Strategy
Stop Counting Engineers, Start Proving Value
May 19, 2025
Over the past few years, I’ve worked in fintech engineering leadership roles where platform scale, team efficiency, and business alignment weren’t just ideals—they were mandates. Across the industry, those pressures are intensifying.
When Microsoft cut 6,000 roles last week, AI dominated the headlines. But behind the scenes, another story emerged: Microsoft’s revenue per employee has lagged for years. According to Bullfincher, Microsoft generates roughly $1M per employee, while Apple ($2.4M), Meta ($2.2M), and Google ($1.9M) produce almost twice that figure or more.
This isn’t just a Big Tech problem. It’s a broader market correction—and it’s coming for all of us.
The Efficiency Awakening Is Already Here
During the 2020–22 boom, many engineering orgs grew headcount faster than output. Teams doubled while value delivery grew by only 30–40%. That math was always going to break, especially without corresponding gains in process maturity or outcome clarity.
Now, leaders are being asked to reconcile team size with measurable value. This isn’t about reactionary cost-cutting. It’s about restoring the connection between resources and results.
Reframing How We Measure Engineering Value
For years, we’ve leaned on internal metrics—velocity, story points, deployment counts—as proxies for productivity. But those metrics don’t resonate in boardrooms. They explain effort, not impact.
It’s time to translate engineering contributions into business terms.
1. Map Technical Work to Business Impact
Every significant initiative should connect to a tangible outcome:
Revenue growth (via retention, monetization, or expansion)
Cost savings (via automation, efficiency, or tooling)
Risk reduction (via uptime, security, or compliance)
Market enablement (via scale or regional expansion)
These links must be explicit. One VP I know holds quarterly value reviews where each team must tie their work to an OKR or KPI. It’s not easy—but it’s made prioritization sharper and roadmaps more strategic.
2. Make the Case for “Invisible” Work
Some of the most essential engineering efforts don’t produce features. Things like reducing technical debt, platform modernization, or improving developer experience often get deprioritized—unless they’re framed in terms of business value.
Examples that work:
Quantify the drag: “Our legacy auth system burns 22 engineering-days/month in maintenance overhead.”
Forecast the upside: “Refactoring this pipeline will save $380K/year in cloud spend.”
Show strategic leverage: “Deployment automation will shrink feedback cycles from weeks to days, enabling us to act on customer input 70% faster.”
Don’t sneak this work in. Surface it with confidence and clarity.
3. Organize Around Outcomes, Not Just Tech Stacks
Conway’s Law is still undefeated. If teams are structured by layer (frontend, backend, infrastructure), the output often mirrors internal complexity—not user outcomes.
Instead, consider outcome-aligned teams that:
Own customer-facing verticals
Influence real business metrics
Ship and operate independently
Understand how their work ties to growth, cost, or risk
This shift creates natural accountability—not just for shipping code, but for moving the needle.
What This Means for Engineering Leaders
Your job security—and advancement—now depends on two things:
The real business value your teams deliver
Your ability to explain that value in non-technical terms
I’ve seen technically brilliant leaders let go because they couldn’t tell that story. And I’ve seen technically modest leaders succeed because they spoke the language of outcomes, not effort.
The strongest leaders I know:
Track impact through business metrics, not just technical KPIs
Teach engineers how to communicate value, not just code quality
Make the ROI case for infrastructure, architecture, and tooling—alongside product features
Beyond Survival: Engineering Leverage
This isn’t about doing more with less. It’s about doing more with clarity.
The goal isn’t headcount—it’s leverage.
High-leverage engineering orgs:
Build internal platforms that multiply delivery
Automate entire categories of manual work
Enable self-service across functions
These aren’t theoretical ideals—they’re repeatable strategies. The leaders who’ll thrive now aren’t the ones who grow the biggest teams. They’re the ones who prove outsized value per engineer.
Yes, this shift is uncomfortable. But it’s a return to first principles: we build technology to create outcomes that matter. It’s time to lead accordingly.
