Make or Buy Cost Comparison Calculator
A make or buy decision goes wrong when allocated overhead is mistaken for cost you can actually avoid. This calculator compares the relevant cost of making a part with the full cost of buying it, and shows the volume where the answer flips.
Your numbers
Pieces per year.
Power, tooling wear, consumables.
Only costs that disappear if you stop making it.
Depreciation plus financing of equipment needed to make it.
Your results
Uses relevant (avoidable) costs only. Allocated fixed overhead that continues either way should not be included. Strategic factors such as quality, IP, capacity and supply risk are outside this calculation.
Cost per piece vs annual volume
Sweeps Annual volume from 1000 to 30000, holding your other inputs fixed.
Run make or buy across your item master
Optional: see how routing and purchase price data can drive this analysis at scale.
Optional. The tool and every export work without this. No spam.
How to use the calculator
Enter annual volume and the variable cost of making one piece: material, direct labor and variable overhead. Add the fixed costs that would disappear if you stopped making the part, such as a dedicated operator, a lease or maintenance contract, and the annualized cost of any equipment you would need. On the buy side enter the supplier price plus the extra cost you bear: freight, incoming inspection and handling. Read the per piece costs and the break-even volume, and review the chart for sensitivity.
- Use avoidable fixed cost, not allocated plant overhead
- Include equipment you must buy to make it
- Add inspection and freight to the buy side
The method behind it
This is relevant-cost analysis. Only costs that differ between the two options matter. Making costs variable cost per piece plus avoidable fixed cost spread over volume. Buying costs the supplier price plus extra handling. Break-even volume equals avoidable fixed cost divided by the buy cost minus make variable cost per piece. Above that volume, spreading fixed cost over more pieces makes in-house cheaper. Below it, buying wins on cost.
Reading the result
In the default example, making costs about 9.40 per piece against 11.00 to buy, saving roughly 19,000 a year. The break-even volume tells you how much volume risk you carry: if the forecast falls near break-even, the decision is fragile. If making wins only because you included no equipment cost, revisit the inputs. Use the chart to see how the lines converge as volume drops.
Common mistakes and wider factors
The biggest error is using fully absorbed standard cost for the make side, which buries unavoidable overhead in the comparison and often pushes work out wrongly. Other errors: ignoring the capacity freed up and what it could earn, forgetting scrap and rework, and treating the supplier price as fixed when volume or material price may change. Quality history, lead time, IP control and supplier concentration risk sit alongside the numbers.
Frequently Asked Questions
Which fixed costs should I include?
Only those that would be avoided if you stopped making the part, such as dedicated labor, lease, maintenance contracts and equipment you would not otherwise own. Allocated overhead that continues regardless is not relevant to this decision.
What does break-even volume mean here?
It is the annual volume at which making and buying cost the same. Above it, making is cheaper because fixed cost is spread across more pieces. Below it, buying is cheaper. It is only valid while prices and costs hold.
Should I include the opportunity cost of capacity?
Yes, when the capacity has a better use. If making this part blocks higher margin work, add that lost contribution to the make side. This calculator does not do that automatically, so adjust the avoidable fixed input.
Is this enough to decide?
It covers cost only. Also weigh quality, delivery performance, intellectual property, supply risk and strategic fit. Treat the result as one input to the decision, not the decision itself.
If you want to run this across your item master using ERP routings and purchase prices, we can help build a read-only analysis that shows each assumption.
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