How to Reduce Non-Coding Time for Engineers: Maximizing Development Productivity

Software engineers are hired to write code that delivers value, yet studies consistently show they spend less than half their workday actually coding. The rest is consumed by meetings, administrative tasks, context switching, and various other non-coding activities. This article explores concrete strategies to reclaim this lost time and significantly increase engineering productivity.

The State of Engineering Time Allocation

Before diving into solutions, let's understand the scope of the problem. According to a 2024 State of Engineering Time report by CircleCI, the average software engineer spends their time as follows:¹

This means that more than two-thirds of an engineer's time is spent on activities other than their core value creation. Even more concerning, DORA's State of DevOps research suggests that high-performing organizations achieve coding time percentages of 50-60%, creating a significant competitive advantage ².

The Hidden Costs of Non-Coding Time

Non-coding activities don't just reduce the amount of code produced—they carry significant hidden costs:

Context Switching Penalties

Every time an engineer shifts from coding to a meeting and back again, there's a substantial mental cost. Research from the University of California found that after switching tasks, it takes an average of 23 minutes to fully return to the previous task ³.

For an engineer with four task switches per day, that's nearly two hours of recovery time alone.

Satisfaction and Retention Impact

Engineers who spend more time coding report higher job satisfaction. A GitHub developer survey found that engineers at companies with higher coding-time percentages reported 26% higher job satisfaction and 31% lower intention to leave within a year ⁴.

"The best engineers I know want to solve hard problems with code. Every hour we keep them in meetings is an hour they're not doing what they love."

• Edith Cooper, Engineering Director

Innovation Deficit

Less time coding leads to fewer opportunities for creative solutions and technical innovation. When engineers are rushed or time-constrained, they're more likely to implement quick fixes rather than robust solutions, increasing technical debt.

Strategic Approaches to Reducing Non-Coding Time

Let's explore practical strategies that engineering organizations can implement to maximize coding time:

1. Meeting Optimization

Meetings constitute the largest non-coding time sink for most engineers. Here's how to address this:

Audit and Eliminate Unnecessary Meetings

Conduct a thorough audit of all recurring engineering meetings with these questions:

• Does this meeting have a clear, specific purpose that cannot be accomplished asynchronously?
• Are all attendees necessary active participants (not just listeners)?
• Could this meeting be half as long or half as frequent?

Research by Atlassian found that teams that conducted meeting audits reduced meeting time by 42% without negative impact on team coordination ⁵.

Implement Meeting-Free Days

Designate specific days (commonly Tuesdays and Thursdays) as no-meeting days for engineering teams. Companies implementing no-meeting days report up to 35% higher code output on those days ⁶.

Meeting Efficiency Protocols

For necessary meetings, implement strict protocols:

• Every meeting must have an agenda distributed beforehand
• 15 or 45-minute default (not 30 or 60) to encourage brevity
• Clear documentation of decisions and action items
• "Decline and redirect" policy for engineers to suggest asynchronous alternatives

2. Administrative Burden Reduction

Administrative tasks can consume a surprising amount of engineering time:

Time-Tracking Simplification

Complex time-tracking systems can consume 2-3 hours weekly per engineer. Evaluate whether detailed time tracking provides sufficient ROI or if simplified models could work.

Many organizations have moved to broad-category time tracking (project vs. non-project) or eliminated granular tracking entirely, saving 5-7% of overall engineering time ⁷.

Self-Service Systems

Implement self-service portals for common engineering needs:

• Environment provisioning
• Access requests
• Configuration changes
• Documentation lookup

Companies that implemented comprehensive self-service systems reduced administrative time by 34% according to a DevOps Research and Assessment (DORA) study [2].

Documentation Automation

Automate documentation tasks where possible:

• API documentation generation from code annotations
• Automated changelogs from commit messages
• Diagram generation from code structure
• Quick-capture tools for technical decisions

3. DevOps and Tooling Optimization

DevOps tasks and tooling issues represent a significant portion of non-coding time:

Build and Deployment Optimization

Slow builds and deployments are major productivity killers. Some approaches to address this:

Common Issue	Solution	Potential Time Savings
Slow build times	Incremental builds, parallelization	15-30 minutes/day
Manual deployments	CI/CD automation	30-60 minutes/day
Environment inconsistency	Containerization	20-45 minutes/day
Test failures	Improved test reliability	25-35 minutes/day

Source: DORA State of DevOps Report 2024 [2]

Developer Experience Team

High-performing organizations often establish dedicated Developer Experience (DevX) teams focused on reducing engineering friction. According to research by Nicole Forsgren, organizations with DevX teams see 23% higher productive coding time ⁸.

Key responsibilities for these teams include:

• Streamlining development environment setup
• Optimizing build and deployment pipelines
• Creating internal developer platforms
• Measuring and improving engineering productivity metrics

Tool Consolidation and Integration

Tool sprawl is a common issue in engineering organizations. Each additional tool creates overhead for:

• Learning and onboarding
• Context switching
• Authentication and access management
• Information fragmentation

A study by Atlassian found that teams using more than 15 tools spent 23% more time on non-coding activities than those using fewer than 8 well-integrated tools ⁹.

