Improving the Economics of the Last Mile
As customers’ e-commerce expectations for next-day and same-day delivery continue to expand, “last mile” delivery has become an essential aspect of the retail supply chain. However, providing door-to-door delivery within in these timeframes is logistically challenging and very costly, as retailers’ current supply chain infrastructure is primarily focused on the movement goods over the long haul. In order to compete with e-commerce brands like Amazon, brick-and-mortar retailers must develop a solution that delivers goods to consumers extremely efficiently, regardless of whether the item is transported from a store, distribution center, or other location.
Retailers are experimenting with a variety of tactics to increase delivery speed and reduce costs, like delivering from existing stores and using hired part-time workers and even store associates to deliver items on their way home. In addition, many traditional retailers have already adopted “buy online, pick up in store” or BOPUS capabilities to satisfy consumers’ demands. This process alleviates some of the high shipping costs associated with last mile by having the physical store become the distribution center. However, these kinds of delivery tactics are not sufficient solutions, as they either inconvenience customers or result in increased labor costs that drive down productivity.
As such, retailers are seeking an industry-wide solution that will optimize delivery to meet customer expectations for next-day and same-day delivery, while at least matching the unit economics of 3 to 4-day delivery). Retailers are agnostic to both the “mode(s)” of transportation used (small robots, drones, etc.) and the ultimate destination – that is, the solution shouldn’t be affected by where it is delivered to (home, car, park, locker, etc.). This Challenge is not designed address the inventory/forecasting issues that would need to be in place to execute on last mile delivery – it focuses on the delivery mechanism itself.
The Challenge Sponsors seek a cost-effective solution that:
• Meets customer expectation on time of delivery. Assume 2 days at slowest.
• Be competitive (better than) current options
• Must be reliable, predictable, scalable
• Maintain brand/customer experience of retailer
• Aggregates the size, weight etc. of packages, pickup/drop off time expectations, and other pertinent delivery data
• Anonymizes actual product information
• Securely delivers products to customers (identity or payment verification should be required)
- Submission Deadline:
- September 30, 2018
- Submission Contact: