The procurement of freight services is an important element for the supply chain management of a shipper (i.e., a manufacturer or retailer) that sources transportation services from the third-party logistics market. Motivated by a practical freight procurement problem faced by shippers, we provide a holistic approach to designing freight procurement strategies for transportation-inventory systems that captures the interconnections between freight procurement, transportation, and inventory management. In view of the supply and demand uncertainties, we consider the problem in a multi-stage decision process that complies with the revealing process of the uncertain data. To handle instances of realistic size, we propose an enhanced stochastic dual dynamic programming solution approach. We conduct extensive numerical experiments to test the performance of the approach. The results demonstrate that our approach scales to huge instances with up to $50^{18}$ scenarios and that the proposed enhancement strategies significantly improve its performance. Compared to methods commonly adopted to solve similar problems, our approach could potentially help reduce the total cost for shippers by 7.5% to 47.2% based on our generated instances from real-world data and simulations.