By JAMES SPENCE
Themes help corral ideas and make connections between companies across sectors.
As captioned in a recently recorded presentation (click here to listen, 10 minute run-time) themes are a convenient hand-hold for long term equity investment. If we have a theme in place, we are definitely investing in and around it.
Sectors themselves are less useful markers as sectors derive from models of industrial classification and vastly different business models can be subsumed into sector headings.
Renishaw is classified by GICS as an IT company and yet we understand it to be a precision engineering company. EssilorLuxottica is arraigned under Health but bears more resemblance to a fashion or retail company. Givaudan and Novonesis are classified as Materials but the materiality of each lies within microbiology, some of it living biology – a long way from the worlds of metals and rocks.
For us, the level below themes is ecosystems not sectors. The word ecosystems describe companies that are connected, either through a customer-supplier relationship or competitive dynamics or some other form of alignment.
The below chart, from that presentation, lists the themes extant in the portfolio today. They currently number 7 and we don’t envisage that list growing beyond 10.
In the below text, we profile our thinking on the first on the list: IP, rich and deep data and in the year ended quarterly, we will address the others.
The broad reach of this theme encompasses, at the one end, entertainment and at the other deep pools or sorted data.
As the consumption channels for entertainment have become digitalised, distribution channels have become commoditised. For TV, music, and games, the barriers to competing for consumer attention have collapsed. There remain some chokepoints, which prove the rule, such as the iPhone. What matters to consumers is content. The value of creative intellectual property has retained its scarcity premium. Music, perhaps uniquely, exhibits the Lindy effect, whereby the older the song the more persistent its value is likely to be in the future. As the pace of change in consumer experience accelerates in the digital age, content provides one of the most reliable sources of value creation.
Content IP takes a long time to build and is a scarce resource. SONY not only has a lot of valuable intellectual property (IP) but, unlike any other global entertainment company, its IP sits in leading position in all verticals. This makes revenues more resilient to switches in how consumers spend their time. Entertainment platforms all compete for attention and regardless of whether the expanding time is with TikTok or Netflix, SONY has a route to monetise its highly valuable IP. The breadth of its IP offers the possibility of following Tencent’s ecosystem approach to cross-fertilising IP across the verticals. This strategy is only just beginning and has a long runway ahead.
We also argue that the importance of owning IP cannot be overstated in today’s knowledge based economy. It is a source of competitive advantage, revenue generation, and the foundation to building brand equity and protective moat around a business. IP takes many forms: patents, trademarks, copyrights, industrial designs, institutional knowledge, and proprietary content and datasets.
If SONY best represents value in content within the portfolio, then we also think that the portfolio company S&P Global best represents value in data.
Data forms the bedrock of any business. It is paramount in driving strategic decision-making, R&D, market analysis, and ensuring operational efficiency. In an increasingly data-driven world, leveraging data effectively is essential for success and sustainability.
The ownership of proprietary data is even more pronounced in the age of artificial intelligence, touted as ‘the new oil’. The quality of any Large Language Model (LLM) hinges on the underlying input. Therefore, high quality, diverse, and continuous influx of data are essential for training models effectively to ensure the reliability of the outputs. As AI continues to evolve, the ability to harness and manage data effectively will be critical for organisations aiming to thrive in this digital landscape.
When contemplating the interaction of AI with data it is important to think across different modes: LLM’s gain most attention as they deliver syntheses and (critically for time poor workers) summaries of primarily verbal sources. AI has equal or greater facility in numerical and chemical/biological data sets, hence what we believe will be well-proven optimism behind the ability of AI to spur drug formulations and further unlock biology and micro-chemistry to our benefit.
S&P Global (SPGI) is the owner of the ubiquitous indices S&P 500 and the Dow Jones Industrial Average. But the index business is in fact the smallest of its five divisions at 11% of group revenues. It is also the top credit ratings agency globally, and a leading provider of a breadth of specialist data, analytics, and research across the financial, automotive and commodity markets worldwide.
The company has several advantages stemming from its extensive coverage, historical depth, sophisticated analytics & research, and trusted methodologies. Most significantly, clients depend on these non-discretionary data to make informed decisions in a high frequency, high stakes environment.
The nature of this business is ideally suited for leveraging AI and machine learning to uncover innovative methods for dissecting data and distil information. This enables clients to derive greater value from SPGI’s offerings through enhanced data analysis, improved speed and accuracy, pattern identification, and process automation.