Resource Optimization Through Allocation Transparency
Automatic work classification, effort distribution analysis, and tech debt patterns. No manual time tracking required.
The Allocation Blind Spot
Most CTOs can't answer "Where are we actually spending our engineering time?" with confidence. This lack of visibility makes strategic planning and resource optimization nearly impossible.
Questions That Keep CTOs Up at Night:
Roadmap vs Reality
Are we actually building what we planned, or just fighting fires?
Feature vs Maintenance
How much time goes to new features versus bugs, tech debt, and operational work?
Epic Cost Reality
What did that major feature actually cost us in engineering time and opportunity?
Tech Stack Distribution
Which technologies consume the most engineering effort and why?
How Allocation Lens Works
Automatic time tracking and categorization that reveals exactly where your engineering capacity goes.
Automatic Work Classification
AI automatically categorizes all engineering work into meaningful themes:
• Automatic classification of commits, PRs, and issues by impact area
• Automatic detection of work types: features, bugs, tech debt, maintenance
• Theme clustering that surfaces patterns in engineering effort
• Continuous learning that improves categorization accuracy over time
Roadmap Adherence Tracking
Compare planned initiatives against actual engineering effort:
• Planned vs actual effort for each roadmap item
• Scope creep detection and cost overrun alerts
• Initiative progress relative to resource allocation
• Cross-team dependency impact on timelines
Epic Cost Analysis
See the true cost of major features and initiatives:
• Total engineering hours per epic with breakdown by team
• Hidden costs like rework, testing, and documentation
• Opportunity cost analysis of delayed features
• ROI calculation based on actual delivery effort
Bugs vs Features Balance
Understand your engineering investment distribution:
• Percentage of time on new features vs bug fixes
• Technical debt accumulation and payment trends
• Operational overhead and maintenance burden
• Quality investment impact on future velocity
Tech Stack Workload
See which technologies and systems consume the most effort:
• Engineering time by technology, framework, and system
• Legacy system maintenance burden quantification
• New technology adoption cost and learning curve
• Infrastructure vs application development ratio
Strategic Resource Optimization
Make informed decisions about where to invest your most valuable asset: engineering time
Data-Driven Planning
Use historical allocation data to create realistic timelines and resource plans
Budget Justification
Show executives exactly where engineering investment goes and its business impact
Bottleneck Identification
Spot resource constraints and allocation inefficiencies before they impact delivery
Strategic Alignment
Ensure engineering effort aligns with business priorities and strategic objectives
How Teams Use Allocation Lens
From daily team standup insights to quarterly strategic reviews
Daily Team Usage
Engineering managers check allocation dashboards during standups to ensure team focus aligns with sprint goals. Teams can see if they're spending too much time on unplanned work or if certain technologies are creating unexpected overhead.
Weekly Leadership Reviews
CTOs and VPs use weekly allocation reports to identify trends, spot resource imbalances, and make tactical adjustments. The data helps in sprint planning and capacity allocation across multiple teams and projects.
Quarterly Strategic Planning
Historical allocation data informs roadmap planning, budget requests, and hiring decisions. Leadership can predict resource needs for upcoming initiatives based on similar past projects and current team capacity patterns.