We’ve been closely following the highs and lows of Fever-Tree since it was listed in 2014. From 2011-21, revenue grew 39% CAGR at sustainable 30%+ ROICs. According to Nielsen, FEVR is the market leader by value in tonic water across the UK and EMEA and in ginger beer and tonic in the US. It’s much more than just a tonic brand today:
However, over the last 5 years, Fever-Tree’s gross margin has compressed from 50%+ to ~35% in H1 24. Although FEVR continues to win share, the margin compression and slower organic growth has caused the stock to reach 7 year lows.
After revisiting the thesis, we’ve curated our historical Fever-Tree primary research into a learning journey. This aims to help you navigate the history of the business and core drivers of long-term value. There are three aspects that attracted us to study Fever-Tree:
We share our research on all three topics. We first share the history of Schweppes and why it seems to be an ineffective competitor to FEVR. But the main focus of our research is how Fever-Tree's relationship with spirit companies and distribution strategy may build a durable moat.
We also curate our work on why and how the company’s gross margin has evolved over the last 5 years. Fevertree's gross margin was hit from both sides. From 2018-23, inventory costs as a percentage of sales (blue line) has increased from 41% to 52.7%. Non-inventory costs (red line), mainly logistics and bottling, have increased from 7.2% to 15.1% of sales.
This IP Learning Journey also helps you navigate the history of Fever-Tree’s bottling arrangements, questions around pricing power, and the temporary post-covid operational challenges. The full contents of our research is as follows:
We're fascinated with how Danaher deploys DBS policies across its businesses. As the group has shifted from an industrial conglomerate to a life sciences group, DBS has remained at the heart of the company’s operating philosophy.
DBS isn’t simply lean and six sigma methodologies. DBS is a toolbox of over 100 policies targeting all functions across the business. Danaher has extended the kaizen principle of continuous improvement to sales and marketing, R&D, and leadership.
This is interesting because DHR is fundamentally a different business today than it was 10 years ago. It’s not operating industrial businesses like Fluke or MasterShield; it owns assets that generate recurring, high gross margin, consumable revenue. This requires a different sales motion and inventory management techniques.
Can DHR deploy DBS to its bioprocessing or life sciences assets just as well as it did to its industrial assets?
Maybe high-quality assets with 80% gross margin consumables are actually more inefficient than some manufacturing businesses? High-margin businesses can afford to hold too much inventory or not be rigorous around value-based pricing, for example.
Also, how DHR can deploy DBS in life sciences is even more important given it’s paying premium prices for assets like Aldevron.
Over the next 6 months, we plan to explore how DHR deploys DBS across sales and marketing, R&D, and leadership. We aim to compare the potential to improve life sciences operations relative to industrial assets.
This interview is the first in the series and covers how the DBS office is structured and how to measure and manage R&D spend:
The DBS architecture, at least when I left in 2019, was organized into different segments and domains. They have DBS core fundamentals, growth, lean, and leadership tools. Within the growth category, they might have commercial sales, marketing, and innovation. The DBS office is structured similarly to align with the toolkit. There's a VP of the DBSO who sits on the Danaher corporate leadership team. Underneath that person, there are vice presidents or senior vice presidents for different segments, like growth, innovation, and lean. Each Danaher tool has a single owner in the corporate office responsible for governance and content updates. Across the company, DBS leaders and other individuals could be certified in various tools, requiring a process to demonstrate understanding and capability. The person owning the tool would vet this. In the corporate office, they scaled it differently, with advanced practitioners granting certification. There's a structure where a single person in the corporate office owns each tool and defines certification criteria. - Former Senior Executive at Danaher
In 2022, Tesla made the decision to remove its ultrasonic sensors from its vehicles and replaced it with Tesla Vision, its vision-based occupancy network. Tesla is all-in on camera vision data as the critical input to reaching L4 autonomy.
Musk seems to be betting on end-to-end machine learning to automate driving. On the other hand, Waymo believes the problem it’s more nuanced and fuses together lidar, radar, and camera perception data from its vehicles.
This interview with a Former Waymo Senior Executive, who has over 25 years robotics experience, explores Tesla vs Waymo’s strategy in reaching L4 and how the development in machine learning has influenced autonomous technology.
