Throughput

Throughput directly affects pricing outcomes because it determines how quickly acquired inventory reaches market. Low throughput increases lag between intake and listing, which can leave sellers posting at stale market levels after rapid price movement events such as new flagship launches. Automation in diagnostics and grading improves throughput by reducing per-device processing time and shrinking the gap between acquisition assumptions and live resale pricing.

Throughput bottlenecks typically occur at one of three stages: initial triage, functional diagnostics, or cosmetic grading. Triage backlogs delay identification of non-viable units, keeping them in the processing queue unnecessarily. Diagnostics bottlenecks, often due to limited testing station capacity, slow the conversion of intake devices into priced and listed inventory. Grading bottlenecks, usually caused by manual visual inspection at scale, are the most common constraint and the one most amenable to improvement through autograding technology.

Measuring throughput as devices per day or per week gives an operational benchmark, but throughput should also be tracked against market movement during the processing period. A batch of devices processed in three days during a flat market is commercially equivalent to the same batch processed in seven days. But the same batch processed in seven days during a post-launch depreciation event may arrive at listing with a materially lower resale ceiling than existed at intake, turning a planned margin into a loss. Throughput targets should be calibrated against expected market volatility, not just operational convenience.