Research:Question-01-Factor-Performance-Correlation
Research Question 01: How do the 10 success factors correlate with actual job performance across different developer experience levels?
Summary
This research question examines the correlation between key developer success factors and actual job performance across different experience levels. Through analysis of multiple empirical studies, the evidence reveals complex relationships between technical skills, communication abilities, team dynamics, and individual performance metrics. Notably, recent studies on AI coding tools provide unprecedented insights into how experience levels interact with productivity measures in modern development environments.
Research Question
How do the 10 success factors correlate with actual job performance across different developer experience levels?
This question seeks to understand which developer characteristics most strongly predict job success, how these correlations vary across experience levels, and what empirical evidence exists to support or challenge traditional assumptions about developer effectiveness.
Background and Motivation
The software development industry has long debated which factors most reliably predict developer success and productivity. Traditional assumptions about the primacy of technical skills and experience have been challenged by recent empirical research, particularly studies examining how AI coding tools interact with developer capabilities at different experience levels.
Research Findings from Literature
Primary Empirical Studies
Critical Success Factors Research
Springer Software Quality Journal (2018) - Major empirical study involving 101 software projects in the Turkish software industry:
Key Finding on Experience vs Management: Template:Quote
Group-Level Performance Analysis
ScienceDirect (1993) - Analysis of 31 software development groups examining cohesiveness, experience, and capability:
Technical vs Non-Technical Skills Framework
ScienceDirect (2025) - Comprehensive framework study with 158 participants:
Non-Technical Skills Impact: Template:Quote
AI Tools and Experience Level Studies
METR Study (2025) - Experienced Developer Performance
Randomized Controlled Trial with 16 Experienced Developers:
Surprising Performance Results: Template:Quote
Source: Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
Junior vs Senior Developer AI Performance
Multiple Industry Studies on Experience-Performance Paradox:
Complex Task Performance: Template:Quote
Source: AI coding tools may not speed up every developer, study shows
Communication and Collaboration Factors
Communication as Critical Success Factor: Template:Quote
Social and Human Factors Impact: Template:Quote
Source: Factors Affecting Software Developer's Performance
Analysis: Relationship to Original 10-Factor Framework
Strong Empirical Support
The literature provides substantial support for several factors in the original 10-factor framework:
1. Context Retention: The METR study's finding that experienced developers slow down with AI tools aligns with the importance of context retention - experienced developers may struggle because AI disrupts their established context-management workflows.
2. Strategic Thinking: The Turkish software industry study's finding that "project monitoring and controlling" ranked higher than technical experience directly supports the strategic thinking factor's importance.
3. Communication Skills: Multiple studies cite communication breakdowns as major productivity inhibitors, strongly supporting this factor's inclusion.
4. Collaboration: The group dynamics study showing cohesiveness as more important than individual experience validates team collaboration factors.
Contradictions and Surprises
Experience Paradox: The most significant contradiction is the finding that experience was "the weakest" factor in group performance studies, and that experienced developers actually perform worse with AI tools. This challenges traditional assumptions about experience being a primary success predictor.
Technical vs Management Skills: The finding that project management capabilities often outweigh pure technical abilities suggests a need to weight strategic and organizational factors higher than initially conceptualized.
Framework Expansions
The empirical research suggests expanding the original framework to include:
1. Emotional Intelligence: Studies emphasizing "emotions, long-term memory, belief, desire, intention, and commitment" suggest psychological factors deserve more prominence.
2. Adaptation Capacity: The AI tool studies suggest that adaptability to new technologies may be more important than baseline technical skill.
3. Task Context Sensitivity: Research showing performance varies dramatically based on task complexity suggests context-dependent factor weighting.
Conclusions
The empirical literature reveals that developer success factors show complex, non-linear relationships with performance that vary significantly by experience level and context. The most striking finding is the "experience paradox" - that traditional experience metrics may be less predictive of success than previously assumed, particularly in AI-augmented development environments.
Key validated factors include strategic thinking, team collaboration, communication skills, and surprisingly, project management capabilities. The research suggests that soft skills and adaptability may be more predictive of long-term success than pure technical proficiency.
Sources and References
- Correlation of critical success factors with success of software projects: an empirical investigation - Software Quality Journal
- Understanding the factors influencing the performance of software development groups - ScienceDirect
- A novel framework for evaluating developers' code comprehension proficiency - ScienceDirect
- Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity - METR
- AI coding tools may not speed up every developer, study shows - TechCrunch
- Factors Affecting Software Developer's Performance - ResearchGate