Are We There Yet? Part II

A Study of Investment Timing in Emerging Technology Platforms

by Mike Droesch and Gus Warren, Samsung NEXT

In Part I, we highlighted trends in adoption of historical consumer technology platforms and analyzed the timing of the best VC investments in software and services companies built on these platforms. In Part II, we discuss how we have extrapolated these trends forward, and how we expect them to play out in some of the emerging consumer tech platforms.

Opportunities on the Horizon

In Part I, we discussed a trend of successful VC investments being made earlier in the consumer adoption cycle, and how we expect this trend to continue over the next ten years (also illustrated in Figure 2 below). While we expect this pattern to continue, we predict that the trend in successful investments being made with less adoption will begin to level off. This trend has been driven by two factors that have structural limitations:

1. Platform adoption times compressing – Platform adoption times have dramatically compressed over the past 30 years, as shown in Figure 1. However, there are some practical limitations to how fast a platform can be deployed, such as manufacturing and distributing hardware, and building out infrastructure. Therefore, while technological advancements may continue at exponential rates, we do not expect platform adoption times to compress indefinitely.

Fig 2. Reduction in Time Required to Scale a Consumer Technology Platform [1]
2. VCs investing earlier – VCs have been making first institutional investments earlier in the lifecycle of a company than in previous decades. However, we expect this trend to level off. Over the last decade the cost required to found a company dropped dramatically. This led to a substantial increase in seed funding and heated competition to invest earlier and earlier. Seed funding though, appears to have peaked in 2013. Therefore, while we expect investors to continue investing actively at the seed-stage we don’t expect the trend of investors competing to invest earlier and earlier to continue.

Based on this assessment, we have estimated that future platforms will become ready for their first successful venture investments when they reach customer adoption of between 5% and 12% of maximum adoption.

Fig 2. Projected Consumer Adoption at Time of 1st Successful VC Investments in Emerging Platforms [1]
The next step was to determine what platforms are currently in this range, and when we expect other emerging platforms to reach this range of customer adoption.

In terms of emerging consumer technology platforms, we are at an interesting time in the history of computing where there is no one definitive platform expected to follow the past platform waves of the PC, internet, and smartphone. Instead, many thought leaders debate what the next platform will be, speculating about everything from wearables to AI. For the purposes of this analysis, we have focused on four platforms that we at Samsung NEXT expect to reach broad consumer adoption, although it is too early to guarantee they will all be successful. These four platforms are:

  • Smart Home
  • Consumer Drones
  • Voice Interfaces
  • VR/AR

All of these technologies could potentially serve as platforms for a host of other successful software application businesses. We left out other major technology trends such as 3D printers and blockchain because of uncertainty over the role they can play as platforms for other consumer businesses.

We have projected the consumer adoption of each platform based on public forecasts for each market. While we are skeptical of long-term forecasts, we do think they are helpful in putting a stake in the ground and recognizing one potential way that the future may play out. In the plot below, we have identified when each platform is expected to reach 7% of maximum customer adoption, which aligns with the timing of the first successful investments in the smartphone and 4G markets.

Fig 3. Forecast of When Emerging Platforms Will Become Ready for Investment [2]
The figure above illustrates roughly when these four consumer platforms will reach a level of adoption where successful VC investments can be made in software companies built on top of them. However, we acknowledge that it is still too early to tell how big each of these markets will eventually be, and what the “killer use-case” will be for most of these platforms.

Analyzing Investments Across Software Layers

Within our broader analysis of investment timing, we also looked at differences in when different types (or layers) of companies are built. We grouped all of the software and services companies into 3 broad buckets:

1. Utility Layer – The underlying infrastructure software that supports other functionality on the platform, including utilities such as analytics and developer tools
2. Application Layer – Consumer-facing applications and services, including games, content and marketplaces
3. Optimization Layer – Software designed to help improve application performance and monetization, including services such as discovery, aggregation, and revenue optimization

Take for example the smartphone era. We looked at a large swath of software businesses built on the smartphone platform that exited for at least a 1X multiple of invested capital, and sorted them into one of these three buckets. In the figure below, we plotted how the share of these buckets changed over the adoption cycle of the smartphone. The smartphone market illustrates a common theme that we saw in other markets as well, where in the early days, more than 50% of companies with >1X exit were utility layer businesses. However, as the platform evolved, more than 70% of companies were application layer businesses with a small share being optimization layer companies.

