Process Bottleneck Finder

Why this question matters

When work accumulates, the busiest looking department is not always the true constraint. A sequential workflow can only deliver as fast as its least capable step under the assumptions being examined. This tool compares up to eight steps using processing time, available team hours and rework. It helps direct observation towards the part of the process most likely to limit throughput. The purpose is to improve the whole flow, not to make every department equally busy.

Describe a process in which each item passes through each entered step. Define the item consistently, such as an order, application, design or finished unit. Enter the minutes of active work required at each step and the total team hours genuinely available to that step each week. Do not multiply capacity by headcount again if the hours already include the whole team. Remove time routinely committed to other work from the available hours.

Estimate the percentage of items that require one repeat of a step. The model treats that repeat as another full processing cycle at the same step. Keep rework separate from waiting time and explain the reason it happens in your own notes. Where jobs vary greatly in complexity, analyse a coherent job type or compare separate scenarios. A single average across very different work can conceal the queue that matters.

Understand the method

1. Effective step capacity per week = available team hours × 60 ÷ (minutes per item × (1 + rework percentage ÷ 100)).
2. Workflow capacity is the smallest step capacity.
3. Estimated weekly queue growth = max(0, demand − workflow capacity).

Effective weekly capacity equals available hours multiplied by sixty, divided by minutes per item multiplied by one plus the rework fraction. Rework therefore increases expected effort per completed item. The smallest calculated step capacity becomes the workflow capacity. Estimated weekly queue growth is demand less that capacity, with negative differences shown as zero. The demand coverage score is capped at one hundred.

Read the result as a hypothesis to verify on the floor or in the actual workflow. Check whether work is waiting before the identified step and whether it regularly runs out of time. Observe interruptions, missing information and the mix of jobs. The lowest calculated capacity may not be the practical constraint if an upstream step starves it of work or a scheduling rule prevents available capacity from being used.

Test a small change at the constraint and measure completed output and quality together. Reducing avoidable rework, improving incoming information or reallocating a trained person may help. Improving a faster step alone can simply create a larger queue before the constraint. After a successful change, calculate again because the constraint may move. The goal is a better flow of completed work, not a permanent label attached to one department.

Keep the result in perspective

This is a transparent planning calculation or self assessment, not a sector benchmark, professional valuation or a prediction of an outcome.

Assumes every item passes through each step and rework repeats the step once. Scheduling, downtime, waiting time and variable job sizes need a deeper process study.

The model assumes every item passes through every step and that rework repeats the step once. It does not represent parallel routes, batching, machine downtime, travel, setup changes, priority interruptions or complex scheduling. Available hours and processing times are estimates supplied by you. Small differences between steps should not be treated as decisive without observation of normal variation.

A high capacity coverage score does not guarantee that promised lead times will be met. Queues can form even when average capacity exceeds average demand, especially when arrivals and job sizes vary. The calculation also does not establish safe staffing, equipment capability or employee performance. Use it to choose a process study, and involve the people who perform the work when investigating causes.

Read the full limitations or explore how Ayodeji approaches this work.