batching

Batching is the practice of processing items in groups, or batches, rather than individually. The goal is to improve efficiency by handling setup, changeover, and resource allocation in bulk, reducing repetitive overhead and improving throughput.

In manufacturing and production, batching is common in batch production, where a finite quantity of similar items is produced before switching to another batch. It contrasts with continuous production or job-shop layouts. Examples include baking bread in batches, chemical processing in reactors, and electronics assembly in lots.

In computing and data processing, batch processing executes a set of jobs without interactive input. Jobs are collected, queued, and run when resources permit, often during off-peak hours. Typical uses include nightly data ETL, payroll processing, and bulk report generation.

In logistics and services, batching groups tasks or requests to improve efficiency, such as batching customer orders for shipment, grouping support tickets for triage, or batching financial transactions.

Advantages include higher throughput, lower per-unit cost, and better resource utilization by amortizing setup. Disadvantages include higher latency, reduced flexibility, the risk that a failed item affects an entire batch, and scheduling complexity.

Key considerations include choosing batch size to balance throughput and lead time, minimizing variance between items, and employing strategies such as dynamic or staggered batching, pull-based batching, or lean approaches to avoid overproduction.