13 posts tagged with "financial-analytics"

It's budget season. The CTO submits an engineering budget request: $8.2M for next year, up 18% from this year. The CFO asks for justification. The CTO points to headcount growth, salary inflation, and a list of planned projects. The CFO pushes back: "Can we do it for $7M?" The CTO says no. They compromise at $7.5M.

Neither number is based on data. The CTO added a buffer to last year's spend. The CFO cut it by a round number. The compromise has no analytical basis. Both sides walk away slightly unhappy. A Deloitte CFO Survey found that technology spending is consistently one of the hardest budget categories for finance teams to evaluate — largely because the inputs are opaque.

This is how most IT budgets are built. It doesn't have to be.

Jellyfish is an enterprise Engineering Management Platform with a price tag to match — typically $50K to $250K per year. It claims over 50,000 teams on its platform, hosts GLOWLive events for engineering leaders, and provides an ROI calculator to help justify the investment. It's designed for large engineering organizations (200+ developers) that need portfolio-level visibility into engineering investment.

PanDev Metrics offers many of the same capabilities — including financial analytics, team metrics, and delivery insights — at a lower price point, with some features Jellyfish does not have. But Jellyfish brings unique strengths too, particularly in strategic portfolio management.

Here is an honest comparison to help you decide.

Digital agency CEOs live and die by utilization rates. According to SoDA (Society of Digital Agencies) benchmarks, the target billable utilization for development teams is ~75-85% — and most agencies fall short. Every hour a developer spends on non-billable work is lost revenue. Every project that goes over budget eats into margins. And with 5, 10, or 20 client projects running simultaneously, knowing where everyone's time actually goes is nearly impossible.

Most agencies rely on manual time tracking. Developers fill in timesheets at the end of the week, guessing how many hours went to each project. The data is inaccurate, the process is hated, and the resulting numbers drive decisions worth hundreds of thousands of dollars.

There's a better way.