When to Hire a Data Analyst vs. Outsource Data Infrastructure

You've outgrown spreadsheets. Leadership needs better reporting. The question everyone asks: Should we hire a data analyst or outsource?

Here's a framework I use with mid-sized companies facing this exact decision.

The $100k+ Question

A full-time data analyst costs $100,000+ in salary and benefits. Add 3-6 months for recruiting and onboarding, and you're looking at significant investment before seeing any value.

But the real question isn't about cost; it's about what problem you're actually solving.

Three Questions to Ask First

1. Do you need ongoing analysis or reliable infrastructure?

If you need: Ad-hoc analysis, exploratory data work, predictive models → Consider hiring a data analyst

If you need: Automated reporting, data centralization, pipeline reliability → Consider outsourcing

Most mid-sized companies think they need the first when they actually need the second.

2. Is your data mess a one-time fix or an ongoing problem?

One-time fix signals:

Data is scattered but systems are stable
You need it centralized and automated
Once built, internal team can maintain it

→ Outsource the build, train your team, then run it internally

Ongoing problem signals:

Business model is rapidly changing
Constantly adding new data sources
Need continuous data strategy evolution

→ Hire internally for ongoing iteration

3. What happens if this person leaves?

Here's the uncomfortable truth: when your solo data person leaves, your reporting breaks.

With hiring:

All knowledge lives in one person's head
Documentation is often incomplete
Replacement takes months to get up to speed

With outsourcing (done right):

System is documented as it's built
Multiple people understand the infrastructure
Handoff includes training for your team

The Hidden Costs of Hiring

Beyond the $100k+ salary, consider:

Ramp-up time: 3-6 months before they're productive
Management overhead: They need direction and context
Tool costs: Licenses, infrastructure, training
Opportunity cost: What if you hire the wrong person?
Knowledge risk: Everything breaks when they leave

When Hiring Makes Sense

Don't get me wrong; hiring can be the right move if:

You need ongoing analytical work (not just infrastructure)
You have data strategy questions that require continuous iteration
Your business is complex enough to justify a full-time role
You're ready to build a data team (not just hire one person)
You have 100+ employees and growing fast

When Outsourcing Makes Sense

Outsourcing typically works better when:

You need infrastructure, not ongoing analysis
Your reporting needs are predictable (monthly close, board packs, operational dashboards)
You want to de-risk the knowledge problem (documented, transferable)
You need results in weeks, not months
You're not ready to commit to $100k+ annually

The Hybrid Approach

Here's what I see working for mid-sized companies:

Phase 1: Outsource the infrastructure build

Centralize data sources
Automate core pipelines
Build standardized dashboards
Document everything
Train internal superuser

Phase 2: Run it internally

Your finance/ops team maintains the system
Make minor updates and adjustments
Use the working infrastructure daily

Phase 3 (maybe): Hire when you need more

Once infrastructure is stable
When you need advanced analytics
After you understand what the role should actually do

A Framework for Your Decision

Ask yourself:

"If we had perfect data infrastructure tomorrow; automated pipelines, reliable dashboards, single source of truth; would we still need to hire someone?"

If yes → You need ongoing analytical capability → Consider hiring

If no → You need infrastructure, not headcount → Consider outsourcing

The Real Risk

The biggest risk isn't choosing wrong between hiring and outsourcing.

It's doing neither and continuing to run your business on fragile spreadsheets and manual reporting that breaks when Sally from Finance goes on vacation.

Next Steps

If you're trying to decide:

Map your current reporting process - What's manual? What breaks?
Define what "success" looks like - Do you need analysis or automation?
Calculate the actual cost - Include time, risk, and opportunity cost
Talk to companies who've done both - Learn from their experience

Need help thinking through your specific situation? We work with mid-sized companies on exactly this decision. No sales pitch; just a practical conversation about what makes sense for your business.