Written by Bob Bloem, Managing Director at Unify Consulting
Once an organization has a balanced view of both speed and quality, it can use its analytics capability for more than just operational improvement; it can use it for strategic validation. The most pressing example today is measuring the true impact of Generative AI in the development lifecycle.
Anecdotes from developers are valuable, but a significant investment in tools like GitHub Copilot demands quantitative proof. The holistic data model we’ve built is the only way to provide it. By flagging developers who are using AI tools in the HRIS data, we can conduct a powerful comparative analysis:
- Impact on Velocity: We can definitively measure the difference in Cycle Time for tasks completed by AI-assisted developers versus their peers. Are they truly delivering value faster?
- Impact on Quality: Does AI-generated code lead to more rework? We analyze the Code Churn and First-Time Pass Rate of merge requests to see if AI-assisted code is stable and meets quality standards from the start.
- Impact on Onboarding: We track the time-to-first-commit for new engineers with and
without AI tools to measure its effect on ramp-up time.
This analysis provides the clear ROI needed to guide investment, training, and adoption strategies. It’s the final step in the maturation journey—from having no visibility, to seeing velocity, to balancing it with quality, and finally, to using data to make strategic technology decisions with confidence.
Across our client base, the results of this journey are consistent: a 15-30% reduction in cycle time, up to a 20% reduction in costly talent turnover, and clear, quantitative validation of technology ROI.
Ready to turn your data into your most powerful strategic asset? Let’s partner together. Contact Unify to learn more about our Workforce Analytics offering.
