Scaling First Mile planning at Amazon Japan

Context

A rapidly scaling logistics program required stronger forecasting, network planning, stakeholder alignment, and cost control across multiple planning horizons.

What I did

As the single-threaded owner of planning across all miles and planning horizons, I connected forecast performance, operational constraints, network inputs, and execution signals into a clearer planning process.

Alongside the core program-management work, I used Kiro to structure analytical requirements, develop repeatable analysis logic, document planning mechanisms, and prototype workflows for investigating relationships between forecast accuracy, seller behaviour, capacity, cost, routes, and execution.

The aim was not simply to produce analysis faster. It was to make the reasoning behind the analysis more explicit, reusable, and easier to extend.

Impact

• Supported significant program growth to multi-million-package scale.
• Substantially reduced First Mile cost per package as the program scaled.
• Improved First Mile forecast accuracy by more than 20 percentage points.
• Maintained downstream plan-versus-actual performance within its target range.

What this demonstrates

The ability to scale an operation while improving cost efficiency, forecast quality, and downstream planning control—and to use an AI coding assistant practically to strengthen the analytical systems supporting that operation.