It’s about the high performance data capture (and a little about the auto manufacturing capabilities) — McLaren meets Apple??
At Notion we have been keeping an eye on the automotive industry for a while now as we believe it’s a market that, as it transitions from selling cars to offering mobility as a service, will cause broader tectonic shifts into our overall way of life, and not just in terms of transportation. We started our venture in this massive transition by joining FIVE.AI’s journey earlier this year.
So when the rumors started a couple of weeks ago that Apple might have taken an interest in McLaren we decided to take a look at why McLaren might make an interesting acquisition target, and what this means for tech companies trying to partner with more traditional auto manufacturers. And to be clear, we’re still not sure if we are looking at an acquisition, strategic investment, a partnership, or just unfounded gossip.
The British automotive company was founded in 1965 by Bruce McLaren as a motor racing team. It has since then grown into a conglomerate with $475M in revenues and has diversified into other precision manufacturing areas. The group is now broken down into:
McLaren Applied Technologies
Absolute Taste (A thriving luxury catering business…)
McLaren Technology Centre
While a few of these might represent an interesting acquisition target, the one to focus on is McLaren Applied Technologies (previous McLaren Electronic Systems); in my view the crown jewel. The Applied Technology team which creates control and data systems has applied its research across healthcare and energy amongst other sectors but their true expertise lies of course in automotive and especially in the highest levels of motorsport. Their high-rate real time telemetry systems were first used for sports cars at Le Mans in 1991 and in F1 in 1993. They now provide the powertrain control and principal data logging tools for all competitors in those championships which are capable of dealing with large volumes of time-series data generated from various sensors in real time (including F1, Nascar, IndyCar etc). Some of their flagship products, like vTAG and ATLAS, focus on the viewing, analysis, recording and management of data primarily in the field of body dynamics (body roll, damper height, body flex etc). The team also developed an extensive and impressive collection of sensors. All of this allows teams to analyze data in real time, run simulations, and optimize their vehicles accordingly.
It is easy to understand why Apple might be interested in a team that has developed such high quality hardware and software technologies that have successfully been embedded into racing cars, performing while being subjected to the most extreme conditions. Especially the modeling and simulation expertise on the team would be a highly sought after talent pool. This would allow anyone managing an autonomous vehicle fleet, the ability to track, analyze, and control virtually all aspects of vehicles in motion, in real time. This is a set of capabilities which Apple (rumoured to be building its own vehicle), and most pure tech players have yet to develop, and acquiring/partnering with someone like McLaren could help them significantly speed up their product roadmap. The traditional vehicle OEMs would have developed in-house expertise for some of these capabilities over the years, but for someone building a vehicle themselves, Apple will need to have this in house as well to complete another piece of its full-stack puzzle.
While working at Living PlanIT I had the pleasure of engaging extensively with the Mclaren Applied Technologies team as one of our partners and seen their impressive operations and quality of their work. (I also had the pleasure to also visit their amazing technology centre in Woking on several occasions — a must visit for F1 fans). So no wonder they’re a target for any serious player in the autonomous vehicle space.
As this point, it’s hard to tell if these rumors are substantiated, nothing but gossips, or serious acquisition talks that fall through without ever going public. What is clear is that pure tech players will struggle to build a car on their own. We’ve seen Google and Apple push back their release dates and cycle through a few project leaders. Up until now, analysts have focused on traditional OEM’s lead in terms of manufacturing and infrastructure as opposed to tech player’s owning the state of the art in terms of machine learning. Players have tried to compensate with investments (Tesla Giga-Factory) and acquisitions (GM-Cruise), but one area that has been ignored is high performance data capture. Regular winners at LeMan and F1 have used, and enriched, systems like those produced by McLaren Applied Technology. Just a GM’s acquisition of Cruise triggered an applied ML for automotive acquisition race, an Apple-McLaren announcement could do the same for high performance data capture systems.