What recent data tells us about developer productivity and team health

Research by Jellyfish shows declining operational effectiveness as engineering teams continue to feel the crunch.

This was a year unlike most, as the sobering reality of an economic downturn has influenced the way engineering management prepared for the coming year, and it’s impacting developers across the globe.

Every year, the Jellyfish Research team analyzes data from its Engineering Management Platform and conducts a survey of engineering leaders across North America to better understand the current state of engineering management. 

This year’s research uncovered some of the hardships that engineering teams face. The dataset included an analysis of the work of thousands of engineering teams, with the intention of better understanding three main areas:

• Where are engineering teams investing their time? 
• What challenges are teams facing on an operational level?
• Are there notable differences in behavior between underperforming and overachieving teams?

This year’s research showed that teams are being asked to do more than ever with fewer resources, and it’s already impacting productivity.

Declining engineering operational effectiveness

Our findings show that software development teams have been less effective operationally across four key metric vectors: tempo, throughput, collaboration, and planning. There are a few data points that stick out from this year’s research that show where teams are struggling operationally:

• Teams are taking longer to complete development work, with issue cycle time and PR cycle time increasing 2.3% and 6.4% Year-on-Year (YoY).
• Teams are working on more projects at the same time, thus being pulled in more directions with less time to focus.
• Developers are working on larger chunks of code at a time, with commits down 10.4% YoY and PR size is rising.

Engineering leaders cited the drastic shift from growth to efficiency strategies as a key reason for this operational whiplash.

They went from hiring new team members to fuel future innovation, to cutting back priorities and focusing on calculated profitable growth. At the time of the survey, towards the end of 2022, about 25% of teams faced headcount reductions and about 44% had experienced hiring freezes. The shifts in strategic priorities, coupled with reduced headcount, appear to be putting real strain on teams’ operations.

2023: The year of engineering operational efficiency

If 2022 was supposed to be the year of growth for engineering teams, 2023 is turning out to be the year of efficiency. Recent survey results show that leaders are focused on efficiency and better aligning their engineering resources to business priorities.  

Engineering teams are calling on leadership to provide clarity on what their priorities and focus areas are. If we see leadership rise to this challenge, it’s possible that the operational slowdown of last year does not become the defining trend in 2023.  

Are engineering management platforms the answer?

In stark contrast to the rest of the research, data-driven teams leveraging Engineering Management Platforms (EMPs) saw drastically better results operationally than those that didn’t in 2022. They are moving faster, increasing throughput, increasing their team collaboration, and sticking to DevOps best practices. Here are some quick highlights from the data: 

• Issue cycle times were 11% faster than non-EMP users
• PR cycle times were 8.7% faster at 2.4 days
• PRs merged were 12% higher than other teams 
• Issues resolved were up 7.8% YoY
• Commits were up nearly 7% from last year and are 20% higher than average teams
• Data-driven teams made 21% more PR comments, and 18% more reviews than other teams

Part of this can be explained by the compounding effect of having visibility into the impact of engineering work. For example, teams that have the access to Allocation data – which is the measurement of the distribution of a software engineering team’s work across a number of key axes – appear to focus more on growth and innovation work, on average. They are also more mindful of taking on work that does not support current focus areas. 

Data-driven engineering teams using EMPs:

• Devote 31% more of their efforts to growth and innovation work than their non-EMP using counterparts
• Increase visibility into exactly what work is being done by 46%
• Categorize less than 15% of their work as “Other” on average, (46% less than non-EMP users)

Closing thoughts

Engineering management is already difficult, but it’s being made even more difficult in 2023 with an acute focus on efficiency. We now have insights that explain some of the pain points that teams have been feeling over the past year.

The reasons for rising burnout among teams are related to the growing stress associated with economic pressures, unclear priorities, shifts in strategic direction, headcount reductions, and hiring freezes.   

This post was only a sample of the insights and takeaways from this year’s research. Download the full report today to learn more about the State of Engineering Management in 2023.