Winning the race to customers with micro-fulfillment centers: an approach for network planning in quick commerce
- In 2020, the first quick commerce businesses in grocery retail emerged in the European market. Customers can order online and receive their groceries within 15 min in the best case. The ability to provide short lead times is, therefore, essential. However, the ambitious service promises of quick deliveries further complicate order fulfillment, and many retailers are struggling to achieve profitability. Quick commerce retailers need to establish an efficient network of micro-fulfillment centers (MFCs) in customer proximity, i.e., urban areas, to master these challenges. We address this strategic network problem and formulate it as a location routing problem. This enables us to define the number, location, type, and size of MFCs based on setup, replenishment, order processing, and transportation costs. We solve the problem using a cluster-first-route-second heuristic based on agglomerative clustering to approximate transportation costs. Our numerical experiments show that our heuristicIn 2020, the first quick commerce businesses in grocery retail emerged in the European market. Customers can order online and receive their groceries within 15 min in the best case. The ability to provide short lead times is, therefore, essential. However, the ambitious service promises of quick deliveries further complicate order fulfillment, and many retailers are struggling to achieve profitability. Quick commerce retailers need to establish an efficient network of micro-fulfillment centers (MFCs) in customer proximity, i.e., urban areas, to master these challenges. We address this strategic network problem and formulate it as a location routing problem. This enables us to define the number, location, type, and size of MFCs based on setup, replenishment, order processing, and transportation costs. We solve the problem using a cluster-first-route-second heuristic based on agglomerative clustering to approximate transportation costs. Our numerical experiments show that our heuristic solves the problem effectively and provides efficient decision support for quick commerce retailing. We generate managerial insights by analyzing key aspects of a quick commerce business, such as lead times and problem-specific cost factors. We show, for example, that allowing slightly higher delivery flexibility (e.g., offering extended lead times) enables bundling effects and results in cost savings of 50% or more of fulfillment costs. Furthermore, using multiple small MFCs is more efficient than larger, automated MFCs from a lead time and cost perspective.…