Take the end-to-end argument, for example. The argument is that end-to-end learning is the most natural. If you have enough data and a large enough model, you can capture everything. In theory, that's true. In practice, the idea of just inputting data and optimizing the output is elegant because it's not an engineered system; it's pure. However, you have a truly infinite problem, and you encounter issues where it doesn't work as well as desired. With one gigantic model, determining the cause of issues becomes challenging. Is it a lack of examples of unusual sunlight on sensors? Is it inadequate handling of rain? Is pedestrian tracking not nuanced enough? Is it the behavior and negotiation with people? It's all mixed in. In theory, you struggle in certain situations but have few levers to understand why. - Former Senior Executive at Waymo
It will be interesting to see if Tesla can fine-tune its perception data to improve its behavior models:
There's a trade-off between an end-to-end solution and an architecture with a flow of information, allowing system-level confirmation. You can perform structured tests on perception and behavior in specific situations, clamping parts of the system to understand what's working. This isn't proven and could be wrong, but most find that end-to-end systems show beautiful results early on and scale well. However, with a mature system, improvements become difficult due to rare examples. The only option is to add more end-to-end examples. You can't fine-tune specific perception data or train behavior models in certain circumstances with adversarial scenarios. - Former Senior Executive at Waymo
Tesla is a defendant in a class action lawsuit regarding its 'near-monopolistic behaviors' regarding vehicle repair. The main argument against Tesla surrounds the higher-than-average repair cost. One reason is that it's not possible to perform a key test in a repair shop called a structural pull. When a mechanic repairs an ICE vehicle, it performs a pull test to certify the structure of the car is robust. Because of Tesla's manufacturing techniques, it doesn't seem possible to conduct pull tests. This leads to more replacement parts which drive TSLA gross profit and higher cost of ownership for car owners.
As this Tesla-certified body shop owner explains, what might seem like an anti-competitive approach to repairing cars, could very well be the safest way to go about it.
"You can't do a structural pull on a Tesla, which is one of the smartest things I've seen. I wish other manufacturers would adopt that logic. If you do a pull on a vehicle, you can't test the integrity of that spot weld. It's genius. If you can't test what has been done by the manufacturer, how can you trust that the repair will hold? It's a good mentality to have. It's a smart way of doing it, and I like it. You can say what you want, but it's a very smart way of thinking. The logic makes sense. - Tesla-Certified Body Shop Owner
This interview with a Former Senior Sales Executive at Ecolab explores its sales organization structure, pricing power and relationship core Food customers.
"There's a lot more of that sentiment in the institutional world than anyone inside the company might realize. When you're inside, you don't think that way. But yes, a significant portion of the market buys from Ecolab begrudgingly because it's soap, and they are the best. Even though it's expensive and the company can be arrogant, customers know they won't have to deal with issues. They have enough to deal with in their lives, and soap is not something they want to think about. There's a lot of that sentiment out there - Former Senior Sales Executive at Ecolab
Multiple PE shops are aggressively rolling up IVF clinics. The industry is fragmented with ~50% independent, 35% part of a clinic network typically PE-backed, and the rest ran by the health system / academia.
In this interview with a COO for a US group with a dozen clinics, we explore the US fertility clinic economics & regulation.
Unless you live in Massachusetts, the mandates are really like a tease. They get you into treatment, but statistically, you need at least three or more cycles to walk home with a baby. Some of these mandates get you enough to start treatment but not enough to get a take-home baby. When you are done with your lifetime max, you have to figure out if you're going to walk away from treatment or how you're going to afford to become a private pay patient. - Chief Operating Officer at Large IVF Clinic
State regulations around insurance coverage have a big impact on the volumes IVF clinics can expect in certain geographies.
Over 4% of births in the Northeast of the US are Assisted Reproductive Technology (ART) due to insurance coverage.
We plan to curate our research on IVF and the fertility equipment manufacturers over the next few weeks.
Braze is a $3.2 billion market cap provider for marketing software. This Sales Executive for competitor Customer.io and formerly Oracle explains how Braze targets new verticals and what drives the shift from legacy martech providers to newer products like Braze & Iterable.
In terms of opportunity, there is plenty. In terms of verticals, they move across them. For example, when gaming becomes a big focus, they target three or four major gaming brands, making that their enterprise team's priority. They are well-covered. Braze, in particular, has good coverage across travel, gaming, and QSRs. Do I think there's white space? Yes, both in new sectors and in terms of clients that follow those big names. - Former Sales Executive at Braze Competitor
In this interview, a Former VP at Trussway Manufacturing sheds light on the US truss manufacturing market and Builders FirstSource positioning. One interesting insight is the potential impact robotics on profit margins.
"At 90% [utilization on a robotics plant], you're looking at 18% to 20% [EBITDA margins], somewhere in there. - Former VP at Trussway Manufacturing
In this interview, a former VP at Manchester Tank shares his views on the threat of Asian manufacturers of small to mid-sized propane tanks.
I would say anything like a 100-pound cylinder and less is fair game, and that's kind of heading that way. It's a major competitor and threat. As you get to the 420 vertical, which is a larger storage tank, that's where it starts getting probably uncompetitive, although we have seen some of that starting to happen. So, I would say the break would be between the 420 and 100-pound vertical. - Former VP at Manchester Tank
In this interview, a former Senior Director at Norwegian Cruise Line sheds light on the evolution of the luxury cruise market, the main players involved, repeat rates, and the economics behind it.
The mass market repeat rate is greater than a 50% chance that a mass market person will repeat within 18 months. The luxury guest, without a doubt, is cruising every year. On the high side, the ultra-luxury client could be taking six cruises a year. - Former Senior Director at Norwegian Cruise Line
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