At Episode 1 we think of ourselves as stage specialists, investing in amazing founders with compelling insight into important problems. We try to be the best partner in leading them on the journey from Seed to Series A, and we invest opportunistically with no overarching thesis.
However, we do research ideas we like and develop patterns we see in the market, and we wanted to share some of our thoughts in this multi-post blog.
Theme 5: Smarter Infrastructure — What’s Not To Like?
So what then do we like or do we see in this sector? Start with things we stay away from. There are lots of interesting things taking place at the edge — a lot of sophisticated science can be done by sensors these days. But we’re software only, so that’s not for us. The whole home automation space is extremely crowded and lacks compelling applications. Measurable-me has consumer engagement but lacks clear business models — it’s either going to be hardware or part of an advertising platform.
We like enabling software — there’s a lot of work to do around specialized data handling, storage and management of voluminous time series data, data analytics and rapid organization and processing. There’s a lot of value in specific datasets that are being created, and analytics services on top of or between them. There are foundational software technologies that are interesting, for example mapping, routing or co-ordination for transportation or logistics applications. Interpretation and management of high volume data streams like video is another one.
And there’s still a lot of work to do around some of the basic architecture — security needs to be close to unbreakable on the device during transport, at the gateway and once it is stored, collected and processed. Hacking a vending machine is one thing, but hacking a car, energy supplier or nuclear reactor — not so much. It’s a different order of problem to stealing a bunch of credit card information.
“There’s still a lot of work to do around some of the basic architecture — security needs to be close to unbreakable on the device during transport, at the gateway and once it is stored, collected and processed.”
Perhaps the most important problem to be solved is the basic architectural topography of the IoT platform. Enterprise computing is rapidly consolidating around a cloud centric approach, where compute, storage and application are centered on hyper-scale datacenters run by large tech companies. It’s efficient cheap, well run, secure — but also fundamentally wrong for many IoT applications. If you are rolling up gigabytes of seismic or material science data at a remote mine, oil well or dam to make a decision about drilling or sluicing you may well not be able to rely on poor connectivity to send and process that much data. Similarly, you don’t want traffic lights to be run from the cloud, or many other sensor based telemetries that drive control applications — healthcare, power and telecommunications, aerospace and many other industrial uses. Think about autonomous vehicles or drones for example — data need to be processed and decisions made locally.
“The most important problem to be solved is the basic architectural topography of the IoT platform.”
This balance of so called “fog” computing — done at or near the edge — and “cloud” computing — central processing, scale compute and analytics — is still to be figured out. If you get it wrong, apart from unnecessary cost you risk introducing delays, failure points and security issues into the architecture. We think there is lots of opportunity in software tools for analytics, management and processing in these kinds of applications — lots of interesting businesses to be built.
“There is lots of opportunity in software tools for analytics, management and processing in these kinds of applications — lots of interesting businesses to be built.”
Another potentially fruitful area is Smart Cities — a lot has been written about this, and it is certainly easy to find compelling problems to solve. For example, an enormous percentage of global energy production is lost through poorly insulated and managed buildings. Enormous multi-billion dollar business cases can be constructed with ease, and small investments can be demonstrated to yield huge returns. Similarly, many other civic resources are poorly distributed and consequently wasted — think about food and transportation as examples. In addition, there are many substantial opportunities to increase productivity in maintenance and construction applications, and healthcare, social or public safety and security outcomes could be significantly improved by adopting new technologies.
The challenge is always what’s the business model? Who owns the problem? And the answer to this is often very diffuse — there are lots of “tragedy of the commons” situations. To continue with the same example, having correctly identified the opportunity city governments can introduce legislation or incentives to lower energy consumption. However, the technology needed to manage energy in a building typically needs to be built in from the beginning, it’s often close to impossible to retrofit. And developers often have small operating budgets and with any kind of project pressure IT and BMS budgets get put under pressure.
And then think about who the benefit accrues to — the person who pays the energy bill may be a tenant or a subtenant of a landlord who leased the property from the developer — or costs may be bundled at any point. There are so many parties involved, and lots of investment and benefit timing mismatches that despite the best of intentions it is hard to get to the right outcomes. You often find similar situations in many Smart City applications — a large compelling business problem, with unclear ownership, a complex deployment and tenuous business model.
So a total mess, right? Well yes — but then again a really complex problem with a huge business case attached in an environment where the basic enabling technologies are rapidly standardizing and moving down the cost curve is fertile ground for entrepreneurs. And we expect to see some compelling businesses in this area over the next few years. Each actor in the ecosystem has a role to play — and the aspiring innovator needs to align them all to build a successful business. It’s all about figuring out where the money is in the value chain — often some kind of service provider — and aligning with regulators to drive adoption at the end-consumer. For example, we’ve seen interesting ideas around helping businesses or consumers solve compliance or access problems, and then creating marketplaces for specialized service providers, bridging knowledge and timing gaps.
“It’s all about figuring out where the money is in the value chain — often some kind of service provider — and aligning with regulators to drive adoption at the end-consumer.”
In summary, we believe the hype. This is going to be the next major wave of the IT revolution, every industry and governmental service will be transformed. While much has taken place away from the public eye to create the right environment, there are still many more large technology problems to solve and enabling services to build. Progress on some of the large business cases can be made, but needs crisp identification of a proximate problem and clear focus on a near term business case. In this new age of discovery, there are plenty of maps and compasses to be sold whereas funding fleets or voyages is likely to take bravery, deep pockets and amazing foresight.
Successful entrepreneurs and teams in this area are likely to have strong technical skills and deep knowledge of the underlying technology currents. This must be combined with skills higher up the stack — the team also need to have a deep understanding of the structure of the value chain you are trying to disrupt as well as having identified a real problem and someone who will pay for it. But we want to see as many brave adventurers here as possible — because there are real fortunes to be made.
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