When you support a company the size of T-Mobile, the questions never stop:
How should we price this role? Where does it fit? What are these skills worth in today’s market?
For Ardavan Khosravi, Compensation Market Research Manager, the challenge wasn’t the volume, it was the uncertainty behind each request.
Job descriptions were “creatively written,” full of emerging skills and hybrid responsibilities that didn’t map neatly to T-Mobile’s job architecture.
“Sometimes a JD wouldn’t fit the mold at all,” Ardavan says. “I had to figure out which skills mattered and whether the market paid a premium for them.”
Ardavan fields a steady stream of questions from analysts and business partners.
Many requests hinge on one difficult step: translating job descriptions into T-Mobile’s structure and understanding what the skills inside those descriptions are worth in the market.
Before Analyst Agent
Before Analyst Agent, answering those questions took hours.
Ardavan started with a generic GPT tool to extract skills, then jumped into manual research—Googling terms, scanning job postings, comparing roles across the industry, and piecing together data from inconsistent sources.
The output worked in a pinch, but it wasn’t something he could defend with confidence.
“There was always noise in the data,” he says. “I knew the methodology wasn’t strong enough for high-stakes decisions.”
Analyst Agent
Everything changed when the team adopted Analyst Agent.
Now Ardavan drops the job description into Analyst Agent and gets a full readout in seconds:
- Skills extracted directly from the JD
- Market premiums tied to those skills
- Recommended benchmarks and leveling
- Suggested matches within T-Mobile’s job architecture
“I finally have a place to start,” he says. “And I trust the data because it’s built on the same Compa dataset our team already relies on.”
Instead of patching together insights, Ardavan now responds with answers he can stand behind, fast.
“The difference is trust,” Ardavan says. “Analyst Agent uses the same Compa data our team already relies on. When I respond to the business, I know the answer is grounded in data, not guesswork.”
With Analyst Agent, T-Mobile’s compensation team has:
- Cut hours of manual research on ad hoc requests
- Increased confidence in pricing, leveling, and skill-based recommendations
- Delivered consistent, defensible answers across the business
- Freed up analysts to focus on strategic projects like annual cycles and deep-dive reviews
The bigger shift is credibility.
The team now provides fast, accurate insights that hold up with Finance, business partners, and the board.
“Having an agent built on Compa’s data gives me confidence when questions come in,” Ardavan says. “It’s what we all hoped agents would deliver: better, faster, more precise answers we can use for high-stakes decisions. We’re no longer reactive; we’re empowered.”
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