When you look at large manufacturing companies, it becomes very clear that the machine that makes the machine is just as important as the machine itself. There’s a lot of work in the iPhone, but there’s also a lot of work in the machine that can manufacture over 200m iPhones in a year. Equally, there’s a lot of work in a Tesla Model 3, but Tesla has yet to build a machine that can manufacture Model 3s efficiently, reliable, quickly and at quality at the scale of the incumbent car industry.
More than any of the other big tech platform companies, Amazon is a machine that makes the machine.
.. Amazon at its core is two platforms – the physical logistics platform and the ecommerce platform. Sitting on top of those, there is radical decentralization.
.. Amazon is hundreds of small, decentralized, atomized teams sitting on top of standardised common internal systems. If Amazon decides that it’s going to do (say) shoes in Germany, it hires half a dozen people from very different backgrounds, maybe with none of them having anything to do with shoes or ecommerce, and it gives them those platforms, with internal transparency of the metrics of every other team, and of course, other people (and Jeff) have internal transparency to their metrics.
These are the famous ‘two pizza teams’. The obvious advantage of a small team is that you can do things quickly within the team, but the structural advantage of them, in Amazon at least (and in theory, at least) is that you can multiply them. You can add new product lines without adding new internal structure or direct reports, and you can add them without meetings and projects and process in the logistics and ecommerce platforms. You don’t (in theory!) need to fly to Seattle and schedule a bunch of meetings to get people to implement support for launching make-up in Italy, or persuade anyone to add things to their roadmap.
This means not so much that products on Amazon are commodities (this much is self-evident) but that product categories on Amazon are commodities.
This model has two obvious consequences for Amazon. The first is that
- it can scale almost indefinitely – if you can launch x in y without a meeting or a new org structure, the speed of expansion into new categories is limited mostly by your ability to hire and to procure (and also by consumers’ willingness to buy a new category online, of course). The second is that
- the buying experience for any given product category ultimately needs to fit a lowest-common-denominator model. The platform teams cannot easily create custom experiences for each new category.
.. There’s a third consequence, though: those atomised teams don’t actually need to work for Amazon. This is the insight behind both AWS,
.. Estimates of the total value of goods being sold both though Amazon itself and through marketplace vendors (together this is termed gross marketplace value, or GMV) are generally about double Amazon’s reported revenue.
.. it now has a 25% operating margin.
.. Amazon invests cash from profitable units into the creation of new, unprofitable units, and you have no real idea what the distribution looks like. This, I think, is how we should see both AWS and the marketplace business: Amazon is uniquely obliged to disclose the profitability of AWS, but it’s not the only profitable part of the company.
.. The opposite extreme might be Apple, which rather than radical decentralization looks more like an ASIC, with everything carefully structured and everyone in their box, which allows Apple to create certain kinds of new product with huge efficiency but makes it pretty hard to add new product lines indefinitely. Steve Jobs was fond of talking about saying ‘no’ to new projects – that’s not a very relevant virtue to Amazon.
a16z Podcast: Platforming the Future: Tim O’Reilly & Benedict Evans
Why do platforms make the mistake of competing with the participants in the ecosystems they create? (4:02 min)
Google’s original strength was as a switchboard, but it was attracted to the idea of being a destination platform. (8:30 min)
The Romans made the conquered tribes citizens.
There is this gravitational attraction for who knows the most about me. (18:40 min)
Could you imagine if it were Google that came out with the echo, a device that was always listening.
Amazon’s image gave it greater room to innovate.
Benedict Evans
Winner-takes all effects in autonomous cars
Rather, the place to look is not within the cars directly but still further up the stack – in the autonomous software that enables a car to move down a road without hitting anything, in the city-wide optimisation and routing that mean we might automate all cars as a system, not just each individual car, and in the on-demand fleets of ‘robo-taxis’ that will ride on all of this. The network effects in on-demand are self-evident, but will will get much more complex with autonomy (which will cut the cost of an on-demand ride by three quarters or more). On-demand robo-taxi fleets will dynamically pre-position their cars, and both these and quite possibly all other cars will co-ordinate their routes in real time for maximum efficiency, perhaps across fleets, to avoid, for example, all cars picking the same route at the same time. This in turn could be combined not just with surge pricing but with all sorts of differential road pricing – you might pay more to get to your destination faster in busy times, or pick an arrival time by price.
.. From a technological point of view, these three layers (driving, routing & optimisation, and on-demand) are largely independent – you could install the Lyft app in a GM autonomous car and let the pre-installed Waymo autonomy module drive people around, hypothetically. Clearly, some people hope there will be leverage across layers, or perhaps bundling – Tesla says that it plans to forbid people from using its autonomous cars with any on-demand service other than its own. This doesn’t work the other way – Uber won’t insist you use only its own autonomous systems. But though Microsoft cross-leveraged Office and Windows, both of these won in their own markets with their own network effects: a small OEM insisting you use its small robo-taxi service would be like Apple insisting you buy AppleWorks instead of Microsoft Office in 1995.
.. If you have sold 500,000 AVs and someone else has only sold 10,000, your maps will be updated more often and be more accurate, and so your cars will have less chance of encountering something totally new and unexpected and getting confused. The more cars you sell the better all of your cars are – the definition of a network effect.
.. It could be argued that Tesla has a lead in both maps and driving data: since late 2016, those of its new vehicles whose buyers bought the ‘Autopilot’ add-on have eight cameras giving a near-360 degree field of view, supplemented by a forward-facing radar
.. So, the network effects – the winner-takes-all effects – are in data: in driving data and in maps. This prompts two questions: who gets that data, and how much do you need?
Benedict Evans: Creation and consumption
There’s a pretty common argument in tech that though of course there are billions more smartphones than PCs, and will be many more still, smartphones are not really the next computing platform, just a computing platform, because smartphones (and the tablets that derive from them) are only used for consumption where PCs are used for creation. You might look at your smartphone a lot, but once you need to create, you’ll go back to a PC.
.. There are two pretty basic problems with this line of thinking. First, the idea that you cannot create on a smartphone or tablet assumes both that the software on the new device doesn’t change and that the nature of the work won’t change.
.. there are perhaps 100m people who today engage in some form of complex creation using what one might call ‘sophisticated professional software’ on a windows + mouse + keyboard-based personal computer.
.. If less than 10% of PCs are actually doing professional, precise, complex creation, what are the other 90% being used for, if not creation?
.. Well, they do email, and the web. Some of the consumer ones also play games ..
.. They do Facebook and buy groceries.
.. More recently, I’ve seen data suggesting that a large proportion of people who owned digital cameras never loaded the pictures onto a computer (even if they owned one). They looked at the pictures on the camera screen, or got them printed at a kiosk – but didn’t print them until the card was full
.. But then there are all of the things that a normal person (the other 90% or 95%) can’t do on a PC but can do on a smartphone, because the step change in user interface abstraction and simplicity means that they know how to do it on a phone and didn’t know how to do it on a PC.
.. So, 100m or so people are doing things on PCs now that can’t be done on tablets or smartphones. Some portion of those tasks will change and become possible on mobile, and some portion of them will remain restricted to PCs for a long time. But there are another 3bn people who were using PCs (but mostly sharing them) but who weren’t doing any of those things with them, and are now doing on mobile almost all of the stuff that they actually did do on PCs, plus a lot more.