Task Batching

Our tasks are well-sized for efficient work.

What is task batching?

Task batching is the practice of making tasks the right size or grouping similar tasks together to be completed in dedicated time blocks. For engineering teams, this means intentionally sizing and structuring work items to minimize context switching and maximize productive flow states. Instead of handling oversized tasks or constantly shifting between unrelated work, developers focus on smaller, related activities that require the same mental context, tools, or codebase areas.

Why is task batching important for development teams?

Task batching is crucial for successful development teams because it increases the likelihood of completing tasks and minimizes context switching—one of the biggest productivity killers for developers. When tasks are well-sized or grouped by similarity or focus, developers can maintain flow states longer, enabling deeper concentration and higher-quality work.

As one engineering leader noted:

"One obvious but underutilized practice is breaking tasks into smaller pieces. When you reduce the size of tasks or deliverables, you dramatically shorten feedback loops. This improved granularity enhances the predictability of your entire process. Making things smaller—whether it's task batching or code reviews—creates a system that works better in terms of timelines, required effort, and overall predictability."

Director of Engineering at Networking and Communications Company

By batching tasks appropriately, teams can reduce cognitive overload, streamline workflows, and foster a more predictable and efficient development process.

How does poor task batching affect developer experience?

Poor task batching creates several negative effects:

1. Increased cognitive load: Constantly switching between unrelated tasks forces developers to load different mental models and contexts.

2. Productivity loss: Research shows that context switching can waste up to 40% of productive time, as the brain needs time to refocus after each switch.

3. Higher error rates: Too big tasks or fragmented attention across tasks leads to more mistakes and oversights in code.

4. Longer completion times: Large tasks or projects take longer to finish as developers struggle with frequent reorientation.

5. Developer burnout: The mental strain of constant task switching contributes significantly to stress and fatigue.

One engineering leader described this experience perfectly:

"Developer experience suffers when we can't complete what we've started. Yes, we constantly receive change requests and being agile means we should accommodate them. But the question becomes: can you actually focus? Can you deliver something complete and experience that satisfaction—that dopamine rush—of finishing a task?"

Principal Technical Program Manager at Software Development Company

How can teams measure the effectiveness of their task batching?

Measuring task batching effectiveness can be approached through multiple methods:

Developer Experience Surveys

The most direct way to assess task batching is through structured feedback using developer experience surveys. At Network Perspective, we use the question:

"Our tasks are well-sized for efficient work."

This question appears in the Planning and Clarity section of our DevEx Survey, alongside other related questions about direction, specification, priorities, and timelines. By tracking responses to this question over time, teams can identify whether their task sizing and batching approaches are improving.

Workflow Metrics

Track and analyze metrics that indicate potential task batching issues:

• Cycle time variance: High variance often indicates inconsistent task sizing
• Work in Progress (WIP) counts: Excessive WIP suggests too many parallel tasks
• Task completion rates: Low completion rates may indicate poorly batched or oversized tasks
• Code commit patterns: Sporadic or very small commits can indicate fragmented work

What are the most common task batching pitfalls?

The most common pitfalls:

Oversized tasks: Tasks that are too large become unwieldy, hard to estimate, and difficult to complete in a reasonable timeframe.

Undersized tasks: Breaking work into extremely small pieces creates excess overhead in planning, tracking, and integrating.

Mismatched skill assignments: When specialized work is assigned to teams lacking that expertise, tasks take longer and create more cognitive load.

"When one of my ten teams appears to be underperforming, I need to determine if it's because they lack productivity and capability, or if we're setting them up for failure. Are we constantly switching their focus—front-end work one week, back-end the next, then suddenly they're doing quantum computing? Of course they'll struggle when they don't know what they're doing, while other teams consistently work in their area of expertise."

Staff Software Engineer at Payment Processing Company

Excessive work in progress: Taking on too many concurrent tasks dilutes focus and creates bottlenecks.

"We don't need ten tasks in progress when we can barely complete one. Stop adding to our workload—we need to focus on finishing what we've started rather than constantly beginning new things."

Principal Technical Program Manager at Software Development Company

Fragmented time blocks: When developers' calendars are filled with scattered meetings, the remaining time becomes too fragmented for effective task work.

"When you only have 30-minute gaps between meetings or you're constantly monitoring multiple chat channels, you simply don't have the capacity to deeply focus on a single task."

Senior Staff Software Engineer at IT Services Company

What are proven strategies for effective task batching?

Size tasks appropriately

Aim for tasks that can be completed in 1-2 days. As one engineering leader practices:

"Our approach is to create user stories of very consistent size—small enough that we can deliver several each day. When stories are sufficiently small, they statistically even out performance metrics. The biggest problem that disrupts all your metrics is having outliers or anomalies."

VP of Software Engineering at Software Development Company

Implement work-in-progress limits

Restrict the number of concurrent tasks to prevent context switching and ensure focus on completing work rather than starting new tasks.

Group similar tasks together

Batch tasks that use the same tools, technologies, or mental models. This reduces the cognitive load of switching contexts.

Create focus time blocks

Dedicate chunks of uninterrupted time for specific types of work:

"We've successfully freed up two hours per week for each employee to engage in deep work. We achieved this by eliminating inefficient meetings and reducing context switching, all without negatively impacting team morale, cross-functional collaboration, or key performance indicators related to productivity, retention, and innovation."

Global Head of Agile at Software Development Company

Break down complex work systematically

Use techniques like user story mapping or domain-driven design to decompose large features into coherent, manageable tasks.

"We're currently focused on teaching teams how to break down their work into smaller components, which directly reduces cycle times. In my experience, this approach always works—when you require people to divide work into smaller pieces, they develop a deeper understanding of what actually needs to be accomplished."

Director of Software Engineering at Mobile Games Developer and Publisher

Optimize meeting schedules

Structure meetings to minimize interruption of flow time. Group meetings together at the beginning or end of the day rather than spreading them throughout.

Why do some teams resist effective task batching?

Despite its benefits, teams may resist effective task batching for several reasons:

1. Misconception that smaller tasks reduce productivity: Some teams believe that breaking work into smaller pieces creates overhead without benefits.

2. Pressure to multitask: Organizational culture may emphasize "being busy" with multiple streams of work rather than focused completion.

3. Poor estimation skills: Teams struggle to break down work into appropriately sized chunks when they lack experience with estimation.

4. Misaligned incentives: When teams are rewarded for starting new work rather than completing existing work, task batching suffers.

5. Inadequate tooling: Without proper tools to visualize and manage work, efficient batching becomes difficult.

How does task batching relate to other development practices?

Task batching complements several established development practices:

1. Agile methodologies: Task batching enhances sprint planning by ensuring appropriately sized stories.

2. Kanban systems: Work-in-progress limits enforce batch size discipline and flow.

3. Continuous integration/delivery: Well-batched tasks are easier to integrate and test incrementally.

4. Test-driven development: Smaller, focused tasks lend themselves to clear test criteria.

5. DevOps practices: Batched operational tasks integrate better with development workflows.

Conclusion

Effective task batching represents one of the highest-impact, lowest-cost interventions available to engineering leaders. By simply restructuring how work is sized, organized, and scheduled, teams can achieve significant improvements in productivity and developer satisfaction.

As our research across hundreds of engineering organizations shows, teams that excel at task batching consistently outperform their peers in both delivery metrics and developer experience scores. By measuring and improving how your organization approaches task batching, you can unlock deeper flow states, higher quality work, and more predictable delivery—all while improving the day-to-day experience of your engineering team.