5 posts tagged with "cfo"

The standing monthly engineering cost review at the 80-person org we worked with in March 2026 ran 90 minutes. Six dashboards. Four department leads each defending their numbers. The output: a Slack message saying "let's dig in next month." Same message in February. Same in January. The dashboards were excellent. The decisions were zero.

The problem is not data scarcity. Asana's 2024 Anatomy of Work report found knowledge workers spend 58% of the day on "work about work," meetings, status updates, and dashboard reviews, and that the modal review meeting produces no concrete next action. Engineering cost reviews are a textbook case. Too many numbers, no forcing function for a decision.

A 60-person engineering org we instrumented through 14 months of finance data ran an average overhead coefficient of K = 0.41. That number is useless. The actual monthly series is Jan 0.46, Feb 0.40, Mar 0.39, Apr 0.40, May 0.41, Jun 0.43, Jul 0.48, Aug 0.49, Sep 0.42, Oct 0.40, Nov 0.43, Dec 0.52. The flat-K finance model predicted December overhead of $185K. Reality came in at $235K. The 27% miss is not a forecasting bug. It is the entire story of every Q4 budget surprise the CFO has ever asked engineering to explain.

DORA's 2024 State of DevOps report flagged the same shape from a different angle: deployment frequency in Q4 drops 12–18% across the surveyed cohort, while incident volume rises. Stack Overflow's 2024 Developer Survey reports developers take an average of 17 vacation days per year, with concentration in late December and August. Harvard Business Review's Why Most Product Launches Fail notes Q4 launch density runs 30–40% above other quarters. Three different datasets, one consequence: engineering capacity in December is structurally different from June. Treating it as the same in your finance model is the mistake.

A 50-engineer R&D org we worked with last fiscal year set its annual budget the way most do: take last year's spend ($5.4M), add 10%, call it $5.94M. By Q3, finance was negotiating a $700K supplemental from the board. The shortfall was almost exactly $710K, 12% above the top-down number, and the postmortem traced every dollar to assumptions nobody had written down. Holiday months ran hotter on overhead. Two contractors were on-paper part-time but billed 0.9 FTE. One team grew by three heads in March, and the cost compounded for nine months instead of the four the planner had pencilled.

Gartner's 2025 IT Spending Forecast puts software R&D growth at 9-11% YoY, but the variance band on individual company budgets is much wider. Deloitte's CFO Insights: Budgeting in Volatile Times (2024) found median forecast error of 18% in software-heavy organizations using top-down methods, and the worst quartile missed by more than 30%. McKinsey's 2023 Tech Talent Tectonics report sharpens the case: top-quartile engineering organizations don't just spend less per output. They forecast more accurately, which lets them allocate aggressively where bottom-quartile organizations have to keep cash slack as a hedge against their own bad math.

A 50-person engineering org we instrumented in February 2026 had a monthly overhead coefficient of K = 0.37. That means every $1 of direct development work was shadowed by 37 cents of indirect cost: meetings, code review, ramp-up, and a slice of CTO/EM/DevOps salary spread across the team. The CFO had been modelling overhead at a flat 30% loaded multiplier for three years. The actual number was 23% higher, and almost nobody in the company knew.

The bigger problem was not the gap. The bigger problem was that the 30% number was a single bucket, so even after you discovered the gap, there was nothing actionable inside it. Boston Consulting Group's 2024 report on G&A allocation in software firms made the same observation at industry scale: companies that report overhead as one line item find it nearly impossible to trim, while companies that decompose it into three components reduce it by 8–15% within two quarters.

A CFO usually sees engineering on one line of the P&L: salaries. A headcount column, a loaded-cost multiplier, a big number growing faster than revenue. That's it. Deloitte's 2024 Global Technology Leadership Study put the gap at its starkest: only 31% of CFOs said they could tell whether their engineering investment was producing returns proportionate to cost. The other 69% were flying blind on roughly the largest discretionary spend in the company.

This is not a tooling problem. It's a question problem. The numbers exist. Your CFO peers just haven't learned which five questions extract them.