The Hype Cycle

I came across an article today which talked about why IoT has fallen short of expectations (check it out here). In summary, the key themes were:

  • Optimism of prediction
  • Niche consumer value
  • Privacy concerns
  • Inconsistent standards across hardware/software
  • Costs and limitations
  • Slow promise of the smart home use case

Reading this reminded me of what tends to happen with the adoption of most disruptive (or new) technologies, whether the Internet, AR/VR, AI, blockchain, or cryptocurrency. It is best represented by the Hype Cycle for Emerging Technologies who shows the rise-fall-rise of how markets tend to adopt innovations.

Below I’ve pasted in a Hype Cycle dedicated to IoT:

The key takeaway from the above charts is time. People always overestimate how quickly the mass market will adopt new innovations. There’s an entire body of work dedicated to explaining the reasons and not for this post. But it’s just not easy to get technology to a cost/performance level that works beyond the early adopters. A lot of things have to go right. And that includes one of the biggest things beyond technology: changing human behaviour.

 

1 Trillion Connected Devices

In a previous post I talked about how SoftBank recently announced that by 2035 1 Trillion devices would be connected. Whether or not that happens is not the point, as it’s about the ambition & not necessarily the result. But for that to happen, what needs to occur?

1. Market adoption by consumers and businesses of new products/services that help them solve most of their important daily problems & challenges;

2. Significant improvement in connectivity, cloud, data analytics & management, AI & other IoT solution & related technologies to help enterprises and the ecosystem handle all the real-time data being generated by the devices at such a significant scale;

3. Digital transformation of established enterprise & government to rapidly adapt to the new paradigm and compete with IoT focussed startups;

4. Deep ecosystem & cluster development with value-chain players working together & aligned in R&D and GTM within specific industry sectors or use cases.

5. Significant lowering of device manufacturing costs to enable business model innovations to drive market adoption, such as subscriptions, service models and so on.

There may be others but this is just a sample of my initial thoughts right now. If you have any others be sure to let me know

Internet Regulation

 

2018 has been a significant year for internet regulation. The EU’s GDPR has significantly raised the bar for data protection & leading technology companies have been hammered from all sides due to various scandals & Congressional investigations. Today more than ever, citizens & governments are rightly concerned about personal data & issues including privacy, security, payments etc. Whether or not the regulators & consumers will be able to force the requisite amount of change on the leading tech companies, we shall see.

Interestingly, these issues were hot topics way back when the internet was early but going mainstream. Between 2000-2004, I wrote and delivered a brand new university course called ‘e-commerce law’ with key modules covering these issues. In 2004, I analysed the Governments prohibition of online casinos in my first academic article published in QUT’s law journal, titled ‘The Prohibition of Online Casinos in Australia: Is It Working?’. If you fancy a read, access it here.

I’ve pasted the introduction here as a few points are still interesting:

Preliminary online research of consumer gaming activity was utilised to develop an assumption that [after 2 years of prohibition] prohibition is not working. A key reason for this is the futility of prohibition given the unique nature of Internet technology. This article will also critique Government motives for prohibition, as arguably, the best approach to deal with interactive gaming was not implemented. The relevant question for public policy appears to be not whether online gambling can be controlled, but the extent to which it can be controlled.

These issues are still relevant in today’s online world where a handful of companies control the majority of our online data, purchases, browsing habits etc. Whether the current local & global regulatory frameworks and user tools go far enough to balance that control – and whether enough users actually care about this – only time will tell.

The Big 5

This post won’t be about what you might see on an African safari. Instead, today I’m thinking about where we are now, and where we are going in relation to the full potential of five disruptive technologies that get the most attention: AI, IoT, Blockchain, AR/VR, & Big Data.

Each technology is still in their infancy but fast maturing and gathering steam. We saw with cryptocurrencies in 2018 as a key use case for Blockchain which drove significant consumer & business adoption & later, government intervention

As I look ahead, the most interesting thing for me two-fold: (i) the timeframe(s) for the intersection of these technologies from a market adoption and technology maturity perspective, and (ii) the subsequent implications for established firms, and opportunities for new ones. If we think back to the late 2000s (over a decade since consumer internet introduction), it wasn’t until the launch of next generation mobile phones (via smartphones, tablets) that dramatically accelerated internet adoption driven largely by e-commerce. This opened up entirely new ecosystems (Apple, Google, Facebook, Uber, Amazon) whilst destroying others (Nokia, Motorola, Sears) in the process. For B2B/C, this enabled a new lawyer of applications & services for consumers & businesses alike, such as local discovery (e.g. restaurants), on-demand services (e.g. taxis, TV), & mobile (e.g. Amazon, eBay, banking). All designed to make life easier & better.

In 2018, such continued technology disruption – driven by the intersection of mobility & the internet – is only getting started (think retail, financial services, real estate etc). If we layer on top one or more the Big 5 technologies, it will be like pouring kerosene over an already burning fire. I can’t wait to see how it all plays out.

The IoT Opportunity

Softbank recently predicated about 1 trillion connected devices by 2032. That’s up from about 30 billion today. The chart below shows the growth until 2025.

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It’s pretty impossible to easily grasp how big of a number that is. A better way is to look at what all those devices enable, what consumer and business benefits will it deliver, and how will life become easier, better, and so on. Here are some examples:

  • Smart Cities equipped with self-driving transport, smart energy management, intelligent security systems, and automated environmental monitoring.
  • Smart farming with the entry of monitored farming devices like sensors to determine soil moisture levels for enhanced irrigation systems.
  • Connected vehicles with remotely monitored engine diagnostics or infotainment systems.
  • Industrial safety, where natural disasters like floods are easily detected in high-risk areas to prevent damages to valuable assets.
  • Health sector where remote patient monitoring & associated self-services will transform the operating model with established healthcare providers across the entire ecosystem.
  • Livestock management, such as successfully impregnating cows by using a smart pedometer strapped to the leg to help figure out exactly when is the best time to inseminate the cow.
  • Consumer products such as mattresses, using IoT technology to help identify and offer the right kind of mattress to offer customers as per their body shape, sleep patterns, & movements during the night.
If you compare this with what happens today, the next 5-10 years will be fascinating. Even moreso if you think about the inevitable confluence of other emerging (and equally disruptive) technologies such as Blockchain, AI, AR/VR, & Big Data. It is anyone’s guess as to how these technologies will interconnect and enable each other, although with IoT growth, this means lots of data. Advanced data & analytics through AI, ML & Big Data will be critical here. More on that in another post.