A common challenge facing engineering leadership today is that as teams scale, it becomes increasingly difficult to keep a pulse on what they are working on, how they’re performing, and whether their work aligns directly to the company’s strategy. The Jellyfish Data Science team analyzed the work of over 4000 engineers, and surveyed dozens of engineering leaders to better understand this challenge.

In this report, you’ll learn:

1. How and why engineering leaders overestimate the amount of resources they can devote to new feature work
2. How that changes as teams scale in size and age
3. Best practices for making sure your teams don’t follow the same patterns