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August 3, 2021updated 06 Aug 2021 3:07pm

Future technology bets: 15 innovation-led technologies to watch out for

By GlobalData Thematic Research

Technology innovation is relentless, and businesses face high risk of being disrupted if they fail to detect and adapt to rapid shifts in the technology landscape early enough. GlobalData believes understanding the pace of growth in key drivers of technology innovation – Patents and Funding – are ideally suited to identify the key inflection points in a technology evolution which enables making the right technology bets at the right time.

Combining the two chief drivers of innovation, GlobalData has developed the Technology Innovation Intensity (TII) indicator, which yields the below top 15 innovation-led technologies to bet on which will likely deliver the biggest strategic advantage in the future.

Adarsh Jain, director of financial markets at GlobalData, says: “Patents capture intellectual property on top of which business build products and services, while Funding captures seasoned Venture Capital (VC) and Private Equity (PE) investors anticipation of returns from technology, and these two in unison captures rather well the future pace of growth and evolution of a technology.”

Solid innovation fundamentals underpin future outlook

In general, rising patent grants and venture capital investors’ interest in a technology are solid forward-looking indicators pointing to rapidly accelerating technology innovation with potentially transformative impacts across sectors upending existing business models. Find a couple of examples below.

GlobalData believes Autonomous vehicles (AV’s) will feature prominently in the future of mobility and transportation, and it currently ranks in the top 10 of GlobalData’s TII as it has exhibited a rapid surge in patent grants over the last 3-4 years. This has incentivised ramp-up in venture capital funding over the same period.

This trend of rapid surges in patent grants and VC funding are solid innovation fundamentals to have, pointing to rapid acceleration in the AV sector’s innovation intensity. As a consequence, this points to its immense potential to meaningfully impact and transform the status quo in mobility and transportation sectors.

This is evidenced in Autonomous vehicles startups steadily evolving to fulfil the software and hardware value chain in SAE Level-02 and above with their niche offerings in the areas of resource optimization, passenger comfort and safety, and navigation to enable wide scale adoption of fully automated vehicles.

Below is GlobalData’s list of top-ranked Autonomous vehicles start-ups with a high probability of becoming unicorns.

Click here for more details.

To take another example, consider how Virtual and Augmented Reality (VAR), currently ranked 15 but poised to move up the rankings in the future, is witnessing rapid growth in patents – a sign that companies in this ecosystem are bringing out more innovative products and at a rapid pace.

What’s interesting is that the distinction between companies in the VAR space is fast disappearing with many companies diversifying at an early stage. GlobalData notices a concentration of companies in the hardware development and content creation areas with applications in diverse fields.

Below is GlobalData’s list of top-ranked Virtual and Augmented Reality start-ups with a high probability of becoming unicorns.

 

Click here for more details.

Early identification of technology shifts

GlobalData’s work on the TII has shown that using key innovation drivers to help identify rapid technology shifts early and thus plan ahead to extract the maximum strategic advantage.

The below chart plots the trend in TII over the last few years. A few interesting points are:

  • Technologies ranking high in 2015 have tended towards the bottom in 2020 and vice versa, meaning technologies to bet on today are vastly different from technology bets placed in 2015.
  • Top ranked technologies in 2020 have moved to the top in just the past 2-3 years, suggesting rapid shifts in the technology landscape.

Mr Jain adds: “An important element of our work on TII has been to validate the efficacy of our indicator. We have robustly tested and validated our TII indicators against key external benchmarks (which tend to proxy technology adoption), like thematic price index, Google trends and technology fundamental datapoints like tech sales, subscribers etc.,  and found our indicator to be predictive – meaning our framework credibly informs placing the right bets on the technology at the right time and profit from it.”

On average, the TII indicator provides 2+ years of lead information in predicting the key inflection points in a technology to enable businesses and investors to plan ahead and extract the maximum strategic advantage and value.

Additionally, deploying our TII at company level enables thematic/technology investing by building custom stock baskets with highest innovation intensity for a technology. For instance, below is GlobalData’s Artificial Intelligence stock basket comprising companies from the S&P 500 with highest innovation intensity. We note that such custom stock baskets out-perform the benchmark significantly and help investors reliably capture ‘Innovation Premium / Alpha’.

How is the TII indicator predictive?

Over the past decade or so technology has started to play a more dominant role across industries and sectors and as a consequence all companies in essence are turning into ‘technology’ companies, with increased focus on building products and services on top of patentable Intellectual Property (IP) to drive sustainable competitive advantage.

And as the TII indicator measures innovation using patents (which details firms’ intellectual property), it is able to capture the future growth potential of the company based on the growth of its IP, and its therefore predictive in nature.

Mr Jain concludes: “Technology Innovation Intensity helps identify the right technology to bet on at the right time to ensure building sustainable competitive advantage. Plus our work is robustly validated to be predictive and our conclusions are completely explainable by the behaviour of key innovation drivers. Finally, our work is objective, completely data-driven and free from personal biases which so often polarises views on a technology making it hard to separate hype from what’s real and impactful”.