A while ago I was asked “how Amazon thinks and is different”. There are many books written on this topic, but if you want the Cliff notes, here’s my take:
How Amazon ticks (at least a small set of those principles)
A lot of the operating principles for Amazon are coded in the leadership principles, which everyone lives by on a daily basis. You will notice that there is often a tension between two leadership principles, which is intentional, as it forces everyone to consistently make conscious trade-off decisions.
Aligned goals while preserving autonomy
Hierarchy of goals – Amazon follows and tracks a hierarchy of goals. Some of those goals are set top-down, but the majority are aggregated bottoms-up. All goals are focused on the outcome, not the method, allowing for ample degrees of freedom to adjust process and solutions, as the team learns more about what works and what doesn’t. Aligning those goals up the chain ensures that everyone agrees on the priorities, and teams are given a framework to make an autonomous decision. There are several categories of importance for goals (company, department, team) to empower teams to make local decisions if some of those goals start to conflict with each other (e.g. one goal needs additional funding at the expense of another one).
Local autonomy – With a clear decision and priority framework through agreed-upon goals, teams are granted high local decision authority. That authority typically lies at the scope of two-pizza-teams, meaning teams that are small enough so that they can be fed with two pizzas in a meeting (i.e. no more than 10-12 people). Those units design their programs such that they can exist with minimal dependencies on other teams. Authority for most decisions lies with the leader of that team (typically a Manager or Senior Manager).
With that, Amazon, in many ways, functions like a group of many independent startups that work towards common goals with high independence and are well funded.
Starting small and embracing failure
Embracing experimentation and failure – Experimentation and failure is highly encouraged. There is a lot of deep thinking done in advance, and decisions are made based on extensive data analysis. However, there is also an understanding that all data is incomplete, and analysis-paralysis needs to be avoided. One-way versus two-way doors is a mental framework that helps navigate through that ambiguity. There is a high willingness in management to write off failures if the initial thinking was valid and data-driven. Experimentation in small pilots is the standard procedure to avoid costly mistakes at large scale. Teams meet on a weekly basis for project reviews where they look at all operational data to make quick course corrections if needed.
Start frugal, start scrappy – Contrary to public perception, every idea and implementation begins in a very scrappy and frugal way. That minimizes losses for ideas that don’t work. Once an idea is successful and gains traction, systems often have to be completely re-written in order to become more scalable and manageable and meet the larger scale and operational demand. This approach ensures extremely high agility and velocity at a very low initial cost (two pizza teams). Substantial investments are only made once an idea has proven to be successful. The extra cost of re-engineering a system is a conscious trade-off that is being made to allow quick and cost-effective initial development.
It’s all about the customer experience!
Customer focus – The customer and value for the customer are truly always put first. That is not so much for altruistic reasons, but because Amazon focuses on the lifetime value of a customer. Short-term losses are acceptable if they lead to a stronger engagement with the customer, thus ensuring a higher lifetime value. Customers are an investment for the long run, and short-term losses are acceptable toward that goal.
Of course, there is way more to what makes Amazon tick, but the above – together with the leadership principles – are some of the principles that, in my mind, make the most difference.
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