Fig 4. Distribution of Successful Companies by Type, Throughout the Smartphone Adoption Cycle [3]

A Forward-Looking Framework

To condense our findings into an easy-to-use tool for investors and/or founders, we developed a scale to try and correlate risk with level of customer adoption. This framework is designed to help investors decide if they are comfortable with the ‘timing risk’ associated with application or service businesses in a market, given the customer adoption of the underlying platform.

Fig 5. Emerging Platform Timing Risk Scale

As we applied this scale to the four markets we analyzed, we were able to better visualize where each market falls on the scale. Based on this analysis, we expect to see many of the emerging consumer tech platforms ripen for investment over the next few years.

Fig 6. Forecasted Positions of Emerging Consumer Technology Platforms on the Timing Risk Scale [2]
To better illustrate what the chart above shows, take the example of voice interfaces. From 2014 to 2016, simple voice interfaces started emerging on devices like phones and TVs; however, the technology was generally limited and the platform was too small to support any highly successful third-party software applications. From 2017 through 2018, we expect voice technology to reach a tipping point in terms of speech recognition precision and customer adoption, enabling startups to build voice-based software businesses with the potential for outsized venture returns. From 2019 onwards, we expect continued innovation in the space; however, it is likely that the opportunities for great early-stage venture investments will decrease after this point.

It’s important to reiterate that these time frames only apply to early-stage institutional investments in software businesses built on top of consumer tech platforms. This scope does not include investments in companies building out the platforms themselves (e.g. Oculus for VR).

Notes on Putting This Framework to Work

While we hope our analysis and framework help investors identify when markets first become appropriate for venture investment, timing is obviously only a small part of the investment decision making process. Once an investor has conviction in a market, we think this approach can provide them with strong perspective through which to analyze investment timing risk.

In addition, the approach we have outlined is only as good as the data points that investors can feed into it. In particular, our assessment of customer adoption is highly dependent on both forecasts of future user adoption, and the maximum expected user adoption for a given platform. Therefore, if an investor overestimates the future market potential, they may overestimate the amount of penetration needed to hit our target range of customer adoption and be late to invest in a market. Similarly, if an investor overestimates how quickly market adoption will accelerate, they may be more likely to jump into a new market too early.

Finally, as early stage investors, we will continue diving head-first into emerging technology platforms and helping founders push the boundaries of these new frontiers. And we hope this research will help other investors become more comfortable with the timing risks associated with new consumer technology markets.

Reference Notes:
[1] See below for data sources used to model adoption for all platforms.
[2] See below for data sources used to model adoption for all platforms. Voice Interface forecast is based primarily on forecasted adoption of Amazon Echo platform.
[3] See below for data sources used to model adoption for all platforms. Investment data from custom analyses in CB Insights and Pitchbook. Investments were manually categorized into one of the three buckets.
Modeling Sources:

Smartphone Adoption:
2005 – 2015: Deutsche Bank

Consumer PC Adoption:
1975 – 1980: PC Adoption – eTForecasts
Households 1975 – 1980: US Census
1984 – 2012: US Census
2015: Pew Research

Enterprise PC Adoption:
1975 – 1980: ArsTechnica
1984 – 2001: US Census
2003: US Bureau of Labor Statistics
2014: Reality Mine
Dial-Up Adoption:
1990 – 1994: WorldBank
1995 – 2014: Pew Research
2015 – 2016: Internet Live Stats

Broadband Adoption:
2000 – 2015: Pew Research
2000 – 2015: Pew Research
Gaming Console Adoption:
1977 – 2001: A Brief Social History of Game Play, Dmitri Williams, University of Illinois at Urbana-Champaign

4G Adoption:
2010 – 2012: GSMA and Navigant Economics
2014: 4G Americas
2015: 4G Americas
2016 – 2020: 4G Americas

VR/AR Adoption Forecast, 2015 – 2025, Average of 4 Different Forecasts:
Goldman Sachs
Business Insider
Greenlight VR

Smart Home Forecast, 2014 – 2020: Statista
Voice Forecast, Extrapolated Based on: Business Insider
Drones Forecast, Extrapolated Based on: Tractica
US Share Estimate: Emberify