With more time on my hand, I have actually started reading more books on subject matters about which I was very curious but never had time to go beyond reading the headlines.
In healthcare, I heard so many times about how artificial intelligence would bring about dramatic changes and how big data will disrupt everything within healthcare, including drug development. I also heard a lot about cloud computing and how Amazon ($AMZN) and Microsoft ($MSFT) were making so much money from it.
In reality, a lot of those big “buzz words” were highly abstract things and I never understood them because I never spent serious time to study them. With more time on hand, I wanted to learn more about them – while I started listening to webcasts or reading blogposts, it was tough to understand because I had no basic knowledge. Luckily, I came across a book that really is cloud/AI/big data 101 that was kindly written by a CEO of one of the most prominent AI companies – C3.Ai, and the author is Thomas Siebel – one of the first gen tech entrepreneurs who created CRM industry as we know it now and has the ears of prominent CEOs across the world as they consult him for driving digital transformation.
There are so many things I learned from the book – but reading the book was really profitable for me because I was able to bake key learnings into my investment / stock selection in Palantir ($PLTR), Teladoc ($TDOC), and C3.Ai ($AI). It allow me to build strong conviction, double-down on drawdown, and have patience to wait until stock prices went back up.
Hoping that my key lessons from the book would be helpful to your investment process as we all navigate through the ever-evolving business landscape, I wanted to share my key findings. I am using Teladoc ($TDOC) case to illustrate the power of AI and my case for bullish view on the company.
Fully integrated platform is more important than ever as the amount of information, speed of transmission, and real-time analytic are becoming critical for system reliability and actionability
As the information flow becomes constant and very fast, the analytics is also improving and this requires extreme stability of the systems – if all different vendors, it becomes extremely difficult to coordinate changes and the bottleneck becomes enormous (the system is as fast as the slowest segment). In addition, new updates from one vendor can introduce bugs across the system – it becomes nightmare.
In case of TDOC, they are fully integrated from providers (doctors), payors (insurance companies), and patients – the enclosed ecosystem makes sure continuous care and monitoring are delivered and utilized/monetized by all stakeholders reliably and predictably.
First-mover advantage in deploying AI platform will be even more profound as data aggregation lead and track record will translate to sustainable competitive advantage
The beauty of big data is that more data allows more accurate results – you will have more data and experience if you start earlier. the institutional data and knowledge base should remain competitive edge – particularly, track record of building and delivering AI systems successfully will be also increasingly important. Digital transformation is life-or-death situation for many companies – a corporation and its key decision markers want to make sure they get the best (capability) and also make sure they are covered (politics) by going with the party that has most experience. It could be similar to using Goldman or McKinsey as your advisor for a key transaction – you want to make sure you get the best. And the pricing for the best is NEVER cheap.
With lead in patient data in diabetes, Teladoc is probably best-positioned to provide virtual and continuous care for diabetes patients within the space – everyday there is more data gives more power to predictability of $TDOC platform.
Operating leverage on AI platform product will be enormous and top talent will be EXTREMELY critical (more than ever) to create the best in class product
Platform deployment is essentially virtual as the product is delivered as a service. However, beauty of AI platform is that it is EXTREMELY scalable and easy to deploy once you have the right program and talent. Top talent attracts and begets even better talent as the company builds reputation over time as the premier place – it not only becomes a resume builder for engineers, but also a great learning place to develop.
While there is incremental capital deployment for device for each patient, it is a very small fraction of life-time value of each patient (chronic diseases are sadly life-long diseases).
Chronic diseases can sometimes lead to acute events that can be life-threatening – you want to make sure you have the best-in-class product if the cost differential is not huge.
AI, big data, and real-time data means MUCH MUCH MORE powerful predictability that no longer requires academia-based experts
AI will diminish need for experts because constantly streaming data-based model essentially would be more accurate than a simple elegant model. There will still be need for theoretical exercise of hypothesis testing, but the demand will be much less. Back-testing could be an extremely powerful tool based on big data.
AI applicability is enormous and the companies that leverage AI the fastest will be likely to sustain their competitive advantage because they will have continued lead in the amount and quality of data and therefore value-added analytics
Data lead will be extremely difficult to challenge as long as the leader continues to innovate. Analytics with strong predictability can empower insights that deliver value to stakeholders and customers. For instance, I am bullish on Teladoc because they will be able to deliver premier care to millions of patients that suffer from chronic diseases like diabetes and hypertension based on their massive database that is built from all patients’ connected devices, including CGMs. TDOC will have software-based data collection, analytics, and care delivery that is extremely scalable and deployable across the world. And that subscription revenue should be able to carry very high multiple as they are durable and have massive secular tailwind. The core of this value creation is AI-powered data analytics and insight delivery that directly translates to $$ savings. In Teladoc’s case, virtual chronic disease patient management will massively cheaper than the drugs that these patients have to take – some of which could cost over $100K per year just on drug – additional cost keeps going, including constant monitoring by human care takers, etc.
Conclusion
I definitely learned a lot from the book and I am grateful that he took the time to write it so that all of us can be educated in the new world. The link to the book is below and I hope you enjoy reading and learning from the book as much as I did!
*not investment advice.
