Insight
7/4/25
Build vs Buy in Data: True Cost, TCO Framework, and Opportunity Cost
Thinking of building your own data tools? Learn why internal tools cost more than you think, how to calculate TCO, and when to buy vs build. A CFO’s guide to avoiding hidden costs.
Most mid-market firms think they’re saving money by building internal data tools.
On paper, it looks cheap:
Two engineers.
Three months of work.
$150k in salaries.
You think you “own” the tool. You think you avoided vendor fees.
But here’s the truth: your $150k tool is actually costing you millions.
Not in the build — but in the hidden costs of maintenance, turnover, and opportunity lost.
This is why the build vs buy debate isn’t a technical decision. It’s a financial and strategic one.
What Is the True Cost of Building Internal Data Tools?
When execs calculate build cost, they only add up salaries and time. That’s just the tip of the iceberg.
Here’s what they miss:
Maintenance Overhead: Every custom tool requires ongoing fixes, patches, and on-call support.
Turnover Risk: When the engineer who built it leaves, new hires spend months learning undocumented systems.
Feature Backlogs: Requests pile up, and the tool quickly becomes outdated.
Opportunity Cost: While your team is babysitting pipelines, your competitors are building products that win revenue.
What looks like $150k on paper often adds up to millions in hidden cost over three years.
How to Calculate TCO (Total Cost of Ownership) for Build vs Buy
CFOs and COOs should run a TCO framework before green-lighting any internal build.
Step 1: Build Cost
Engineer salaries × time invested.
Initial project management overhead.
Step 2: Maintenance Cost
% of engineering hours per month spent fixing or updating.
On-call costs (alerts, downtime, firefighting).
Step 3: Turnover Cost
Training/replacement cost when original engineers leave.
Ramp-up time for new hires to learn the tool.
Step 4: Opportunity Cost
Revenue lost because engineers were fixing tools instead of driving growth.
Market share lost to competitors innovating faster.
Add these up. Compare against vendor subscription costs.
In most cases, buying beats building by 3–5x over a 3-year horizon.
When Does It Actually Make Sense to Build?
There are rare cases where building is the right call:
Differentiation: The tool directly creates competitive advantage (e.g., proprietary ML model).
Industry-specific needs: No vendor solution fits due to unique compliance/regulatory requirements.
Strategic IP: The tool itself is the product (e.g., data-driven SaaS).
If your reason is “we don’t want to pay vendor fees” — you’re not building strategically. You’re just adding hidden cost.
The Opportunity Cost of Plumbing
Your engineers are your most expensive asset.
So ask yourself: what are they working on?
Your competitors are building predictive models to increase LTV.
Your team is building a custom Airflow operator.
Every hour spent on “plumbing” is an hour not spent on revenue.
That’s the real opportunity cost of building.
Checklist: Should You Build or Buy?
Use this simple decision checklist before building:
Does it create direct revenue impact? (Yes = maybe build. No = buy.)
Can a vendor do it 80% as well? (If yes, buy.)
Will engineers spend >20% of time maintaining it? (If yes, buy.)
Can the CFO explain the ROI to the board? (If no, buy.)
If you can’t answer these clearly, you’re building a liability — not an asset.
The Bottom Line
Your $150k internal tool is not an asset. It’s a liability.
It doesn’t just cost you money to run — it prevents your best people from working on business growth.
The build vs buy debate is not an engineering choice. It’s a CFO-level decision about ROI and competitive survival.
Stop calculating the build cost.
Start calculating the business cost.
Next step: Audit your internal tools. You’ll find at least 2–3 “zombie tools” quietly draining millions.
