Decision Systems for IT
I study how IT organizations make decisions.
For nearly three decades, I have worked across software engineering, solution architecture, and business analytics, observing how complex technology environments succeed — and why they sometimes fail.
My work focuses on the structural quality of IT decision-making: how initiatives are evaluated, how effort is estimated, how uncertainty is modeled, and how architectural sustainability is protected under delivery pressure.
Academic & Professional Foundation
I bring 28 years of experience in software-related roles, including more than a decade in formal Solution Architecture leadership.
My academic background spans Business Computing (Informatique de gestion), International Affairs, and Business Analytics. This combination allows me to approach IT not only as a technical discipline, but as an organizational system shaped by incentives, governance structures, economic trade-offs, and measurable uncertainty.
Research Focus
Modern IT organizations have improved execution practices significantly. Iterative delivery models and cross-functional collaboration have increased adaptability at the team level.
However, organizational decision systems have not evolved at the same pace.
In many environments:
Estimation remains informal.
Risk remains implicit.
Trade-offs remain unquantified.
Architectural impact remains reactive.
I study how structured, measurable mechanisms can improve clarity, predictability, and long-term system health without sacrificing execution speed.
Core Orientation
I do not focus on methodologies.
I focus on decision quality.
This work examines how to:
- Transform estimation into structured modeling rather than negotiation
- Make uncertainty explicit and measurable
- Strengthen architecture as a governance instrument
- Use delivery data to improve predictive capability
- Reduce political noise through structural transparency
The objective is not additional process.
It is improved decision intelligence.