When tech writers and analysts talk about long-term competitive advantages held by market leaders, the discussion often turns to how network effects -- for example, among marketplace buyers and sellers, or among users of a social media or messaging platform -- set companies apart.
And in many other cases, the discussion revolves around how the hardware and/or software ecosystems built up by a market leader -- for example, by Apple (AAPL) and Alphabet/Google (GOOGL) in mobile operating systems, or by Microsoft (MSFT) in PC operating systems and productivity software -- serve as a major barrier to entry.
Relatively speaking, less attention is given to a more basic and straightforward advantage that market leaders tend to have: They can financially justify spending a lot more on R&D to roll out new offerings and improve existing ones.
Amazon Web Services (AWS), which is now on a $40 billion-plus annual revenue run rate, is a good case in point. While Microsoft and Google are making large R&D investments of their own in their respective public cloud platforms, Amazon.com's (AMZN) remains unmatched in terms of the number of new features and services it rolls out each year, as the dozens of announcements made each year at its fall AWS re:Invent conference drive home.
Individual AWS R&D efforts, such as the development of its ARM-architecture server CPUs to power new cloud computing instances, also show how superior scale can justify R&D investments that allow a leader to further differentiate itself. Developing a server CPU that can hold its own against Intel (INTC) and AMD's (AMD) offerings when running some (though admittedly not all) popular workloads is far from cheap, and can only be justified if a cloud provider has a giant number of customers that are willing to give such an offering a look.
Google Search, which (based on recent disclosures) appears to be generating over $90 billion in annual revenue, is able to use its large R&D investments to make numerous behind-the-scenes changes to its complex search algorithms (including ones that lean on AI/machine learning models) to improve search relevance and/or performance. Google is also able to invest heavily in baking contextual information and content into search results, and in developing a popular voice assistant that integrates with its search engine.
Nvidia (NVDA) , which in its last fiscal year generated $10.9 billion in revenue and spent $2.8 billion on R&D, shows how a market-leading chip developer can also leverage superior R&D resources to keep hungry rivals at bay. Even though (ahead of next-gen gaming GPU launches that should take place soon) Nvidia's gaming GPU line has been at a manufacturing process disadvantage relative to AMD's since early 2019, Nvidia's enormous chip engineering investments have helped it maintain a performance edge in the high-end gaming GPU market, as well as differentiate its products via specialized processing cores.
The story has been somewhat similar in the server GPU market. Prior to the recent launch of its A100 flagship server GPU, Nvidia was at a manufacturing process disadvantage here for close to 18 months. But it maintained a dominant position thanks to its chip engineering work, developer ecosystem and investments in building out a comprehensive software stack for AI/deep learning and high-performance computing (HPC) workloads.
A superior R&D budget isn't by any means a guarantee that a market leader won't lose ground to a challenger or two. For example, though it has a much smaller R&D budget, AMD has -- thanks to both solid execution and Intel's manufacturing setbacks -- rolled out PC and server CPUs that outperform comparably-priced Intel CPUs when running many popular workloads, and has gained meaningful share.
But when a market leader's execution is reasonably good, the virtuous cycle that exists between generating more revenue than one's rivals and being able to justify spending more than them on making one's products/services better can act as a pretty important competitive strength.