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The purchase price of a component or system is often the smallest part of what it will cost over its life. Lifecycle cost analysis (LCA) accounts for acquisition, operation, maintenance, downtime, and disposal — revealing total cost of ownership and enabling comparisons that unit price alone cannot make.
Material selection determines performance, cost, and supply reliability for the life of a product. The right method is systematic: define requirements as measurable performance indices, screen by function, rank by cost and availability, then verify against the full specification.
A prototype that costs $800 and eliminates a $15,000 tooling rework is not an expense — it is a 1,775% return. The question is never whether prototyping has value. The question is whether the value of the risk it eliminates exceeds its cost. A simple framework makes that calculation explicit.
Every product contains components that were either made in-house or sourced externally. For most engineering teams, the default is to design what is unique to the product and buy everything else — a reasonable starting point but a poor stopping point. The make vs. buy decision becomes strategic when you account for volume thresholds, core competency alignment, supply security, and the full cost of ownership on both sides.
This post gives you a structured framework for making those decisions explicitly rather than by intuition or habit. The previous post introduced value engineering as a tool for reducing cost within an existing design. This post steps back further: before optimising how you make a component, it is worth asking whether you should be making it at all.
Core Competency
A core competency is a capability that drives your competitive differentiation — something you do better than alternatives that customers value. Make what you are uniquely good at. Buy everything else, unless total cost or supply security says otherwise.
The question "should we make this or buy it?" sounds like a cost problem. It is actually three problems layered together:
Teams that only answer the cost problem make poor decisions. A component that is 10% cheaper to buy might still be worth making if it embodies a proprietary process. A component that is 30% cheaper to make might still be worth buying if it consumes skilled labour that should be applied elsewhere.
The make vs. buy analysis is a recurring exercise, not a one-time decision. Volumes change. Supplier markets shift. Your own capabilities evolve. A decision made at 500 units per year may be completely wrong at 5,000.
The foundation of any make vs. buy analysis is total cost of ownership (TCO) on both sides. Unit cost is the start, not the answer.
True cost to make: direct labour (setup time + run time), direct material, machine overhead allocation, tooling and fixtures (amortised), quality inspection time, rework and scrap rate, storage and handling, and the engineering overhead to maintain drawings and specifications.
True cost to buy: quoted unit price, incoming freight, receiving and incoming inspection, approved vendor qualification cost, supplier management overhead, MOQ implications (cost of excess inventory), currency risk for offshore suppliers, and lead time premium (expedite cost when supply is disrupted).
Both sides include costs that do not appear in the obvious place. The make side includes overhead absorption — if your machine shop is running at 60% utilisation, adding work fills slack without adding overhead cost. If it is running at 95%, you are adding to a bottleneck and the true marginal cost is much higher than the standard rate.
Sole-source risk: if you have one approved supplier for a critical component, their lead time, pricing, and continuity are entirely outside your control. Sole-source components are a supply chain liability that rarely shows up in the unit price analysis.
Quality escapes: a supplier quality problem that reaches your assembly line costs much more than the part itself. Rework, scrap, and line stoppages convert a cheap part into an expensive one quickly. Supplier qualification and ongoing quality management have real cost.
IP exposure: components manufactured by a contract supplier may involve disclosing proprietary geometry, tolerances, or processes. For components that contain competitive advantage, this risk is non-trivial.
Long lead time: a part with a 10-week lead time forces you to carry 10+ weeks of inventory or risk production gaps. The carrying cost of that inventory is a real cost that often disappears from the comparison.
Capacity constraint: if the work competes with higher-value production, the true cost is the opportunity cost of the displaced work, not the direct cost of the part.
Skill availability: custom manufacturing requires skilled trades. If qualified operators are hard to hire or retain, the true labour cost includes recruitment, training, and turnover overhead.
Minimum viable run size: short production runs carry disproportionate setup cost. A part that requires 45 minutes of setup to produce 10 units has a very different economics than the same part at 200 units per run.
Management overhead: running a production cell means managing schedules, materials, maintenance, quality, and people. This overhead is real even if it does not appear in a standard cost calculation.
