73 posts tagged with "engineering-metrics"

McKinsey's research on developer productivity found that software engineers spend only 25-30% of their working hours on active coding. The rest goes to meetings, planning, waiting, and context switching. In outsourcing, where every hour has a direct revenue implication, this split matters enormously. Your company has 40 developers. You bill clients for their time. But how much of each developer's available time is actually billable? If the answer is "I'm not sure," you have a profitability blind spot that could be costing you hundreds of thousands of dollars annually.

Developer utilization is the single most important financial metric in outsourcing. And most companies measure it wrong — or don't measure it at all.

Staff augmentation is now the fastest-growing segment of the outsourcing market, according to the Deloitte Global Outsourcing Survey. Yet the model introduces a paradox that most buyers discover too late. You've augmented your engineering team with external developers. They attend your standups, push to your repos, and bill you monthly. But when the invoice arrives, you have an uncomfortable thought: "I have no idea how these people actually spend their days."

You trust your in-house team because you see them in Slack, in code reviews, in the office. The augmented developers? They're a black box. And that black box is costing you tens of thousands of dollars a month.

Dashboards are great — until you need an answer that doesn't fit any pre-built chart. "What was our average PR review time last month, excluding the infra team?" That query doesn't have a button. It requires filtering, grouping, and calculating across multiple dimensions.

PanDev's AI assistant lets you ask questions like this in plain English. Powered by Google Gemini, it understands your engineering data and returns answers, charts, and tables in seconds. Gartner predicts that by 2026, over 80% of enterprises will have used generative AI APIs or deployed AI-augmented applications — natural-language analytics is part of that shift.

Your product team just shipped a new reporting dashboard. It took three sprints, involved four developers, a designer, and a QA engineer. How much did it actually cost?

If your answer is "I don't know" or "somewhere between $20K and $80K," you're not alone. Most engineering organizations cannot answer this question with any precision. According to Stripe's Developer Coefficient report, companies collectively spend over $300 billion annually on developer time — yet few can attribute those costs to individual features. That disconnect turns every product decision into a guess.

Every quarter, CTOs face the same uncomfortable meeting. The CEO asks: "We spent $2.4M on engineering last quarter. What did we get for it?" And the answer is usually a list of shipped features — not a financial return.

Engineering is the largest cost center in most technology companies, yet it's the one with the least financial accountability. Marketing can show customer acquisition cost. Sales can show revenue per rep. Engineering shows... velocity points? McKinsey's analysis of software developer productivity highlights this gap: engineering output is measurable, but most organizations haven't built the systems to do it.

It's time to change that.

Your engineering team has 40 developers across three offices, a mix of full-time employees and contractors, salary ranges from $60K to $190K, and contractor rates from $45/h to $150/h. Someone asks: "How much did Project X cost last month?"

You open a spreadsheet. You check Jira. You send three Slack messages. An hour later, you have a rough guess. With global IT spending projected to exceed $5 trillion in 2025, that level of imprecision is expensive at any scale.

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.

WakaTime is one of the most well-known developer time tracking tools, with over 500K users, 40+ IDE plugins, and an annual "Yearly Wrapped" report that has become a community tradition. At $9/month for the Premium plan, it is one of the best values in developer tooling. PanDev Metrics is an Engineering Intelligence platform built for teams and organizations. They both track coding activity via IDE plugins — but that is where the similarity ends.

If you are evaluating both tools, this comparison will help you understand which one fits your needs.

LinearB is one of the more established players in the Engineering Intelligence space, known for strong DORA metrics implementation and workflow automation. PanDev Metrics is a newer platform that takes a broader approach — combining engineering metrics with financial analytics and on-premise deployment.

Both platforms aim to help engineering leaders make better decisions. But they differ significantly in pricing, deployment options, and the types of insights they provide. Here's a detailed, honest comparison.

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.