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Success and Scale Bring Broad Responsibility at Amazon

Success and Scale Bring Broad Responsibility is the newest and longest of Amazon's leadership principles, added in 2021 alongside Strive to Be Earth's Best Employer. It is the principle about second-order effects: what else changes when you act, and for whom.

At Amazon's size, a decision that looks like a rounding error touches millions of customers, sellers, employees and communities. Interviewers do not expect you to have operated at that scale. They want to see whether you look past the metric you were asked to move and notice who else your work touches.

This guide covers the official wording, what the principle looks like in a normal job, examples across roles, the interview questions to prepare, and a worked STAR answer.

The official wording from Amazon

Leaders create more than they consume and always leave things better than how they found them.

That is the closing sentence on Amazon's leadership principles page, and the one interviewers quote most. The principle opens by acknowledging that Amazon started in a garage and is now big, imperfect and consequential, and it asks leaders to be humble and thoughtful about even the secondary effects of their actions, for local communities, the planet and future generations. Read it as a scaling rule: the more impact you have, the wider the circle of people you are accountable to.

What Success and Scale Bring Broad Responsibility means in practice

You ask "who else does this touch" before you ship: sellers, support staff, the team that inherits the code, the users who are not your target persona.
You treat externalities as your problem. Cost pushed onto another team, waste, a dark pattern that moves a metric: these are things you flag rather than things you benefit from quietly.
You leave things better. The codebase, the process, the documentation, the team you pass through.
You own unintended consequences. When your decision produced a harm nobody predicted, you say so and change course.
You keep your humility proportional to your reach. The bigger the decision, the harder you work to disconfirm your own view before acting.

Success and Scale Bring Broad Responsibility examples at work

A growth engineer and the notification experiment. An A/B test showed that a third daily push notification lifted a session metric. The engineer also pulled the uninstall rate for the variant, found it noticeably up, and recommended against shipping. The team adopted a rule that engagement experiments must report retention and opt-outs alongside the primary metric.

A platform engineer and the deprecation. Retiring an internal API would save his team a quarter of its maintenance load. Instead of announcing a date, he listed the eleven services that depended on it, met each owner, and built a compatibility shim so the three teams with no capacity that quarter could migrate later. The API was retired on schedule with no incidents.

A product manager and the seller fee change. A pricing change improved margin on paper. The PM modeled it by seller size and found that the smallest sellers would see the biggest percentage increase. She proposed a tiered version that kept most of the margin and took the analysis to leadership before the decision was made rather than after.

A finance analyst and the vendor contract. Consolidating suppliers would cut costs. The analyst noticed that the losing bidder was a local company employing people in a town where the firm had just opened a site, and raised it with the sourcing lead so the decision was made with that context. The consolidation still went ahead, phased over a year.

Success and Scale Bring Broad Responsibility interview questions

Direct questions

Tell me about a decision of yours that had unintended consequences. What did you do?
Describe a time you considered the broader impact of your work beyond your immediate goal.
Tell me about a time you left a project, codebase or team better than you found it.
Have you ever flagged an ethical or fairness concern with something you were building?
Describe a time you balanced business goals against a broader responsibility.
What is something you built that outlived your involvement? Why did it last?
Tell me about a time you declined to ship something that would have hit your metric.

Questions that test it indirectly

Who are the stakeholders in your current project that nobody talks about?
Tell me about a time a change you made affected another team. How did you find out?
Describe a time you pushed a cost onto someone else to meet your goal. Would you do it again?
Tell me about a time you were wrong about the impact of a decision. How did you learn?
How do you decide when a secondary effect is big enough to change a plan?
Tell me about a time you improved something that wasn't your job to improve.

A sample STAR answer

Question: tell me about a decision of yours that had unintended consequences.

Situation. I led the team that ran fraud rules for an online marketplace. A spike in chargebacks from one country was costing us real money every week, and I owned the fix.

Task. My goal was to cut chargebacks from that corridor by half within a month.

Action. I shipped a rule that added a manual review step to orders matching a set of risk signals. It worked immediately on the chargeback number. A week later I checked the review queue and saw that about one in five of the held orders came from long-standing legitimate sellers, who were now waiting three days for payouts. Nobody had asked me to look at that, and the chargeback metric was green. I paused the rule, split it so sellers with a clean twelve-month history were exempt, and added a dashboard that shows the false-hold rate next to the chargeback rate so the team sees both every morning. I also wrote to the affected sellers explaining the delay and the fix.

Result. Chargebacks from the corridor stayed down by about forty percent, slightly short of my target, with the false-hold rate under two percent. The paired dashboard became the standard for every fraud rule we shipped afterward.

Why this answer works

The harm was found by looking, not by complaint. That is the unprompted breadth the principle rewards.
The candidate gave back part of the metric win to remove the harm and says so, including the missed target.
It leaves a mechanism behind (the paired dashboard), which is "leave things better" in concrete form.

What the interviewer probes next

How did you find the false holds? "I checked the queue" is good; "a seller complained" is weaker, and the interviewer will ask what you changed so you find it first next time.
Who did you tell, and when? The principle values transparency with the people affected.
What was the cost of the fix? Be ready with the ten percentage points of chargeback reduction you gave up.
Would you have shipped the first rule again? A thoughtful answer says yes, with the dashboard in place from day one.
What is the bigger version of this at Amazon's scale? Show you can reason about effects on sellers, customers or communities you have never met.

Common mistakes

Reaching for a save-the-world story. A real consequence you noticed at your own scale beats an abstract one.
Ending with "and that is why I was right." The principle is about humility; the story should include something you got wrong or gave up.
Describing a program you joined. Interviewers want a secondary effect you found, not a volunteer day.
Leaving out the business. Responsibility that costs the company everything is not the principle either; the strong story keeps most of the win.
Having no mechanism. If nothing changed in how decisions get made afterward, the story ends too early.

Related leadership principles

Ownership is the root: you act on behalf of the whole company, beyond your own metric.
Dive Deep is how you find the secondary effect: you look at the queue instead of trusting the green number.
Strive to Be Earth's Best Employer was added the same year and covers the responsibility to the people inside the company.

The full list, with questions for every principle, is in the Amazon leadership principles guide.

Work through this story with a coach who has sat on an Amazon loop: get matched. Build it first with the STAR method guide and the story bank guide.