hold from my portfolio, so I’ll be a net buyer once the general market timing feels right. The investments I’m currently considering are:
- Buy Crispr 1% starter position ($6B market cap)
- Increase Teladoc position to 2% ($18B market cap)
- Buy Datadog 1% starter position ($26B market cap)
- Buy Fastly 1% starter position ($9B market cap)
Albert brought Crispr to my attention a few weeks ago. The wilder end of my portfolio currently holds Editas, and I’m a firm believer that genome editing is a key part of the future of medicine. Editas is actually the baby brother to Crispr with a materially smaller market cap, but they’re both in the same business, and after some fairly furious patent battles a few years ago seem to have settled into different parts of the market. Crispr would be a very speculative play, but it’s a complementary holding to Editas, and it feels wise to back a couple of horses, given that this race has still barely started.
Teladoc recently acquired Livongo Health, another very complementary telemedicine service. Teladoc’s business has been to connect customers with general physicians and behavioral health professionals via mobile, web, video, and phone. Livongo focuses more on chronic disease, and helps customers manage conditions such as diabetes, hypertension, weight, and behavioral disorders. These are clearly very complementary services, and although the market initially reacted poorly to the merger announcement, I think it’s a positive step forwards, and one more likely to take dominance in what is currently a highly fragmented industry still in its infancy. I’ve been a Teladoc shareholder since February and feel like I have a better handle on the company, so it’s definitely overdue timing to increase my position from the starter 1% to at least a full 2%, if not a little more.
Datadog and Fastly are interesting choices for me. I consider them companion companies to MongoDB, which I analysed in detail at the start of August. They each use a ‘software as a service’ (SaaS) model to provide part of the infrastructure that a company needs to have a robust internet presence – essentially they’re part of the bricks and mortar of the new economy.
I’m self confessed that I have a somewhat limited understanding of Datadog and Fastly’s technologies, but two sources that I’ve come to trust over the last few months rate both companies very highly, and so to some extent I’m happy to build a starter position in this space, more driven by their recommendations than by my own analysis.
The two sources I’m currently referencing are Software Stack Investing, and Saul’s Board on the Motley Fool community. Saul is a retired investment professional, who has a strong track record in his personal portfolio, and a very similar investment philosophy to my own, with a focus on finding high quality companies on a huge growth trajectory. A large community of like-minded investors has sprung up around Saul, and the discussion on the board is a rich source of insight and different perspectives.
As of July, the current holdings of Saul and SSI are as follows:
Saul
- Zoom 22.9%
- Datadog 21.8%
- Crowdstrike 19.8%
- Okta 11.5%
- Fastly 10.4%
- Alteryx 9.9%
- Coupa 2.1%
SSI
- Fastly 23%
- Twilio 21%
- DocuSign 18%
- The Trade Desk 10%
- Cloudflare 10%
- Elastic 7%
- MongoDB 6%
- Okta 5%
These are both extremely concentrated SaaS focused portfolios that have done incredibly well through the Coronaconomy. Although my own portfolio is much more varied, there’s a lot of insight to be had across SSI and Saul’s Board when looking specifically at internet infrastructure companies.
Although I very recently said that I’d use the antifragile framework to drive my own investment decisions, having spent some time digging through these new sources, my thinking has evolved a little and I’ve decided I’d like to to adapt my investment assessment methodology to incorporate some of the growth metrics that Saul uses for his own analysis. I still see huge value in quantifying an investment decision using a framework, but with Brian’s questions as a starting point I’d like to score companies in a little more of a homebrew way, that pulls in some additional insights and weights factors differently.
From the Saul and SSI portfolios, I already have holdings in Zoom and DocuSign, and I ran my own analysis of MongoDB last month, determining that this probably wasn’t right for me. Looking across the rest of the SaaS stack, I am however fairly taken by the capabilities offered by two of the suggested companies, Datadog and Fastly.
Datadog provide a “monitoring and analytics platform for developers, IT operations teams and business users in the cloud age”. I’ve previously been a shareholder of one of DDOG’s competitors, Splunk, making a 42% return between Oct 2018 and May 2020. I sold Splunk primarily to free-up capital for more Coronaconomy focused opportunities, not for any real lack of faith in their product, but it does appear that Datadog has the superior offering from a technology standpoint, focusing on ‘observability’ across a whole system, rather the monitoring of any one component.
To quote from Software Stack Investing, “Datadog entered this rapidly evolving space at the right time with the right approach. They capitalized on the observability trend by offering both monitoring and context. They did this in one solution across the areas that matter – metrics, logs, traces, and for all relevant systems – applications, server infrastructure, network, third party services in all types of hosting configurations. They were the first company to offer a complete solution across these dimensions in one consolidated view (a single pane of glass).”
Fastly are an industry leader in “edge computing”, a much more advanced form of Content Delivery Network, enabling large-scale, coordination-free distributed systems. A traditional CDN deploys content at the edge of a network, closer to customers, e.g. Netflix have copies of their media distributed across the internet using AWS, so when you watch a movie at home, you’re streaming it from an Amazon server that’s close to your end-point, rather than from a huge centralised server in the core Netflix infrastructure.
The key difference between a CDN and true edge computing is in the level of complexity and processing logic that can be deployed at the edge – close to the customer rather than in the core platform. As an example, Shopify are now using Fastly’s Compute@Edge capability to allow their merchants to do real-time calculation of a product discount based on custom logic defined by the merchant. It would be computationally expensive for Shopify to allow their million plus merchants to define their own unique discount logic beyond a set of basic options, e.g. “buy 1, get 1 free”. By moving this processing to the edge, closer to the customer, the Fastly runtime environment allows Shopify’s merchants to create their own discount rules, running them in a fast, compact, secure manner that doesn’t put a drain on Shopify’s core infrastructure, and allows the discount rule to be applied on the fly during the rendering of the end customer’s check-out page.
Giving a slightly more personal perspective, I have a pretty dated but fairly foundational understanding of technology, with a Computer Science degree and my first 15 years in a technology career with roles that included C++ programmer, Unix system admin, Oracle DBA, and infrastructure manager. I recall many long nights (I purchased a couple of beds for the office during one very tough few month stint!) navigating our array of disconnected monitoring tools trying to figure out why a batch wasn’t running, so I get the concept of the unified observability offered by Datadog.
System performance can easily be bottlenecked by poorly written code, and we used to have endless debates between development and production teams to solve performance problems. Edge computing wasn’t the right answer for the internal facing banking system we were deploying, but I get the concept of highly distributed computing, and how this can help as systems scale up to meet ever increasing demand.
Although I consider myself a technology dinosaur these days, I do feel I have a decent handle on what’s going on ‘under the hood’, and I recognise the business agility created by SaaS.
My advice to friends has always been to “buy what you know”, so while I’ve shied away from technology infrastructure companies in recent years, it’s probably not for the right reasons, so it may soon be time to rebuild this part of my technology portfolio.
1 comment