Unit Price Is Not a Make vs Buy Analysis
Comparing your internal direct cost to a supplier's quoted price is not a make vs. buy analysis. You must include tooling amortisation, overhead allocation, quality cost, lead time risk, and supplier management before drawing a conclusion. Missing any of these has led engineering teams to decisions they later reversed at significant cost.
A structured make vs. buy analysis has four steps:
Step 1 — Define the scope. What exactly is being made or bought? Include the fully finished, delivered, inspected state on both sides.
Step 2 — Build full TCO models for each option. Use actual overhead rates, not standard assumptions. For the buy side, get real quotes at the volumes you expect, not catalogue prices.
Step 3 — Apply the core competency test. Ask: "If this capability were removed from our operation, would it damage our competitive advantage?" If yes, there is strategic value to making that does not appear in the cost model. If no, the cost model can be trusted.
Step 4 — Assess risk and flexibility. Rate supply risk (sole source, offshore, long lead time) and flexibility (can volumes flex up or down without penalty?). These adjust the cost comparison by the expected cost of disruption events.
Break-even analysis is a useful tool within Step 2: plot cumulative cost of make vs. buy as a function of volume. The crossover point tells you which option pays off and at what volume the decision should be revisited.
A small equipment manufacturer designs custom aluminium fixturing for their assembly process. One fixture type — a motor locating plate — requires precise parallelism and is currently machined in-house.
Make analysis at current volume (80 units per year):
Buy analysis (three quotes obtained):
Break-even check: buy saves $18.82 per unit × 80 per year = $1,506 per year. Core competency test: fixturing is not the company's competitive advantage — their differentiation is in the assembly process, not fixture manufacturing. Risk check: three competing suppliers exist; sole-source risk is low.
Decision: buy. Redeploy machine capacity to a bottleneck operation that directly supports core production.
A small robotics company was manufacturing custom cable assemblies in-house. The rationale at founding was control over quality and lead time. Four years later, the operation employed two technicians full-time and occupied a dedicated workbench area.
Full TCO analysis:
External quotes for the same assembly mix:
Core competency test: cable assembly was not their competitive differentiation — system integration and software were. The two technicians were fully capable of contributing to integration work, which was the bottleneck.
Decision: outsource cable assembly. Negotiate quality specifications, minimum stock requirements, and a second approved supplier into the contract. Save $32,500/year in direct cost. Redeploy two FTEs to integration work where they generated significantly more value per hour.
Break-Even Volume
Plot cumulative cost of make vs. buy as a function of annual volume. The crossover point is the volume at which the decision flips. If you are near the crossover, small changes in volume, overhead rates, or quotes will change the answer — flag it for annual review.
Always compare fully-loaded TCO. Never compare your internal direct cost to a supplier's quoted price — the comparison is inherently misleading. Both sides must include all cost elements before the numbers mean anything.
Revisit decisions every two to three years. Volumes, supplier markets, your own capabilities, and overhead rates all change. A make decision at $95/machine-hour looks different at $140/machine-hour. A buy decision for an offshore part looks different when lead times double.
Always develop a backup source for critical purchased components. For any bought component that would stop production if supply were disrupted, qualify at least one alternative supplier before you need them. The cost of dual qualification is almost always less than the cost of a single supply disruption.
Start with standard before specifying custom. Before committing to a custom design, check whether a standard part meets the requirements. Standard parts are available immediately, have no MOQ constraints, and come with known quality and support. Custom parts carry lead time, tooling cost, and sole-source risk from day one.
Document the decision and its assumptions. When you decide to make or buy, record the volume assumption, TCO numbers, and core competency assessment. When conditions change, you will know whether the original logic still holds.
The Right Question
Make vs. buy is not primarily a cost question — it is a focus question. The goal is to concentrate your team's time and capital on the work that differentiates your product. Everything else is overhead, regardless of whether the unit cost comparison slightly favours in-house production.
Once you have decided what to make in-house, the next decision is what to make it from. Material selection determines performance, weight, cost, machinability, and supply reliability — and the choice made at the design stage locks in cost and risk for the life of the product.
