The Amazon machine

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

  1. 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
  2. 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.

 

Alibaba’s Jack Ma Tells U.S. Companies to Stop Whining About China

Magnate tells firms to ‘follow the rules’ and plan for the long term

Companies that struggle here may simply not be taking the right approach, Mr. Ma said Tuesday at a prominent internet forum.

“I gave advice to Jeff Bezos 10 years ago,” Mr. Ma said, referring to Amazon.com Inc.’s chief executive. “I said: ‘Please send people with entrepreneurial spirit, not professional management. Because wherever you go, doing business in another country is very difficult.’”

.. “Give me five examples of Chinese companies that succeed in America,” he said. “Or Asian companies that succeed in America. Because it’s not easy to do business across nations, it takes time.”

.. Mr. Ma’s comparison is flawed, said Kenneth Jarrett, president of the American Chamber of Commerce in Shanghai. He said American firms have been active in China for a long time, while Chinese companies are just making inroads in the U.S.

.. Mr. Ma said foreign firms must be prepared to abide by China’s laws and not expect quick success.

“When you determine to come, prepare for it. Follow the rules and laws and spend 10 years,”

.. Facebook and Google cannot be accessed in China without VPNs, but both companies have been exploring ways to increase their presence here.

In The Works – Amazon Aurora Serverless

When you create an Aurora Database Instance, you choose the desired instance size and have the option to increase read throughput using read replicas. If your processing needs or your query rate changes you have the option to modify the instance size or to alter the number of read replicas as needed. This model works really well in an environment where the workload is predictable, with bounds on the request rate and processing requirement.

In some cases the workloads can be intermittent and/or unpredictable, with bursts of requests that might span just a few minutes or hours per day or per week. Flash sales, infrequent or one-time events, online gaming, reporting workloads (hourly or daily), dev/test, and brand-new applications all fit the bill. Arranging to have just the right amount of capacity can be a lot work; paying for it on steady-state basis might not be sensible.

Get Ready for Amazon Aurora Serverless
Today we are launching a preview (sign up now) of Amazon Aurora Serverless. Designed for workloads that are highly variable and subject to rapid change, this new configuration allows you to pay for the database resources you use, on a second-by-second basis.

This serverless model builds on the clean separation of processing and storage that’s an intrinsic part of the Aurora architecture (read Design Considerations for High-Throughput Cloud-Native Relational Databases to learn more). Instead of choosing your database instance size up front, you create an endpoint, set the desired minimum and maximum capacity if you like, and issue queries to the endpoint. The endpoint is a simple proxy that routes your queries to a rapidly scaled fleet of database resources. This allows your connections to remain intact even as scaling operations take place behind the scenes. Scaling is rapid, with new resources coming online within 5 seconds. Here’s how it all fits together:

Amazon and Big Apartment Landlords Strike Deals on Package Delivery

Amazon Hub program gives the retail giant control over the last mile of the logistics chain

For several years, landlords have struggled with how to manage the mountains of packages they receive each day. Staff at larger buildings end up devoting several hours a day sorting mail, while boxes are piled in every spare cranny. Most say it is the single largest problem they face.

.. The locker program, dubbed Hub by Amazon, will accept packages from all carriers and not just for purchases made on Amazon. They will be open only to residents, not the wider community. Residents will receive a notification when they have a package and a code allowing them to open one of the slots.

Apartment owners pay about $10,000 to $20,000 to purchase the lockers initially and don’t pay a monthly fee.

.. The lockers will also have cellular connectivity so apartment owners don’t have to worry about connecting an Ethernet cable.

.. Owners said Amazon is offering its lockers at about half the cost some other companies previously had been charging.