What is Engineering Productivity?
Engineering productivity measures how effectively a software engineering team converts resources (time, people, money) into valuable software output. It's one of the most debated topics in technology leadership because measuring it incorrectly can damage morale and incentivize the wrong behaviors.
Common productivity metrics include: DORA metrics (deployment frequency, lead time, change failure rate, MTTR), SPACE framework (satisfaction, performance, activity, communication, efficiency), story points completed, and code review turnaround time.
Richard Ewing's perspective: raw productivity metrics like lines of code or story points are misleading. The Revenue Per Engineer (APER) metric connects engineering output to business outcomes — measuring the revenue generated per engineer rather than the activity generated.
Why It Matters
Engineering typically consumes 20-40% of a technology company's total spend. Improving engineering productivity by even 10-15% has massive financial impact. But measuring productivity wrong (e.g., lines of code) can be worse than not measuring it at all.
Frequently Asked Questions
How do you measure engineering productivity?
Use a combination of DORA metrics (deployment frequency, lead time, change failure rate, MTTR), the SPACE framework, and business outcome metrics like Revenue Per Engineer (APER).
What is a good revenue per engineer?
Varies by stage. Pre-product-market-fit: not meaningful. Growth stage: $200K-500K. Scale: $500K-1M+. Elite (Stripe, Figma): $1M+. Use the APER calculator at richardewing.io/tools/aper.
Free Tools
Related Terms
Free Tool
Calculate your revenue per engineer
Use the free APER Diagnostic diagnostic to put numbers behind your engineering productivity challenges.
Try APER Diagnostic Free →Need Expert Help?
Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
Book Advisory Call →