Warehouse dashboards often report backlog and inventory turnover without showing which operating decisions can change them. This paper develops a three-tier KPI hierarchy and a diagnostic cycle for third-party logistics operations. Strategic outcomes are linked to client-level flow measures and owned process indicators, supported by explicit definitions, segmentation and exception review. The framework distinguishes average work in process from aged backlog and uses consistent units when relating throughput, time in system and inventory. Practitioner experience reports a 2.5 percent improvement in inventory turnover alongside a reduction in backlog. These outcomes are descriptive: the baseline, observation period and transaction-level estimates are not available for independent recomputation. The contribution is a practical link between measurement design and root-cause investigation, rather than an identified causal effect. Prospective validation should publish denominators, client and product mix, implementation dates, lag analyses and comparison-period uncertainty. The framework offers a structured basis for testing whether better diagnosis improves warehouse flow while separating operator-controlled delays from client inventory policy.