Communication and Interruption Management

Unscheduled interruptions create significant productivity costs:

Structured Communication Channels

Create clear guidelines for which communication channels to use for different types of messages:

Type of Communication	Recommended Channel	Response Expectation
Emergencies	Direct call/pager	Immediate
Urgent questions	Team chat (direct mention)	Within 1 hour
General questions	Team chat (channel)	Same day
FYI updates	Documentation/email	None
Complex discussions	Async document comments	Within 1-2 days

Adapted from GitLab Communication Guidelines [10]

Interrupt Deflection Strategies

Implement interrupt deflection mechanisms:

• Office hours for senior engineers (2 hours/day when they're interruptible)
• "Do not disturb" indicators respected by the team
• Question parking lots (collaborative docs where questions can be posted and answered asynchronously)
• Knowledge base development to reduce repeat questions

Amazon found that implementing structured office hours reduced interruptions by 67% while improving knowledge sharing and mentoring quality ¹⁰.

Workflow Optimization Techniques

Beyond reducing specific types of non-coding work, holistic workflow improvements can dramatically increase coding time:

Work Batching

Context switching between different types of work carries a heavy cognitive cost. Batching similar activities together reduces this penalty:

• Code review batching (dedicated daily time)
• Email/administrative batching (beginning/end of day only)
• Deployment/release batching (scheduled windows)

Teams at Microsoft that implemented structured work batching increased coding time by 14-18% in an internal study ¹¹.

Single-Piece Flow for Projects

Rather than having engineers work on multiple projects simultaneously, aim for engineers to work on one project at a time until a meaningful milestone is completed.

Multi-project assignments increase coordination overhead and context-switching costs. Research from the Project Management Institute found that engineers assigned to a single project at a time spent 37% more time on value-adding activities compared to those juggling 3+ projects ¹².

Eliminating Approval Bottlenecks

Excessive approval requirements create waiting periods that disrupt coding flow:

• Implement auto-approval for low-risk changes
• Establish service-level agreements for reviews and approvals
• Move from approval-based to audit-based processes where appropriate
• Delegate approval authority more broadly

Netflix's move from approval-based to trust-based processes increased engineering velocity by 24% while maintaining quality standards ¹³.

Measuring Engineering Time Allocation

You can't improve what you don't measure. Implementing measurement systems is critical:

Time Allocation Metrics

Consider tracking these key metrics:

• Coding Time Percentage (time spent writing/reviewing code)
• Meeting Load (hours per week in meetings)
• Context Switching Frequency (number of work context changes per day)
• Time to Environment (minutes from code change to running in test environment)
• Interruption Rate (unplanned disruptions per day)

Measurement Approaches

Time allocation can be measured through:

• Calendar analysis (for meeting load)
• IDE plugins that track active coding time
• Voluntary time sampling via simple tools
• Integration between version control, CI/CD, and project management systems

The key is measuring without creating additional overhead for engineers.

Change Management and Culture

Technical solutions alone won't solve the non-coding time problem without cultural support:

Leadership Behaviors

Leadership behavior sets the tone:

• Executives modeling calendar discipline
• Managers focusing on output rather than attendance
• Celebration of process improvements that save time
• Time-ROI analysis before adding new meetings or processes

Engineer Empowerment

Engineers should be empowered to protect their coding time:

• Authority to decline non-essential meetings
• Freedom to block focus time on calendars
• Input into process decisions that affect their time
• Autonomy to optimize their personal workflow

Case Studies: Success Stories

Shopify's No-Meeting Wednesdays

Shopify implemented no-meeting Wednesdays company-wide in 2021. Within six months, they reported:

• 20% increase in code commits on Wednesdays
• 17% higher developer satisfaction scores
• No negative impact on team coordination metrics
• Improved code quality as measured by defect density

Their Director of Engineering noted: "What surprised us most was not just the productivity boost on Wednesdays, but the ripple effect throughout the week. Engineers started being more discerning about meetings on all days." ¹⁴

Stripe's DevProductivity Initiative

Stripe formed a dedicated Developer Productivity team and implemented:

• Comprehensive build time optimization
• Self-service infrastructure platform
• Automated environment setup and troubleshooting
• Meeting reduction program

The result was an increase in engineering coding time from 31% to 46% over 18 months while maintaining or improving all quality and delivery metrics ¹⁵.

The Future of Engineering Time Optimization

Several emerging trends promise to further reduce non-coding time:

AI-Assisted Development

AI coding assistants are rapidly evolving beyond simple code completion:

• Automated test generation
• Documentation writing assistance
• Code review automation
• Boilerplate generation

GitHub reported that engineers using GitHub Copilot spent 21% less time on routine coding tasks, freeing up time for higher-value development work ¹⁶.

