Cost-Service quality trade-offs in e-commerce order fulfilment: Integrating order picking, batching, and last-mile delivery



To guarantee high customer service and short and accurate lead times, many e-commerce retailers have started to home deliver their customer orders. Order fulfilment consists of three main processes: order picking in the warehouse, order batching for delivery, and last-mile de-livery. The ultimate delivery performance depends on managing all three processes, which are highly stochastic, and interdependent. We capture this stochasticity and interdependency in an integrated analytical framework and derive approximate analytical expressions for the mean and variance of the total order fulfilment time. We validate the analytical expressions with detailed simulations.  We then analyze the delivery cost-service quality trade-offs using an optimization model that minimizes the expected order fulfilment cost with delivery sharpness (DS) and delivery probability(DP) constraints, focusing on meeting exact delivery time windows. The optimization model determines the number of pickers, the optimal delivery batch size, and the number of vehicles required to deliver the customer orders. Achieving a high delivery accuracy comes at a cost. Using realistic data, we show that the expected order fulfilment cost and time obtained from the model without service quality constraints are 25% and 10% less, respectively, compared to the model with service quality constraints. However, the model without service quality constraints has 105% higher variance of order fulfilment time than the model with service quality constraints, which results in low delivery sharpness and low delivery probability.

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Meeting ID: 925 7642 1770