Choosing capacity planning tools
Published
Before buying equipment or adding a person, ask: will the extra capacity help the whole process finish more work?
Put demand and capacity in the same period
Demand is how much work needs completing. Capacity is how much a step could handle with the time and resources available. Compare orders per day with orders per day, not orders per hour with a weekly target.
This fictional example needs 50 orders a day. Each step has one person with 480 available minutes, all orders visit every step, and there is no lost time or rework in these assumptions.
Checking limits estimated output to 30 orders a day, leaving a gap of 20. Preparing faster would not remove that limit.
Test the change, not just the local saving
If checking takes 8 minutes instead of 16, estimated output rises to 40 orders a day. Packing then becomes the limiting step, and the demand gap is still 10. Halving one step’s time has not doubled the output of the whole process.
The figures use Improve First’s calculation engine. They are estimates under the stated assumptions, not a prediction of exact completion times, waiting or delivery performance.
Match the tool to the next decision
- A spreadsheet
- Choose this if you want to build your own capacity assumptions and formulas, and can check how the steps connect.
- A first-pass calculator
- Use Improve First to test whether a change to a simple, sequential process could increase completed output. Free calculations do not require an account; Pro adds saved models and saved scenario comparison.
- Detailed planning or simulation
- Investigate this when the decision needs a shift roster, shared resources, changing work types, branching routes or time spent waiting. Those questions need more detail than this calculator models.
If the times are uncertain, test a range
Try a lower and a higher estimate in separate calculations. If both point to the same first improvement, you have a clearer next question. If they point to different steps, measure those steps before spending. This is a comparison of assumptions, not a statistical confidence interval.