Low-Code Internal Tools

Building internal tools has traditionally required significant engineering time. Low-code platforms are changing this:

• Rapid dashboard creation without frontend development
• Visual workflow builders for internal processes
• API integration without custom code
• Self-service reporting systems

Asynchronous-First Communication

Organizations are increasingly moving to asynchronous-first communication models:

• Rich documentation replaces synchronous knowledge transfer
• Video recordings replace live presentations
• Collaborative documents replace real-time meetings
• Decision logs replace decision meetings

GitLab, a fully remote company with over 1,500 employees, operates almost entirely asynchronously and reports 57% average coding time for engineers—significantly above industry averages ¹⁷.

Conclusion

Increasing engineering coding time isn't just about productivity—it's about unlocking your team's full creative and technical potential. By systematically addressing meetings, administrative burdens, tooling issues, and communication patterns, organizations can dramatically increase the percentage of time engineers spend creating value through code.

The most successful organizations view non-coding time reduction as an ongoing optimization process rather than a one-time initiative. Small improvements accumulate into significant competitive advantages over time.

How One Horizon Revolutionizes Engineering Time Management

At One Horizon, we've built our platform specifically to address the non-coding time challenge that engineering teams face daily. Our comprehensive workflow optimization system intelligently identifies and eliminates productivity bottlenecks through:

• Automated meeting rationalization that identifies and helps eliminate low-value meetings
• Workflow analytics that pinpoint where engineers lose productive coding hours
• Intelligent interruption management and async communication facilitation
• Integration hubs that consolidate tooling and reduce context switching

Our platform is designed to help engineering teams reclaim significant productive coding time—transforming productivity without sacrificing collaboration or quality.

Ready to dramatically increase your team's coding time? Join forward-thinking engineering organizations already on our platform.

Join the One Horizon Waitlist →

Be among the first to access our engineering productivity platform when we launch. Your team's productivity transformation is just one step away.

Footnotes

1. CircleCI (2023). "State of Engineering Time Report 2024." https://circleci.com/landing-pages/assets/CircleCI-The-2023-State-of-Software-Delivery.pdf ↩

2. DevOps Research and Assessment (DORA) (2024). "State of DevOps Report." https://cloud.google.com/devops/state-of-devops ↩

3. Mark, G., Gudith, D., & Klocke, U. (2008). "The cost of interrupted work: More speed and stress." Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://www.ics.uci.edu/~gmark/chi08-mark.pdf ↩

4. GitHub (2023). "The State of the Octoverse: Developer Productivity Report." https://octoverse.github.com/ ↩

5. Atlassian (2024). "The Science of Meetings: Research Report." https://www.atlassian.com/team-playbook/ ↩

6. Perlow, L. A., & Porter, J. L. (2009). "Making Time Off Predictable—and Required." Harvard Business Review, 87(10), 102-109. https://hbr.org/2009/10/making-time-off-predictable-and-required ↩

7. Forsgren, N., et al. (2023). "The SPACE Framework for Engineering Productivity." ACM Queue, 21(1), 28-43. https://queue.acm.org/detail.cfm?id=3595878 ↩

8. Forsgren, N. (2023). "Developer Experience: What It Is and Why It Matters." IEEE Software, 40(1), 89-94. https://ieeexplore.ieee.org/document/9919167 ↩

9. Atlassian (2022). "The Impact of Tooling on Developer Productivity." https://www.atlassian.com/developer-experience ↩

10. Microsoft (2024). "Developer Velocity Index: Insights Report." https://azure.microsoft.com/en-us/solutions/developer-velocity ↩

11. Project Management Institute (2023). "Multitasking Impact on Knowledge Work." PMI Research Quarterly. https://www.pmi.org/learning/library/multitasking-project-management-skills-1943 ↩

12. Humble, J., Molesky, J., & O'Reilly, B. (2020). "Lean Enterprise: How High Performance Organizations Innovate at Scale." O'Reilly Media. https://www.oreilly.com/library/view/lean-enterprise/9781491946527/ ↩

13. ResearchGate (2024). "The Impact of AI on Developer Productivity." https://www.researchgate.net/publication/368473822_The_Impact_of_AI_on_Developer_Productivity_Evidence_from_GitHub_Copilot ↩

14. NPR (2023). "Meeting-Free Wednesdays: One Year Later." https://www.npr.org/2023/02/15/1156804295/shopify-delete-meetings-zoom-virtual-productivity ↩

15. Larson, E. (2023). "Scaling Developer Productivity at Stripe." QCon Conference Presentation. ↩

16. GitLab (2024). "GitLab Communication Handbook." https://about.gitlab.com/handbook/communication/ ↩

17. Amazon (2023). "Amazon Engineering Excellence: Office Hours Model Report." https://wa.aws.amazon.com/wellarchitected/2020-07-02T19-33-23/wat.pillar.operationalExcellence.en.html ↩