Why Mid-Sized Businesses Need a Fractional Data Team
Here's a scenario we see all the time: a mid-sized business knows they need to do more with their data. They've been talking about it for months. Maybe they've even posted a job listing for a "Data Analyst" or "BI Developer." Six months later, the role is still open, or they hired someone junior who is learning on the job while the business waits for results.
There is a better way.
The Hiring Problem
Building an in-house data team is expensive and slow. A senior data engineer costs $150K-$200K+ in salary alone. A data scientist adds another $140K-$180K. A BI developer, $120K-$160K. Add benefits, tooling, management overhead, and the 3-6 months it takes each hire to ramp up on your business.
For a mid-sized business doing $5M-$50M in revenue, that math does not work. You need the expertise, but you do not need three full-time people sitting in seats 52 weeks a year.
The Consultancy Trap
The alternative most companies try is hiring a large consultancy. The pitch sounds great: a team of experts who can start immediately. Here is what actually happens:
- You pay for a team of 10-20 people, but only 2-3 do the actual work
- Junior analysts are staffed on your project as a training ground
- An account manager sits between you and the people doing the work, slowing everything down
- Hourly rates of $250-$400+ mean your budget burns fast with little to show for it
- The "methodology" and "discovery phase" adds weeks before any real work begins
The Fractional Model
A fractional data team gives you senior specialists who work on your projects as needed, without the overhead of full-time hires or the bloat of a large consultancy. You get the people who actually do the work, with direct access and no layers in between.
At Figment Analytics, our team is three senior specialists: a BI and data storytelling lead, a data scientist and engineer, and a full-stack software and data engineer. When you hire us, you get all three, working directly on your problem from day one.
What This Looks Like in Practice
A typical engagement starts with a focused conversation about what decisions you need your data to support. Not a six-week discovery phase. A conversation. (Wondering which BI tool to use? See our Power BI vs Tableau comparison.)
From there, we scope the work, build it, and deliver. A dashboard that was going to take an in-house hire three months to figure out gets delivered in weeks. A data pipeline that a large consultancy would quote six figures for gets built at a fraction of the cost because we are not padding the team with junior staff.
Some examples from our portfolio:
- Figment Forge: A Power BI dashboard tracking $1.18M+ in retail revenue with ML forecasting, delivered as a turnkey solution
- FlightPulse: An interactive geospatial visualization demonstrating what location-based data can do for operations teams
- Figment Gaming: A full-stack production platform proving we build and ship real software, not just reports
When Does the Fractional Model Make Sense?
The fractional model works best when:
- You have data but no one dedicated to turning it into decisions
- You need senior expertise but cannot justify full-time headcount
- You have a specific project (dashboard, pipeline, forecast model) with a clear outcome
- Your current team is strong in operations but lacks data and analytics skills
- You tried hiring and the role has been open for months
The Bottom Line
Every week without analytics is another week of decisions made on gut instinct. You do not need a 20-person department to fix that. You need a small team of senior specialists who can start delivering results immediately.
If that sounds like what your business needs, book a free 30-minute call and we will show you exactly where your data can drive revenue.
