EEBO Metrics & GenAI Driven Software Development

EEBO Metrics & GenAI Driven Software Development

Dinker Charak

Jan 27, 2024

The rapid emergence of Generative AI (GenAI) has revolutionized numerous sectors, including software development. As this technology reshapes traditional processes, a pertinent question arises: does the EEBO (Engineering Excellence to Business Outcomes) Metrics framework retain its relevance in this new era? This article delves into the compatibility of EEBO Metrics with GenAI-driven Software Development Life Cycle (SDLC), assessing its ability to accentuate the value GenAI brings to Engineering Excellence.

The Misdirection of Speed

It's crucial to understand that speed in development and deployment is inconsequential if it doesn't lead in the right direction. GenAI, while accelerating certain processes, must be aligned with strategic goals.

EEBO Metrics: The Guiding Framework

The recommended EEBO Metrics include three key metrics for excellence in software development and four for excellence in production deployment, correlating to four essential business outcome categories.

EEBO Metrics Framework

Software Development Excellence Metrics

Build Failure Rate, Security Warnings & Technical Debt

Production Deployment Excellence Metrics (DORA's Four Key Metrics)

Deployment Frequency, Mean Time to Restore, Change Fail Percentage & Lead Time

Business Outcome Categories

Market Sensing, Efficiency and Effectiveness Improvement, Experience Enhancement & Influence Increase

EEBO Metrics: How it Helps

Evaluating Engineering Excellence

The framework underscores the significance of fitness metrics in ensuring that technological investments align with and contribute to desired business outcomes. In the GenAI context, this means evaluating how AI technologies can be integrated into existing practices to enhance overall efficiency and quality.

Establishing Success Correlations

Utilizing metrics to draw connections between engineering practices and business outcomes provides critical insights. This becomes even more pertinent with GenAI, as it offers novel ways to achieve these outcomes, demanding a nuanced approach to measurement.

Bridging Engineering and ROI

EEBO Metrics act as a conduit, connecting engineering efforts to Return on Investment (ROI). In the GenAI era, this involves understanding how AI-driven processes can be quantified and linked to tangible business benefits.

Redefining SDLC with GenAI

The article offers a glimpse into how GenAI transforms the SDLC, focusing on areas where GenAI can significantly reduce time-to-market and enhance the journey towards engineering excellence.

Assessing GenAI's Impact on Outcomes

By applying EEBO Metrics, organizations can compare pre- and post-GenAI scenarios, gauging the tangible value GenAI brings to complex product development.

GenAI's Positive Impact Indicators

GenAI's Positive Impact on EEBO Metrics

In Software Development

Reduction in Technical Debt

In Production Deployment

Shortened Lead Time

In Business Outcomes

Enhanced Market Sensing, Improved Efficiency and Effectiveness, Elevated User Experience & Increased Influence


The integration of GenAI in SDLC presents both challenges and opportunities. EEBO Metrics serve as a crucial tool in this transition, helping organizations navigate the complexities of this new landscape. By focusing on the right metrics, businesses can harness the power of GenAI not just to accelerate processes, but to drive meaningful, directionally correct outcomes.

Cross posted on LinkedIn. Cover art created using ChatGPT's DALL-E