As the demand for home delivery continues to grow, so too does the need for organisations to implement more efficient delivery operations. For our clients, the constraints imposed on home delivery are numerous - and it is a challenge that causes many organisations to struggle. Our clients have any number of vehicles, each with limited capacity. Vehicles are limited to certain routes, and routes are often limited by traffic, accidents or road closures. Add driver shifts, multiple destinations and the rising desire for nominated time-window delivery (slots) and you get a scheduling problem no human operator can solve with any degree of accuracy. Our data-driven, operations research approach has, and will continue to improve the efficiency of home delivery; reducing costs for our clients, and vastly improving the customer experience.
In this talk, as well as discussing the above in more depth, we will describe how optimisation and machine learning can be leveraged to build highly impactful last-mile delivery solutions. We will illustrate, through case studies from our own consulting experiences, how some of the UK’s largest retailers are using optimisation to schedule their fleets of vehicles, and disclose just how impactful it has been for their costs, and their customers. We will provide an insight into the business challenges associated with applying the latest optimisation techniques into organisations of all sizes, and describe how the rising expectations of customers is forcing the optimisation community to react.