Problem

• Woolies delivers online groceries around the nation. These deliveries tend to result in a net loss due to capacity, distance and planning. Unless its Monday when everything is at capacity.
• The routes that drivers need to follow are usually longer distances, with heavy loads, resulting in more time driving and more wear and tear on trucks for lower deliveries.
• Our planning logic didn’t consider geographic restrictions like freeways, or high congestion traffic areas using existing movement data, resulting in planning being wildly inaccurate.
• Logistics teams would assign a delivery area to a store at a suburb level, leaving no room for flexibility or partial allocations of orders (resulting in lower margins on orders).

My Role

• Senior Experience Designer within the logistics space, Last Mile, at WooliesX.
• Led the design, facilitation and research from initial concept through to delivery and implementation of the solution.
• Partnered with multiple enabling squads (data science, route optimisation, logistics) to deliver a solution that solved the core issues while maintaining a high level of the needs of operators.

Process

• This work kicked off with a known problem → known solution.
• Followed a standard double diamond framework, relying on an existing design system that had been partially rolled out.
• Research and usability of the infrastructure planning tool was the critical path. There was a need that if we rolled out a solution, it was going to result in increased planning efficacy for route optimisation staff while not impacting their tempo and workflow.
• The solution was the implementation of a mesh block level mapping system. This meant that instead of mapping stores to suburbs, they could be mapped to streets. This increased the level of granularity from 15k suburbs, to 368k mesh blocks.